MECHANISTIC INSIGHTS RELATED TO THE DESIGN AND CONSTRUCTION OF
LITHIUM SINGLE ION CONDUCTORS
By
Gregory Spahlinger

A DISSERTATION
Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of
Chemistry - Doctor of Philosophy
2014

ABSTRACT
MECHANISTIC INSIGHTS RELATED TO THE DESIGN AND CONSTRUCTION OF
LITHIUM SINGLE ION CONDUCTORS
By
Gregory Spahlinger
Lithium single ion conductors are a class of electrolytes, typically designed for lithium
ion batteries, with the potential to improve the performance of these batteries. The benefits of
single ion conductors arise out of the fact that their immobile anions are not capable of
concentrating near the anode of the battery, causing an increase in resistance as the battery is
discharged. Unfortunately lithium single ion conductors suffer severe drawbacks in their
conductivity which have been attributed to diverse causes. Because of the low success rate of
single ion conductors in the literature and previous work in the Baker group, I have chosen to
investigate mechanistic questions related to the design and construction of these materials,
without engineering new materials.
An attractive design strategy for the screening of immobile anion moieties for single ion
conductors would be the use of the copper catalyzed alkyne azide (CUAAC) “click” reaction in
order to efficiently introduce anions onto a support chemistry in a way that is efficient and
tunable. A variable added by this strategy would be the presence of a 1,2,3-triazole moiety which
is not commonly used in electrolyte chemistry. In order to assess the impact of the triazole on the
conductivity of an electrolyte, a series of model compounds were synthesized containing a
variable number of triazoles in an otherwise poly(ethylene glycol) like oligomer chain. The
model compounds were subjected to differential scanning calorimetry, electrochemical
impedance spectroscopy, and in one case single crystal X-ray diffraction, and solvent shells were
modeled for lithium with and without triazoles using ab initio quantum chemistry calculations. It

was concluded that the affinity to Li+ of the triazole and ether oxygen are similar, however the
triazole has a substantial dipole which exerts some deleterious effects on the conductivity,
leading to an increase in the activation energy for the process. These effects are balanced by an
increase in the pre-exponential factor which leads to “compensation behavior” due to the
dependence of that quantity on the dipole density in the material. The observed effect is one of a
lower conductivity for the model compounds relative to poly(ethylene glycol)dimethyl ether 500
at room temperature, which converges to roughly the same conductivity around 80 °C.
In synthetic studies, attempts were made to synthesize N-triflylpropanesultam (TPS) a
five membered heterocycle whose nucleophilic ring opening would yield a desirable anion for
use in single ion conductors. TPS proved to be significantly more difficult to open than expected,
which prompted a computational study.
In order to study the nucleofugality of polyatomic anionic leaving groups derived from
oxygen and nitrogen, a contingent of 19 methylating agents consisting of amines or alcohols
activated with carbonyl or sulfonyl substituents has been examined via ab initio calculations.
Activation energies for alkylation of ammonia, and gas phase methyl cation affinitys were
calculated. It was found that polyatomic anionic leaving groups derived from nitrogen will have
higher activation energies for Menshutkin (SN2) alkylation even when they have similar methyl
cation affinities. This inherent deficit in the nucleofugality of nitrogen derived leaving groups
appears to be a result of the way bond cleavage is synchronized with bond formation to the
incoming ammonia nucleophile. Additionally the second sulfonyl group present in a sulfonimide
appears to be less effective at activating nitrogen due to a preference for tetrahedral geometries at
nitrogen in the transition states of sulfonamide groups. Optimal delocalization of electron density
is therefore frustrated due to the symmetry of the leaving group.

Copyright by
GREGORY SPAHLINGER
2014

iv

To those who devote themselves to the pursuit and transmission of knowledge
To those who have been my mentors and role models
To science

v

ACKNOWLEDGMENTS

My Ph.D. has been an epic journey and I’ve been fortunate to share it with many
companions. I would like to recognize the support of my family, particularly Carol, Dave,
Melissa, Diana, Bruce, Brenda, Nathan and my (too numerous to name individually) extended
family, who have been there for me during some of the most difficult times in my life, and who
have always supported me in my aspirations.
Similarly I would like to acknowledge my friends and colleagues at MSU and otherwise.
This includes Ned Jackson, and members of his group: Souful, Jason, Darya, Tayeb, Chao,
Andrew, Fatmata, Mahlet, Jake, Gracie Lou and Misha who have been great friends and valued
colleagues. I would also like to recognize Greg Baker, whose mentorship got me started in this
program and some of his group: Zhe Jia, Gina, Salinda, Yu Ling, Olivia and Patty for largely the
same reasons. Likewise I acknowledge my guidance committee Mitch Smith, Keith Promislow,
Tom Hamann, and Xuefei Huang, for their role in my professional development. I acknowledge
my friends from Ann Arbor: Marcus, Kim, Ted, Laura, Chuck and others for providing me an
escape from East Lansing. I acknowledge Matt and the Lansing Pinball League for giving me
someplace to evade calculations and think about a different kind of physics every couple of
weeks, I acknowledge my friend Kristen for listening to my songs and cat stories, and my friend
Xin for sharing an apartment with me for a couple years.
I would also like to acknowledge the technical support staff who have helped me enable
my research or directly contributed to this dissertation. This includes Richard Staples, who
solved the crystal structures found in this work, Dan Holmes and Kermit Johnson who were both
extremely helpful when NMR problems arose, Kathy Severin who helped me learn Labview,

vi

Paul Reed, who helped me troubleshoot calculations and gain access to the HPCC, Glenn Wesley
who made my coin cell for electrochemical impedance spectroscopy, Scott Bankroff who
constructed my mercury bubbler and cleaned my vacuum manifold, Bob Rasico who helped me
troubleshoot the Baker glovebox, and Joni Tucker for jerry rigging my schedule this semester.
Finally I would like to acknowledge the MSU college of Natural Science for conference
and dissertation continuation fellowship funding, the MSU Chemistry IT department and
Institute for Cyber Enabled Research (iCER) for access to computational resources, the MSU
Center for Crystolographic Research for crystallographic services, The MSU center for Mass
Spectrometry, for high resolution mass spectrometry analyses, and the MSU Chemistry
Department for the 12 semesters of support I received as a teaching assistant.

vii

TABLE OF CONTENTS
LIST OF TABLES ..................................................................................................................................... x
LIST OF FIGURES ................................................................................................................................xvii
LIST OF SCHEMES ...............................................................................................................................xxi
KEY TO ABBREVIATIONS................................................................................................................ xxii
1

Chapter 1: Introduction ...................................................................................................................... 1
1.1 General Background .................................................................................................................. 1
1.2 Physical Models of Lithium Ion Transport in Liquid and Polymer Electrolytes ............... 3
1.3 Electrolyte Polarization in Lithium Ion Batteries ................................................................ 13
1.4 Design Strategies for the Improvement of Lithium Ion Electrolyte Performance ........... 14
1.5 Strategies of Single Ion Conductor Design from the Baker Research Group .................. 19
1.6 Problems with Single Ion Conductors Demonstrated in Experiment and Simulation .... 23
1.7 On the Construction of Lithium Single Ion Conductors and the Making of Lemonade . 26

2 Chapter 2: 1,2,3-Triazoles as Pseudo-Ether Moieties in Oligo (Ethylene Glycol) Based
Lithium Ion Electrolytes .......................................................................................................................... 31
2.1 Introduction ............................................................................................................................... 31
2.2 Experimental ............................................................................................................................. 34
2.2.1
Computational methods ................................................................................................... 34
2.2.2
Electrochemical Impedance Spectroscopy.................................................................... 35
2.2.3
Single Crystal X-Ray Diffraction ................................................................................... 36
2.2.4
Synthesis of Model Compounds..................................................................................... 38
2.2.4.1 Materials and Instrumentation .................................................................................... 39
2.2.4.2 Synthesis of Tosylates 1 – 5........................................................................................ 39
2.2.4.3 Synthesis of Azides 6 – 8 ............................................................................................ 41
2.2.4.4 Synthesis of Alkynes 9 – 11........................................................................................ 43
2.2.4.5 Synthesis of Model Compounds 12 – 15127 .............................................................. 44
2.3 Results and Discussion ............................................................................................................ 47
2.3.1
Ab Initio Calculations ...................................................................................................... 47
2.3.2
Experimental Measurement of Conductivity and Thermal Behavior ........................ 52
2.3.3
The Explanation for and Significance of Compensation Behavior ........................... 60
2.4 Conclusions ............................................................................................................................... 67
3

Chapter 3: Nucleofugality in Nitrogen and Oxygen derived leaving groups ........................... 68
3.1 Introduction ............................................................................................................................... 68
3.2 Computational Methods .......................................................................................................... 71
3.3 Results and Discussion ............................................................................................................ 74
3.3.1
Energies Associated with Nucleofugality, and their Trends....................................... 74
3.3.2
On the Fitness of MCA to Describe Inherent Nucleofugality .................................... 83
3.4 Conclusion ................................................................................................................................. 94

viii

4

Chapter 4: Summary and Future Study ........................................................................................ 95
4.1 Summary.................................................................................................................................... 95
4.2 Future Directions for CUAAC Derived Lithium Single Ion Conductors ......................... 97
4.3 Future Directions for Studies of Nucleofugality in Activated Leaving Groups .............. 99

APPENDICES ........................................................................................................................................ 101
4.4 Appendix 1 – Additional Study of TPS............................................................................... 102
4.5 Appendix 2 – Spectal Data and Geometric Results from Computations ........................ 113
REFERENCES ....................................................................................................................................... 176

ix

LIST OF TABLES

Table 1 – Physical Data Pertaining to Thermal and Conductive Properties of Materials ............ 53
Table 2 – Crystal Data and Structure Refinement for 6EO2T ...................................................... 59
Table 3 – Calculated ΔES→TS values and Relevant Transition State Geometries ......................... 79
Table 4 – Methyl Cation Affinity in Experiment and Theory. All values are in kcal/mol. .......... 80
Table 5 – Transition State Pyramidalization in Sulfonamide Species at HF and MP2 geometries
(all values are given in degrees).................................................................................................... 93
Table 6 – Crystal Data and Structure Refinement for TPS ......................................................... 108
Table 7 – Comparison Between the Crystal Geometry of TPS and Geometry at MP2(full)/631G(d) (Bond Lengths) ............................................................................................................... 110
Table 8 – Comparison Between the Crystal Geometry of TPS and Geometry at MP2(full)/631G(d) (Bond Angles) ................................................................................................................ 111
Table 9 - Glyme, Energy: -307.87678 ........................................................................................ 119
Table 10 - Glyme-(Li+), Complex Energy: -315.22669 ............................................................. 119
Table 11 - Glyme + DME, Energy: -462.40188 ......................................................................... 120
Table 12 - Glyme-(Li+)-DME, Energy: -469.796041 ................................................................ 121
Table 13 - Glyme + Glyme, Energy: -615.75824 ....................................................................... 122
Table 14 - Glyme-(Li+)-Glyme, Energy: -623.18874 ................................................................ 123
Table 15 - 4-Methoxymethyl-1,2,3-Triazole, Energy: -394.90167 ............................................ 124
Table 16 - 4-Methoxymethyl-1,2,3-Triazole-(Li+), ................................................................... 124
Table 17 - 4-MeOMe-1,2,3-Triazole + DME, Energy: -549.42683 ........................................... 125

x

Table 18 - 4-MeOMe-1,2,3-Triazole-(Li+)-DME, ..................................................................... 126
Table 19 - 4-MeOMe-1,2,3-Triazole + Glyme, Energy: -702.78713 ......................................... 127
Table 20 - 4-MeOMe-1,2,3-Triazole-(Li+)-Glyme, ................................................................... 128
Table 21 - Water, Energy: -76.23099 ......................................................................................... 129
Table 22 - Water-Li, Energy: -83.56307 ................................................................................... 129
Table 23 - 1H-1,2,3-Triazole, Energy: -241.56224 .................................................................... 129
Table 24 - 1H-1,2,3-Triazole-(Li+), Energy: -248.91584 .......................................................... 129
Table 25 - 2H-1,2,3-Triazole, Energy: -241.57086 .................................................................... 130
Table 26 - 2H-1,2,3-Triazole-(Li+), Energy: -248.89669 .......................................................... 130
Table 27 – Pyrazole, Energy: -225.55411 .................................................................................. 130
Table 28 - Pyrazole-(Li+), Energy: -232.89344 ......................................................................... 131
Table 29 - Pyridizine, Energy: -263.52492 ................................................................................. 131
Table 30 - Pyridazine-(Li+), Energy: -270.88587 ...................................................................... 131
Table 31 - Pyrimidine, Energy: -263.55995 ............................................................................... 132
Table 32 - Pyrimidine-(Li+), Energy: -270.89194...................................................................... 132
Table 33 - 1-Methoxyethyl-1,2,3-Triazole, Energy: -434.13854 ............................................... 133
Table 34 - 1-Methoxyethyl-1,2,3-Triazole-(Li+), ...................................................................... 133
Table 35 - 4-Methoxymethyl-1,2,3-Triazole, Energy: -394.95807 ............................................ 134
Table 36 - 4-Methoxymethyl-1,2,3-Triazole-(Li+), ................................................................... 134
Table 37 - Methyl Mesylate, Cs, Energy: -758.53145 ................................................................ 135

xi

Table 38 - Dimethylsulfate, C1, Energy: -833.56441 ................................................................. 136
Table 39 - Methyl Triflate, C1, Energy: -1055.61053................................................................. 136
Table 40 - Methylfluorosulfonate, C1, Energy: -818.40115 ....................................................... 137
Table 41 - Methyl TFSI (anti) C1, Energy: -1919.67259 ........................................................... 137
Table 42 - Methyl TFSI (gauche) C1, Energy: -1919.67076 ...................................................... 138
Table 43 - Methyl FSI, C1, Energy: -1445.25353 ....................................................................... 138
Table 44 - Methyl MSI (anti) C1, Energy: -1325.52993 ............................................................. 139
Table 45 - Methyl MSI (gauche) C1, Energy: -1325.52302 ....................................................... 140
Table 46 - Methyl MSA, C1, Energy: -738.64549 ...................................................................... 140
Table 47 - Methyl FSA, C1, Energy: -798.52240 ....................................................................... 141
Table 48 - MeiprFSA, C1, Energy: -916.03637 ......................................................................... 141
Table 49 - Methyl Acetate, Cs, Energy: -323.88097.................................................................. 142
Table 50 - Methyl Trifluoroacetate, Cs, Energy: -620.97437 ..................................................... 142
Table 51 - Methyl Cyanoformate, Cs, Energy: -376.72778 ........................................................ 143
Table 52 - Dimethylcarbonate, Cs, Energy: -398.92298 ............................................................. 143
Table 53 - Dimethylurethane, Cs, Energy: -379.04927............................................................... 144
Table 54 - Methyl Acetamide, Cs, Energy: -304.00329 ............................................................. 144
Table 55 - Methyl Trifluoroacetamide, Cs, Energy: -601.10242 ................................................ 145
Table 56 - Methylcyanoformamide, Cs, Energy: -356.85536 ..................................................... 145
Table 57 - Methyl Succinimide, Cs, Energy: -455.08510 ........................................................... 146

xii

Table 58 - 1,3-Propanesultone, C1, Energy: -796.52517 ............................................................ 146
Table 59 - N-Triflylpropanesultam, C1, Energy: -1660.59152 ................................................... 147
Table 60 - Methyl Chloride, C3v, Energy: -555.66764 ............................................................... 147
Table 61 - Methyl Mesylate, C1, Energy: -758.58709 ................................................................ 148
Table 62 - Dimethylsulfate, C1, Energy: -833.61240 ................................................................. 148
Table 63 - Methyl Triflate, C1, Energy: -1055.65367................................................................. 149
Table 64 - Methylfluorosulfonate, C1, Energy: -818.44356 ....................................................... 149
Table 65 - Methyl TFSI (anti) C1, Energy: -1919.72254 ............................................................ 150
Table 66 - Methyl TFSI (gauche) C1, Energy: -1919.71949 ...................................................... 151
Table 67 - Methyl FSI, C1, Energy: -1445.30276 ....................................................................... 151
Table 68 - Methyl MSI (anti) C1, Energy: -1325.59716 ............................................................. 152
Table 69 - Methyl MSI (gauche) C1, Energy: -1325.59135 ....................................................... 153
Table 70 - Methyl MSA, C1, Energy: -738.74012 ...................................................................... 153
Table 71 - Methyl FSA, C1, Energy: -798.60455 ....................................................................... 154
Table 72 - MeiprFSA, C1, Energy: -916.11962 .......................................................................... 154
Table 73 - Methyl Acetate, C1, Energy: -323.95778 ................................................................. 155
Table 74 - Methyl Trifluoroacetate, C1, Energy: -621.03443 ..................................................... 155
Table 75 - Methyl Cyanoformate, Cs, Energy: -376.78433 ........................................................ 156
Table 76 - Dimethylcarbonate, C1, Energy: -398.99274 ............................................................ 156
Table 77 - Dimethylurethane, C1, Energy: -379.16693 .............................................................. 157

xiii

Table 78 - Methyl Acetamide, C1, Energy: -304.12207 ............................................................. 157
Table 79 - Methyl Trifluoroacetamide, C1, Energy: -601.21078 ................................................ 158
Table 80 - Methylcyanoformamide, Cs, Energy: -356.96347 ..................................................... 158
Table 81 - Methyl Succinimide, C1, Energy: -455.18368........................................................... 159
Table 82 - 1,3-Propanesultone, C1, Energy: -796.58767 ............................................................ 159
Table 83 - N-Triflylpropanesultam, C1, Energy: -1660.66338 ................................................... 160
Table 84 - Methyl Chloride, C3v, Energy: -555.73069 ............................................................... 160
Table 85 - Methyl Mesylate, Cs, Energy: -702.21914 ................................................................ 161
Table 86 - Dimethylsulfate, C1, Energy: -777.24377 ................................................................. 161
Table 87 - Methyl Triflate, C1, Energy: -999.28488.................................................................. 162
Table 88 - Methylfluorosulfonate, C1, Energy: -762.07625 ....................................................... 162
Table 89 - Methyl TFSI (anti) C1, Energy: -1863.35495 ............................................................ 163
Table 90 - Methyl FSI, C1, Energy: -1388.93439 ....................................................................... 163
Table 91 - Methyl MSI (anti) C1, Energy: -1269.22819 ............................................................. 164
Table 92 - Methyl MSA, C1, Energy: -682.37105 ...................................................................... 164
Table 93 - Methyl FSA, C1, Energy: -742.23853 ....................................................................... 165
Table 94 - MeiprFSA, C1, Energy: -859.75289 .......................................................................... 165
Table 95 - Methyl Acetate, Cs, Energy: -267.59323................................................................... 166
Table 96 - Methyl Trifluoroacetate, Cs, Energy: -564.66942 .................................................... 166
Table 97 - Methyl Cyanoformate, Cs, Energy: -320.41939 ........................................................ 166

xiv

Table 98 - Dimethylcarbonate, Cs, Energy: -342.62576 ............................................................. 167
Table 99 - Dimethylurethane, C1, Energy: -322.79444 .............................................................. 167
Table 100 - Methyl Acetamide, C1, Energy: -247.75036 ........................................................... 167
Table 101 - Methyl Trifluoroacetamide, Cs, Energy: -544.83515 .............................................. 168
Table 102 - Methylcyanoformamide, Cs, Energy: -300.58450 ................................................... 168
Table 103 - Methyl Succinimide, Cs, Energy: -398.81698 ......................................................... 168
Table 104 - Methyl Chloride, C3v, Energy: -499.36908 ............................................................. 169
Table 105 - Mesylate (-) C3v, Energy: -662.53310 ..................................................................... 170
Table 106 - Methylsulfate (-) Cs, Energy: -737.57487 ............................................................... 170
Table 107 - Triflate (-) C3v, Energy: -959.63081 ........................................................................ 170
Table 108 - Fluorosulfonate (-) C3v, Energy: -722.42035 .......................................................... 171
Table 109 - TFSI (anti)(-) C2, Energy: -1823.69893 .................................................................. 171
Table 110 - FSI (-)C2, Energy -1349.28297 ............................................................................... 171
Table 111 - MSI (anti)(-) C2, Energy: -1229.53832 ................................................................... 172
Table 112 - MSA (-) C1, Energy: -642.63252 ............................................................................ 172
Table 113 - FSA (-) C1, Energy: -702.52414 .............................................................................. 172
Table 114 - Isopropyl FSA (-) C1, -820.03729 ........................................................................... 173
Table 115 - Acetate (-) Cs, Energy: -227.85413 ......................................................................... 173
Table 116 - Trifluoroacetate (-) Cs, Energy: -524.96954............................................................ 173
Table 117 - Cyanoformate (-) C2v, Energy: -280.73023 ............................................................. 173

xv

Table 118 - Methylcarbonate (-) Cs, Energy: -302.90805 .......................................................... 174
Table 119 - Methylurethane (-) Cs, Energy: -283.02333 ........................................................... 174
Table 120 - Acetamide (-) Cs, Energy: -207.96859 .................................................................... 174
Table 121 - Trifluoroacetamide (-) Cs, Energy: -505.08677 ...................................................... 174
Table 122 - Cyanoformamide (-) Cs, Energy: -260.84632 ......................................................... 175
Table 123 - Succinimide (-) C2v, Energy: -359.07164 ................................................................ 175

xvi

LIST OF FIGURES

Figure 1 - A Schematic of a lithium ion battery, featuring typical materials for the anode
(graphite) and the cathode (LiCoO2). A likely choice of electrolyte would be ethylene carbonate
and dimethyl carbonate 1:1.1 Figure 1 is reprinted with permission from Bruce, P.; Scrosati, B.;
Tarascon, J. Angew. Chem. Int. Ed. 2008, 47, 2930 – 2946. Copywrite 2008 Wiley-VCH Verlag
GmbH & Co. KGaA, Weinheim. .................................................................................................... 2
Figure 2 - Rouse theory describes a polymer chain as a series of balls connected by springs.A
hypothetical Rouse chain contains NR segments of 1 bead and 1 spring; beads have a designation
l which starts at 0 such that l = NR at the end of the chain. The end to end distance vector of the
chain is R, and the mean square length of a segment is aR, such that a Gaussian distribution of
segment lengths exist in the chain (length variability not represented above).22............................ 8
Figure 3 – Three mechanisms (M) and times (τ) are associated with lithium ion transport Rouse
model adapted theory of Maitra and Heuer. Lithium diffusion parallel to a chain, chain
relaxation, and chain to chain transfer.23 ...................................................................................... 10
Figure 4 – The Maitra and Hueur model as compared to experimental data. N denotes the
number of rouse segments in the model, while D is the coefficient of diffusion. Experimental
data comes from the work of Shi et al.42 DM is the coefficient of diffusion from the three
mechanisms discussed above and Dc.m. arises from diffusion of the polymer chain with associated
lithium ions. Figure 4 has been reprinted with permission from Maitra, A.; Hueur, A. Phys. Rev.
Lett. 2007, 98, 227802. http://journals.aps.org/prl/abstract/10.1103/PhysRevLett.98.227802
Copywrite 2007, American Physical Society. .............................................................................. 12
Figure 5 – Lithium ion transference, T+, is a figure of merit describing the relative mobility of
the cation and anion. It is defined as the ratio of the initial current which passes through an
electrolyte (which drops during discharge) and the current flowing once an equilibrium has been
established.4, 132 ............................................................................................................................. 14
Figure 6 – Silicate functionalized fillers used in the nanocomposites of the Baker (top) and
Archer groups (bottom two). 27,29,30............................................................................................... 16
Figure 7 – Monomers produced by Kerr et al. (left) produced a crosslinked single ion conducting
solid in the presence of a platinum catalyst. Endo et al. produced monomers (right) which could
produce the same effect when heated.32,33 .................................................................................... 17

xvii

Figure 8 – Nanoparticle designed of Asfour (top), and the most conductive design of Zhao
(middle) and an attempt to improve the interfacial properties of synthesized polyelectrolytes
(bottom). Polyelectrolytes allow for higher ratios of lithium to oxygen, but have not improved
conductive performance to date.4, 26.............................................................................................. 20
Figure 9 – Proposed fillers for nanocomposite conductors. Clickable Particle 9 can be used to
access designs 10 and 23 among others. ....................................................................................... 23
Figure 10 – Tethering anions to a host material has a dramatic deleterious effect on the
conductivity of single ion conductors.20 Image reprinted with permission from Borodin, O.;
Smith, G. D.; Geiculescu, O.; Creager, S. E.; Hallac, B.; DesMarteau, D. J. Phys. Chem. B 2006,
110, 24266 – 24274. Copywrite 2006, American Chemical Society........................................... 24
Figure 11 – Ohno-like triple ions proposed as novel single ion conductors. ................................ 28
Figure 12 – Three attempts to synthesize triple ions. The last of these featured TPS, a previously
unknown molecule whose reactivity was much less pronounced than expected, sparked interest
in the nucleofugality of polyatomic anionic nitrogen nucleofuges. .............................................. 29
Figure 13 – As more solvent moieties are added to the lithium coordination sphere the average
bond strength decreases, effecting both triazole and ether ligands. Triazoles can interact with the
2p orbitals of the lithium ion leading to net stabilization in the two and three coordinate
complexes which are planar. Lithium becomes sp3 hybridized in the tetracoordinate complex,
and this effect is seen to diminish. Simulations and experimental data have shown four and five
membered complexes to be most common in polyether ion conductors.19 .................................. 49
Figure 14 – Gas phase lithium ion to ligand affinities in experiment and theory. Typical
agreement between the experiments of Rodgers et al.51-54 and the MP2(full)/Aug-cc-pVTZ(LiC)//MP2(full)/cc-pVDZ(Li-C) calculations recommended by the same group for quantitatively
accurate lithium ion affinities are shown in (a) .51 Calculations typically over estimate affinities
relative to experiment but are usually within 10 kJ/mol, which is comparable to the uncertainty
of the experiment. In (b) G3 methods were compared to the methods of Rodgers et al. due to
unfavorable scaling of the latter to larger ligand systems.51 The computational expense of G3 is
similar to that of the Rodgers method, with G3(MP2) being somewhat cheaper. G3(MP2) was
found to be in better agreement with experiment due to being consistently lower in its energy
estimates. ....................................................................................................................................... 50

xviii

Figure 15 – Conductivity of oligomer salt complexes. In (a) model oligomer salt complexes were
run at a concentration of 1 Li : 64 ligand atoms, where two of the triazole nitrogens were
considered ligands (but not the pyrrole-like nitrogen) run with PEG 500 dimethyl ether controls.
Model oligomers and the PEG control were run with LiTFSI, while a variable concentration
standards curve was run with LiClO4. In (b) the same data shown without standards. ................ 54
Figure 16 – Descriptions of trends in the conductivity of oligomer salt complexes. In part (a) a
strong correlation between conductivity at 30°C and the glass transition temperature is found
within the model series. In part (b) a linear relation is shown between the pre-exponential factor
and activation derived from Arrhenius plotting in PEG and the triazole containing model
compounds. ................................................................................................................................... 55
Figure 17 – Single crystal X-ray diffraction of 6EO2T. In part (a) the Single Crystal XRD
structure of 6EO2T is shown with thermal elipsoids set at 50% probability. Packing as viewed
from the b axis of the 6EO2T crystal is shown in (b) and the c axis in (c). While a layered
structure is evident in the crystal, pi-pi stacking interactions and hydrogen bonding appear to be
absent. The angle shown in (c) reveals that triazole moieties align roughly along the dipole of the
ring within the layers. ................................................................................................................... 57
Figure 18 – Computed Barrier Heights from the MP2/G3large level of theory. Thermal
corrections for the ΔH values were computed at 298K. ............................................................... 78
Figure 19 – Barrier heights are very well predicted by methyl cation affinities within subsets
derived from oxygen and nitrogen, but less so in the full set. Nitrogen leaving groups universally
have higher barriers at a given value of MCA. ............................................................................. 83
Figure 20 – Correlations between ΔES→Ts, MCA and bond length. ΔES→Ts correlates very
strongly to methyl leaving group bond length, as a percentage of its value in the parent
methylating agent at its ground state (a) This is also true for the MCA (b) which shows that our
simulated reactions obey the Hammond postulate........................................................................ 84
Figure 21 – Dependence of activation energy on theoretical method. At HF/6-31G(d) Methyl FSI
and Methylfluorosulfonate have the same activation energy. When the wave function is
correlated FSI is found to have a higher activation energy by several kcal/mol. Additional MP2
and CCSD(T) calculations at the MP2(full)/6-31G(d) geometry confirm this trend. Of the leaving
groups calculated, only the sulfonimides show a higher activation energy at MP2(full)/6-31G(d)
than HF/6-31G(d).......................................................................................................................... 85

xix

Figure 22 – Nitrogen leaving groups exhibit more extensive C-X bond elongation in their
transition states than do oxygen groups. This is very apparent when raw bond lengths are
compared (a) But this trend holds up even when %C-X elongation is used to correct for the
longer C-N bonds present in the parent alkylating agents (b). ..................................................... 86
Figure 23 – A correlation is evident between the transition state HOMO energy and the
magnitude of ΔES→TS. ................................................................................................................... 88
Figure 24 – Natural charge on the leaving group atom correlates with ΔES→TS. ......................... 89
Figure 25 – The transition states of nitrogen leaving groups become progressively more bent as
C-X bond gets longer. No such trend occurs in oxygen leaving groups....................................... 90
Figure 26 – Some origins in the gap between the nucleofugality of sulfonimide and sulfonate
leaving groups can be linked to differences in the electronic structure. Imide spanning orbitals
such as HOMO-5 in FSI ( Top Left) have better overlap in the planar HF/6-31G(d) geometry (
left) In the MP2(full)/6-31G(d) geometry (Right) HOMO-5 and HOMO-6 mix. Presumably these
bonding interactions are opposed by n → σ* interactions localized to one sulfonyl group or the
other. ............................................................................................................................................. 92
Figure 27 – The crystal structure of TPS. A view of a single molecule is shown in part a with
thermal elipsoids shown at 50% probability. The packing along the b axis of the crystal is also
shown (b). ................................................................................................................................... 109
Figure 28 – Homeodesmotic reactions used to calculate the strain energy of sulfonyl
herterocycles. .............................................................................................................................. 112
Figure 29 - 6EO2T ...................................................................................................................... 114
Figure 30 - 8EO2T ...................................................................................................................... 115
Figure 31 - 6EO1T ...................................................................................................................... 116
Figure 32 - 8EO1T ...................................................................................................................... 117
Figure 33 - N-Triflylpropanesultam (TPS) ................................................................................. 118

xx

LIST OF SCHEMES

Scheme 1 – Model compounds with whole number triazole to ether oxygen ratios. Each has a
name derived from the number of ether oxygens and triazoles in the compound, hence “8 ether
oxygens, 2 triazoles” becomes “8EO2T”...................................................................................... 33
Scheme 2 – Synthesis of triazole containing poly(ethylene glycol) based model oligomers ..... 38
Scheme 3 – Relevant energies are derived from electronic structures calculated along the
reaction coordinate of an SN2 reaction (A) The difference in energy between a methylating agent
in its bound state, and the sum of the separated ions after heterolytic cleavage is defined as the
methyl cation affinity (MCA) (B) ................................................................................................. 75
Scheme 4 – Alkylating agents and the names they are referred to by in this study.................... 77
Scheme 5 – Proposed materials and synthesis for the investigation of triazoles as an activating
moiety in lithium single ion conductors........................................................................................ 98
Scheme 6 – Synthetic Route from 1,3 Propane sultone to TPS. ................................................. 103

xxi

KEY TO ABBREVIATIONS

CUAAC – Copper Catalyzed Alkyne Azide Reaction
TPS- N-Triflylpropanesultam
PEG- Poly(ethylene glycol)
PEO – Poly(ethylene oxide)
DBP – dynamic bond percolation model
DDH – dynamically disordered hopping model
VTF – Vogel Tamman Fulcher
σ - conductivity
V – volts or potential
I – Current
R – Resistance or the Gas constant (context dependant)
G - Conductance
S - Siemens
Ω – Ohms
μ – mobility or dipole moment (context dependent)
q – charge
D – coefficient of diffusion
Λm – Molar conductivity
F – Faraday’s constant
T – Temperature
z - charge count
ν – stoichiometric coefficient
Tg – Glass transition temperature

xxii

Tm – Melting transition temperature
k or kB – Bolzmann’s constant
σ0 – exponential prefactor for conductivity in Arrhenius or VTF formalisms
Ea – activation energy
P(t) – probability of an event as a function of time
wi→j – Probability of a transition
τren – Renewal time
r - Displacement
<r2> - mean squared displacement of a particle (triangular braces always denote an ensemble
average)
Ts – Shifted temperature
TFSI – bis(trifluoromethanesulfonyl)imide
MSD(t) – mean squared displacement of a particle as a function of time
a(T) – temperature dependent shift factor
NR – the number of Rouse segments (a bead connected to a spring) in a modeled chain
l – numerical designation of a rouse segment
aR – mean squared distance between rouse beads
R – vector describing the shortest distance between the ends of a polymer chain
ζR – Coefficient of friction
M1 – mechanism 1 of Li+ diffusion (diffusion along polymer chains)
M2 - mechanism 2 of Li+ diffusion (diffusion mediated by chain deformation)
M3 – mechanism 3 of Li+ diffusion (diffusion by chain hopping)
τ1, τ2, and τ3 – times associated with the above mechanisms (M1 through M3)
R0 – initial value of R
Re – equilibrium value of R

xxiii

DM – diffusion resulting from the three mechanisms detailed above
Dc.m. – diffusion resulting from movement of a lithium resulting from center of mass
displacement of the polymer chain
T+ - Lithium ion transference number
PEGDME – Poly(ethylene glycol) dimethyl ether
APTES – 3-aminopropyltriethoxysilane
6EO2T – A model compound, “6 ether oxygens 2 triazoles”
8EO2T – “8 ether oxygens 2 triazoles”
8EO1T – “8 ether oxygens 1 triazole”
6EO1T – “6 ether oxygens 1 triazole”
GAMESS – General Atomic and Molecular Electronic Structure System – a computational
software package
HF – Hartree Fock
MP2 – Moller Plesset second order perturbation theory
MP2(full) – MP2 calculation where perturbative correction is applied to all electrons including
core electrons
MP2(FC) – MP2 “frozen core” where only valence electrons receive perturbative correction.
This is the default MP2 treatment, and FC need not be explicitly specified.
CCSD – Coupled Cluster Singles and Doubles
QCISD(T) – Quadratic Configuration Interaction Singles Doubles and non-iterative Triples
CCSD(T) – Coupled Cluster Singles Doubles and non-iterative Triples
B3LYP – “Becke 3 parameter Lee-Yang-Parr”, B3LYP is a hybrid functional and the most
common functional used in density functional theory.
G3 – Gaussian 3 theory
G3(MP2) – Gaussian 3 with reduced Moller Plesset order
cc-pVDZ or cc-pVTZ – common Dunning basis sets. DZ is double zeta TZ is triple zeta
Aug-cc-pVNZ – Dunning basis set with added diffuse functions

xxiv

Aug-cc-pVNZ(Li-C) – Dunning basis set with core correlation functions on lithium
3-21G – a Pople minimal basis set
6-31G(d) – a common Pople basis set of double zeta quality. Contains a d function for
polarization on first row atoms.
ΔE – a change in energy
ΔEass – association energy of a ligand to a metal
Ecomplex – the energy of a complex
Eligand – the energy of a ligand
ELi – energy of a lithium atom or ion
THF – tetrahydrofuran
NMR – nuclear magnetic resonance spectroscopy
IR – infrared spectroscopy
Ts – Tosyl or p-toluenesulfonyl
4-MEOMET – 4-methoxymethyltriazole
1-MEOET – 1-methoxyethyltriazole
Mn – number average molecular weight
Å – angstrom
TD – Disordering temperature
εs – static dielectric constant
Nd – dipole density
D – Debye (chapter 2 only)
I – Ionization energy (chapter 3 only)
A – Electron affinity (chapter 3 only)
μ – electronic chemical potential (chapter 3 only)
η – chemical hardness (chapter 3 only)

xxv

ω – electrophilicity
ΔEnucleofuge – an energy scale to describe the ease with which a nucleofuge departs
HPCC – High Performance Computing Cluster
MAD – Mean Average Deviation
MCA – Methyl Cation Affinity
ΔES→TS – the difference between separated species and transition states
ΔE‡ - the difference between an association complex and a transition state
%BE – percentage bond elongation
MSI – (methylsulfonyl)imide
FSI – (fluorosulfonyl)imide
FSA – fluorosulfonamide
MSA – methylsulfonamide
MeiprFSA – methyl isopropyl fluorosulfonamide
Ec – Crossing energy
B – quantum mechanical resonance energy (chapter 3 only)
HOMO – Highest Occupied Molecular Orbital
LUMO – Lowest Unoccupied Molecular Orbital
s – singlet
d – doublet
dd – doublet of doublets
t – triplet
q – quartet
p – pentet
m - multiplet

xxvi

1
1.1

Chapter 1: Introduction
General Background
In the overall scheme of fuels and energy storage technology, batteries play an important

and ever increasing role. With an increasing need for a sustainable, carbon-neutral energy
economy, the need for safe, energy dense batteries capable of translating electrical energy into
such technologies as light duty vehicles is also increasing.1 Lithium ion batteries are one of the
most famous and promising technologies with the potential to fill this niche.2
The Lithium ion battery was first proposed in 1976 based on lithium intercalation into a
TiS2 cathode.3 Energy storage in a lithium ion battery is facilitated by the difference in electron
affinity between Li0, which is strongly electropositive, and an oxidizing transition metal center.4
During the discharge process of the battery, electrons flow from the anode (lithium metal or an
intercalation compound such as lithium intercalated graphite) through an outside circuit,
providing energy to a device, and finally to the cathode where they reduce the cathode material,
which is usually a transition metal chalcogenide.1 The accompanying process within the cell
consists of lithium atoms undergoing oxidation in the anode and traveling as Li+ through the
electrolyte and into the cathode, where they intercalate to balance the reduction of the cathode
material.1

1

Figure 1 - A Schematic of a lithium ion battery, featuring typical materials for the anode
(graphite) and the cathode (LiCoO2). A likely choice of electrolyte would be ethylene carbonate
and dimethyl carbonate 1:1.1 Figure 1 is reprinted with permission from Bruce, P.; Scrosati, B.;
Tarascon, J. Angew. Chem. Int. Ed. 2008, 47, 2930 – 2946. Copywrite 2008 Wiley-VCH Verlag
GmbH & Co. KGaA, Weinheim.
The electrolyte of a lithium ion battery is a solvent capable of dissociating a lithium salt,
and allowing the ions to migrate under an applied potential. Such solvents must be relatively
polar, and relatively unreactive toward the anode and cathode.4,5 The most common choices of
electrolytes are solutions of the lithium salts of strong acids such as LiSO3CF3 or LiClO4, in polar
aprotic organic solvents such as propylene carbonate, dimethyl carbonate or tetrahydrofuran.4,6
The conductivities of optimized electrolytes of this class may be as high as 10-2 S/cm at room
temperature.4,6
Most of the drawbacks of liquid electrolytes are straightforward consequences of the fact
that they are organic liquids. Organic electrolytes are flammable, and may leak from a damaged
battery casing.7 Lithium metal anodes may not be used with most liquid electrolytes, as they are

2

too reactive.4,7 Additionally, the application of an over potential during the charging process can
cause dendrites of lithium metal to form which can lead to reduced capacity and failure of the
battery.4,7 These drawbacks have led to the development of solid polymer electrolytes,
particularly for applications in electric vehicles.7
Solid polymer electrolytes should, in theory, be capable of resolving many of the
problems associated with liquid electrolytes, and these systems have been the focus of intensive
study since Wright and Armand first reported the conductivity of salt complexes of polyethylene
glycol in the late 1970s.5 Polyethylene glycol (PEG or PEO) is a linear polymer of the formula
(CH2CH2O)n which is capable of acting as a solvent for alkali metal salts. Polyethylene glycol
based electrolytes run into their own problems, however, due to ionic conductivities which are
dramatically lower than those of liquid electrolytes; on the order of 10-5 S/cm or less.
1.2

Physical Models of Lithium Ion Transport in Liquid and Polymer Electrolytes
The conductivity of a lithium electrolyte is the inverse of its resistance as given by Ohm’s

law V=IR, such that conductivity (σ) can be understood as a measure of current (I) per unit
potential (V).4,5 Conductivity is an intensive property of the system derived from the extensive
property Conductance (G) through the relation σ=Gl/A, where A is the cross sectional area of a
sample and l is the thickness.8 G is typically reported in Siemens (S) which are the inverse of
Ohms (Ω) the SI unit for resistance. Conductivity is therefore typically given in S/cm.
Physics and physical chemistry have well defined tools for understanding the
conductivity of dilute aqueous solutions of ions, which have been understood for decades. If full
dissociation and independent motion of ions are assumed, then conductivity can be related to the
mobilities of the ions by the Kohl-Rausch summation:

3

𝜎 = ∑𝑖 𝜇𝑖 𝑛𝑖 𝑞𝑖

(eq. 1)

where μ is the carrier mobility, n is the carrier concentration, and q is the charge of the carrier
species in the electrolyte.4,5,9 Additionally, molar conductivity (Λm) can be related to the sum of
the coefficients of diffusion (D) of ions in a solution by the Nernst-Einstein equation:
𝐹2

𝛬𝑚 = 𝑅𝑇 ∑𝑖 𝐷𝑖 𝑧𝑖2 𝜈𝑖

(eq. 2)

Where F is Faraday’s constant, R is the gas constant; T is the temperature of the system, z is the
charge of the ion and ν is the count of the ion in the chemical formula (e.g. the Cl(-) in ZnCl2
would have ν = 2, while Zn(2+) would have z = 2).5,8,9 Conceptually, these relationships still
hold in liquid and solid polymeric lithium ion electrolytes, but they become less and less useful
for describing the conductivity of a system, as lithium ion conductors tend to be more
concentrated, non-aqueous, and have less than full dissociation.5,9,10
Polymer hosts for lithium electrolytes do exhibit local fluidity analogous to ionic
solutions, provided they are amorphous rather than crystalline, and provided they are above their
glass transition temperature (Tg).5 The importance of side chain flexibility can be understood by
invoking the Vogel Tamman Fulcher (VTF) model of conductivity, a modified Arrhenius
equation:
−𝐵

𝜎𝑇 = 𝜎0 𝑒 𝑘(𝑇−𝑇0)

(eq. 3)

wherein temperature T is normalized by subtracting the equilibrium glass transition temperature
T0 which is generally considered to be a value ‘close to’ but not equal to Tg.5 This rationalization

4

is made based on the fact that the polymer behaves as a frozen solid beneath its glass transition
temperature, and thermal energy cannot enhance segmental motion below this point.5
Ratner, Nitzan and co-workers have attempted to derive a more satisfactory model, a
Dynamic Bond Percolation theory (DBP) their model builds on static bond percolation: a
microscopic theory of diffusion based on the probability of ionic movement in a disordered
material whose local structure is stationary.5, 9, 11-15 Ratner et al. begin by defining a static bond
percolation theory in a system of 1 spatial dimension, with an immobile lattice and spaces in the
lattice which may or may not contain particles.11 There is said to be a “bond” between any two
sites in the lattice with a traversable path between them, and the bond is “filled” if a particle is
present in one of the sites and can traverse the path. The transport of ions can be described in this
system by first defining P(t) the probability of a particle being at a given site i per unit time, t.11
A related quantity is defined which describes the probability of a particle traveling from site i to
an adjacent site j : this is wi→j.11 From here diffusive behavior can be derived from a differential
equation which relates the evolution of probability with time to a sum of probabilities across the
full lattice:
𝑑𝑃
𝑑𝑡

(𝑡) = ∑𝑗≠𝑖{𝑃𝑗 (𝑡)𝑤𝑗→𝑖 − 𝑃𝑖 (𝑡)𝑤𝑖→𝑗 }

(eq. 4)

A variety of individual restrictions apply to the migration probabilities which are
explained in detail in the paper. However we can generalize that in cases where sites i and j are
unconnected, or a lattice element or particle prevents migration, w is set to zero.11 A similar, but
more general model, known as the Dynamically Disordered Hopping (DDH) model was also
derived in which some of the conditions for hopping are relaxed, the most notable of these being
the condition that hopping only occur between a site and its nearest neighbor.12

5

The key feature of the DBP and DDH models, is that the lattice is not static, but rather
bonds i→j may open and close via time dependent changes in the lattice configuration. Ratner et
al. therefore define a renewal time τren after which the bonds in the lattice are randomly assigned
to be open or closed.11 In their seminal paper on the model, Ratner et al. devised simulations of a
one dimensional system and reported that for running times greater than τren diffusive behavior
was observed. In a one dimensional system the coefficient of diffusion, D, is related to the
ensemble average of the squared distance traveled by a particle, <r2> over the renewal time, such
that D=<r2>/τren .11
After the initial formulation of the DBP and DDH models modifications and expansions
were proposed in order to make the theories more applicable to real systems. This included
developing a frequency dependent formalism, which is important because of the prevalence of
electrochemical impedance spectroscopy, which utilizes an AC potential in the analysis of
polymer electrolytes.12 Additionally, the idea of τren was further developed.13,15 Because dynamic
movements in a polymer host are thermal in nature, it was proposed that τren is temperature
dependant.13,15
A complementary approach to the theoretical methods of Ratner et al. for gaining
mechanistic insight into diffusive phenomena in lithium electrolytes, is the use of molecular
dynamics (MD) simulations. MD simulations have been used extensively in understanding the
microscopic dynamic behaviors of polymers generally, and this work has been the topic of at
least one review.16 In the field of polymer electrolytes, Grant Smith, Oleg Borodin, and coworkers have published a series of papers which bring significant new insight.17-21 The work of
these authors was not the first attempt to apply molecular dynamics to the diffusive behavior of
ions in a polymer matrix. They are notable, however, in their attention to detail in designing a

6

polarizable force field, capable of reproducing experimental diffusion measurements in models
of lithium tetrafluoroborate (LiBF4) doped PEO.17,18 Further studies focused on lithium
bis(trifluoromethanesulfonyl)imide (LiTFSI) doped PEO.19-21
The PEO/LiTFSI system utilized PEO chains in the Rouse dynamic regime (which
governs relatively short, unentangled polymers) with 54 repeating units (2380g/mol) at
temperatures ranging from 333 K to 423 K and salt concentrations ranging from 39 – 7.5
ethylene oxide units per lithium ion.19 The results were shown to be in good agreement with
experimental measures, both from diffusion NMR measurements, and structural characteristics.19
Lithium ions in the simulations were shown to have an average of 4.6 coordinating oxygens in
their first solvent shell, which was in good agreement with the 4.9 oxygen average found using
neutron diffraction.19 Additionally degree of dissociation was compared to inferred dissociation
from Raman data, and found to be in good agreement; degree of dissociation ranged from 0.95
(95% free ions) to 0.77, and was negatively correlated with concentration.19
Molecular dynamics simulations give detailed information about the movement of
particles in a system, so coefficients of diffusion can be calculated from the Einstein equation
such that
𝐷 = lim

𝑡→∞

〈𝑀𝑆𝐷(𝑡)〉

(eq. 5)

6𝑡

Where MSD(t) is the mean square displacement of a particle as a function of time.19 Smith and
Borodin then determined temperature dependent coefficients for the polymer host by scaling the
time domain obtained at 423K by a “temperature-dependent time-shift factor” such that
D(T)=D(423K)/a(T).19 This was done because of the excessive simulation time demands
involved in observing true diffusion at lower temperatures for a host polymer of this size.19

7

Once the simulations were shown to conform to experimental results, analyses of the
transport of TFSI(-) and Li(+) were conducted based on the observed trajectories. In contrast to
previous theory, two separate kinds of motion were found to contribute to the overall coefficient
of diffusion for the lithium ion.19 The first motion was a chain to chain transfer, which the
authors considered comparable to the “hops” described in dynamic bond percolation, while a
second type of diffusive motion consisted of diffusion of the lithium along the polymer chain.19
Additionally it was found that lithium ions could be grouped by mobility; lithium ions which had
undergone a chain to chain transfer event generally were more mobile than ions which had
remained complexed with a single polymer chain, while ions in complex with two separate
chains were the least mobile.19 A microscopic model of lithium ion transport was formulated
using the two different transport processes observed and the Monte Carlo algorithm for
simulating movement.19 This simplified simulation was able to reproduce results from the initial
runs.19

Figure 2 - Rouse theory describes a polymer chain as a series of balls connected by springs.A
hypothetical Rouse chain contains NR segments of 1 bead and 1 spring; beads have a designation
l which starts at 0 such that l = NR at the end of the chain. The end to end distance vector of the
chain is R, and the mean square length of a segment is aR, such that a Gaussian distribution of
segment lengths exist in the chain (length variability not represented above).22

8

The model proposed by Borodin and Smith was an improvement on standard dynamic
bond percolation, but it still did not explicitly incorporate any physical theories of polymer
dynamics. In order to address this omission Maitra and Heuer revisited the simulations and
proposed a microscopic theory of lithium transport using the formalisms of Rouse theory.22,23
Rouse theory is a model of polymer chain dynamics, in which molecular details of the
chain are absent, and the chain is instead modeled as a series of beads connected by springs.22
Each bead and the spring connected to it make a Rouse segment, such that NR Rouse segments
exist in the chain.22 When a polymer of know composition is modeled using this formalism, NR
will generally be less than the number of monomer units in the chain, and as such, Rouse theory
is not useful for describing movements at the level of conformational changes, and can only be
applied in order to model large scale coiling behavior.22 At any point there will exist a vector R
representing the distance from one end of the chain to another, and a mean square distance, aR,
defines the length of a Rouse segment (see figure 2). The velocity (drl/dt) of each bead
(designated l ) can then be written as a differential equation with a term for friction, ζR, and
forces originating from the nearest neighbor beads being given by a term deriving from spring
mechanics 3kbT/aR2, and the displacement vectors of the beads, such that the form of the
equation is
𝜁R

𝑑𝒓𝑙
𝑑𝑡

=

3𝑘𝐵 𝑇
2
𝑎R

(𝒓𝑙+1 − 𝒓𝑙 ) +

3𝑘𝐵 𝑇
2
𝑎R

(𝒓𝑙−1 − 𝒓𝑙 )

(eq. 6)

As such this is a description of velocity that derives from a restoring force that a bead feels when
the displacements r-r between the bead and its neighbor differ from the equilibrium distance
aR2.22

9

Figure 3 – Three mechanisms (M) and times (τ) are associated with lithium ion transport Rouse
model adapted theory of Maitra and Heuer. Lithium diffusion parallel to a chain, chain
relaxation, and chain to chain transfer.23
There will be one such equation for each segment in the model, and solving the set of
equations leads to a set of eigenvalues known as the rouse modes, which describe the motions of
the polymer chain. The lowest order mode designated mode 0 describes translational motion of
the polymer, and as the mode number increases the motions described become increasingly more
localized, such that most of the motion occurs in the lower order modes.22
Maitra et al. approached the problem by first defining three mechanisms for transport in
polymer hosts. Mechanism 1 (M1) is defined as the motion of lithium ions along polymer chains,
mechanism 2 (M2) is Rouse mediated diffusion, not including displacement of the lithium ion as
a result of translational motion of the polymer, and M3 is transfer of a lithium ion from one chain
to another (see figure 3).23 Each mechanism has an associated time τ1, τ2, and τ3 so lithium
diffusion DLi can be written as a function DLi= Dc.m.+ DM(τ1, τ2, τ3) where Dc.m. is lithium ion
transport mediated by diffusion of the ion in concert with the polymer chain such that the center
of mass of the chain is displaced (i.e. movement arising from Rouse mode 0).23 The times τ1 and

10

τ3 are relatively straightforward to understand, but τ2 is related to a quantity τR which is the
Rouse time or relaxation time of the polymer chain. This is the time associated with relaxation;
the process where the initial end to end distance of the polymer, R0, approaches its equilibrium
value Re. Rouse time τR is a property of a neat polymer medium, but the presence of complexing
ions slows down relaxation, creating a need for a separate value τ2 to describe the equivalent time
in a chain with an associated ion.23
The authors then derived approximate analytical expressions for the dependence of DM
on the various times associated with each mechanism. The reader is referred to the paper for the
full derivation, but it is necessary to clarify that the authors have used 1/τ12= 1/τ1 + 1/τ2 for
convenience in the result. It was shown that the result depends on the relative magnitude of the
times involved such that
𝑹2𝑒

𝐷𝑀 = 6𝜋 (𝜏
𝐷𝑀 =

1
3 𝜏12

𝑹2𝑒
18𝜏3

)

1
2

when τ3 << τ12

(eq. 7)

when τ3 >> τ12

(eq. 8)

In order to make sense of this model and connect it to DBP theory, it should be noted that
as the size of the polymer chains of increases (increasing NR) τ12 should increase.23 Furthermore
the authors felt that τ3 should be proportional to the τren described in DBP, as they describe a
similar process. It is therefore shown that in systems of large polymers DBP can systematically
err due to the increasing contribution of diffusion along polymer chains and with the chains as
they relax.23
Finally, the authors compared their model with data from simulations similar to those of
Borodin et al. and experimental diffusion data from 7Li pulse gradient spin echo experiments,

11

and estimated the dependence of diffusivity on Rouse number NR, which for this study was
defined as the number of monomer units. Results are shown in figure 4.23

Figure 4 – The Maitra and Hueur model as compared to experimental data. N denotes the
number of rouse segments in the model, while D is the coefficient of diffusion. Experimental
data comes from the work of Shi et al.42 DM is the coefficient of diffusion from the three
mechanisms discussed above and Dc.m. arises from diffusion of the polymer chain with associated
lithium ions. Figure 4 has been reprinted with permission from Maitra, A.; Hueur, A. Phys. Rev.
Lett. 2007, 98, 227802. http://journals.aps.org/prl/abstract/10.1103/PhysRevLett.98.227802
Copywrite 2007, American Physical Society.
Using this data we can come up with a few generalizations about the low conductivity of
dry polymers. Most importantly Maitra et al. show that as NR increases DM stays relatively
constant but Dc.m. approaches zero.23 This implies that most of the loss in conductivity between
liquids and dry polymers is from Dc.m.. It follows that a liquid component is probably important
for all or most electrolyte design. An important limitation to note about this model is that it does
not take phenomena such as polymer crystallization or entanglement into account, which could
additionally diminish both modes of conductivity, and cause departure from predicted behavior.

12

1.3

Electrolyte Polarization in Lithium Ion Batteries
Aside from low conductivity, the next problematic behavior exhibited by polymer

electrolytes is anion mediated polarization. As the cations percolate through the polymer matrix,
the anions are also free to move, and migrate in the direction of the anode. This movement
results in a high concentration of anions near the anode which experience a coulombic attraction
to cations moving toward the cathode; hindering their mobility, and leading to a reduction of
current density in the outside circuit. Anions are often 5 to 10 times more mobile than the lithium
cations in common electrolyte materials.4
The figure of merit used to describe polarization in an electrolyte is the lithium
transference number, T+, which is defined by two values of DC current.132 The initial value of
DC current, I0, will be high, because it accounts for both anionic and cationic diffusion. The
current drops as the electrolyte polarizes, until it reaches an equilibrium value Is, which is
considered to be an approximate value of the portion of current due to cation diffusion. Lithium
ion transference T+ is computed simply as T+ = Is/I0 and is interpreted to be related to the relative
mobilities of the cation relative to the anion.132 When transference is measured experimentally
though, these values are not measured directly, but rather calculated from DC conductivity
values.132 The reader is referred to the work of Bruce et al. for the details of this experimental
setup and calculation.132 Figure 5 illustrates the concept of polarization and its relationship to T+.
Literature strategies for improving solid or solid like lithium ion electrolytes typically
focus on one or both of these problems, with optimization of the overall carrier mobility being
emphasized over selective lithium ion transference. Electrolytes that have value of T+ which
approach unity are termed single ion conductors and resist polarization because the only mobile
ions in the system are lithium ions, and therefore I0 = Is for these systems.

13

Figure 5 – Lithium ion transference, T+, is a figure of merit describing the relative mobility of
the cation and anion. It is defined as the ratio of the initial current which passes through an
electrolyte (which drops during discharge) and the current flowing once an equilibrium has been
established.4, 132
1.4

Design Strategies for the Improvement of Lithium Ion Electrolyte Performance
In attempts to make dry polymer electrolytes which are more conductive than high

molecular weight PEG, many polymers have been synthesized and characterized for
conductivity.7 These schemes included linear polymers aimed at preventing crystallization, and
at improving segmental mobility, and “comb like” polymers with low molecular weight side
chains. However dry systems have invariably shown suboptimal conductivity.4,7 Conductivity
can be improved through the use of “gel” electrolytes, which are comprised of a porous solid
polymer membrane which has been swelled by an organic solvent.7 Gel like systems can be as
conductive as liquids, as the conductivity is mediated by the solvent, rather than the motion of
the polymer chains. However they may lose of mechanical stability, as well as electrochemical
stability, due to the reactivity of the solvent toward the anode.6,7
A third class of materials has been assembled in an attempt to improve the conductive
properties of polymer electrolytes by blending them with inorganic filler materials. In the late

14

1990s Scrosati and coworkers reported a composite of PEG with TiO2 nanoparticles, which they
showed to enhance the mechanical strength of the material, as well as the interfacial stability
with a lithium electrode.26 These materials were later shown to have the effect of reducing
crystallinity in the electrolyte, by providing so many nucleation centers for the formation of
crystals that the formation of a lattice is actually impeded by the competing affects.1,4,7,26
A similar approach was employed by the Baker group during this time period. A low
molecular weight PEG dimethyl ether, which is a highly conductive liquid, was used as a
conductive media.27,28 Mechanical support was provided by a variety of surface functionalized
fumed silica particles (fig.4), which could be dispersed in the PEG and cured using a UV
crosslinking reaction. These electrolyte systems showed improved mechanical strength, and
conductivities in the range of 10-4 – 10-3 S/cm.27,28
A more recent approach involves the direct functionalization of silica or zirconia
nanoparticles with a conductive medium, of either PEG or ionic liquid derivation.8,29,30 PEG
derivatives were bound directly to the nanoparticles, using either a covalent silicate linkage, or
acid base chemistry between amine functionalized particles, and sulfonic acid functionalized
PEG chains.24 PEG functionalized particles were doped with 1M lithium
Bis(trifluoromethane)sulfonimide (TFSI), and showed molecular weight dependant conductivity,
which was above 10-4 S/cm for some materials.24 Additionally, silicate functionalized particles
with a corona of 400 molecular weight PEG (fig.4) were blended with poly(ethylene glycol)
dimethyl ether 250 (PEGDME250) a short polyethylene glycol chain terminated with a methyl
ether at each end. This improved the conductivity of the system over that of the solvent free
particles.30 It was shown that the onset of solid like behavior occurs in the PEGDME at a
composition of roughly 38% particles (v/v), at which point the system has a conductivity of

15

nearly 10-3 S/cm.30 While the ionic liquid functionalized particle is an intriguing idea, this system
had lower performance at room temperature; on the order of 10-5 to 10-6 S/cm.29

Figure 6 – Silicate functionalized fillers used in the nanocomposites of the Baker (top) and
Archer groups (bottom two). 27,29,30
The problem of lithium transference in polymer electrolytes has also been an area of prolific
research, with many of the proposed schemes involving synthetic modifications of PEG derived
macromolecules. Published polymeric single ion conductors chiefly employ one of two common
strategies to suppress anion movement; Lewis acidic anion receptors can be installed in the
polymer, to bind anions after the introduction of a lithium salt,31 or a polyelectrolyte can be
synthesized, consisting of polymer bound anions with lithium counter ions.32,33
Mehta, Inoue and colleagues offer a representative example of the anion receptor
approach.31 Their material is composed of a blend of PEG mono methyl ether and triethylene
glycol which is condensed in the presence of boroxine, to yield a solid material composed of

16

branched PEG chains with Lewis acidic boroxine rings at the branch points. This material is
compatible with a variety of common lithium salts, including LiTFSI, LiClO4 and lithium
triflate. Transference numbers measured for lithium were in the range of 0.62-0.88 (where a
value of unity indicates that all current is a result of lithium transport) which is a significant
improvement over the typical values given for PEG of 0.15 – 0.45.31 Single ion conductive
systems unfortunately are also subject to problems of low conductivity; values for this system
were on the order of 10-5 – 10-7 S/cm.31

Figure 7 – Monomers produced by Kerr et al. (left) produced a crosslinked single ion conducting
solid in the presence of a platinum catalyst. Endo et al. produced monomers (right) which could
produce the same effect when heated.32,33
A common approach for the production of single ion conductors based on covalently
bound anions is the synthesis of alkylated lithium salts, which can then be used to chemically
crosslink the conductive material in situ.32,33 The groups of Kerr and Endo have described
materials based on schemes such as these, relying on PEG derivatives and hydrosilation, or
epoxide ring opening chemistry respectively for crosslinking (fig 5).32,33

17

Ionic liquids have likewise been considered as candidates for high transference
electrolytes. Unlike most of the electrolytes previously discussed, ionic liquids are true liquids,
but their resistance to flammability, inherent conductivity, and low vapor pressure make them
good candidates for electrolyte materials.91 On the other hand, there is no obvious reason that a
conventional binary ionic liquid would offer an advantage with respect to Lithium transference.
Ohno and coworkers have made several attempts at designing selective lithium
conductors based on ionic liquids.123-125 One such attempt involved the use of linked zwitterions
blended with lithium TFSI.123 A set of zwitterions were synthesized, each of which contained a
cation and anion linked by an alkyl spacer group.123 The cation and anion chemistries were
varied in the study, and so was the length of the spacer group. While most of the zwitterions
themselves had melting points over 100 °C, it was discovered that some of them could be
blended with LiTFSI to make liquids. Unfortunately these liquids suffered from low conductivity
and low transference.123
A similar class of materials engineered by this group was composed of triple ions
containing two anions and one cation.124,125 The first of these was obtained by reacting
imidazoles with two equivalents of 1,3-propanesultone under basic conditions, which led to the
formation of imidazolium salts with twin sulfonate groups and an alkali metal counter ion.124 A
second class of similar materials was later developed, containing one borate and one sulfonate
group on an imidazolium scaffold.125 These classes of materials had lithium transference
numbers as high as 0.76. However the general tendency of these materials was to have a high
melting (Tm) and glass transition temperature (Tg).124,125 The materials with dual sulfonates were
the worst in this regard; they melted above 200 °C and had glass transitions around room
temperatures.124 The borate materials improved significantly; they were liquids with Tg as low as

18

-25 °C.125 The highest room temperature conductivity for any of these materials was below 10-7
S/cm, well below what would be useful in application.125
At least one novel approach has sought to avoid the limitations of dynamic percolation
altogether. In noting that PEG forms helical structures when crystalline34 Bruce and co-workers
authored several remarkable papers in which they sought to tune ionic mobility of lithium ions in
crystalline PEG lithium salt complexes.35-37 By crystallizing PEG with several different anions
including antimony hexafluoride or tetrafluoroborate it was possible to generate regular
structures, in which lithium ions were mobile, and could percolate down the helical channels in
the crystal structure of the polymer, with the counter ions trapped in the lattice. Successive
attempts were made to raise the room temperature conductivity of this system, which started on
the order of 10-7 to 10-8 S/cm, by using doping with different monovalent ions,35 doping with
divalent Li2SiF6 in order to increase the number of mobile lithium ions in the channels,36 and
using low molecular weight glymes as a host.37 Unfortunately, none of these strategies resulted
in a conductivity above 10-5 S/cm at room temperature.
1.5

Strategies of Single Ion Conductor Design from the Baker Research Group
Attempts to improve the lithium transference in polymer nanocomposites have been

made in the Baker Group starting with the work of Fadi Asfour in the early 2000s.26 This scheme
entailed grafting a single layer of trifluorosulfonamide terminated alkyl chains (Fig. 6) which
would be deprotonated using butyl lithium to yield nanoparticle localized negative charges,
which would then be combined with PEGDME 500 for analyses of conductivity. The particles
tested by Fadi had low loadings of lithium, limited by the grafting density of the particles. The
lithium to ether oxygen ratios tested were in the range of 1:250 to 1:710, depending on the

19

loading of nanoparticles, which increased to 40% w/w.26 Conductivities observed for this system
were on the order of 10-6 S/cm at 30°C.

Figure 8 – Nanoparticle designed of Asfour (top), and the most conductive design of Zhao
(middle) and an attempt to improve the interfacial properties of synthesized polyelectrolytes
(bottom). Polyelectrolytes allow for higher ratios of lithium to oxygen, but have not improved
conductive performance to date.4, 26
This work was continued by Hui Zhao, who designed a variety of nanocomposites with
many layers of ions, in an attempt to improve on earlier work by increasing the concentration of
lithium ions in the electrolye.4 These polymers are comb-like polyelectrolytes based on
hydrophobic alkyl chains constructed through radical polymerizations of functionalized styrenes
and methacrylates (Fig. 6). Oxygen to Lithium ratio in these experiments was in the range of
1:250 to 1:30, with optimal loading typically occurring in the neighborhood of 1:60. The best
system of Zhao’s devising has a measured room temperature conductivity of roughly 10-6 S/cm.4
This result was both surprising and disturbing, as he had increased the lithium ion concentration

20

of the system significantly relative to Asfour’s materials, but the performance he observed was
no better.
Several hypotheses were considered for why the higher lithium density polymers of Zhao
have not outperformed the monolayer particles of Asfour. In considering equation 1, it can be
reasoned that if carrier concentration has been increased, while new sets of carrier species have
not been introduced by experimental design; a comparable ionic conductivity should therefore
reflect an overall loss in the mobility of lithium. The most apparent potential problem of the
polyelectrolyte particles that our lab has so far produced is related to solubility. The significantly
lipophilic polymethacrylates and polystyrene backbones are being expected to interface with
water soluble PEGDME 500. Zhao has attempted to improve the interfacial properties between
the PEGDME500 and polyelectrolyte particles in the synthesis of a random copolymer of styrene
sulfonate and PEG methacrylate monomers (fig.6). This approach did not significantly improve
conductivity in composites.4
An additional consideration for the ionic mobility of a polyelectrolyte is the flexibility of
the particle bound chains. While differential scanning calorimetry data have not been published
on the polyelectrolyte particles to date, literature values put the Tg of 1 – 4 carbon n-alkyl
polymethacrylates in the range of 20 to 100°C43 indicating that a high glass transition may be a
problem for these materials.
Finally, we considered a problem which might reasonably be described as
“micropolarization”; in effect, when the concentration of charge carriers is increased in the
composite the new charges are all bound to particles. The particles are then introduced into
PEGDME 500 which has no charge carriers. As the lithium cations move under an applied

21

potential, the lithium cation becomes isolated in the PEGDME 500 and a coulombic attraction
builds between the negative charge left on the particle and the cation in the PEGDME. Mobile
cations must therefore pass from particle to particle, and the conductivity will be inversely
proportional to the distance between particles. A suggested fix for this would be the use of an
ionic liquid conductive media rather than PEGDME 500. Alternatively, at high concentrations of
particles this should become a negligible problem.
A solution I proposed for oral exam is shown below; it is composed of a silica
nanoparticle functionalized with a brush of alkyne terminated PEG chains (fig. 7). The alkyne
termination is intended to make use of the copper catalyzed alkyne azide cycloaddition
(CUAAC) “click” reaction, which exhibits excellent yield and conversion, with easily removable
side products.44 This allows rapid assembly of a nanoparticulate electrolyte system which was
designed to be tunable in lithium content and interfacial properties by “clicking” with alkylated
lithium salts of various derivations, chain lengths and lithium contents. Systems like this have
been reported previously in the literature,40,41 but, to the best of my knowledge such a scheme
has not been previously proposed for use as a lithium electrolyte material.

22

Figure 9 – Proposed fillers for nanocomposite conductors. Clickable Particle 9 can be used to
access designs 10 and 23 among others.
At the time of my oral however we were unaware of a helpful physical study into the
nature of the underlying problems with single ion conductors. This study will be described in the
next section.
1.6

Problems with Single Ion Conductors Demonstrated in Experiment and Simulation
Problems with single ion conductors have attracted interest from others, and in 2006 a

seminal paper was published exploring the fundamental problem with these materials. The paper
was a collaboration between the theorists Borodin and Smith, and the research group of Darryl
DesMarteau, an experienced fluorine chemist.20 In order to isolate the tethered anion as a
variable, the experimentalists compared a system of methyl capped PEO with 12 repeating units
(EO12/LiTFSI) with a synthetic analogue composed of a PEO system with a tethered
bis(sulfonimide) group closely resembling the TFSI(-) moiety (figure 10) .20

23

Figure 10 – Tethering anions to a host material has a dramatic deleterious effect on the
conductivity of single ion conductors.20 Image reprinted with permission from Borodin, O.;
Smith, G. D.; Geiculescu, O.; Creager, S. E.; Hallac, B.; DesMarteau, D. J. Phys. Chem. B 2006,
110, 24266 – 24274. Copywrite 2006, American Chemical Society.
Measurements done by the experimental part of the group provide a powerful
demonstration of the problems inherent in polymer single ion conductors. The data shown in fig.
10 indicates that at 294 K (21 °C) conductivity drops from roughly 10-3 S/cm (binary) to roughly
10-6 S/cm (tethered) or three orders of magnitude.20 This data puts the work of Zhao and Asfour
in a new light, as it demonstrates that the concerns about phase separation and Tg of particle

24

grafted polymers are probably not necessary to explain the low conductivity observed, because
neither would have been a factor in the work of DesMarteu et al.
Borodin et al. used this data as a benchmark for their MD simulations.20 The close
agreement between the experimental and simulated results lends credibility to insights drawn
from the simulated systems.
The authors looked at mechanisms similar to those described in the Rouse based model of
lithium ion transport detailed above. The authors mainly discussed conductivity resulting from
diffusion of a lithium ion with an associated chain, and conductivity resulting from migration of
a lithium between chains; to use the formalism developed later by Maitra et al., the first of these
would be Dc.m..20,23 When considering the contribution of DM, Borodin et al. explicitly consider
the effect of M3 (interchain transfer) and neglect M1, and M2.20,23 This is a defensible omission,
as the contribution of these mechanisms should be negligible for systems composed of short
chains which should be governed by the dependence described by equation 8.23
The most important difference between a tethered system and a binary system relates to
the nature of Dc.m. in these systems.20,23 Classical conductivity described by the Nernst/Einstein
equation (eq. 2) either assumes full dissociation (i. e. independent movement) of cations and
anions in the system, or explicitly includes a term, α, to describe the ratio of ions which are
diffusing independently of a counter ion.20 In a binary system this term is independent of Dc.m. as
a lithium ion may diffuse with a chain whether or not an anion is also associated.20 When the
anion is connected to the chain however, Dc.m. describes the diffusion of an associated ion pair by
definition, and does not contribute to the conductivity of an electrolyte unless multiple cations
are bound to the chain.20 This problem was evident in the α values reported for the two

25

electrolytes at 294 K, whereas the value in the binary electrolyte was 0.9, the tethered electrolyte
had an α value of 0.5.20
This change causes the conductivity to be more dependant on the rate of interchain
transfer events in the electrolyte with a tethered anion.20 Unfortunately, chain to chain transfer is
also retarded by the presence of an anionic head group on the chain.20 The reported Li(+)-chain
residence time ( analogous to the τ3 of Maitra et al.) was over twice as long for the tethered
system as it was for the binary system (~40 ns to ~90 ns) at ~90 °C.20
1.7

On the Construction of Lithium Single Ion Conductors and the Making of Lemonade
A critical reading of the literature on single ion conductors might seem like a hopeless

litany of failure, but this is not necessarily the case. While there is unlikely to be an organically
based lithium single ion conductor which is itself useful as an electrolyte, single ion conductors
such as the ones produced by DesMarteau or Ohno might be a useful additive to binary
electrolytes in order to reduce polarization without completely sacrificing conductivity.
On the other hand, research strategies that require difficult synthesis of elaborate
materials are probably a misguided way to approach the single ion conductor problem. Many
papers in the materials literature describe complicated materials designed to be applicable, rather
than simple materials designed to test a hypothesis. If no clear hypothesis is being tested,
disappointing results equate to wasted time, as it becomes difficult to draw conclusions from the
data. In this regard the work of DesMarteau and Borodin et al. is inspiring; regardless of whether
the single ion conductor they report is useful for application, the results are clearly interpretable
because of good study design, adequate controls, and the attention paid to rigorous mechanistic
interpretation of the results.

26

This change in thinking is the main reason why the synthesis and characterization of the
materials in figure 9 will not be reported in this work. Too many variables exist in such systems
to be adequately controlled for, and the synthesis of particle 9 is a difficult six step process with
two steps related to nanoparticle functionalization that are difficult to do reproducibly. Further,
functionalized nanoparticles produced from orthosilicate materials such as 3aminopropyltriethoxysilane (APTES) and its derivatives are chemically ill-defined due to
variables in functionalization density and oligomer formation. Finally, the work of DesMarteau
and Borodin et al. make the success of ionomer grafted nanoparticle designs of the sort that we
were considering seem unlikely.
While work in the style of Zhao and Asfour has been abandoned, the use of the CUAAC
reaction to construct lithium ion electrolytes is still an intriguing and untested idea. The CUAAC
reaction accomplishes a coupling by forming a triazole from alkyne and azide precursors.
However triazoles are not a common feature of lithium ion elecrolytes. Professor Baker was
interested in potential effects of triazoles on conductivity as an unintended consequence of
introducing them into the electrolytes, and encouraged Zhao to investigate this problem.126 Zhao
synthesized a series of polymer containing triazoles with molecular weights of roughly 104 g/mol
and showed that at 90 °C their salt composites had conductivity similar to that of PEG of a
similar molecular weight.126 A study which controls for dispersity, and analyzes this finding can
be found in chapter 2 of this document.
A second focus was the pursuit of a single ion conductor material to improve the chain to chain
transfer time of lithium ions. A class of triple ions similar to those of Ohno et al. was initially
proposed for this, partially owing to the fact that we were not aware of their work, and did not
expect the high Tm and Tg and low conductivity that they observed.124,125

27

Figure 11 – Ohno-like triple ions proposed as novel single ion conductors.
Synthesis of the triple ions shown in figure 11 proved to be a significant challenge and
several different routes were attempted in the process (figure 12). In one of the routes attempted,
an analogue of 1,3-propanesultone which we called N-triflylpropanesultam (TPS) was used as a
precursor to the triple ion. A synthesis of TPS was devised and successfully executed, but the
difficulties of obtaining pure samples of triple ions, and the discovery of Ohno’s work led to the
abandonment of the triple ion project. Instead attempts were made to map the reactivity of TPS
and establish whether it could be a useful material for producing alkylated TFSI-like anions.
Initial expectations were that TPS would be a highly reactive material given that it
contained a nitrogen leaving group which had two sulfonyl groups and ring strain activating it.
Preliminary exploration in the beginning of the triple ion project had suggested that alkylated
TFSI materials were very powerful alkylating agents. Several experiments were done in which
amines were quaternized with these materials in good yield with modest reaction times. However

28

TPS had to be boiled with an amine for days in order to react, and it often gave significant
amounts of side products resulting from nucleophilic attack at sulfur.

Figure 12 – Three attempts to synthesize triple ions. The last of these featured TPS, a previously
unknown molecule whose reactivity was much less pronounced than expected, sparked interest
in the nucleofugality of polyatomic anionic nitrogen nucleofuges.
While the reactivity of TPS did not appear to be promising, the surprise of its relative
inertness seemed worth investigating. Computational studies were initiated which analyzed
Menshutkin reactions of polyatomic anionic leaving groups of nitrogen and oxygen in order to
better understand why TPS had been less reactive than expected. While the proceedings of this
study are probably of limited use to the materials chemistry community, there is ongoing

29

discussion in the physical chemistry literature about the precise nature of nucleofugalty (leaving
group ability) which would benefit from this research. This research appears in its entirety in
chapter 3 of this document.

30

2

2.1

Chapter 2: 1,2,3-Triazoles as Pseudo-Ether Moieties in Oligo (Ethylene Glycol) Based
Lithium Ion Electrolytes
Introduction
As the average global temperature continues to rise, the importance of finding novel,

clean strategies for generating and storing energy continues to be an imperative for scientists and
engineers. Lithium ion batteries were first demonstrated in the 1976,42 and research into cathode,
anode and electrolyte materials for lithium ion batteries continues to be avidly pursued today.
Polymer electrolytes were developed contemporaneously with lithium battery technologies,
however the conductivity of polymer electrolytes are often too low for use in lithium batteries.
In the interest of raising the conductivity of dry polymer electrolytes, many different host
polymers including polyethers, polysiloxanes, polyphosphazines, and architectures including
comb polymers and nanoparticle composites have been tried.7 Additionally, physical studies
have been performed and models proposed in order to rationalize lithium ion transport dynamics
in a polymer host.5,9 Among these models, one of the most prominent is the dynamic bond
percolation theory (DBP) of Ratner et al.11-15 DBP is formulated in terms of a renewal time τ in
which one path between coordination sites has opened and closed to each lithium ion in a
system. The conductivity of a system depends on the renewal time and therefore has been found
to depend on polymer segmental dynamics generally and the glass transition temperature (Tg)
specifically.15 Additional studies have utilized ab-initio calculations to show that glyme-derived
complexes with divergent geometries have similar energies within the same coordination
number, at coordination numbers of 4, 5 and 6 ether oxygens around lithium.43
A recently developing trend in polymer chemistry has been the application of click
chemistry; a set of reliably working, high efficiency reactions originally promoted for rapid

31

construction of complexity in drug discovery,39 which have been adopted by materials chemists
for such tasks as post synthetic modifications of polymers and surface functionalization of
nanoparticles, and the construction of dentrimers.44,45 One of the most common of these socalled “click” reactions is the copper catalyzed alkyne azide cycloaddition reaction (CuAAC) or
Huisgen reaction used to couple materials through the formation of a distinctive 1,2,3- triazole
motif.39 The 1,2,3-triazole species has been used in the manipulation of ionic species previously
in the design of anion receptors46 and occasionally proton conductors,47-49 however these
heterocycles have been use in only one lithium conductor that we are aware of.50
The decision by the materials community to eschew the use of the CuAAC reaction in the
development of lithium ion conductors may have its roots in concerns about the effect of the
1,2,3-triazole moiety formed in the reaction on the conductivity of the electrolyte. Deleterious
effects of on conductivity might reasonably include a net stiffening of the polymer material and
associated increase in the Tg,15 a decrease in lithium ion mobility due to a higher energy
association between the lithium cation and the triazole ring, or a loss of solubility of lithium due
to unfavorable association.43 Lithium ion affinities of various nitrogen heterocycles including 2H-1,2,3-triazole, 1-H-1,2,4-triazole and various other azoles and azines have been measured
using collision induced dissociation mass spectrometry, and calculated at various levels of
theory, by Rodgers and co-workers.51-54 These affinities typically exceed those measured and
calculated for dimethyl ether using the same methods (Fig. 14), making loss of solubility of
lithium salts seem unrealistic, but strong complex formation with lithium potentially
problematic.43

32

Scheme 1 – Model compounds with whole number triazole to ether oxygen ratios. Each has a
name derived from the number of ether oxygens and triazoles in the compound, hence “8 ether
oxygens, 2 triazoles” becomes “8EO2T”.
In order to investigate the effect of 1,2,3-triazole moieties on the conductivity of lithium
ion transporting polymers, we report a study on a series of monodisperse oligomer model
compounds (Scheme 1) with increasing 1,2,3-triazole to ether oxygen ratios. In order to build on
the work of Rodgers et al. we model hypothetical solvation shells for lithium ions using high
level ab initio calculations. Additionally we have synthesized the model compounds and
measured the conductivity of oligomer salt complexes using AC impedance spectroscopy.

33

Calculations and empirical modeling of the conductivity enable us to pinpoint dynamic effects
brought on by introduction of the stiff triazole moieties into the chain as the chief reason for
depressed conductivity in the model compounds.

2.2

Experimental

2.2.1 Computational methods
All calculations were initiated on the Cambridge Software Chem3D interface for General
Atomic and Molecular Electronic Structure System55 (GAMESS) in order to find coordinates for
the model compounds. Our main calculation for smaller models was the MP2(full)/Aug-ccpVTZ(Li-C)//MP2(full)/cc-pVDZ(Li-C) composite method previously reported by Rodgers et
al.51 This calculation was one of the best performers in a study conducted by these authors which
included high quality methods such as coupled cluster methods, complete basis set extrapolation,
and the Gaussian theory methods of Pople et al.51
Our models were typically run at the HF/3-21G level of theory prior to the application of
higher levels of theory, and in the case of 2, 3 and 4 coordinate models the complexes were
manipulated manually in the Chem3D interface to get the highest number of ligations possible
and minimized using the MM2 force field prior to minimization at HF/3-21G. Pre-optimization
calculations were run on a laptop. Starting points from HF/3-21G, were then optimized using
three composite methods: MP2(full)/Aug-cc-pVTZ(Li-C)//MP2(full)/cc-pVDZ(Li-C),51
Gaussian 3 (G3),56 or G3(MP2)57 using the Gaussian 03 computational package.58 The Aug-ccpVTZ(Li-C) and cc-pVDZ(Li-C) basis sets reported by Rodgers et al. were generated by
obtaining cc-pCVDZ and Aug-cc-pCVTZ basis sets59 for lithium from EMSL Basis Set

34

Exchange,60, 61 and applying them to the Li ion, while the other atoms received the parent ccpVDZ or Aug-cc-pVTZ basis set. This allocation was accomplished in Gaussian 03 through use
of the Gen keyword. Association energies (ΔEass) were calculated by comparison of the
minimized ligand to the complex and lithium ion such that
ΔEass = Ecomplex - Eligand -ELi

(eq. 9)

Zero point energy corrections were applied from the MP2(full)/cc-pVDZ(Li-C) level of
theory and scaled by a factor of 0.9646.51 The reader is referred to the original paper for
additional details on the MP2(full)/Aug-cc-pVTZ(Li-C)//MP2(full)/cc-pVDZ(Li-C)
calculation.51 G3 and G3(MP2) were used as implemented in Gaussian 03. All Gaussian 03
calculations were run on the MSU Chemistry Department hydra cluster.
2.2.2 Electrochemical Impedance Spectroscopy
All impedance spectroscopy was done on an HP4192A LF impedance analyzer setup
which has been fed into a Vacuum Atmospheres Dri-Train M040-1 model glove box with a
nitrogen atmosphere. Model compounds were rigorously dried in preparation for conductivity
measurements by stirring on a mass equivalent of 4 Å molecular sieves in dry ethyl ether or
dichloromethane. Following this the compounds were filtered and solvent was removed on a
standard rotovap connected to a vacuum aspirator. Finally, model compounds were placed on a
Schlenk line and heated to 70°C. The line was allowed to equilibrate to a pressure of < 100mTorr
which was sustained for at least 24 hours. Inhibitors were removed from PEG500 DME prior to
drying, by elution through a flash column with a dry ethyl ether mobile phase. All samples were
then inserted and stored in the glove box. Samples were prepared by addition of LiTFSI or
LiClO4 to the electrolyte media, followed by stirring until the salt composite became

35

homogenous. The amount of salt added was normalized to the number of ligand atoms in the
PEG 500 DME or model compound, such that a triazole was considered to have two ligand
atoms, and PEG 500 DME was considered to contain 12 ligand atoms on average. Samples were
loaded into a homemade coin cell with stainless steel blocking electrodes, and clamped together
with leads from the impedance analyzer in a homemade temperature controlled bell jar.
Measurements were taken from 30°C - 85°C, using a virtual instrument code written for Labview
5. Temperature control was adjusted manually, and is estimated to have a precision of +/- 1°C.

2.2.3 Single Crystal X-Ray Diffraction
Single crystals of 6EO2T (C9H16N3O3) were crystallized from toluene. A suitable crystal
was selected and mounted on a nylon loop using Paratone Oil. The crystal was kept at 173.01 K
during data collection. Data were collected using a Bruker APEX-II CCD (charge coupled
device) based diffractometer equipped with an Oxford Cryostream low-temperature apparatus
operating at 173 K. Data were measured using omega and phi scans of 0.5°per frame for 30 s.
The total number of images was based on results from the program COSMO,74 where
redundancy was expected to be 4.0 and completeness to 0.83 Å to 100%. Cell parameters were
retrieved using APEX II software75 and refined using SAINT on all observed reflections. Data
reduction was performed using the SAINT software76 which corrects for Lp. Scaling and
absorption corrections were applied using SADABS77 multi-scan technique, supplied by George
Sheldrick. Using Olex2,77 the structure was solved with the XS 78 structure solution program
using Direct Methods and refined with the XL 79 refinement package using Least Squares
minimisation.

36

The structure was solved in the space group C2/c (no. 15). All non-hydrogen atoms are
refined anisotropically. Hydrogens were calculated by geometrical methods and refined as a
riding model.

37

2.2.4 Synthesis of Model Compounds

Scheme 2 - Synthesis of triazole containing poly(ethylene glycol) based model oligomers

38

2.2.4.1 Materials and Instrumentation
Starting materials were procured and used as obtained from commercial suppliers
including Sigma-Aldrich, Alfa Aesir and Jade Scientific. NMR spectra were obtained using
Varian 500 MHz and 300 MHz instruments in the MSU NMR facility, all NMR specra were run
in CDCl3. IR Spectra were obtained using a Mattson Galaxy FTIR spectrometer. High resolution
mass spectrometry was performed by the MSU Mass Spectrometry Core using a Micromass QTOF Ultima instrument. Phase and glass transitions of the model compounds were measured
using the TA Q2000 Differential Scanning Calorimeter in the Composite Materials and
Structures Center at MSU College of Engineering.
2.2.4.2 Synthesis of Tosylates 1 – 5.
Method 162
Methoxy oligo(ethylene glycol) precursors and p-toluenesulfonylchloride (1.02 equiv. per
hydroxyl) were added to flask equipped with a mechanical stirring apparatus, and charged with
CH2Cl2 on ice, such that the concentration of the oligo(ethylene glycol) species was
approximately 0.95 M. Potassium hydroxide was then measured (4 equiv. per hydroxyl) and
added without crushing in portions over a one hour period. After the addition of the potassium
hydroxide pellets was complete, the ice bath was allowed to melt and warm to room temperature.
Stirring was allowed to continue for 24 hours. Reaction was quenched by the slow addition of
water until water soluble salts were dissolved. The layers were then separated, and the aqueous
layer extracted with two additional portions of CH2Cl2. The combined organic layer was dried
over sodium sulfate and solvent was removed on a Rotovap, followed by a hard vacuum. The
products were used without further purification.

39

Method 263
A tetrahydrofuran solution of the methoxy oligo(ethylene glycol) solution of roughly 0.75
M concentration was prepared in a round bottom flask with magnetic stirring. To this solution
1.5 equiv. of p-toluenesulfonyl chloride were added, and the flask was chilled on ice. To the
cooled flask a 16 M solution of potassium hydroxide (6.5 equiv. per hydroxyl group) in water
were added in parts over roughly 1 hour. Following addition of the potassium hydroxide, the ice
bath was removed. The reaction was then allowed to stir roughly 12 hours at room temperature.
The reaction was subsequently quenched by addition of the reaction mixture to 5 mL ice per mL
of the mixture and extracted with 3 portions of CH2Cl2. Drying and solvent removal proceeded
as in method 1. Product was used without further purification. This method was used for
compound 4 only and was discontinued due to poor yield.
2-methoxyethyl 4-methylbenzenesulfonate (1) 92% 1H NMR (500 MHz) (CDCl3) δ: 2.42 (s, 3H,
CH3O) 3.28 (s, 3H, Tosyl-CH3) 3.55 (dd, 2H, CH3OCH2, J= 5 Hz, J= 5 Hz) 4.13 (dd, 2H,
TsOCH2, J= 5 Hz, J= 5 Hz) 7.31 (d, 2H, CH3CCHCHCSO3, J = 8 Hz) 7.77 (d, 2H,
CH3CCHCHCSO3, J = 8 Hz) 13C NMR (500 MHz) (CDCl3) δ: 21.82, 59.17, 69.25, 70.13,
128.16, 129.99, 133.25, 144.96

2-(2-methoxyethoxy)ethyl 4-methylbenzenesulfonate (2) 93% 1H NMR (500 MHz) (CDCl3) δ:
2.41 (s, 3H, CH3O) 3.31 (s, 3H, Tosyl-CH3) 3.45 (m, 2H, CH3OCH2) 3.53 (m, 2H,
CH3OCH2CH2) 3.65 (m, 2H, TsOCH2CH2) 4.13 (m, 2H, TsOCH2) 7.30 (d, 2H,
CH3CCHCHCSO3, J = 8 Hz) 7.76 (d, 2H, CH3CCHCHCSO3, J = 8 Hz) 13C NMR (600 MHz)
(CDCl3) δ: 21.79, 59.20, 68.88, 69.40, 70.85, 71.99, 128.16, 129.98, 133.19, 144.97

40

2-(2-(2-methoxyethoxy)ethoxy)ethyl 4-methylbenzenesulfonate (3) 91% 1H NMR (500 MHz)
(CDCl3) δ: 2.41 (s, 3H, CH3O) 3.31 (s, 3H, Tosyl-CH3) 3.49 (m, 2H, CH3OCH2) 3.57 (m, 6H,
OCH2CH2O) 3.64 (t, 2H, TsOCH2CH2, J= 5 Hz ) 4.12 (t, 2H, TsOCH2, J= 5 Hz ) 7.30 (d, 2H,
CH3CCHCHCSO3, J = 8 Hz) 7.75 (d, 2H, CH3CCHCHCSO3, J = 8 Hz) 13C NMR (500 MHz)
(CDCl3) δ: 21.76, 59.15, 68.82, 69.39, 70.69, 70.71, 70.89, 72.06, 128.11, 129.96, 133.23,
144.92
2,5,8,11-tetraoxatridecan-13-yl 4-methylbenzenesulfonate (4) 66% 1H NMR (500 MHz) (CDCl3)
δ: 2.41, (s, 3H, CH3O) 3.33 (m, 3H, Tosyl-CH3) 3.50 (m, 2H, CH3OCH2) 3.54 (m, 4H,
OCH2CH2O) 3.60 (m, 6H, OCH2CH2O) 3.65 (m, 2H, TsOCH2CH2) 4.13 (m, 2H, TsOCH2) 7.30
(d, 2H, CH3CCHCHCSO3) 7.75 (m, 2H, CH3CCHCHCSO3) 13C NMR (500 MHz) (CDCl3) δ:
21.79, 59.17, 68.81, 69.40, 70.67, 70.73, 70.74, 70.88, 72.07, 128.12, 129.97, 133.14, 144.95
(ethane-1,2-diylbis(oxy))bis(ethane-2,1-diyl) bis(4-methylbenzenesulfonate) (5) 81% 1H NMR
(500 MHz) (CDCl3) δ: 2.43 (s, 6H, Tosyl-CH3) 3.50 (s, 4H, OCH2CH2O) 3.63 (dd, 4H,
TsOCH2CH2O, J = 5 Hz J = 5 Hz ) 4.12 (dd, 4H, TsOCH2CH2O, J= 5 Hz J=5 Hz ) 7.33 (d, 4H,
CH3CCHCHCSO3, J = 8 Hz) 7.77 (d, 4H, CH3CCHCHCSO3, J = 8 Hz) 13C NMR (500Hz)
(CDCl3) δ: 21.27, 68.79, 69.37, 70.73, 128.026, 129.97, 132.97, 145.01
2.2.4.3 Synthesis of Azides 6 – 8
A flask was set up with a condenser magnetic stir bar, and charged with DMF, and a
tosylate precursor (3 – 5). Two equiv. sodium azide were then added such that 0.44 mol of
sodium azide were added per liter of DMF (note: sodium azide did not fully dissolve, and some
amount of precipitate persisted throughout reaction, intensifying as TsONa is produced). DMF
solution was heated to 70°C and allowed to react overnight or roughly 12 hours. DMF was

41

removed directly by distillation under reduced pressure. Concentrated reaction mixture and
solids were dissolved into 1 portion water and 1 portion diethyl ether. The layers were separated
and the water was washed with two additional portions of diethyl ether. The ether layer was
combined and dried over sodium sulfate and concentrated on a rotovap and a vacuum line.
Azides (especially 8) may be volatile enough that extended use of a vacuum pump will reduce
yield considerably. Residual DMF was removed by flash chromatography on a silica mobile
phase with diethyl ether eluent, followed by reconcentration.
WARNING: The synthesis and concentration of organic azides is an especially hazardous
procedure. Concentrated azides may detonate in contact with heat, reactive chemical species or
mechanical stimulation. Sodium azide can react to form extremely unstable compounds if
exposed to chlorinated solvents (including but not limited to dichloromethane and chloroform) or
transition metals. None of the azides described in this paper have caused the authors problems,
but scaling these procedures should not be done by anyone not experienced in the synthesis of
azides or related compounds. The authors, furthermore, make no representation that synthesis on
the scale done by the authors is safe for other chemists to attempt. Azides must be diluted in
solvent before catalyst is introduced in the CuAAC reaction, or potentially fatal explosions can
result. Azides were stored under nitrogen gas, and protected from light in a -20°C freezer.
Special caution should be used in the making and handling of compound 8.
1-azido-2-(2-(2-methoxyethoxy)ethoxy)ethane (6) 65% 1H NMR (500 MHz) (CDCl3) δ: 3.34 (m,
5H) 3.51 (m, 2H, CH3OCH2) 3.63 (m, 8H) 13C NMR (500Hz) (CDCl3) δ: 50.85, 59.15, 70.17,
70.76, 70.82, 70.86, 72.09

42

13-azido-2,5,8,11-tetraoxatridecane (7) 93% (500 MHz) (CDCl3) δ: 3.33 (m, 5H) 3.50 (m, 2H,
CH3OCH2) 3.63 (m, 12H) 13C NMR (500Hz) (CDCl3) δ: 50.79, 59.15, 70.14, 70.63, 70.73,
70.75, 70.77, 70.80, 72.05
1,2-bis(2-azidoethoxy)ethane (8) 91% 1H NMR (500 MHz) (CDCl3) δ: 3.36 (t, 4H, N3CH2, J = 5
Hz) 3.65 (m, 8H) 13C NMR (500Hz) (CDCl3) δ: 50.87, 70.31, 70.9
2.2.4.4 Synthesis of Alkynes 9 – 11
Tosylate precursor (1 – 3) was diluted in THF to a concentration of 0.5 M and chilled on ice in a
flask with magnetic stirring. In a separate flask a 1.2 M solution of propargyl alcohol (5 equiv.
per tosyl ester) was made in THF and chilled on an ice bath. NaH (60% dispersion in mineral oil,
2 equiv. per tosyl ester) was measured, and washed twice with hexane in order to remove the
mineral oil. After two washes, the NaH hexane slurry was added to the propargyl alcohol, and
the deprotonation was monitored visually by the release of hydrogen. NaH was added at a slow
enough rate that the bubbling was steady but not overly rapid. Bubbling was allowed to subside
completely, and solution was observed to clear. The partially deprotonated propargyl alcohol
solution was then carefully but rapidly poured into the tosylate solution, which was kept on ice
until the addition was complete. The reaction flask was allowed to stir on ice roughly 20 min
longer, after which time the ice was removed and the flask was stirred for 16 – 24 hours longer.
All portions of this reaction were carried out under nitrogen. Reaction was quenched by addition
of water until all solids are dissolved, followed by rotary evaporation to remove most of the
THF. The resulting aqueous layer was extracted three times with dichloromethane. The
combined organic layer was then dried over sodium sulfate and evaporated. Alkyne products
were purified by distillation under reduced pressure. (Note: this reaction should not be run more
concentrated than specified – concentration has been optimized against eliminative biproducts)

43

3-(2-methoxyethoxy)prop-1-yne (9) 45% 1H NMR (500 MHz) (CDCl3) δ: 2.40 (t, 1H, CH2CCH,
J = 2.4 Hz) 3.35 (s, 3H) 3.54 (m, 2H, CH2OCH3) 3.65 (m, 2H, CH2OCH2CC) 4.17 (d, 4.17, J =
2.4 Hz) 13C NMR (500Hz) (CDCl3) δ: 58.58, 59.20, 69.09, 71.83, 74.76, 79.70
3-(2-(2-methoxyethoxy)ethoxy)prop-1-yne (10) 71% 1H NMR (500 MHz) (CDCl3) δ: 2.39 (t,
1H, CH2CCH, J = 2.5 Hz) 3.33 (s, 3H, OCH3) 3.51 (m, 2H) 3.61 (m, 2H) 3.65 (m, 4H,
OCH2CH2O) 4.16 (d, 2H, CH2CCH, J = 2.4 Hz) 13C NMR (500Hz) (CDCl3) δ: 58.55, 59.19,
69.25, 70.58, 70.70, 72.06, 74.67, 79.79
2,5,8,11-tetraoxatetradec-13-yne (11) 80% 1H NMR (500 MHz) (CDCl3) δ: 2.38 (t, 1H,
CH2CCH, J = 2.4 Hz) 3.32 (s, 3H, OCH3) 3.49 (m, 2H, CH2OCH3) 3.61 (m, 10H, OCH2CH2O)
4.14 (d, 2H, CH2CCH, J = 2.5 Hz) 13C NMR (500Hz) (CDCl3) δ: 58.50, 59.14, 69.20, 70.52,
70.63, 70.71, 72.04, 74.64, 79.77
2.2.4.5 Synthesis of Model Compounds 12 – 15127
A magnetic stirrer, Azide (6 – 8) and chloroform (such that the concentration of
alkyne+azide in chloroform = 0.6M) were added to a Schlenk flask followed by the alkyne (9 –
11, 2.1 equiv. for azide 8, 1.2 equiv. otherwise). IMPORTANT: this order must be used; under
NO CIRCUMSTANCES should catalyst be added to neat precursor materials. Catalytic
Tris(triphenylphosphine)copper(I)bromide was then added at a rate of 2% mol relative to the
molar amount of the azide. Three freeze-pump-thaw cycles were carried out in order to de-gas
the reaction (synthesis of Tris(triphenylphosphine)copper(I)bromide is described elsewhere).
Following this the reaction was placed on an oil bath and heated to 60°C for 24h with stirring.
Nitrogen was not reintroduced into the reaction after the last freeze-pump-thaw, so the
atmosphere in the reaction should be mostly chloroform. Some refluxing off the side was

44

observed. Following the reaction, the chloroform was extracted with three washes of 0.1
disodium EDTA pH 8. In all cases the final EDTA wash was colorless. Aqueous layer was back
extracted once with CH2Cl2; the combined organic layer was then dried over sodium sulfate and
concentrated using a rotovap. Material was purified using silica gel chromatography with
CH2Cl2 eluent containing 8 – 10% methanol v/v%. Materials were pale yellow to colorless oils.
6EO2T was observed to crystalize spontaneously below room temperature.
12 6EO1T 3.9g, 70%
HR-ESI-MS Calculated C15H30N3O6 (M+H)+: 348.2135, Observed: 348.2138 1H NMR
(500MHz) (CDCl3) δ: 3.32 (s, 6H, OCH3) 3.50 (m, 4H, CH2OCH3) 3.57 (m, 12H, OCH2) 3.81
(t, 2H, N-CH2CH2O, J = ) 4.48 (t, 2H, N-CH2CH2-O, J=) 4.63 (s, 2H, OCH2-triazole) 7.70 (s,
1H, triazole H)

13

C NMR (500 MHz) (CDCl3) δ: 50.33, 59.15, 64.73, 69.59, 69.74, 70.61, 70.64,

70.66, 72.03, 123.93, 145.06 IR (neat): 3569 (water), 3136, 2873, 1956, 1641, 1547, 1460, 1353,
1247, 1199, 1102, 932, 850, 776
13 8EO1T 74%
HR-ESI-MS Calculated C19H38N3O8 (M+H)+: 436.2659, Observed: 436.2670 1H NMR
(500MHz) (CDCl3) δ: 3.32 (s, 6H, OCH3) 3.50 (m, 4H, CH2OCH3) 3.59 (m, 20H, OCH2) 3.82 (t,
2H, N-CH2CH2O, J = 5 Hz) 4.48 (t, 2H, N-CH2CH2-O, J = 5Hz ) 4.63 (s, 2H, OCH2-triazole)
7.69 (s, 1H, triazole H) 13C NMR (500 MHz) (CDCl3) δ: 50.35, 59.15, 64.74, 69.61, 69.76,
70.62, 70.65, 70.70, 70.73, 72.06, 123.92, 145.07 IR(neat): 3566 (water), 3137, 2873, 1957,
1645, 1545, 1457, 1351, 1297, 1247, 1199, 1105, 1048, 984, 850, 776

45

14 6EO2T 71%
HR-ESI-MS Calculated C18H33N6O6 (M+H)+: 429.2462, Observed: 429.2457 1H NMR (500
MHz) (CDCl3) δ = 3.31 (s, 6H, OCH3) 3.51 (m, 8H, OCH2) 3.64 (m, 4H, OCH2CH2OCH2triazole) 3.78 (t, 4H, N-CH2CH2O, J = 5Hz ) 4.47 (t, 4H, N-CH2CH2-O J= 5 Hz) 4.64 (s, 4H,
OCH2-triazole) 7.66 (s, 2H, triazole H) 13C NMR (500 MHz) (CDCl3) δ = 50.33, 59.13, 64.86,
69.60, 69.79, 70.56, 71.97, 76.97, 77.23, 77.48, 123.83, 145.12 IR(neat): 3537 (water), 3137,
2875, 1944, 1652, 1549, 1459, 1361, 1292, 1223, 1198, 1094, 1049, 982, 924, 892, 848, 776
15 8EO2T 77%
HR-ESI-MS Calculated C22H41N6O8 (M+H)+: 517.2986, Observed: 517.2992 1H NMR (500
MHz) (CDCl3) δ: 3.33 (s, 6H, OCH3) 3.51 (m, 8H, OCH2) 3.59 (m, 4H) 3.62 (m, 4H) 3.79 (t,
4H, N-CH2CH2O, J=5 Hz) 4.47 (t, 4H, N-CH2CH2-O, J=5 Hz ) 4.64 (s, 4H, OCH2-triazole)
7.67 (s, 2H, triazole H) 13C NMR (600 MHz) (CDCl3) δ = 50.30, 59.10, 64.77, 69.56, 69.85,
70.52, 70.58, 70.62, 72.01, 123.86, 145.07 IR (neat): 3557 (water), 3137, 2892, 1955, 1646,
1549, 1459, 1354, 1294, 1245, 1223, 1199, 1100, 982, 928, 892, 848

46

2.3

Results and Discussion

2.3.1 Ab Initio Calculations
Lithium ion affinities with various nitrogen heterocycles are calculated using the
MP2(full)/Aug-cc-pVTZ(Li-C)//MP2(full)/cc-pVDZ(Li-C) calculation recommended for this
kind of estimate by Rodgers et al. which we show to be in good agreement with the G3 and
G3(MP2) calculations of Pople and co-workers. G3(MP2) was found to be the most amenable to
larger species, so we use this level of theory to model a hypothetical solvation shell for the
lithium ion with and without triazole participation.
The absolute ligand – lithium association energies of heterocyclic and other ligands have
been extensively studied by Rodgers and co-workers, but computational estimates accompanying
the measurements have been carried out using calculations with varying levels of
sophistication.52-54 Additionally, Rodgers et al. have benchmarked the MP2(full)/Aug-ccpVTZ//MP2(full)/cc-pVDZ calculation against a test set which included few nitrogen
heterocycles.51 In order to test the applicability of this calculation to nitrogen heterocycles we
have extended these calculations to azines and azoles, and found similar agreement to
experiment as the initial test set (fig. 14). Additionally we have two bidentate lithium complexes
at this level of theory on models designed to resemble complexation geometries expected in the
model compounds. As the number of dative bonds between lithium and its coordination sphere
increases, the strength of each additional dative bond has been seen to decrease in previous
studies.43 It is notable however that while 1-H-1,2,3-triazole shows an association energy 51.5
kJ/mol greater than dimethyl ether, the difference between the binding energy of stronger of the
two bidentate complexes and glyme is only 15.1 kJ/mol. This result is attributable to the
geometries of the two complexes; the 1-H-1,2,3-triazole minimum is a scalene triangular

47

complex, which features bonds from the two adjacent aprotic nitrogen atoms to the lithium ion,
whereas the minimum observed in the 4-methoxymethyl-1H-1,2,3-triazole (4MeOMeT) complex
features only one lithium nitrogen bond.
Attempts to calculate the energies of larger complexes became impractical due to the
prohibitive expense of the MP2(full)/Aug-cc-pVTZ(Li-C) single point calculation on complexes
featuring coordination numbers of three and four. A small comparison of G3 and G3(MP2)
energies to experiment and theory for only the most relevant glyme and triazole species was
conducted to evaluate the appropriateness of these methods (fig. 14). The agreement of G3
theory with mass spectrometry experiments was tested for lithium association calculations, and
found to have a mean average deviation of 8.6 kJ/mol compared to 8.1 kJ/mol for
MP2(full)/Aug-cc-pVTZ(Li-C)//MP2(full)/cc-pVDZ(Li-C) in the test set of Rodgers et al.51
Additionally both G3 and G3(MP2) are extensively benchmarked for general thermochemical
accuracy in a variety of applications.56,57
Larger coordination spheres were modeled using two distinct “chains” up to a
coordination sphere of four. Justification for this treatment can be found in molecular dynamics
simulations which show that lithium cations complexed between two chains are the most
important for lithium ion transport, and that the average occupancy of the first coordination shell
around lithium contains four.19 oxygens, meaning that four and five coordinate complexes should
be most important in transport behavior, with lithium rarely containing less than four ligands.19

48

G3(MP2) Energies of Reconstructed Solvent
Shells for Li+ Using Glyme Based Ligands
Glyme solvent shells without triazoles

Glyme solvent shells with 1 triazole

430

380
kJ/mol
330

280

230
0

1

2

3

4

5

Coordination number

Figure 13 – As more solvent moieties are added to the lithium coordination sphere the average
bond strength decreases, effecting both triazole and ether ligands. Triazoles can interact with the
2p orbitals of the lithium ion leading to net stabilization in the two and three coordinate
complexes which are planar. Lithium becomes sp3 hybridized in the tetracoordinate complex,
and this effect is seen to diminish. Simulations and experimental data have shown four and five
membered complexes to be most common in polyether ion conductors.19

49

a)

Lithium Association Energies in Theory and Experiment
Present work

Experiment

Rodgers et al.

300
250
Lithium
200
Association
Energy 150
(kJ/mol)
100
50

Figure 14 – Gas phase lithium ion to ligand affinities in experiment and theory. Typical
agreement between the experiments of Rodgers et al.51-54 and the MP2(full)/Aug-cc-pVTZ(LiC)//MP2(full)/cc-pVDZ(Li-C) calculations recommended by the same group for quantitatively
accurate lithium ion affinities are shown in (a) .51 Calculations typically over estimate affinities
relative to experiment but are usually within 10 kJ/mol, which is comparable to the uncertainty
of the experiment. In (b) G3 methods were compared to the methods of Rodgers et al. due to
unfavorable scaling of the latter to larger ligand systems.51 The computational expense of G3 is
similar to that of the Rodgers method, with G3(MP2) being somewhat cheaper. G3(MP2) was
found to be in better agreement with experiment due to being consistently lower in its energy
estimates.

50

Figure 14 (cont’d)
b)

Calculated and Measured Li+ Energies with G3 Methods
MP2(full) composite)

G3

G3(MP2)

Experiments

280
260
240
220
kJ/mol

200
180

160
140
120
100
1H-1,2,3-triazole

glyme

2H-1,2,3-triazole

4-MEOMET

c)

The behavior seen in our three and four coordinate complexes (fig. 13) shows that as the
coordination number increases, the lithium triazole bond becomes roughly indistinguishable
from a lithium ether bond on the basis of energy. The difference in energies between the four
coordinate complex with and without a triazole is approximately 3 kJ/mol.

51

2.3.2 Experimental Measurement of Conductivity and Thermal Behavior
Model compounds 8EO1T, 6EO1T, 8EO2T, and 6EO2T were first synthesized using the
methodologies described by scheme 2. Model compounds were designed such that their
molecular weights cluster around 500 g/mol so that they can be fairly compared to poly (ethylene
glycol) dimethyl ether Mn=500 ( henceforth PEGDME 500), and such that each model gives a
whole number ratio of ether oxygen atoms and triazole rings; 8:1, 6:1, 4:1, and 3:1 respectively.
The model compound 6EO2T was also devised intentionally to make five and six coordinate
complexes containing only ether oxygens uncommon, so that triazole containing complexes
resembling the one shown in fig. 13 would be relevant to the transport behavior.
Synthesized materials were purified and dried as described in the experimental section.
Dry materials were then analyzed by differential scanning calorimetry without additives, and by
AC impedance spectroscopy as neat materials with dissolved LiTFSI. The thermal behavior of
PEGDME500 was not characterized, because our equipment cannot access temperatures less
than -80°C. 6EO1T was found to lack thermal behavior in the available temperature window, and
was therefore not used in conductivity measurements; the observed lack of thermal behavior was
probably due to the fact that 6EO1T has the lowest molecular weight of the model compounds.

52

Table 1 – Physical Data Pertaining to Thermal and Conductive Properties of Materials
Compound

Melting
Glass
Temperature, Transition
Tm (°C)
Temperature,
Tg (°C)

Activation
Energy, Ea
(kJ/mol)

Pre-exponential
factor, σ0 (S/cm)

Arrhenius fit R2

8EO1T, 13

-

-74.9

29.7

1.19∙103

0.9707

6EO1T, 12

-

-

n/a

n/a

n/a

8EO2T, 15

-

-59.6

40.4

3.13∙105

0.9872

6EO2T, 14

22.6

-59.1

41.8

5.21∙105

0.9807

PEG 500 DME

-

-

17.5

17.8

0.9583

It was found that the model compounds 6EO2T, 8EO2T, and 8EO1T all had measurable
glass transition temperatures (Tg) and that the measured glass transition was weakly dependent
on the ether oxygen to triazole ratio, and more strongly dependent on the number of ether
oxygens in the chain (Table 1.). 6EO2T and 8EO2T had Tg that were almost identical, and
8EO1T had a Tg roughly 6 degrees lower. 6EO2T was shown to have a melting temperature near
room temperature. Crystallization behavior was noticeable in 6EO2T at reduced temperatures
(including low temperature storage), however room temperature crystallization of samples was
only observed in one occasion, whereas the material usually maintained fluidity at room
temperature. Because of this and the fact that the lowest conductivity measurements taken
occurred at 30°C, crystallization behavior was not observed to affect the conductivity of the
material directly.

53

a)

Conductivtity of Oligomer Complexes
1.00E+00
Conductivity S/cm

2.7

2.9

3.1

3.3
PEG500 1:128
PEG 500 1:64

1.00E-01

PEG500 1:32
8EO2T 1:64 LiTFSI
1.00E-02

PEG 500 1:64 LiTFSI
6EO2T 1:64 LiTFSI
8EO1T 1:64 LiTFSI

1.00E-03

1000/K

b)

Conductivity of Oligomer Complexes 1:64 LiTFSI

Conductivity (S/cm)

1.00E+00
2.7

2.8

2.9

3

3.1

1.00E-01

3.2

3.3

3.4
PEG 500
8EO2T
6EO2T

1.00E-02

8EO1T
1.00E-03

1000/K

Figure 15 – Conductivity of oligomer salt complexes. In (a) model oligomer salt complexes were
run at a concentration of 1 Li : 64 ligand atoms, where two of the triazole nitrogens were
considered ligands (but not the pyrrole-like nitrogen) run with PEG 500 dimethyl ether controls.
Model oligomers and the PEG control were run with LiTFSI, while a variable concentration
standards curve was run with LiClO4. In (b) the same data shown without standards.

54

a)

303K conductivity vs GlassTransition Temperature
y = -0.0004x + 0.087
R² = 0.9999
0.01
0.009
0.008
0.007
0.006
σ (S/cm) 0.005
0.004
0.003
0.002
0.001
0
195.0

200.0

205.0

210.0

215.0

220.0

T (K)

b)

Entropy - Enthalpy Compensation Behavior in Model In
PEG Based Materials with Increasing In-Chain Triazole
Content
14
y = 41.646x - 5.0191
12
R² = 0.9901
10

ln(σ0)

8
6
4
2
0
0.100

0.200

0.300

0.400

0.500

Ea (eV)

Figure 16 – Descriptions of trends in the conductivity of oligomer salt complexes. In part (a) a
strong correlation between conductivity at 30°C and the glass transition temperature is found
within the model series. In part (b) a linear relation is shown between the pre-exponential factor
and activation derived from Arrhenius plotting in PEG and the triazole containing model
compounds.

55

A crystal of 6EO2T was obtained for single crystal X-ray diffraction analysis by slow
evaporation of a toluene solution in a -20°C freezer. While cases of triazole C-H to heteroatom
hydrogen bonding have been reported in the literature,46 hydrogen bonding was not present in the
crystal structure as the closest intermolecular N-H distance was 2.75Å and the shortest O-H
distance was 2.79Å. Triazoles were not observed to pi stack in the crystal. While compound was
observed to crystalize in layers (fig 17b) the faces of the triazole rings seem to avoid one another
(fig 17c). The triazole ring does carry a dipole along which the rings in the model compound
seem to align (fig 17d). We conclude that the most important factors that lead to ordering and
crystallization in the most triazole rich model are loss of conformational freedom and dipole
dipole interactions.
The 30°C conductivity of 6EO2T and 8EO2T salt composites was nearly identical, with
8EO1T being half an order of magnitude and PEGDME 500 being a full order of magnitude
higher (Fig 1.). Room temperature conductivity was shown to correlate nearly perfectly with the
Tg of the material. It was observed that as the temperature was increased, the conductivity of the
materials approached convergence at a single value. This behavior is known as compensation
law, or Meyer-Neldel behavior (Fig 2.).66-68
Meyer-Neldel or entropy-enthaply compensation behavior is a behavior of a set of
processes or reactions that occur in families of materials with similar compositions which are
well described by the Arrhenius equation
−Ea

σ(T) = σ0 e RT

(eq. 10)

where σ(T) is temperature dependent conductivity, Ea is the activation energy of the process, σ0
is an empirical exponential prefactor, and R is the gas constant.66-68

56

a)

b)

Figure 17 – Single crystal X-ray diffraction of 6EO2T. In part (a) the Single Crystal XRD
structure of 6EO2T is shown with thermal elipsoids set at 50% probability. Packing as viewed
from the b axis of the 6EO2T crystal is shown in (b) and the c axis in (c). While a layered
structure is evident in the crystal, pi-pi stacking interactions and hydrogen bonding appear to be
absent. The angle shown in (c) reveals that triazole moieties align roughly along the dipole of the
ring within the layers.

57

Figure 17 (cont’d)
c)

d)

58

Table 2 – Crystal Data and Structure Refinement for 6EO2T
Identification code
6EO2T
Empirical formula
C9H16N3O3
Formula weight
214.25
Temperature/K
173.01
Crystal system
monoclinic
Space group
C2/c
a/Å
47.5520(19)
b/Å
5.5312(2)
c/Å
8.1912(3)
α/°
90.00
β/°
97.576(3)
γ/°
90.00
3
Volume/Å
2135.64(14)
Z
8
3
ρcalcmg/mm
1.333
-1
m/mm
0.843
F(000)
920.0
3
Crystal size/mm
0.189 × 0.066 × 0.059
2Θ range for data collection 3.74 to 140.76°
Index ranges
-57 ≤ h ≤ 57, -6 ≤ k ≤ 6, -9 ≤ l ≤ 9
Reflections collected
14377
exptl absorpt T max, min
0.7533, 0.6448
Independent reflections
1987[R(int) = 0.2141]
Data/restraints/parameters 1987/0/138
2Θ 70.38 fraction collected 0.979
Goodness-of-fit on F2
1.007
Final R indexes [I>=2σ (I)] R1 = 0.0620, wR2 = 0.1222
Final R indexes [all data]
R1 = 0.1497, wR2 = 0.1585
-3
Largest diff. peak/hole / e Å 0.28/-0.26

Compensation behavior is an apparently exponential dependence observed between the
pre-exponential term and the activation energy appear exponential related such that
Ea = α + β ln(σ0 )

(Eq. 11)

59

where α and β are arbitrary constants, σ0 is the pre-exponential term, and Ea is the activation
energy.67,68 Controversy exists over what gives rise to this sort of behavior and what (if anything)
it signifies.68
This behavior is rarely discussed in the context of polymer electrolytes, however one
example of compensation behavior was identified by Wieczorek in an investigation of a series
of polymer composite materials.67 These materials included various polyethylene glycols (PEG)
and blends of PEG with poly methylmethacrylate (PMMA), which were paired with NaI or
LiClO4 carriers and a variety of inorganic nanoparticle fillers.67 Wieczorek cited earlier work
from studies of diffusion in metals in which activation energy was related to the entropy of
migration (ΔSm) by a characteristic temperature (TD or disordering temperature) such that Ea/TD
= ΔSm .66,67 In earlier study TD was considered to be the melting point of the class of alloys
showing compensation behavior.66,67 Wieczorek calculated TD for his materials (1 distinct TD for
each set of materials showing compensation behavior) and found that it was close to the Tm of
the crystalline PEG domains in his materials.67 Reference to the effects of inorganic fillers was
used to explain the discrepancy.67
While the work of Wieczorek is an interesting precedent, it does not provide an
explanation for why the compensation behavior is present in these materials. Furthermore,
references to a TD in our materials could not be related to melting, as only one of our materials
shows a Tm. In order to explain and interpret our results we will look to physical theories of
polymer dynamics, as well as Arrhenius based models.
2.3.3 The Explanation for and Significance of Compensation Behavior
It is generally understood that segmental dynamics of polymer electrolytes are dependent
on the mobility of the individual segments of the polymer chain.5,9,14,15 The connection is

60

conveniently rationalized using the dynamic bond percolation theory (DBP) of Ratner and coworkers.11-15 A bond in the sense of DBP, is a pathway between a void in the polymer host
occupied by an ion, and an unoccupied void. When one bond has opened and closed for each
ionic species in the system it can be said that one renewal time has occurred. Diffusion of an
ionic species can then be written as14
D=

〈r2 〉

(eq. 12)

2d𝜏R

Where τR is the renewal time 〈r2〉 is the mean square displacement of a randomly diffusing ion in
the system, and d is the spatial dimensionality of the system.11
The connection between the Tg and τR is somewhat foggy. A general definition of the
glass transition temperature can be found in Anslyn and Doughrty’s Modern Physical Organic
Chemistry; “[a] transit from an essentially rigid glass to a more flexible rubbery material”.131
Based on this definition it would be intuitive to assume that renewal time becomes essentially
infinite at the glass transition temperature, and would therefore be inversely proportional to T-Tg
as the temperature of a material rises above its Tg. This logic also underlies the VTF equation
(eq. 3) which makes temperature dependent conductivity σ(T) inversely proportional to T-T0,
where T0 is a fitting parameter related to Tg by a constant (usually less than 45°C).15 However as
the replacement of Tg with T0 suggests there is some amount of ambiguity in this idea.15 The
ambiguity is generally related to the fact that Tg is an empirical kinetic quantity related to
molecular motion in a bulk system, and that different types of motion are exhibited by
polymers.15 Thus different experimental techniques may find different values of Tg.15 Further
complexity is introduced by the fact that the addition of a salt to a polymer system increases it’s

61

Tg by introducing dative bonds between and within chains.15 These problems mean that a formal
functional relationship between τR and Tg has not been established.
This complexity makes interpreting the correlation we found between room temperature
conductivity and Tg somewhat difficult. While we cannot use DBP quantitatively to explain this
result, the conceptual connection between Tg and molecular motion is still the best way to
understand it. Materials with a higher Tg are behaving as though they are at a lower temperature
than those with a low Tg because molecular motion (and hence renewal behavior) doesn’t vary
strongly with temperature below the Tg (and in fact stops for all intents and purposes).
A physical theory of cation transport based on the Rouse model was derived by Maitra et
al.23 This model breaks transport down into a component mediated by diffusion of the ion with a
chain (Dc.m.) and three types of independent diffusion (DM) with three independent time scales
(τ1, τ2, τ3).23 These consist of diffusion along a chain (τ1) relaxation mediated diffusion (τ2) and
interchain hopping (τ3) which can be considered analogous to the τR of Ratner et al.23 It was
shown that for short chains such as those in our study that an approximate functional form can be
written for DM(τ1, τ2, τ3) such that
DM =

𝑹2𝑒

(eq. 13)

18𝜏3

Where Re is the equilibrium end to end distance of the polymer.23 Because parameters of chain
flexibility mostly effect τ2, we can reason that the stiffening effect of introducing triazoles into a
chain are only going to be felt if they effect the diffusion behavior of the polymer for some
reason, or the diffusion of lithium ions between chains.

62

Additionally we considered possible effects of the differing number of Rouse segments
(NR) which would affect the available Rouse modes; a set of modes that describe polymer
motion. We might expect that decreasing NR would lead to less thermal energy being lost to
coiling movements which might lead to an increase in Dc.m.. This trend is in fact shown by
Maitra et al for polymers ranging from NR= 1 to ~400 where Dc.m. goes to zero.23 The authors
used PEG models and defined a rouse segment to be one monomer. We estimated NR in our
models by using the number of EO monomers and considering a triazole and the ether oxygen
after it to be one segment. Using this system we found NR=11 for PEGDME 500, 8 for 8EO2T
and 8EO1T, and 6 for 6EO2T. Based on the relatively small differences, and the fact that NR
doesn’t appear to track with differences in the conductivity, we are disinclined to pursue this line
of reasoning further.
The differences in exponential prefactor observed in the model compounds is difficult to
explain, however recent work by Frech et al has focused on understanding the origins of the
exponential prefactor in the conductivity of organic liquids, and using this insight to improve the
Arrhenius formalism.69-72 Citing deficiencies in both phenomenological approaches (such as
Arrhenius, and Vogel Tamman Fulcher or VTF) which tend to yield little physical insight into a
system, but fit data well, and hydrodynamic theory (Nernst-Einstein, DBP) which are
theoretically rigorous, but often fail to adequately describe experimental results, Frech et al. have
developed the compensated Arrhenius formalism (CAF).69-72 The compensated Arrhenius
Formalism starts with the insight that the exponential prefactor in the Arrhenius equation is
actually a function of the static dielectric constant of the material, which is itself a temperature
dependent quantity. The Arrhenius equation that results from this insight can be written
−Ea

σ(𝜀𝑠 , T) = σ0 (𝜀𝑠 (𝑇))e RT

(eq. 14)
63

where εs is the static dielectric constant of the material. The authors then devised a fitting method
whereby the pre-exponential factor could be cancelled, and calculated separately from the
activation energy.69-72 They accomplished by normalizing to a conductivity measurement at a
reference temperature (Tr) and fitting the data using the compensated Arrhenius equation, which
they give as.
𝜎(𝑇,𝜀𝑠 )

𝑙𝑛 (𝜎

𝐸

𝐸

) = − 𝑅𝑇𝑎 + 𝑅𝑇𝑎

𝑟 (𝑇𝑟 ,𝜀𝑠 )

(eq. 15)

𝑟

The activation energy (Ea) can then be obtained as a slope or intercept of the fit.69 The preexponential factor is calculated separately, and must be obtained from a set of related materials
that vary regularly by dielectric constant.69 The pre-exponential factor is given by transforming
the conductivity data so that

𝜎0 =

𝜎

(eq. 16)

̅𝑎
−𝐸
𝑒 𝑅𝑇

Where 𝐸̅𝑎 is the average activation energy for the entire set of materials analyzed.
While this procedure would be impractical for our own data, due to the need for the
materials analyzed to be sets that vary by a single parameter (e.g. primary alcohols of varying
chain length from ethanol to octanol) the insights gained from the development of this formalism
are quite useful.69-72 When this method was used to analyze the ionic conductivity of various ions
in families of polar organic liquids conductivity of each liquid in a class (i.e. 1-alcohols or
methyl ketones of varying chain length) varied roughly linearly by temperature dependent
dielectric constant ε(T) and gave rise to separate curves when plotted. On the other hand, the
pre-exponential factors of each class of liquids overlapped in a single curve when plotted against

64

ε(T). This is a good indication that their assumptions about the dependence of pre-exponential
factor on dielectric constant are likely justified.
Dielectric constant isn’t a useful metric for thinking about molecular details, and
structure activity relationships, as it is a macroscopic property of a system.71 In order to make
their model more useful the authors used Onsager’s model to relate dielectric constant to
permanent dipole, and dipole density of sets of thiols, methyl ketones, nitriles and acetates of
various chain lengths.71 They used a version of the CAF adapted to diffusion, and showed that
the pre-exponential factor D0 varied by Nd/T (where Nd is the dipole density of the material) and
that it varied by solvent class.71 The dipole density used in this study was a number density,
which was easily obtained because the authors used liquids with only one polar functional group
per molecule.71 Thus the were able to calculate the quantity from the molar volume.71 This was
true because very strong correlations were present between ε(T) and Nd(T).71 Finally, it was
shown that alcohols had higher activation energies than the polar aprotic liquids studied.69,70 This
was attributed to the hydrogen bonding capabilities of alcohols, which required additional energy
to dissociate relative to polar aprotics.72
The molecules used in the present study are more complicated than those examined by
Frech et al. in that they are large and contain many polar groups per molecule. One comparison
that is easy to make however is the strength of the permanent dipole moment in a 1,2,3- triazole
ring, relative to that of dimethyl ether, the basic dipole creating moiety in a chain of polyethylene
glycol. The dipole moment of dimethyl ether has been experimentally measured to be 1.310 D,
additionally, ethyl methyl ether has a dipole moment of 1.174 D.73 The dipole for 1,3-dimethyl1,2,3-Triazole has not been measured experimentally, however we have calculated the dipole at
the MP2(full)/6-31G(d) level of theory and found a value of 1.4 D for dimethyl ether, and a

65

value of 4.7 D for the triazole. Additionally and in contrast to standard PEG chains, the triazole
is known to be a hydrogen bond donor with roughly the same affinity for an acceptor as
pyrrole.44
Based on the factors considered up to this point an explanation for the observed
compensation behavior can be proposed. It seems likely that the introduction of the triazole
moiety into the PEG chain provides a ligand for the lithium ion similar to that of an ether
oxygen. However the triazole differs significantly in the magnitude of its dipole which produces
effects that both enhance and impede conductivity. Triazoles stiffen the chains and (probably
more importantly) enhance chain to chain dipole-dipole interactions, which lead to an increase in
Tg and lead to crystallization in the extreme case of 6EO2T. The greater attraction between
chains leads to a higher activation energy for transport as triazoles become a greater fraction of
the ligands in the material. However, conductivity can also be enhanced by the presence of
triazoles. This occurs because the greater polarity of the triazole moiety enhances the Arrhenius
pre-exponential factor which enhances the global conductivity of the material at all temperatures.
A mechanism proposed by Frech et al. for the enhancement of the pre-exponential factor cites
transition state theory of transport processes and ties the polarity of the environment to the ΔG‡
of a moving particle.72 This proposal was favored in part because the authors have observed
similar dependencies on the pre-exponential for self-diffusion of polar liquids.70,72 A similar
effect on self-diffusion of our systems would be unexpected based on the observed thermal
behavior, however the polarity likely is affecting the environments of the mobile ions. We
propose that the presence of strong dipoles is stabilizing to individual ions in the system, and
helps them overcome coulombic correlation to their counter ion. This leads to a higher effective
concentration of ions mediating transport.

66

2.4

Conclusions
As a potential architectural feature of lithium ion elecrolytes, triazoles have some degree

of potential. Triazoles do have a negative effect on conductivity of polymer salt composites, but
it is relatively modest, and the concentrations of triazoles studied were quite high; exceeding
most plausible concentrations of the moieties one would expect to find in functional materials.
Triazoles seem to exert most of their effects on conductivity through their dipole moment
which is significantly stronger than that of dimethyl ether or polyethylene glycol. This has the
effect of attracting the chains together, inducing crystallization and increasing the glass transition
of the material. The stiffness of the triazole may also contribute to these effects.
The deleterious effects of the triazole moiety on conductivity manifest themselves in the
increase in activation energy observed for conductivity seen in the Arrhenius model of the
process. However increases in dipole density have also been shown to enhance the preexponential factor of these processes, which leads to compensation behavior.
Frech et al. who first observed effects of this kind proposed that increasing the dipole
density of conductive materials might be a novel way to increase conductivity in polymer
electrolytes. While it has been shown in this work that triazoles have undesirable effects that
counter the pre-exponential boost in the particular systems studied, it is possible to envision
strategic uses of such moieties in electrolyte design, such as placing strong dipoles (triazoles or
otherwise) near stationary anions found in single ion conductors in order to activate charge
separation. Strategies such as this warrant future study and may be the subject of future work.

67

3
3.1

Chapter 3: Nucleofugality in Nitrogen and Oxygen derived leaving groups*
Introduction
Nucleofugality, or leaving group ability, is a fundamental concept of organic chemistry,

and plays a key role in a broad array of chemical reactions. Despite its centrality to reactions
such as E1, E2, SN1 and SN2, that feature a leaving group (nucleofuge) departure in the rate
limiting step, nucleofugality was sparsely studied until fairly recently.80 The last decade,
however, has seen several attempts to develop an absolute scale of nucleofugality.81-84 These
began with the work of Ayers et al. who attempted to use a truncated Taylor series to model the
electronic energy of a leaving group as a function of increasing charge. In that expression the
first order term is μ, the electronic chemical potential (which can be expressed as -[I+A]/2) and
the second order term is η, or chemical hardness (expressed as [I-A]).81 Using this construction
they argued that electrophilicity ω, could be defined as
μ2

(𝐼+𝐴)2

ω = 2η = 8(𝐼−𝐴)

(eq. 17)

Where I is the ionization potential and A is electron affinity; thus this formulation
approximates continuous derivatives of energy with respect to charge based on quantities that
represent a change in energy with the gain or loss of a full electron.82 Electrophilicity in this
sense is described as “the energy [of] stabilization resulting from the presence of a perfect
electron donor”.81 In an attempt to correct for partial charge already present in a leaving group
prior to leaving, they derived a related quantity ΔEnucleofuge which is defined such that
*

This chapter is an adapted republication of Spahlinger, G.; Jackson J. E. Phys. Chem. Chem.
Phys. 2014, 16, 24559 – 24569. It has been republished with permission from the PCCP Owner
Societies. The original article may be found online at the following link:
http://pubs.rsc.org/en/content/articlelanding/2014/cp/c4cp03741c#!divAbstract

68

∆𝐸nucleofuge =

(μ+η)2
2η

=

(𝐼−3𝐴)2

(eq. 18)

8(𝐼−𝐴)

Because ΔEnucleofuge is derived solely from the ionization potential and electron affinity,
this quantity is relatively easy to calculate, and several groups have followed up by conducting
DFT studies wherein attempts were made to apply or refine this scale.82,83 Most notably,
Geerlings et al. modified the theory to include solvent effects, and applied the resulting
formalism to an extended set of leaving groups.82
Mayr et al., have taken a different approach, utilizing an empirical scale parameterized
with rate constants for the solvolysis of benzhydryl derivatives.84 The benzhydryl group has the
advantage of being tunable via addition of electron donating and withdrawing groups on the aryl
rings, such that leaving groups whose solvolysis rate constant is too fast or slow for study on one
scaffold can be measured on another.84 The group focused on sulfonate, carboxylate and halide
leaving groups in this analysis, and claims to have found a scale that is useful for rates spanning
12 orders of magnitude.84
A noticeable omission from the recent literature on nucleofugality is the amine-derived
anionic leaving group.81-84 While sulfonates and carboxylic acid esters are relatively common,
amides, sulfonamides, imides and sulfonimides have to the best of our knowledge been absent
from any study of nucleofugality to date.
Attempts to activate amines for substitution and elimination do exist in the literature
however, and date back to the 1960s. Based on its low pKa of 1.6,85 initial work explored
derivatives of saccharine.86 Unfortunately these were found to undergo preferential attack at the
carbonyl carbon; however, the authors discovered that bis(sulfonyl)imides (e.g. ditosylamines)
could undergo substitution and elimination.86 The most common activation in this vein appears

69

to be through the addition of dual triflyl groups to form bis(trifluoromethanesulfonyl)imide
derivatives.87-89 This strategy for activation is becoming more common in part because the
bis(trifluoromethanesulfonyl)imide (TFSI) anion is an attractive component in certain types of
ionic liquids.90 Metal salts and ionic liquids derived from TFSI have attracted a great deal of
attention from scientists researching transport materials for lithium ion batteries. TFSI is
generally considered to be a poorly associating ion; it is also thought to plasticize polymeric
lithium ion conductors, leading to a lower glass transition temperature in the polymer, and hence
better conductivity than other anions of similar lithium ion affinities.90,91
Despite this trend, the activation of nitrogen as a nucleofuge remains a rare strategy.
While various researchers have pointed out the viability of alkyl TFSI derivatives for the
synthesis of ionic liquids,88,89 TFSI containing liquids are more commonly accessed by the
general synthetic method used for ionic liquids:92 an onium halide salt is first formed by reaction
of an alkyl halide with an amine; it is then subjected to ion exchange metathesis by treatment
with silver TFSI.92
We elected to study the nucleofugality of polyatomic anionic oxygen and nitrogen
derived leaving groups by modeling the Menshukin reaction, in which ammonia displaces a
leaving group by an SN2 mechanism. The SN2 reaction is itself much better studied than
nucleofugality as a general concept; theoretical studies exist for both ionic and Menshutkin-type
SN2 reactions, including solvent effects,93,94 SN2 reactions at neutral nitrogen,95,96 comparisons of
front side vs. back side SN2,97,98 studies employing valence bond methods,99 analyses of SN2
based on Marcus theory,100 and analyses of the influences of periodicity on the anionic SN2
reaction.118,119 Additionally, the formation of quaternary amine mesylates via the Menshutkin
reaction has been modeled using DFT methods.101 Although we are unaware of any recent

70

reviews of theoretical work on the SN2 reaction, a contribution from Laerdahl and Uggerud
provides a good perspective on the state of the field as of twelve years ago, including discussion
on experimental mechanistic work, and reaction dynamics.102 Surprisingly there seem to be no
studies that systematically analyze and compare the reactivities of nitrogen and oxygen derived
polyatomic anionic leaving groups as a class.
Reservations have previously been expressed about using SN2 reactions as a probe of
nucleofugality.80 In particular Stirling argues in his 1978 account that SN2 and E2 reactions are
tainted by the involvement of a nucleophile or base in the rate limiting step of the reaction.80
While it is true that the nucleophile is an integral part of an SN2 reaction, the present work
controls for this issue by using the same nucleophile throughout the study. Moreover, studies of
bimolecular reactions are necessary to understand the role of nucleofugality in mechanisms that
feature electronic reorganization concurrent with leaving group departure.
3.2

Computational Methods
All calculations were performed using GAMESS versions 12 R3 (2009) and 1 R1

(2012).55 Calculations were run on a personal laptop, the MSU chemistry department hydra
cluster, or the MSU High Performance Computing Cluster (HPCC) depending on the demands of
the job.
Activation energies were calculated by finding minima for Van der Waals complexes of
ammonia and each respective alkylating agent shown in scheme 1, then by locating transition
states for the SN2 reaction. ΔEǂ was considered to be the difference in these two energies.
ΔEcomplex is the difference in energy between the Van der Waals complex and the sum of
ammonia and the alkylating agent being studied. Van der Waals complexes and transition state

71

structures were first located at the HF/3-21G level of theory, and in cases where the
conformational space allowed multiple minima or transition state structures, the lowest energy of
these were selected. Additional geometric optimizations were run at HF/6-31G(d), and
MP2(full)/6-31G(d). In all cases vibrational analyses were run at HF/6-31G(d) on the HF/631G(d) geometries in order to confirm that minima and transition states had zero and one
imaginary vibrations respectively. All calculations were initially run with C1 symmetry. After
optimization, structures were found which converged to C1, Cs, C2, C2v and C3v symmetries.
Structures which appeared to converge out of C1 symmetry were rerun at MP2(full)/6-31G(d)
using the new point group. Coordinates for stationary points and their corresponding Abelian
point groups are listed for all structures in the supporting information.
In order to get relatively accurate energies economically, we have chosen to simplify the
G3(MP2) method of Pople et al.57 The G3(MP2, CCSD(T)), or G3(MP2, CCSD) as it is also
known, is the variant of G3(MP2) implemented in GAMESS.103 The difference between the two
is that QCISD(T) calculations are not available in GAMESS, and therefore have been replaced
by CCSD(T) calculations as shown in equation 3.
E0[G3(MP2, CCSD(T))] = E[CCSD(T)/6-31G(d)//MP2(full)/6-31G(d)] +
E[MP2(FC)/G3large//MP2(full)/6-31G(d)] – E[MP2(FC)/6-31G(d)//MP2(full)/6-31G(d)]
+ ZPE + HLC

(eq. 19)

Where HLC is a higher level correction and ZPE is the zero point energy at the HF/6-31G(d)
level of theory scaled by an empirical factor of 0.8929.57 ,103 We have modified this method by
omitting the CCSD(T)/6-31G(d) calculation and the higher level correction. For brevity we will
refer to this as an “MP2/G3large” calculation, however it is defined below in equation 4.

72

E0[MP2/G3large] = E[MP2(FC)/G3large//MP2(full)/6-31G(d)] + ZPE

(eq. 20)

The quantities described as “ΔE” in this paper are ΔE0[MP2/G3large] energies unless otherwise
indicated. ΔHǂ was also calculated for all activation energies by applying thermal corrections
from the HF/6-31G(d) vibrational analyses which were calculated at 298K.
MP2/G3large calculations of activation showed good agreement with the G3(MP2,
CCSD(T)) in sulfonates (Supporting information). A second set of calculations at the
CCSD(T)/6-31+G(2d,p)//MP2(full)/6-31G(d) level suggested that MP2/G3large might
systematically overestimate barriers, however this level of theory not a feasible basis for the
study at large. MP2/G3large calculations had mean average deviations (MAD) from
experimental methyl cation affinity data similar to G3 and W1 calculations performed by Zipse
et al. (Table 2).104 It is often considered important to include diffuse functions in quantum
chemical descriptions of ions, and structures with partial bonding. This concern has been studied
in the case of SN2 reactions with ionic nucleophiles.105 Boyd et al. found that SN2 transition
states had different geometries when calculations were done with and without diffuse functions,
but that the differences in energy between these geometries were negligible in single point
calculations including diffuse functions.105 Taken together these data lead us to conclude that the
MP2/G3large calculation is adequate for our analysis in this paper.
All graphical representations of wavefunctions or geometries shown in this paper were
generated using MacMolplot V 7.4.3.106

73

3.3

Results and Discussion

3.3.1 Energies Associated with Nucleofugality, and their Trends
Gas phase activation energies (ΔEǂ and ΔHǂ298K) have been calculated at the MP2/G3large
level of theory for all alkylating agents found in Scheme 3. These energies are defined in Scheme
2. The alkylating agents studied consisted of 20 methylating agents, including a contingent of
sulfonamides, sulfonimides, sulfonates, carboxylate esters, carboxamides, and one carboximide.
Additionally, two of the alkylating agents studied were five membered rings which would be
opened by the attack of nitrogen, these were 1,3-propanesultone, and N-triflyl-1,3-propanesultam
(TPS). Methyl Chloride was run as a convenient reference point with a single atom leaving
group. The results of these calculations are displayed in order of ΔEǂ magnitude in figure 18. It
was found that most methylating agents had comparable ΔEcomplex energies, which were on the
order of 4 – 6 kcal/mol. Carboxamides proved to be an outlier, as they contained a hydrogen
bond from the ammonia lone pair to the amide proton, instead of an ammonia proton to oxygen
bond. However, the ΔEcomplex should not be relevant to analyses of nucleofugality, and therefore
was subtracted out of the activation energy, so that the “activation energy” presented, ΔES→TS,
represents the energy difference between the separated species and the transition state of interest.
Geometrical parameters of interest from the transition states were tabulated, and can be found in
table 3.

74

A)

B)

Scheme 3 – Relevant energies are derived from electronic structures calculated along the
reaction coordinate of an SN2 reaction (A) The difference in energy between a methylating agent
in its bound state, and the sum of the separated ions after heterolytic cleavage is defined as the
methyl cation affinity (MCA) (B)
Methyl cation affinity is defined as the sum of the energies of a leaving group anion and a
methyl cation, less the energy of the parent methylating agent (scheme 3).104 Methyl cation
affinities appear in table 4, along with a set of experimental and calculated values which appear
in the work of Zipse et al. for comparison.104

75

Because the energy of a methyl cation is invariant between methylating species, the
methyl cation affinity should depend straightforwardly on the energy of the leaving group anion
relative to its methylated counterpart. Methyl cation affinity should therefore give the
contribution to ΔHrxn arising directly from anion stability, where methylating agents with lower
methyl cation affinities arise from more stable anions. This quantity should also give a trend
analogous to ΔEnucleofuge, of Ayers et al. as it shows the change in energy resulting from the
leaving event, and can be thought of as the activation energy for the corresponding gas phase SN1
reaction.
The ΔES→TS for nitrogen and oxygen derived leaving groups follow an intuitive pattern.
Sulfonates have the lowest average ΔES→TS (25.8 kcal/mol), followed by sulfonimides (30.3
kcal/mol) followed by esters (38.7 kcal/mol), followed by sulfonamides (50.3 kcal/mol) followed
by amides (58.4 kcal/mol). Nothing in this series challenges conventional thinking, but a few
interesting observations can be made. The first of these is simply that while excellent leaving
groups can be obtained by adding sulfonyl groups to alcohols, those obtained from the less
electronegative amines are significantly and uniformly less reactive, even though a second
sulfonyl group may be added to the amine. On average the difference in ΔEǂ between a sulfonate
and its sulfonimide analogue (for instance methyl mesylate and methyl MSI) was 4.5 kcal/mol.

76

Scheme 4 – Alkylating agents and the names they are referred to by in this study.

77

Computed Energies of Activation for Menshutkin Alkylation of Ammonia
80
ΔEǂ

ΔHǂ

ΔE(S→TS)

70
60
50
Energy
(kcal/mol)

40
30
20
10
0

Figure 18 – Computed Barrier Heights from the MP2/G3large level of theory. Thermal
corrections for the ΔH values were computed at 298K.

78

Table 3 – Calculated ΔES→TS values and Relevant Transition State Geometries

rTS(N-C)
Å

rTS(C-X)
Å

r0(C-X)
Å

ΔES→TS
kcal/mol

% C-X
elongation

R= CH3
R= OCH3
R= CF3
R= F

1.907
1.926
1.962
1.951

2.000
1.963
1.940
1.944

1.451
1.454
1.459
1.457

31.9
25.7
22.0
23.4

38
35
33
33

R= CH3
R= CF3
R=OCH3
R=CN

1.798
1.858
1.836
1.873

2.088
2.028
2.040
2.016

1.439
1.446
1.440
1.448

45.3
35.5
40.1
33.8

45
40
42
39

1.960
1.899
1.964
1.805
1.840
1.818

2.004
2.050
1.995
2.178
2.121
2.135

1.484
1.475
1.480
1.459
1.467
1.471

26.7
36.8
27.3
53.5
47.8
49.6

35
39
35
49
45
45

R=CH3
R=CF3
R=OCH3
R=CN

1.771
1.809
1.771
1.816

2.199
2.154
2.185
2.146

1.448
1.475
1.448
1.453

65.1
57.2
64.5
55.5

52
46
51
48

Methylsuccinimide

1.779

2.158

1.449

57.0

49

R'= CF3
R'= CH3
R'= F
R'= CH3
R'= F
R'= F

R= SO2CF3
R=SO2CH3
R=SO2F
R= H
R= H
R= CH(CH3)2

79

Table 4 – Methyl Cation Affinity in Experiment and Theory. All values are in kcal/mol.
Methyl Cation affinity
(Kcal/mol)
Cl (-)
Br (-)
CH3SO3(-)
CH3OSO3(-)
FSO3(-)
CF3SO3(-)
CH3CO2(-)
CF3CO2(-)
CH3OCO2(-)
NCCO2(-)
CH3C(O)NH(-)
CF3C(O)NH(-)
CH3OC(O)NH(-)
NCC(O)NH(-)
(CH3SO2)2N(-)
(CF3SO2)2N(-)
(FSO2)2N(-)
CH3SO2NH(-)
FSO2NH(-)
CH3SO2NCH(CH3)2(-)

MP2/G3large Experiment104 G3104

W1104

225.3
218.0
209.1
201.2
193.2
190.5
238.2
215.8
227.7
210.1
262.4
234.8
258.5
238.1
218.2
192.8
191.6
240.3
227.0
230.6
243.7

228

226.6

227.0

F(-)
OH (-)
SH (-)
PH2 (-)
NH3
H2O
Mean Absolute Deviation

258.1
276.0
246.3
268.6
104.6
65.4
1.13

258.1
277
246.9
266.7
105
66.7

258.0
276.9
246.6
268.0
104.8
66.0
0.66

258.8
276.8
247.8
269.5
105.4
66.5
0.89

80

It is well known that alkylating agents can be activated by factors such as ring strain and
inductive effects, and our series was designed to assess these effects on the barrier height to
alkylation. The most familiar activated sulfonates are activated with fluorine, and this is for good
reason; the replacement of a methyl group with a trifluoromethyl lowers the barrier by 10.
kcal/mol between methyl mesylate and methyl triflate, and 10. kcal/mol between methyl MSI
and methyl TFSI. Perhaps the most interesting illustration of the activating power of fluorine is
seen in the amides, where trifluoroacetamide has a barrier 7.9 kcal/mol lower than acetamide,
while succinimide with an extra carboxyl group is a roughly equivalent 8.1 kcal/mol lower.
Halogens are often considered to be π electron donating, however the differences we find on
barrier height between a fluorine and a trifluormethane group are modest. Oxygen can also act as
an electron withdrawing group by way of the inductive effect so it is unsurprising that we find
the barrier for dimethylsulfate 5.9 kcal/mol lower than the barrier for methyl mesylate. The
effect of ring strain on alkylation is more difficult to assess in our series, as changing the
substitution from methyl to primary alkyl is known to increase the barrier to alkylation for SN2
reactions. It has been recently proposed that this effect is due to weakening of the electrostatic
interactions between the alkyl chain and the incoming nucleophile, although steric repulsion
remains a popular explanation among organic chemists.107 Calculations done at the B3LYP/631G(d) level of theory estimate the ring strain in 1,3-propanesultone to be 10. kcal/mol, and 9.0
kcal/mol in TPS (see supporting information for more details). While these species are not used
for further analysis, we can conclude that the activation of a 5 membered ring for sulfonates and
sulfonimides is not enough to counteract the transition from methyl to primary alkyl.
Conformations in the Sulfonates are degenerate with regard to an S-C bond rotation,
however N-S bond rotations of sulfonimides are capable of producing anti, gauche and syn

81

rotamers with bond rotation. Methyl TFSI and Methyl MSI were found to have minima in the
anti and gauche geometries, and transition states were found corresponding to these minima.
Methyl FSI did not appear to have a gauche minima, but instead converged toward an eclipsed
relationship between the two fluorine substituents this geometry was discarded, and only the anti
geometry was used for FSI in this study. Gauche MSI, and TFSI were found to have ΔEǂ values
very close in energy to their corresponding anti geometries, but the anti-conformers (lowest
minima) were found to lie ~2 kcal/mol and ~6 kcal/mol lower in energy in TFSI and MSI
respectively.
In order to assess the degree to which the Hammond postulate is obeyed by these
Menshutkin reactions we have taken an approach similar to that used by Schlegel et al. for ionic
SN2.108-110 These authors defined a % bond elongation (%BE) formula for a similar analysis of
the geometries of SN2 transition states.110 We use this formula in our analysis as it is given in
equation 21.
%BE =100[ rTS(C-X)-r0(C-X)]/r0(C-X)

(eq. 21)

Where %BE is percent bond elongation, rTS(C-X) is the transition state C-X bond length, and
r0(C-X) is the C-X bond length in the isolated species.
We found the correlation between %BE of the transition state and the methyl cation
affinity to be strong (R2=0.9646, fig. 3B). Schlegel et al. reported that barriers correlate strongly
with transition state geometry in the ionic SN2 reaction with simple leaving groups derived from
a variety of elements including H, N, C and O.108,109 The dependence of ΔES→TS on %BE in our
own work is even stronger than the correlation with methyl cation affinity (R2=0.9813, fig. 3A).

82

With respect to these dependencies, the full set of nitrogen and oxygen derived leaving groups
behave as a single set.
3.3.2 On the Fitness of MCA to Describe Inherent Nucleofugality
Perhaps the most unexpected and important finding presented here is the quantitatively
different relationship between the ΔES→TS and methyl cation affinity between oxygen and
nitrogen derived leaving groups. As shown in figure 19, These quantities are strongly correlated
within each class of leaving group, but they resolve into distinct groups; with two lines appearing
when these energies share the same plot. This discrepancy suggests that there are differences in
ΔES→TS that derive solely from the electronic structure of the transition states, which are not
captured simply by the differences in energy between methyl bonded and ionized leaving groups.
In order to better understand this, analysis was extended to the transition state geometry.

Dependance of Barrier Height [ΔE(S→TS)] on Methyl Cation
Affinity

80
70

y = 0.5659x - 81.04
R² = 0.9733

60

N Leaving
Groups

50
40
ΔE(S→Ts)
(kcal/mol)

O Leaving
Groups

30
y = 0.4953x - 72.172
R² = 0.9743

20
10
0
180

200

220

240

260

280

Methyl Cation Affinity (kcal/mol)

Figure 19 – Barrier heights are very well predicted by methyl cation affinities within subsets
derived from oxygen and nitrogen, but less so in the full set. Nitrogen leaving groups universally
have higher barriers at a given value of MCA.

83

a)

Transition State %C-X Elongation vs ΔE(S→TS)

ΔE(S→Ts)
(kcal/mol)

70
60
50
40
30
20
10
0

y = 2.226x - 51.809
R² = 0.9829
30

35

40

45

50

55

%C-X Bond Elongation

b)

Transition State %C-X Bond Elongation vs MCA

270
250
230
MCA
(kcal/mol)

210
190

y = 3.5619x + 72.261
R² = 0.9659

170
150
30

35

40

45

50

55

%C-X Bond Elongation

Figure 20 – Correlations between ΔES→Ts, MCA and bond length. ΔES→Ts correlates very
strongly to methyl leaving group bond length, as a percentage of its value in the parent
methylating agent at its ground state (a) This is also true for the MCA (b) which shows that our
simulated reactions obey the Hammond postulate.

84

While MCA and ΔES→TS both correlate well with %BE (fig. 20), in the transition states of
nitrogen derived leaving groups the elongation of the C-X bond is more pronounced relative to
shortening of the nascent C-N bond than it was in the oxygen derived leaving groups (fig. 22).
This effect is especially noticeable when the bond lengths are compared directly (fig. 22A) but, it
remains significant even when the C-N and C-O bonds are normalized via %BE to the lengths of
those found in their parent electrophiles (fig. 22B). In nitrogen derived leaving groups the
dissociation process of the SN2 is ahead of the displacement process, relative to oxygen.

ΔΔEǂ Between Sulfonates and Sulfonimides is Dependant on Correlation

34
32
30
ΔEǂ 28
(kcal/mol)

Methylfluorosulfonate

26

MethylFSI

24
22
20

Figure 21 – Dependence of activation energy on theoretical method. At HF/6-31G(d) Methyl FSI
and Methylfluorosulfonate have the same activation energy. When the wave function is
correlated FSI is found to have a higher activation energy by several kcal/mol. Additional MP2
and CCSD(T) calculations at the MP2(full)/6-31G(d) geometry confirm this trend. Of the leaving
groups calculated, only the sulfonimides show a higher activation energy at MP2(full)/6-31G(d)
than HF/6-31G(d).

85

a)

C-X Bonds in Transition States are Longer When X=N

2.25
2.2
2.15
C-X Bond 2.1
length
2.05
(Å)
2
1.95
1.9

y = -1.002x + 3.9634
R² = 0.9732

Oxygen
LG
Nitrogen
LG

y = -0.8834x + 3.671
R² = 0.9805
1.7

1.8

1.9

2

C-N Bond length
(Å)

b)

Transition State % C-X Bond Elongation is More Pronounced
When X=N

55

%C-X Bond
Elongation

Oxygen LG

y = -85.575x + 202.45
R² = 0.9745

50
45

Nitrogen
LG

40
y = -73.119x + 176.3
R² = 0.988

35
30
1.75

1.8

1.85

1.9

1.95

2

C-N Bond length
(Å)

Figure 22 – Nitrogen leaving groups exhibit more extensive C-X bond elongation in their
transition states than do oxygen groups. This is very apparent when raw bond lengths are
compared (a) But this trend holds up even when %C-X elongation is used to correct for the
longer C-N bonds present in the parent alkylating agents (b).
According to the principle of nonperfect synchronization proposed by Bernasconi, a
reaction containing two or more fundamental processes will have a higher inherent barrier if
86

these processes are poorly synchronized than if they are concurrent.111,112 This clearly describes
the difference between the transition states of nitrogen and oxygen leaving groups seen in this
work; however, why this difference would lead to systematically higher ΔES→TS is difficult to
understand. A strong correlation was not observed between the ΔES→TS and the order of either of
the partial bonds found at the transition state. A classic case of nonperfect synchronization cited
by Bernasconi is the late development of resonance stabilization in the deprotonation of carbon
acids.111 An analogy could be drawn between that and the stabilization of the charge on the
leaving group. However, we found no indication that the charge is distributed significantly
differently between the transition states and the corresponding anions of our methylating agents.
A reasonably strong correlation does exist between the natural charge on the leaving
group atom at the transition state, and the ΔES→Ts (supporting information). The effect of the
nonperfect synchronization in the nitrogen cases could be explained based on this fact, as the
nitrogen groups tended to have stronger charges which were more localized on the nitrogen
atom. It seems likely that the gap in barriers is explained generally by the fact that the C-N bond
had to move further, ionizing almost completely, with less involvement of the nucleophile.
Distortions from linearity were observed in the transition states of the nitrogen derived groups
which could be explained by this notion. Whereas oxygen derived groups were nearly linear,
nitrogen derived groups exhibited N-C-X angles which ranged down to ~173° and correlated
moderately well with %BE (supporting information). Additionally, carboxamides and imides
formed hydrogen bonds between the carbonyl oxygen and the in-plane hydrogen of the departing
methyl fragment. These hydrogen bonds, which appeared to oppose the forward path of the
reaction, were not observed in the transition states of esters.

87

Transition State HOMO Energy vs ΔE(S→TS)
-0.25
-0.3
EHOMO
(h)

10

20

30

40

50

60

70

-0.35
-0.4
-0.45
y = 0.0033x - 0.5203
R² = 0.9263

-0.5
ΔE(S→TS) (kcal/mol)

Transition State HOMO Energy vs ΔE(S→TS)
-0.25
-0.3
EHOMO
(h)

-0.35

10

30
50
y = 0.0033x - 0.5115
R² = 0.8939

70

Oxygen Leaving
Groups

-0.4
-0.45
-0.5

Nitrogen Leaving
Groups

y = 0.004x - 0.5612
R² = 0.985
ΔE(S→Ts) (kcal/mol)

Linear (Nitrogen
Leaving Groups)
Linear (Oxygen
Leaving Groups)

Figure 23 – A correlation is evident between the transition state HOMO energy and the
magnitude of ΔES→TS.

88

Natural Charge on Leaving Group Atom vs
ΔE(S→TS)

0
0

10

20

30

40

50

60

70

-0.5
-1

y = -0.0121x - 0.3365
R² = 0.9051

-1.5
ΔE(S→Ts) (kcal/mol)

Natural Charge on Leaving Group Atom vs
ΔE(S→TS)
0
0

-0.5

20

40
60
80
y = -0.0126x - 0.302
R² = 0.875

N LG
O LG
Linear (N LG)

-1
-1.5

y = -0.012x - 0.3511
R² = 0.9251

Linear (O LG)

ΔE(S→TS) (kcal/mol)

Figure 24 – Natural charge on the leaving group atom correlates with ΔES→TS.
Additional support for rationalizing these results can be found in the work of Shaik et al.
who have developed models for understanding kinetic barriers using concepts from valence bond
(VB) theory.113,114 The central theme of their work is the view of a transition state as an avoided
crossing between the ground states and high energy vertically excited states.113 Ionic character
may play a role in one or both of these representations.113 A correlation diagram can be
constructed including the reactant and product complexes in which lines are drawn from the high
energy VB states to the product ground states (and vice versa) and the center point is defined as
the crossing.113 The activation energy can then be given as ΔE‡= ΔEc-B where ΔEc is the energy

89

at the crossing, and B is “quantum mechanical resonance energy” which results from mixing
between different valence bond representations of the transition state.113,114 Factors influencing B
were studied for SN2 transition states including H3(-) and CH5(-) and in both cases it was found
that B was at its highest (i.e. lowest activation energy) when the angle corresponding to the
reaction coordinate was 180°, and decreased with as the angle became more accute.114
Additionally B decreases when the bond lengths of the forming and breaking bond increase.114
Both effects were attributed to a destabilizing increase in the amount of ionic character present in
the transition state.114 These findings seem consistent with our own observations, and might
imply a causal relationship between the relatively loose and bent transition states of nitrogen
centered nucleofuges, and their higher barriers.

%BE vs. N-C-X Angle at the Transition State of Menshutkin
Reactions
181.00
y = 0.0204x + 178.36
Oxygen LG
180.00
R² = 0.1044
179.00
178.00
N-C-X angle 177.00
(degrees)
176.00
175.00
174.00
173.00
172.00

Nitrogen
LG

y = -0.3441x + 191.64
R² = 0.8229
25

35

45

55

65

% C-X Bond Elongation

Figure 25 – The transition states of nitrogen leaving groups become progressively more bent as
C-X bond gets longer. No such trend occurs in oxygen leaving groups.
A separate phenomenon is evident in the difference between sulfonates and
sulfonimides. Two of the three sulfonimides (methyl TFSI and methyl FSI) had comparable

90

barriers to their sulfonate analogues at the HF/6-31G(d) level of theory; the ΔEǂ values of
methylfluorosulfonate and methylFSI differed by only 0.03 kcal/mol. When the geometries are
reoptimized using MP2(full)/6-31G(d) we find that the difference has expanded to 4.3 kcal/mol.
In order to exclude the possibility of an artifact in the MP2 calculation, the barriers to alkylation
in methylfluorosulfonate and methylFSI were calculated using two coupled cluster
calculations,115-117 CCSD(T)/6-31G(d) and CCSD(T)/6-31+G(2d,p) at the MP2(full)/6-31G(d)
geometry. These calculations affirm the difference, with the CCSD(T)/6-31+G(2d,p) showing a
ΔΔEǂ of 5.1 kcal/mol, whereas the ΔΔEǂ for the MP2/G3large (the single point calculation
without vibrational correction) was 5.4 kcal/mol. (fig. 21) We also note that while differences are
present in the methyl cation affinities of sulfonates and sulfonimides, they are not systematic.
The change in activation energy in sulfonimides that we observe occurs concurrently with a
geometric perturbation. The nitrogen atoms of sulfonimide groups are nearly planar at HF/631G(d), whereas they become mildly pyramidal at MP2(full)/6-31G(d). A similar, but more
dramatic effect is noticeable in sulfonamides, where FSA and MSA are basically tetrahedral at
MP2(full)/6-31G(d), and MSA is significantly pyramidal at HF/6-31G(d) (see table 5). When an
isopropyl group is introduced onto the sulfonamide in the case of MeiprFSA, the
pyramidalization effect is somewhat retarded, but not as much as in the case of Methyl FSI with
two sulfonyl groups.

91

HF/6-31G(d)

MP2(full)/6-31G(d)

E= - 0.530 h

E= - 0.525 h

HOMO-5

E= - 0.530 h

E= - 0.527 h

HOMO-6

Figure 26 – Some origins in the gap between the nucleofugality of sulfonimide and sulfonate
leaving groups can be linked to differences in the electronic structure. Imide spanning orbitals
such as HOMO-5 in FSI ( Top Left) have better overlap in the planar HF/6-31G(d) geometry (
left) In the MP2(full)/6-31G(d) geometry (Right) HOMO-5 and HOMO-6 mix. Presumably these
bonding interactions are opposed by n → σ* interactions localized to one sulfonyl group or the
other.
The above observations suggest that orbital interaction between the nitrogen atom and the
two sulfonyl groups are preventing a pyramidalization analogous to that which occurs when only
one is present. Sulfonyl groups have been well studied, and it is commonly been concluded that
hyperconjugative nN→σ* interactions with the S-O bond, delocalize electrons in the sulfonyl
group.118,119 Additionally, it has been shown that sulfamidates, which have a negatively charged
sulfonamide bound to a nitrogen cation, have sulfonyl oxygens that form significantly stronger

92

hydrogen bonds than do sulfonamides, or even the usually more basic sulfones and sulfoxides.120
This suggests an explanation for the drive to pyramidalization as sulfonamide derived species
ionize: a pyramidal geometry at nitrogen facilitates better overlap in the n→σ* conjugation, but
when two sulfonyl groups are present, ideal interaction with each is not possible. While the size
of the sulfonimide wave functions and the relative ambiguity of their frontier orbitals make a full
accounting of this phenomenon difficult, a convincing example of this is illustrated in figure 23,
in the HOMO-5 and HOMO-6 energy levels of the FSI transition state. In the HF/6-31G(d)
structure, HOMO-5 contains a bonding orbital that spans the length of the imide moiety, whereas
at MP2(full)/6-31G(d), mixing occurs between HOMO-5 and HOMO-6, destabilizing both
orbitals.
Table 5 – Transition State Pyramidalization in Sulfonamide Species at HF and MP2 geometries
(all values are given in degrees).
HF/6-31G(d)

MP2(full)/6-31G(d)

Dihedral (S-N-R-C) Dihedral (S-N-R-C)

Angle(S-N-R)

Methyl FSI

178.86

161.00

121.39

Methyl FSA

174.97

126.36

109.31

Methyl MSI

178.83

169.65

121.89

Methyl MSA

132.05

121.27

107.27

Meipr FSA

177.83

134.43

119.9

A literature precedent does exist for the dependence of intrinsic the barrier of SN2
reactions on the leaving group atom. Hoz et al. used G2 derived calculations to study
symmetrical anionic SN2 reactions and concluded that the intrinsic barrier changes between
groups of the periodic table, and stays relatively constant within them, up until the border

93

between metals and non-metals.121 Nitrogen and oxygen had intrinsic barriers of 29.3 and 19.5
kcal/mol respectively, whereas the halogens clustered near 10 kcal/mol.121 This inherent
difference was then shown to extend to similar SN2 displacements occurring at nitrogen.122 In
this work we have shown that these findings generalize beyond symmetric, charged variants of
the SN2, and rationalize them within the context of our systems of interest.
3.4

Conclusion
The ΔES→TS of nitrogen and oxygen derived leaving groups in the Menshutkin reaction

correlate well with the thermodynamic stability of the ions, as determined by MCA, differences
exist between the two classes. These differences are rooted in the synchronization of the events
inherent in the SN2 process, as well as geometric limitations on the efficiency of activating
groups on nitrogen. This finding is relevant to recent work on indices of nucleofugality, because
it shows that complicating factors may exist which are relevant to the dissociation of a
nucleofuge, but are not directly related to the stability of the fully dissociated group.

94

4
4.1

Chapter 4: Summary and Future Study
Summary
In summary, two significant findings have come from my research and have been

described in this work. The first concerns the effect of triazoles on the conductivity of lithium
ion electrolytes.
Model compounds were synthesized which contained increasing numbers of triazoles per
ether oxygen. It was found that increasing the number of triazoles in the material increased the
glass transition temperature, which was inversely proportional to room temperature conductivity.
Increasing the proportion of triazoles also lead to crystallization behavior which enable us to
obtain a single crystal X-ray structure of one of our model compounds, 6EO2T. Ab initio
calculations showed that tetra coordinate solvent shells containing a triazole have roughly the
same energy as those which do not contain triazoles, which led implies another explanation for
the effect of triazoles on conductivity.
A second effect triazoles were observed to have on temperature dependant conductivity
was the induction of compensation behavior, whereby the Arrhenius pre-exponential factor has
an approximately exponential dependence on the activation energy. We rationalize our data by
invoking the polarity of the traizole which has been shown in other studies to affect the
Arrhenius pre-exponential factor of transport processes in polar liquids. Additionally, our crystal
structure showed dipole-dipole interactions between triazole moieties which shows how dipoles
are most likely enhancing the glass transition temperature and the activation energy of
conductivity.

95

A second study probed the nuclefugality of polyatomic oxygen and nitrogen derived
leaving groups. By optimizing the transition states of Menshutkin reactions, and calculating the
methyl cation affinities of the same species, we have been able to pinpoint a difference in the
nucleofugality between these sets of leaving groups that relies on transition state organization
rather than anion stability.
The inherent differences between polyatomic oxygen and nitrogen leaving groups seem
to stem from a few different factors. The first factor is the non-linearity of the nitrogen
nucleofuge transition states relative to those of oxygen nucleofuges. This distortion has been
attributed to a less effective delocalization of electron density, and thus a higher energy in other
work. A second difference arises from the preferred geometry of sulfonamides during the leaving
process. Sulfonamides show a tendancy to pyramidalize during the leaving process which can
most likely be attributed to stabilization via n→σ* interactions from the nitrogen to the sulfur.
When a second sulfonyl group is added, pyramidalization becomes less favorable due to the
presence of orbitals whose lowest energy results from a planar geometry at nitrogen. The effect
of this is that a second sulfonyl group becomes less effective at activating nitrogen as a
nucleofuge than the first sulfonyl.
These findings raise additional questions, which might be addressed by other researchers,
or myself at a later time in my career. These will be expounded in the two sections that follow.

96

4.2

Future Directions for CUAAC Derived Lithium Single Ion Conductors
The effects exerted by the triazole on the conductivity of lithium ion salt complexes are

interesting from a mechanistic standpoint, however the study described here did not demonstrate
any useful consequences of this behavior. Frech et al. actually proposed that the synthesis of
highly polar electrolyte materials aimed at increasing the Arrhenius pre-exponential term might
be a productive way to increase the conductivity of electrolytes for batteries;72 however, my
work has inadvertently shown a limitation of this approach.
However if my explanation for compensation behavior is correct, then the triazoles are
activating and impeding the conductivity of electrolyte materials through different mechanisms,
and this fact could be manipulated to improve single ion conductor materials. Des Marteau and
Borodin et al. showed earlier that ionic correlation is a problem for lithium single ion conductors,
affecting the chain to chain transfer time of the lithium ion in these materials as well as the
ability of the materials to transport charge through co-diffusion of the lithium with the chain.20
A possible mechanism for enhancing the conductivity of lithium electrolytes might be the
enhancement of local dipole density in the region of the anion moiety. In order to keep the
overall concentration of triazoles in the material relatively low this would mean the introduction
of one triazole near an anion moiety (19). Materials of nearly identical composition (22) but
lacking triazoles would be used as controls (Scheme 5).

97

Scheme 5 – Proposed materials and synthesis for the investigation of triazoles as an activating
moiety in lithium single ion conductors.

98

The PEG starting materials used for materials 19 and 22 could be in the range of Mn= 300 –
1000, and the study would probably benefit from the synthesis and testing of several chain
lengths. Shorter PEG materials are technically easier due to the fact that PEG becomes waxy
around Mn= 600 and its solubility in organic solvents diminishes as molecular weight increases.
Additionally blends of 19 and 22 with PEGDME 500 might be worth testing as neat materials
would have high concentrations of ions. Internal data to the Baker group has shown that
PEGDME 500 complexes with LiTFSI show the highest conductivity when they contain roughly
1 lithium per 32 ether oxygens.4 The proposed single ion conductors could have several times
that concentration of lithium depending on the chain length.
In the event that useful data comes from this project, these systems should be modeled
using molecular dynamics simulations in order to better understand the nature of the activation.
Modeling lithium ion transport is tricky and requires a specialized polarizable force field. Rather
than modeling ourselves, I believe it would be advantageous to approach Oleg Borodin about a
collaboration.17
4.3

Future Directions for Studies of Nucleofugality in Activated Leaving Groups
In chapter 3 we showed that inherent differences exist between the Nucleofugality of

polyatomic oxygen and nitrogen derived leaving groups using computational methods. The
obvious next step for this work would be to continue exploring different classes of leaving
groups using similar computational methods. The first group that might be fruitful would be
polyatomic carbon leaving groups. Polyatomic carbon leaving groups are interesting, because
carbon acids are known with pKa values of less than 10, however carbon nucleofuges are
extremely rare in any other context. Polyatomic carbon leaving groups might prove more viable
than expected, or similar problems might be observed to those seen in nitrogen nucleofuges.

99

An additional set of leaving groups which might be interesting to look at would be
positively charged ammonium leaving groups in comparison with negatively charged borates and
borohydrides. These compounds might be an interesting comparision, as the initial electronic
structures should be quite similar, however they lead to quite different outcomes.

100

APPENDICES

101

4.4

Appendix 1 – Additional Study of TPS

Introduction
The Synthesis of TPS was a part of an effort to make stable triple ion type ionic liquids,
similar to those of Ohno et al.124-126 Synthesis of TPS was accomplished in four steps from 1,3
propanesultone, and proceeded mostly through known materials. TPS itself was not a known
material and has been fully characterized, including single crystal X-Ray Diffraction. While most
of the synthetic work shown is derived from literature protocols,127-129 the final step required
extensive independent optimization and is not a trivial procedure. A variety of bases and running
times were tried, however Hünig’s base worked best, under the conditions described below. This
choice was partially informed by the literature synthesis of similar compounds.130 X-Ray section
is courtesy of Dr. Richard Staples. Single crystal geometric data was compared with a geometric
optimization of the TPS structure at MP2(full)/6-31G(d) and the two were found to be in good
agreement.

102

Synthesis of TPS

Scheme 6 – Synthetic Route from 1,3 Propane sultone to TPS.
3-Chloropropane-1-sulfonyl chloride 1127
To an oven dried round bottom flask were added 50g (0.41 mol) 1,3-propanesultone, 100g (0.84
mol) thionyl chloride, and 0.25 g dimethylformamide (3.4 mmol). A jacketed condenser and
drying tube containing anhydrous calcium chloride pellets were affixed to the round bottomed
flask, which was then heated to reflux at 75°C (oil bath temperature). The flask was allowed to
reflux over night after which point it was cooled, and a short path distillation apparatus replaced
the condenser. Excess thionyl chloride and byproducts were removed by distillation (Vapor T =
73°C). Product 1 was purified by distillation under reduced pressure. Two fractions were
collected, the first of which had a Tvap= 60°C at P = 9.7 Torr. This fraction reacted vigorously
with water and contained very little hydrogen when analyzed by NMR, this was believed to be
mostly a mixture of chlorosulfinic acid, and chlorosulfinic anhydride. A second fraction had a
Tvap=105°C at P = 898 mTorr; this proved to be product 1, which was obtained as a tan liquid in
98% yield (69.5g) and stored under nitrogen. Compound was confirmed by comparison to data in
103

(1) and publicly available spectra from Sigma Aldrich. 1H NMR (600MHz) (CDCl3) δ= 2.49 (m,
2H, CH2CH2CH2) 3.70 (dd, 2H, CH2CH2S(O)2, J=6.2, 6.2 Hz) 3.84 (dd, 2H, ClCH2CH2, J=7.5,
7.5 Hz). 13C NMR (CDCl3) δ= 30.01, 44.18, 65.06.

3-Chloropropane-1-sulfonamide 2127
To an oven dried three neck round bottom flask were added 10g (0.056 mol) 1 and 250 mL
dichloromethane, which had been freshly distilled off of calcium hydride to insure dryness. The
flask was cooled on an ice salt bath which was kept at a temperature at or below -5°C for the
duration of the reaction. The flask was initially shielded from water through use of a nitrogen
line. An aspirator and bubbler were affixed to the flask to facilitate the introduction of ammonia
gas. Anhydrous ammonia gas was then bubbled through the reaction for one hour with
continuous stirring using a Teflon coated stirbar. White precipitate developed in the flask. After
the ammonia cylinder was disconnected, the reaction was allowed to stir for an additional forty
five minutes to insure completion. Ammonium chloride was removed by gravity filtration, and
rinsed with acetonitrile. Crude product was concentrated on a rotovap. Pure 3-chloropropane-1sulfonamide was obtained by recrystallization from chloroform in 91% yield (8.2g). The product
was a colorless solid. mp= 62 - 65°C 1H NMR (600 MHz) (CD3CN) δ= 2.22 (m, 2H,
CH2CH2CH2) 3.20 (dd, 2H, CH2CH2S(O)2, J=7.6, 7.6 Hz) 3.72(t, 2H, ClCH2CH2, J=6.4 Hz)
5.35 (broad singlet, 2H, S(O)2NH2) 13C NMR (CD3CN) δ= 29.82, 45.79, 54.61.

104

1,3-Propanesultam 3127
Absolute ethanol (150 mL) was added to a rigorously dried round bottom flask and sparged with
dry nitrogen for 5 – 10 min to remove oxygen. The solvent was cooled on an ice bath, and then
5.08g NaH in 60% dispersion with mineral oil (0.127 mol NaH) were added to the ethanol in
pieces. Once alkoxide generation was complete 20g (0.127 mol) 2 were added as a solution in
625 mL absolute ethanol. The reaction mixture was protected with a condenser and a calcium
chloride drying tube, and refluxed overnight until high conversion was evident in NMR. Ethanol
was removed by rotovap, and reaction mixture was dissolved in chloroform and filtered, then
dried over sodium sulfate. Sodium chloride produced in the reaction was washed with additional
chloroform. Product was purified by distillation under reduced pressure (Tvap= 179 °C, P=629
mTorr) however mineral oil codistilled. Mineral oil was removed by washing the product with
hexanes. Product was then dissolved in dichloromethane and dried over Sodium Sulfate to
remove excess water. Product was obtained in 79% yield (12.1g) as a light yellow oil. Method
used is similar to that of King et al. (127). Product confirmed by comparison to data of Askin et
al. (128) 1H NMR (500 MHz) (CDCl3) δ= 2.39 (p, 2H, CH2CH2CH2, J=7.2 Hz) 3.03 (t, 2H,
NHCH2CH2, J=7.6 Hz) 3.36 (t, 2H, CH2CH2SO2, J= 6.9 Hz) 4.55 (broad singlet, 1H,
SO2NHCH2) 13C NMR δ= 24.10, 42.36, 46.73.

N-triflylpropanesultam (TPS) 4
0.5 g (4.1 mmol) 3 where added to a rigorously dry round bottom flask equipped with a teflon
coated stir bar. A 10 mL addition funnel was added and placed on a nitrogen line to shield the
reaction from water. The round bottom flask was cooled on a dry ice acetone bath. Following

105

cooling, 1.5 mL (8.9 mmol) of trifluoromethanesulfonyl anhydride were added to 8 mL of
freshly distilled rigorously dried dichloromethane, which were added to the flask and allowed to
cool. An aliquot of 0.71 mL (4.1 mmol) diisopropylethylamine was then added to an additional 8
mL of dichloromethane in the addition funnel. The resulting solution was added dropwise over a
period of roughly five minutes. After the reagents were combined, the bath was removed, and the
flask allowed to equilibrate to room temperature. The color of the solution gradually darkened
until it was an opaque jet black. The reaction was allowed to stir for roughly 48 hours, after
which, 10 mL distilled water were added. The biphasic mixture was transferred to a separatory
funnel, and after separation the aqueous phase was extracted with 2 aliquots of 15 mL
dichloromethane. The organic phase was dried of sodium sulfate, and concentrated with a
rotovap to yield darkly colored and tarry crude solids. The crude product was sublimed (p = 668
mTorr, Bath T = 100°C) to yield a white crystalline solid in 65% yield (0.67g). Crystals were
grown for single crystal X-Ray study by slow evaporation from Toluene. Compound is
previously unknown. mp=111-115°C HRMS [M-H]- Calculated: 251.9612 Measured: 251.9604
ppm: -3.2. 1H NMR (CD3OD) (600 MHz) δ= 2.50 (p, 2H, CH2CH2CH2, J= 6.6 Hz) 3.66 (t, 2H,
SO2CH2CH2, J= 7.3) 4.00 (t, 2H, (SO2)2NCH2CH2, J= 6.8 Hz) 13C NMR, (600 MHz) (CD3CN)
δ= 19.10, 48.88, 50.15, 119.47 (q, CF3, J= 323 Hz) IR (KCl Pellet) cm-1= 3022, 2965, 1478,
1403, 1387, 1347, 1325, 1283, 1237, 1204, 1177, 1149, 1133, 1070, 1045, 1014, 980, 851, 727,
661, 600, 575, 552, 499, 449, 427, 403.

106

Crystallography of TPS

Experimental Section
A colorless plate crystal with dimensions 0.30 x 0.27 x 0.03 mm was mounted on a Nylon loop
using very small amount of paratone oil.
Data were collected using a Bruker CCD (charge coupled device) based diffractometer equipped
with an Oxford Cryostream low-temperature apparatus operating at 173 K. Data were measured
using omega and phi scans of 1.0° per frame for 30 s. The total number of images was based on
results from the program COSMO74 where redundancy was expected to be 4.0 and completeness
to 0.83 Å to 100%. Cell parameters were retrieved using APEX II software75 and refined using
SAINT on all observed reflections. Data reduction was performed using the SAINT software76
which corrects for Lp. Scaling and absorption corrections were applied using SADABS77 multiscan technique, supplied by George Sheldrick. The structures are solved by the direct method
using the SHELXS-97 program and refined by least squares method on F2, SHELXL-975,
which are incorporated in OLEX2.77
The structure was solved in the space group P21/c(no. 14). All non-hydrogen atoms are
refined anisotropically. Hydrogens were calculated by geometrical methods and refined as a
riding model.

All drawings are done at 50% ellipsoids.

Acknowledgement. The CCD based x-ray diffractometer at Michigan State University
were upgraded and/or replaced by departmental funds.

107

Table 6 – Crystal Data and Structure Refinement for TPS
Identification code
nej413
Empirical formula
C4H6F3NO4S2
Formula weight
253.22
Temperature/K
173.0
Crystal system
monoclinic
Space group
P21/c
a/Å
13.9496(7)
b/Å
5.9882(3)
c/Å
10.5155(5)
α/°
90
β/°
92.202(3)
γ/°
90
3
Volume/Å
877.74(7)
Z
4
3
ρcalcmg/mm
1.916
-1
m/mm
6.009
F(000)
512.0
3
Crystal size/mm
0.296 × 0.269 × 0.034
2Θ range for data collection 6.34 to 144.042°
Index ranges
-16 ≤ h ≤ 16, -7 ≤ k ≤ 7, -11 ≤ l ≤ 12
Reflections collected
6768
Independent reflections
1675[R(int) = 0.0742]
Data/restraints/parameters
1675/0/127
2
Goodness-of-fit on F
1.140
Final R indexes [I>=2σ (I)] R1 = 0.0681, wR2 = 0.1893
Final R indexes [all data]
R1 = 0.0812, wR2 = 0.1993
-3
Largest diff. peak/hole / e Å 0.85/-0.45

108

a)

b)

Figure 27 – The crystal structure of TPS. A view of a single molecule is shown in part a with
thermal elipsoids shown at 50% probability. The packing along the b axis of the crystal is also
shown (b).

109

Table 7 – Comparison Between the Crystal Geometry of TPS and Geometry at MP2(full)/631G(d) (Bond Lengths)
Bond Lengths for TPS.
Atom
Atom
Experiment/Å
S1
O3
1.410(4)
S1
O4
1.412(5)
S1
N1
1.621(5)
S1
C4
1.843(6)
S2
O1
1.426(5)
S2
O2
1.428(5)
S2
N1
1.715(4)
S2
C1
1.757(5)
F1
C4
1.303(8)
F2
C4
1.297(8)
F3
C4
1.310(8)
N1
C3
1.483(7)
C1
C2
1.524(8)
C2
C3
1.517(8)

Calculated/Å
1.450
1.455
1.653
1.840
1.454
1.459
1.754
1.789
1.330
1.334
1.345
1.475
1.519
1.528

110

Deviation/Å
0.040
0.043
0.032
-0.003
0.028
0.031
0.039
0.032
0.027
0.037
0.035
-0.008
-0.005
0.011

Table 8 – Comparison Between the Crystal Geometry of TPS and Geometry at MP2(full)/631G(d) (Bond Angles)
Bond Angles for TPS.
Atom
Atom
Atom
O3
S1
O4
O3
S1
N1
O3
S1
C4
O4
S1
N1
O4
S1
C4
N1
S1
C4
O1
S2
O2
O1
S2
N1
O1
S2
C1
O2
S2
N1
O2
S2
C1
N1
S2
C1
S1
N1
S2
C3
N1
S1
C3
N1
S2
C2
C1
S2
C3
C2
C1
N1
C3
C2
F1
C4
S1
F1
C4
F3
F2
C4
S1
F2
C4
F1
F2
C4
F3
F3
C4
S1

Experiment/°
121.8(3)
108.3(2)
107.0(3)
109.9(3)
105.1(3)
103.1(3)
118.0(3)
108.0(3)
111.4(3)
110.0(3)
113.8(3)
92.6(2)
122.0(3)
124.0(4)
113.9(4)
103.9(4)
107.4(4)
104.7(4)
110.4(4)
107.4(6)
108.9(5)
110.5(6)
110.2(6)
109.3(4)

111

Calculated/°
124.8
109.0
106.1
107.4
105.6
101.6
121.4
110.3
112.0
108.6
109.7
90.4
123.8
121.7
114.5
104.4
106.0
104.4
110.2
109.1
109.1
109.8
109.1
109.4

Deviation/°
3.0
0.7
-0.9
-2.5
0.5
-1.5
3.4
2.3
0.6
-1.4
-4.1
-2.2
1.8
-2.3
0.6
0.5
-1.4
-0.3
-0.2
1.7
0.2
-0.7
-1.1
0.1

Estimation of Ring Strain in TPS†
Ring strain was calculated for 1,3-Propanesultone and N-Triflylpropanesultam using the
following homeodesmotic reactions seen in figure 25.

Figure 28 – Homeodesmotic reactions used to calculate the strain energy of sulfonyl
herterocycles.
Structures were minimized at the B3LYP/6-31G(d) level of theory in GAMESS using the
DFT=B3LYP keyword (as opposed to the slightly different DFT=B3LYP1 version). Ring strain
was estimated to be 10.2 kcal/mol in 1,3-Propanesultone, and 9.0 kcal/mol in Ntriflylpropanesultam.

†

This page is a republication of data from the supporting information of Spahlinger, G.; Jackson
J. E. Phys. Chem. Chem. Phys. 2014, 16, 24559 – 24569. It has been republished with permission
from the PCCP Owner Societies. The original article may be found online at the following link:
http://pubs.rsc.org/en/content/articlelanding/2014/cp/c4cp03741c#!divAbstract

112

4.5

Appendix 2 – Spectal Data and Geometric Results from Computations
This section contains annotated proton and carbon 13 NMR spectra from the compounds

appearing in this work which had not previously been synthesized. Labels have been added to the
spectra to show how the 1H and 13C atoms in the proposed structure correspond to the lines in the
specra. Additionally, output geometries have been provided for geometric optimizations of
compounds whose electronic structures or energies were analyzed in chapters 2 and 3 at the
relevant levels of theory. All structures described were first optimized in C1 symmetry. The
structures described in Chapter 3 were scrutinized carefully for possible symmetry, and rerun in
the highest Abelian point group they seemed to be capable of converging to. Point groups given
for this set should be considered the highest symmetry in the converged structures. Structures in
chapter 2 were not rerun to confirm symmetry. Although some structures appeared to be
converging to higher symmetries, the point group in these calculations is assumed to be C1.

113

Annotated 1H and 13C Spectra of Selected Compounds
1

H

13

C

Figure 29 - 6EO2T

114

1

H

13

C

Figure 30 - 8EO2T

115

1H

13

C

Figure 31 - 6EO1T

116

1

H

13

C

Figure 32 - 8EO1T

117

1

H (Methanol d4)

13

C (Acetonitrile d3)

Figure 33 - N-Triflylpropanesultam (TPS)

118

MP2(full)/6-31G(d) Geometries and Energies of Simulated Solvent Shells from G3MP2
Calculations with and without a Bound Lithium Cation.

Table 9 - Glyme, Energy: -307.87678
C
C
O
O
C
C
H
H
H
H
H
H
H
H
H
H

6
6
8
8
6
6
1
1
1
1
1
1
1
1
1
1

0.641616
-0.641616
1.708579
-1.708579
2.965284
-2.965284
0.677787
0.677787
-0.677787
-0.677787
3.090045
3.726478
3.090045
-3.726478
-3.090045
-3.090046

0.399513
-0.399513
-0.531639
0.531639
0.120394
-0.120394
1.045847
1.045847
-1.045847
-1.045847
0.749078
-0.660232
0.749080
0.660232
-0.749080
-0.749078

0.000000
0.000000
0.000000
0.000000
0.000000
0.000000
-0.889262
0.889261
-0.889262
0.889262
0.891947
0.000000
-0.891945
-0.000001
-0.891946
0.891947

Table 10 - Glyme-(Li+), Complex Energy: -315.22669
C
C
O
O
C
C
Li
H
H
H
H
H
H
H
H
H
H

6
6
8
8
6
6
3
1
1
1
1
1
1
1
1
1
1

-0.714327
0.714326
-1.313495
1.313495
-2.748016
2.748017
0.000000
-1.258219
-0.765347
1.258219
0.765346
-3.101517
-3.196376
-2.996115
3.101517
3.196376
2.996116

-0.912652
-0.912652
0.329428
0.329428
0.336643
0.336643
1.676941
-1.755075
-0.984161
-1.755075
-0.984162
1.313806
-0.442621
0.173268
1.313806
-0.442621
0.173267

119

0.242036
-0.242036
-0.182073
0.182072
-0.002444
0.002445
0.000000
-0.198903
1.334828
0.198903
-1.334828
-0.326419
-0.621636
1.049427
0.326419
0.621638
-1.049426

Table 11 - Glyme + DME, Energy: -462.40188
C
C
O
C
O
C
C
O
C
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H

6
6
8
6
8
6
6
8
6
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1

-2.749443
-1.845247
-1.561499
-0.549944
-0.019917
1.225974
1.555618
2.121614
1.757107
-2.445309
-3.380290
-3.333940
-2.473329
-2.388798
-0.747625
0.158084
1.575174
1.110864
1.954637
1.851353
0.462493
1.939401
2.253954
2.102877
0.674491

-1.340694
0.557657
-0.671012
1.268741
1.755734
2.402627
-1.936414
-0.852544
-0.922555
-2.270828
-1.570933
-0.739570
1.195884
0.373054
2.102893
0.580776
2.741666
3.273207
1.710349
-1.813572
-1.933950
-2.898355
-0.090417
-1.866106
-0.827695

120

-0.536394
0.498539
-0.151179
0.790593
-0.427915
-0.211788
0.955154
0.236125
-1.137342
-1.016968
0.333246
-1.245194
-0.140051
1.439571
1.485212
1.269913
-1.187951
0.449661
0.223281
1.998419
0.875308
0.586107
-1.636383
-1.583124
-1.259858

Table 12 - Glyme-(Li+)-DME, Energy: -469.796041
O
H
C
C
C
O
C
Li
O
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C

8
1
6
6
6
8
6
3
8
6
6
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1

1.066685
3.150957
2.299057
1.017221
2.299057
1.066687
1.017225
-0.327147
-2.199003
-3.007060
-3.007069
2.356559
2.356555
3.150959
0.044734
1.129833
1.809283
-2.326282
-3.634586
-3.632522
-2.326297
-3.634614
-3.632511
0.044727
1.809276
1.129831

-1.317252
-1.263785
-0.700824
-2.716841
0.700822
1.317252
2.716841
0.000001
-0.000005
-0.604703
0.604707
-0.692824
0.692822
1.263782
3.083454
2.850156
3.253161
-1.034589
0.153422
-1.389995
1.034583
-0.153408
1.390008
-3.083452
-3.253163
-2.850155

121

0.133927
0.121744
-0.276792
-0.205224
0.276794
-0.133929
0.205221
-0.000004
-0.000004
1.026706
-1.026700
-1.372322
1.372325
-0.121739
-0.118649
1.285009
-0.322316
1.760995
1.502159
0.594504
-1.761001
-1.502142
-0.594486
0.118643
0.322315
-1.285011

Table 13 - Glyme + Glyme, Energy: -615.75824
C
O
C
C
O
C
C
O
C
C
O
C
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H

6
8
6
6
8
6
6
8
6
6
8
6
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1

-4.341091
-3.010677
-2.943020
-1.485976
-1.373980
-0.036362
0.046079
1.356048
1.506729
2.925895
3.028982
4.327327
-4.303736
-4.764751
-4.988097
-3.539637
-3.320992
-0.899511
-1.119520
-0.004200
0.668541
0.264864
-0.023711
-0.720045
-0.133035
1.306699
0.812237
3.135992
3.636004
4.322004
4.582947
5.087476

1.058400
0.628004
-0.775380
-1.103986
-2.501374
-2.860332
2.870331
2.502812
1.096719
0.777455
-0.637976
-1.058707
2.138367
0.586363
0.828745
-1.079653
-1.319710
-0.775052
-0.556357
-3.949457
-2.496106
-2.450036
3.953379
2.387047
2.596278
0.679006
0.625964
1.205549
1.214618
-2.148990
-0.704949
-0.693743

122

-0.559869
-0.331164
-0.130095
0.095384
0.279006
0.593603
0.614345
0.207230
0.214243
-0.193210
-0.215615
-0.595780
-0.704640
-1.456178
0.297166
0.742065
-1.007591
-0.773864
0.976275
0.634485
-0.164540
1.566771
0.508708
-0.005489
1.663031
1.212786
-0.493121
-1.184065
0.523637
-0.587054
-1.603428
0.107663

Table 14 - Glyme-(Li+)-Glyme, Energy: -623.18874
O
H
C
C
C
H
O
H
C
Li
O
C
C
H
H
H
H
H
H
H
C
H
H
H
H
H
H
H
O
C
H
H
H

8
1
6
6
6
1
8
1
6
3
8
6
6
1
1
1
1
1
1
1
6
1
1
1
1
1
1
1
8
6
1
1
1

1.435719
3.519662
2.659720
1.342860
2.659693
-3.519644
1.435677
-2.703904
1.342759
0.000000
-1.435694
-2.659703
-1.342800
2.703921
2.703877
3.519622
0.379570
1.397517
2.148514
-2.703894
-2.659708
-3.519638
-0.379614
-2.148562
-1.397566
0.379678
2.148630
1.397641
-1.435700
-1.342821
-0.379635
-1.397595
-2.148584

1.094065
1.027054
0.350627
1.869429
-0.350662
0.742019
-1.094080
1.489831
-1.869436
0.000010
-0.743058
-0.666676
-1.950062
-0.374332
0.374296
-1.027102
-2.376120
-1.218377
-2.607238
-1.489819
0.666688
-0.742012
-1.921332
-1.983819
-2.828049
2.376129
2.607217
1.218373
0.743080
1.950082
1.921361
2.828071
1.983827

123

0.743055
0.741968
0.666653
1.950054
-0.666707
-1.027058
-0.743068
0.374338
-1.950066
0.000009
1.094081
0.350655
1.869432
1.489800
-1.489855
-0.742051
-1.921319
-2.828058
-1.983832
-0.374309
-0.350626
1.027088
2.376123
2.607227
1.218368
1.921341
1.983784
2.828046
-1.094054
-1.869409
-2.376102
-1.218349
-2.607203

Table 15 - 4-Methoxymethyl-1,2,3-Triazole, Energy: -394.90167
N
C
C
N
N
H
C
O
C
H
H
H
H
H
H

7
6
6
7
7
1
6
8
6
1
1
1
1
1
1

-1.400475
-0.370011
-0.870993
-2.211938
-2.547851
-2.954152
1.054389
1.855637
3.236678
-0.398586
1.263739
1.263351
3.778956
3.511352
3.511718

-1.159229
-0.272576
1.014156
0.822928
-0.485243
1.513956
-0.709306
0.460258
0.138116
1.983562
-1.326018
-1.330141
1.083722
-0.437107
-0.441570

-0.000539
0.000493
0.000896
0.000018
-0.000823
-0.000173
0.001325
-0.001432
-0.000326
0.001496
0.889093
-0.883638
-0.002585
0.893653
-0.891301

Table 16 - 4-Methoxymethyl-1,2,3-Triazole-(Li+),
Energy: -402.25682
N
C
C
N
N
H
C
O
C
Li
H
H
H
H
H
H

7
6
6
7
7
1
6
8
6
3
1
1
1
1
1
1

-0.748360
-0.438595
-1.624808
-2.572931
-2.069208
-3.585893
0.989591
1.813108
3.219080
0.889872
-1.857168
1.218020
1.218006
3.767261
3.463803
3.463385

0.891048
-0.433561
-1.145612
-0.181222
1.059394
-0.288401
-0.878671
0.300586
-0.035633
1.977293
-2.200787
-1.477338
-1.479360
0.904859
-0.608513
-0.610704

124

0.000537
0.000293
-0.000347
-0.000413
0.000087
-0.000820
0.000805
-0.000487
-0.000383
-0.000023
-0.000718
0.891258
-0.888279
-0.001684
0.897069
-0.896543

Table 17 - 4-MeOMe-1,2,3-Triazole + DME, Energy: -549.42683
N
N
C
C
N
C
O
C
H
C
O
C
H
H
H
H
H
H
H
H
H
H
H
H

7
7
6
6
7
6
8
6
1
6
8
6
1
1
1
1
1
1
1
1
1
1
1
1

-1.429055
-2.513129
-2.353225
-1.079933
-0.544086
-0.345684
-1.042440
-0.395996
-3.310039
2.948523
2.794781
2.523161
-3.098676
0.692176
-0.317370
-0.976701
0.630667
-0.366387
3.150771
3.796195
2.037363
2.388063
1.614469
3.363555

-2.334785
-1.686233
-0.341364
-0.169356
-1.387436
1.104280
2.126430
3.378770
-2.234331
-0.675802
0.041361
-0.850849
0.353758
1.009627
1.331146
4.105607
3.347288
3.682953
0.064293
-1.372543
-1.233289
-0.238898
-1.432251
-1.540582

125

-0.213231
0.262130
0.267825
-0.238747
-0.522410
-0.480087
0.218988
0.061215
0.567173
-0.997105
0.220960
1.292064
0.620231
-0.133128
-1.558621
0.629767
0.447406
-0.993782
-1.772844
-0.937548
-1.241116
2.185001
1.099155
1.452310

Table 18 - 4-MeOMe-1,2,3-Triazole-(Li+)-DME,
Energy: -556.82511
N
C
C
N
N
H
C
O
C
Li
O
C
C
H
H
H
H
H
H
H
H
H
H
H
H

7
6
6
7
7
1
6
8
6
3
8
6
6
1
1
1
1
1
1
1
1
1
1
1
1

-2.539124
-3.019176
-1.876720
-0.801333
-1.199674
-3.059282
-1.682903
-0.270987
0.018535
0.909566
2.623103
3.919960
2.713420
-4.075021
-2.134743
-2.134755
1.102886
-0.396201
-0.396049
3.764095
4.473732
4.474708
1.694002
3.242174
3.241042

-1.949097
-0.684398
0.095925
-0.734624
-2.005040
-2.824051
1.578916
1.827292
3.238513
0.284648
-0.446236
0.170810
-1.884791
-0.455724
2.036726
2.036726
3.334805
3.707122
3.707166
1.248972
-0.123227
-0.124252
-2.269694
-2.223238
-2.222245

126

-0.000040
0.000349
0.000135
-0.000250
-0.000456
-0.000077
0.000047
0.000068
-0.000003
-0.000422
-0.000385
0.000008
0.000483
0.000654
-0.889266
0.889354
-0.000099
-0.896251
0.896291
-0.000711
0.895538
-0.894577
0.000043
-0.894524
0.896534

Table 19 - 4-MeOMe-1,2,3-Triazole + Glyme, Energy: -702.78713
C
N
N
N
C
C
O
C
H
C
O
C
C
O
C
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H

6
7
7
7
6
6
8
6
1
6
8
6
6
8
6
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1

-2.478803
-2.675589
-3.984193
-4.589200
-3.703818
-1.120907
-1.300824
-0.052026
-5.602680
5.178466
4.557816
3.146629
2.586424
1.176231
0.534779
-3.984840
-0.549808
-0.548367
-0.267295
0.535852
0.537148
6.254884
4.904722
4.903727
2.790691
2.791692
2.940179
2.939294
-0.537682
0.812900
0.812215

0.196905
-1.148750
-1.397440
-0.190870
0.834167
0.810048
2.218779
2.888165
-0.157436
1.082167
-0.190072
-0.079314
-1.483697
-1.363264
-2.634239
1.875212
0.483306
0.482880
3.957131
2.634824
2.634363
0.909111
1.660143
1.662741
0.463721
0.461177
-2.027253
-2.024740
-2.441753
-3.212544
-3.210216

127

0.000124
0.000155
-0.000791
-0.001408
-0.000883
0.001080
0.000641
0.001377
-0.002181
-0.001527
-0.000020
-0.000972
0.000728
-0.000139
0.001279
-0.001233
0.881383
-0.878110
0.000951
0.893783
-0.890041
-0.000673
-0.894656
0.889610
0.887762
-0.891654
-0.887519
0.890859
0.000655
-0.889785
0.894064

Table 20 - 4-MeOMe-1,2,3-Triazole-(Li+)-Glyme,
Energy: -710.21590
N
C
C
N
N
H
C
O
C
Li
C
C
O
O
C
C
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H

7
6
6
7
7
1
6
8
6
3
6
6
8
8
6
6
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1

3.299133
3.591498
2.358265
1.416276
1.988611
3.932742
1.955881
0.539626
0.018763
-0.458915
-2.808212
-3.177147
-1.977638
-1.715303
-1.273437
-2.208439
4.596253
2.206739
2.459727
-1.055442
0.218827
0.464224
-3.660560
-2.497670
-3.939135
-3.565006
-0.442063
-2.083851
-0.940878
-1.238828
-2.878488
-2.644500

-1.391946
-0.208090
0.260171
-0.653765
-1.679782
-2.054501
1.489216
1.618758
2.733839
0.035883
-1.373665
-0.098152
0.392572
-1.058415
-2.203077
1.547679
0.182418
1.401335
2.379743
2.744697
2.609596
3.666621
-1.749429
-2.142975
-0.295526
0.647846
-1.867561
-2.568302
-2.996768
1.850570
1.294219
2.357974

128

-0.956158
-0.370007
0.045327
-0.310829
-0.936820
-1.397485
0.793761
0.644349
1.385323
0.005440
0.162244
-0.549501
-1.160896
1.034457
1.783635
-1.979974
-0.300227
1.859884
0.396824
1.208254
2.453753
1.028300
0.741491
-0.556713
-1.313337
0.156383
2.401161
2.420152
1.107638
-2.371514
-2.805819
-1.386545

MP2(full)/cc-pVDZ and MP2(full)/cc-pVDZ(Li-C) Geometries and Energies of Heterocycle
Ligands With and Without a Bound Lithium Cation

Table 21 - Water, Energy: -76.23099
O
H
H

8
1
1

0.000000
0.749274
-0.749274

0.121440
-0.485761
-0.485761

Table 22 - Water-Li, Energy:
O
H
H
Li

8
1
1
3

0.000031
0.764905
-0.765251
0.000031

0.000000
0.000000
0.000000

-83.56307

-0.336917
-0.933476
-0.932955
1.520589

0.000000
0.000000
0.000000
0.000000

Table 23 - 1H-1,2,3-Triazole, Energy: -241.56224
C
C
N
N
N
H
H
H

6
6
7
7
7
1
1
1

1.044324
-0.193485
-1.068095
-0.442347
0.860325
-2.083561
2.037764
-0.508419

0.501034
1.133670
0.091906
-1.103068
-0.851509
0.114839
0.942418
2.173217

-0.000241
-0.000047
0.000259
-0.000554
0.000522
0.000445
-0.000272
-0.000039

Table 24 - 1H-1,2,3-Triazole-(Li+), Energy: -248.91584
C
C
N
N
N
H
Li
H
H

6
6
7
7
7
1
3
1
1

0.440542
1.352631
0.577164
-0.719560
-0.810911
0.869483
-2.670590
0.616999
2.439403

1.154937
0.102820
-1.012504
-0.714571
0.624864
-1.990796
-0.043960
2.227966
0.063643

129

-0.000143
0.003212
0.000923
-0.005628
-0.004825
0.001092
0.013027
0.000868
0.007266

Table 25 - 2H-1,2,3-Triazole, Energy: -241.57086
N
C
C
N
N
H
H
H

7
6
6
7
7
1
1
1

-5.976577
-5.111302
-3.907648
-4.020073
-5.259169
-5.646359
-5.402483
-2.986913

-0.550631
-0.381201
0.144143
0.303132
-0.126571
-0.130723
-0.642304
0.411958

0.130350
1.159728
0.661051
-0.680253
-0.907476
-1.846358
2.174118
1.173376

Table 26 - 2H-1,2,3-Triazole-(Li+), Energy: -248.89669
N
C
C
N
N
H
Li
H
H

7
6
6
7
7
1
3
1
1

1.199898
1.194157
-0.131225
-0.945933
-0.084359
-0.382425
-2.923887
2.124979
-0.535731

-0.705115
0.647546
1.099654
0.004518
-1.017186
-1.991780
0.071075
1.209522
2.110316

0.000004
0.000047
-0.000038
-0.000018
-0.000028
-0.000011
0.000093
0.000097
-0.000127

Table 27 – Pyrazole, Energy: -225.55411
C
C
C
N
N
H
H
H
H

6
6
6
7
7
1
1
1
1

0.654429
-0.740447
-1.090029
-0.001328
1.026709
1.971089
1.386806
-1.398705
-2.080583

0.959481
0.955062
-0.415639
-1.216843
-0.352978
-0.721745
1.764111
1.820833
-0.867880

130

-0.000192
0.000069
-0.000031
-0.000180
0.000301
0.000245
-0.000753
0.000690
-0.000105

Table 28 - Pyrazole-(Li+), Energy: -232.89344
C
C
C
N
N
H
Li
H
H
H

6
6
6
7
7
1
3
1
1
1

-1.217051
-1.158148
0.212738
0.963468
0.066118
0.373333
2.914486
-2.053066
-1.994736
0.698675

-0.611604
0.782397
1.085759
-0.052213
-1.054316
-2.022973
-0.000124
-1.308393
1.476575
2.061555

0.000197
0.000080
-0.000036
-0.000100
-0.000320
0.000834
0.000342
-0.000238
0.000309
-0.000436

Table 29 - Pyridizine, Energy: -263.52492
C
C
N
N
C
C
H
H
H
H

6
6
7
7
6
6
1
1
1
1

0.696581
1.326496
0.673061
-0.671684
-1.326431
-0.697895
1.281260
2.417781
-2.417621
-1.283570

1.190468
-0.064773
-1.243688
-1.244414
-0.066219
1.189698
2.114235
-0.151384
-0.154020
2.112838

-0.000002
0.000023
-0.000030
-0.000011
0.000028
-0.000009
-0.000010
0.000076
0.000083
-0.000105

Table 30 - Pyridazine-(Li+), Energy: -270.88587
C
C
N
N
C
C
Li
H
H
H
H

6
6
7
7
6
6
3
1
1
1
1

1.382482
0.139661
-1.021672
-1.021853
0.139225
1.382268
-2.890148
2.311177
0.046091
0.045262
2.310773

-0.698373
-1.352618
-0.674691
0.674247
1.352606
0.698777
0.000035
-1.274006
-2.441530
2.441481
1.274705

131

0.000895
-0.000433
-0.001894
-0.001973
-0.000421
0.000941
0.005989
0.002050
-0.000496
-0.000539
0.002194

Table 31 - Pyrimidine, Energy: -263.55995
C
C
C
N
C
C
H
H
H
H

6
6
6
7
6
7
1
1
1
1

-0.624273
-1.359606
-0.627197
0.719664
1.311700
0.722287
-1.123628
-2.452145
-1.128450
2.406827

1.192792
0.001461
-1.191328
-1.210423
-0.001570
1.208875
2.168175
0.002845
-2.165720
-0.002597

0.000048
-0.000036
0.000042
0.000049
-0.000229
0.000044
0.000024
-0.000120
0.000023
0.000472

Table 32 - Pyrimidine-(Li+), Energy: -270.89194
C
C
C
N
C
N
Li
H
H
H
H

6
6
6
7
6
7
3
1
1
1
1

-0.421013
0.973287
1.562278
0.829983
-0.495668
-1.174769
-3.159188
-0.950703
1.573161
2.649698
-1.094388

1.190117
1.133241
-0.139436
-1.269276
-1.113893
0.061071
0.046440
2.148084
2.045580
-0.264078
-2.031644

132

-0.000404
0.000080
0.000478
0.000146
-0.000487
-0.000653
0.001982
-0.000676
0.000190
0.001150
-0.001061

Table 33 - 1-Methoxyethyl-1,2,3-Triazole, Energy: -434.13854
N
C
C
N
N
C
C
O
C
H
H
H
H
H
H
H
H
H

7
6
6
7
7
6
6
8
6
1
1
1
1
1
1
1
1
1

-2.660389
-2.946969
-1.865096
-0.964418
-1.439767
0.392084
1.403030
2.678581
3.700606
-3.899815
-1.670943
0.525358
0.523186
1.257391
1.235656
4.661577
3.643722
3.645302

-1.028133
0.220350
1.061496
0.250844
-1.007626
0.541698
-0.099487
0.262705
-0.323394
0.448900
2.113062
1.632683
0.150360
-1.197239
0.266025
-0.005079
-1.428308
0.008371

-0.078747
-0.546344
-0.304891
0.318990
0.449009
0.754764
-0.186760
0.288964
-0.493869
-1.018944
-0.500751
0.771686
1.773181
-0.187071
-1.221524
-0.068069
-0.473810
-1.548570

Table 34 - 1-Methoxyethyl-1,2,3-Triazole-(Li+),
Energy: -441.52051
N
C
C
N
N
C
C
O
C
Li
H
H
H
H
H
H
H
H
H

7
6
6
7
7
6
6
8
6
3
1
1
1
1
1
1
1
1
1

-2.057818
-2.866208
-2.162886
-0.926551
-0.877527
0.243421
1.487218
1.973659
3.329910
0.799762
-3.894759
-2.428250
-0.007664
0.425982
2.266529
1.284353
3.630291
3.997577
3.381930

-1.335981
-0.301990
0.896430
0.516189
-0.820097
1.323340
0.940146
-0.354630
-0.554034
-1.791957
-0.466432
1.937013
2.369653
1.237932
1.690722
0.943852
-1.567554
0.179810
-0.456208

133

0.013517
0.366757
0.251910
-0.174355
-0.321138
-0.518017
0.268827
-0.128106
0.329461
-0.573712
0.680158
0.424134
-0.292033
-1.600883
0.050081
1.354829
0.032150
-0.147675
1.425441

Table 35 - 4-Methoxymethyl-1,2,3-Triazole, Energy: -394.95807
H
C
C
N
N
H
C
O
C
H
H
H
H
H
H

7
6
6
7
7
1
6
8
6
1
1
1
1
1
1

-1.405969
-0.368718
-0.871700
-2.217947
-2.549332
-2.959968
1.063089
1.858254
3.234027
-0.398628
1.271713
1.270209
3.791413
3.515183
3.516596

-1.162912
-0.277303
1.018914
0.822034
-0.484718
1.515442
-0.706968
0.461184
0.139878
1.995599
-1.324555
-1.340610
1.086312
-0.436320
-0.453294

-0.002175
0.002012
0.002962
0.000423
-0.003212
-0.000579
0.005110
-0.005453
-0.001272
0.005670
0.902202
-0.880984
-0.009800
0.901277
-0.892292

Table 36 - 4-Methoxymethyl-1,2,3-Triazole-(Li+),
Energy: -402.34226
N
C
C
N
N
C
C
O
C
Li
H
H
H
H
H
H

7
6
6
7
7
1
6
8
6
3
1
1
1
1
1
1

0.749594
0.436171
1.631230
2.578102
2.070335
3.592543
-0.998122
-1.815983
-3.217923
-0.889380
1.870559
-1.225006
-1.225061
-3.778754
-3.466332
-3.466300

0.893723
-0.436000
-1.150827
-0.177254
1.059228
-0.285424
-0.877404
0.302844
-0.034976
1.974875
-2.211297
-1.484285
-1.478373
0.907854
-0.618427
-0.612070

134

0.001300
0.000579
-0.000871
-0.000871
0.000317
-0.001846
0.001926
-0.001866
-0.000558
0.000007
-0.001787
-0.892289
0.900141
-0.003961
-0.900680
0.903671

MP2(full)/6-31G(d) Geometries and Energies of SN2 Transition States in Cartesian
Coordinates‡

Table 37 - Methyl Mesylate, Cs, Energy: -758.53145
S
O
C
C
H
N
H
H
H
H
H
H
H
H
O
O

16.0
8.0
6.0
6.0
1.0
7.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
8.0
8.0

1.15939
0.34332
-1.56443
2.83434
3.49926
-3.39174
-1.77836
-3.42903
-3.88908
-3.88908
-1.34932
-1.34932
2.99358
2.99358
0.95553
0.95553

-0.45877
0.83946
0.25102
0.13571
-0.72871
-0.29315
1.30659
-1.31310
0.03958
0.03958
-0.24862
-0.24862
0.73491
0.73491
-1.21641
-1.21641

‡

0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
-0.82614
0.82614
-0.92968
0.92968
-0.89588
0.89588
-1.25308
1.25308

This appendix is a republication of data from the supporting information of Spahlinger, G.;
Jackson J. E. Phys. Chem. Chem. Phys. 2014, 16, 24559 – 24569. It has been republished with
permission from the PCCP Owner Societies. The original article may be found online at the
following link: http://pubs.rsc.org/en/content/articlelanding/2014/cp/c4cp03741c#!divAbstract
135

Table 38 - Dimethylsulfate, C1, Energy: -833.56441
C
O
S
O
C
O
O
N
H
H
H
H
H
H
H
H
H

6.0
8.0
16.0
8.0
6.0
8.0
8.0
7.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0

-3.23105
-2.38762
-1.09812
-0.48480
0.29671
-0.26375
-1.64534
1.08021
-4.02379
-3.65542
-2.66470
-0.70677
0.81085
0.70385
0.74849
2.09771
0.83764

0.53029
1.60405
1.06888
2.41333
3.22502
0.29334
0.37490
4.04056
1.00238
-0.00086
-0.16271
3.34643
2.29328
3.95738
4.99383
4.06770
3.49160

0.56815
0.11677
-0.78967
-1.11775
0.48992
0.14471
-1.94913
2.04906
1.14786
-0.28628
1.19552
0.86179
0.65588
-0.18691
2.19684
1.98137
2.87422

Table 39 - Methyl Triflate, C1, Energy: -1055.61053
S
O
O
O
C
C
F
F
F
N
H
H
H
H
H
H

16.0
8.0
8.0
8.0
6.0
6.0
9.0
9.0
9.0
7.0
1.0
1.0
1.0
1.0
1.0
1.0

2.35501
2.11595
2.82997
3.09460
3.00518
0.69775
0.20757
-0.15989
0.74865
2.95037
2.06759
3.01260
3.92737
3.77193
2.12777
2.90357

0.45850
1.89145
0.01740
-0.19380
0.78181
-0.29530
-0.03145
0.20358
-1.62525
1.74648
0.29666
1.70453
0.28607
2.34060
2.34956
1.12215

136

0.38755
0.14978
1.69291
-0.77547
-2.45037
0.20277
-1.03440
1.10085
0.34790
-4.15797
-2.65665
-1.89490
-2.70168
-4.26976
-4.18146
-4.96329

Table 40 - Methylfluorosulfonate, C1, Energy: -818.40115
S
O
O
O
C
F
N
H
H
H
H
H
H

16.0
8.0
8.0
8.0
6.0
9.0
7.0
1.0
1.0
1.0
1.0
1.0
1.0

-0.45745
-0.73479
-0.66826
0.82628
1.03360
-1.54639
1.26902
0.19039
0.87039
2.01551
2.04944
0.42573
1.43614

-0.38751
1.03262
-0.99018
-0.82380
0.02595
-1.11887
0.86801
-0.54494
0.97787
-0.41591
1.52487
1.39054
0.18837

1.66574
1.46126
2.96502
0.99410
-0.74241
0.67800
-2.48653
-1.09193
-0.26719
-0.75708
-2.48154
-2.72549
-3.22871

Table 41 - Methyl TFSI (anti) C1, Energy:
C
N
S
S
O
O
O
O
C
F
F
F
C
F
F
F
N
H
H
H
H
H
H

6.0
7.0
16.0
16.0
8.0
8.0
8.0
8.0
6.0
9.0
9.0
9.0
6.0
9.0
9.0
9.0
7.0
1.0
1.0
1.0
1.0
1.0
1.0

-0.66116
0.76965
2.28825
0.29060
1.13996
-1.16191
2.38041
3.32762
0.53203
0.13186
1.81216
-0.21007
2.19505
3.34478
1.95190
1.19723
-2.06015
0.12249
-0.94777
-1.08444
-1.93545
-2.05019
-2.98197

-0.61732
0.64248
0.07028
2.15820
2.84436
2.08861
-1.12693
1.08767
3.01854
4.28929
2.98432
2.41267
-0.58939
-1.19444
0.38496
-1.49320
-1.84880
-1.32101
0.12036
-0.56937
-2.09763
-2.71145
-1.42349

137

-1919.67259

0.85893
0.24164
0.04048
-0.14497
-1.10654
-0.30589
0.87802
0.03777
1.46019
1.35324
1.83089
2.40979
-1.67185
-1.98500
-2.54919
-1.74320
1.46472
1.08911
1.58802
-0.12863
2.44612
0.92037
1.36270

Table 42 - Methyl TFSI (gauche) C1, Energy: -1919.67076
C
N
S
S
O
O
O
O
C
F
F
F
C
F
F
F
N
H
H
H
H
H
H

6.0
7.0
16.0
16.0
8.0
8.0
8.0
8.0
6.0
9.0
9.0
9.0
6.0
9.0
9.0
9.0
7.0
1.0
1.0
1.0
1.0
1.0
1.0

-3.87907
-2.46911
-1.05071
-3.05201
-2.15451
-4.46939
-1.05368
-0.71369
-3.07161
-3.58459
-1.84005
-3.84154
0.21236
0.29884
1.39677
-0.10592
-5.28215
-3.12177
-4.03898
-4.42346
-5.07590
-5.36234
-6.19044

-1.83954
-0.66098
-1.37594
0.69649
1.31547
0.47677
-2.66542
-1.28112
1.81762
2.99752
2.00090
1.29557
-0.37542
0.84929
-0.98774
-0.27843
-3.00105
-2.59309
-1.09180
-1.76888
-3.24306
-3.87042
-2.53716

0.39261
-0.40728
-0.82492
-1.12157
-2.08550
-1.41406
-0.12975
-2.23727
0.33687
-0.02300
0.81939
1.31448
0.06172
-0.46056
-0.05052
1.35979
1.17290
0.53190
1.14924
-0.53294
2.14198
0.64556
1.15092

Table 43 - Methyl FSI, C1, Energy: -1445.25353
C
N
S
S
O
O
O
O
F
F
N
H
H
H
H
H
H

6.0
7.0
16.0
16.0
8.0
8.0
8.0
8.0
9.0
9.0
7.0
1.0
1.0
1.0
1.0
1.0
1.0

-1.16332
0.23789
1.79197
-0.16317
0.69968
-1.61089
2.69028
1.76682
0.15377
2.16658
-2.55462
-0.50627
-1.07967
-1.83034
-2.20974
-2.86906
-3.36668

-0.57013
0.55663
0.08379
2.09227
2.72452
2.11438
1.07449
-1.28644
2.82452
-0.02105
-1.69089
-1.41217
0.02351
-0.24811
-2.15762
-2.41160
-1.13160

138

0.76693
-0.09700
-0.02432
-0.43270
-1.40357
-0.53546
0.52532
0.45671
0.97651
-1.58660
1.58284
0.62750
1.66179
-0.01361
2.42195
0.93291
1.84525

Table 44 - Methyl MSI (anti) C1, Energy: -1325.52993
C
N
S
S
O
O
O
O
C
H
H
H
C
H
H
H
N
H
H
H
H
H
H

6.0
7.0
16.0
16.0
8.0
8.0
8.0
8.0
6.0
1.0
1.0
1.0
6.0
1.0
1.0
1.0
7.0
1.0
1.0
1.0
1.0
1.0
1.0

-0.90188
0.57282
2.13085
0.15441
1.05762
-1.29032
2.83856
2.04988
0.36046
0.07588
1.40447
-0.29198
2.92255
3.96082
2.85635
2.40695
-2.27604
-0.22703
-0.78324
-1.51230
-1.93884
-2.59571
-3.08017

-0.77026
0.37880
0.04956
1.72961
1.97950
1.58083
1.23403
-1.15505
3.08876
4.00057
3.11933
2.92828
-0.41104
-0.65469
0.43160
-1.28081
-1.85552
-1.59409
-0.19108
-0.38219
-2.36085
-2.54128
-1.29313

139

1.01037
0.16851
0.55812
-0.65742
-1.79024
-0.90549
1.06923
1.40218
0.47314
-0.05455
0.78265
1.33173
-0.96597
-0.73449
-1.65300
-1.37289
1.74458
0.85233
1.91016
0.21102
2.56473
1.06005
2.02451

Table 45 - Methyl MSI (gauche) C1, Energy: -1325.52302
C
N
S
S
O
O
O
O
C
H
H
H
C
H
H
H
N
H
H
H
H
H
H

6.0
7.0
16.0
16.0
8.0
8.0
8.0
8.0
6.0
1.0
1.0
1.0
6.0
1.0
1.0
1.0
7.0
1.0
1.0
1.0
1.0
1.0
1.0

-1.06997
0.47826
0.77880
0.18542
0.20869
-0.97466
1.17581
-0.33913
1.60757
1.47421
2.50235
1.66760
2.19991
1.94467
2.43613
3.02871
-2.50727
-0.35207
-1.13760
-1.60266
-2.29563
-2.68341
-3.36317

-1.06292
0.13425
-0.46294
1.73729
2.53612
1.83955
-1.86008
-0.21158
2.22517
3.27192
2.10811
1.59679
0.40893
1.46254
-0.02782
0.25597
-2.19857
-1.86516
-0.39700
-0.80954
-2.63776
-2.93659
-1.65415

0.37339
-0.29456
-1.81098
-0.04374
-1.27794
0.85874
-1.57131
-2.73173
0.91248
1.19195
0.30094
1.80065
-2.42786
-2.53264
-3.39992
-1.73627
0.98395
0.35027
1.21640
-0.52860
1.87953
0.30200
1.09124

Table 46 - Methyl MSA, C1, Energy: -738.64549
C
N
S
O
O
C
N
H
H
H
H
H
H
H
H
H
H

6.0
7.0
16.0
8.0
8.0
6.0
7.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0

-1.30251
0.19773
0.23801
1.34285
-1.14025
0.55593
-2.61886
-0.49270
-1.38337
-1.70728
-2.45959
-2.69837
-3.51020
1.15436
0.52943
1.54139
-0.21478

-0.66876
0.67481
0.45781
-0.41401
0.10748
2.05136
-1.74138
-1.37337
0.11501
-0.49913
-2.07242
-2.55369
-1.24395
0.56209
1.93270
2.40051
2.74994

140

0.30504
-0.52460
-2.10706
-2.56768
-2.54485
-2.85423
0.91736
0.40479
1.04049
-0.68266
1.87005
0.30348
0.89449
-0.17789
-3.93872
-2.54249
-2.52914

Table 47 - Methyl FSA, C1, Energy: -798.52240
C
N
S
O
O
F
N
H
H
H
H
H
H
H
Table 48 C
N
S
O
O
F
N
H
H
H
H
H
H
C
H
C
C
H
H
H
H
H
H

6.0
7.0
16.0
8.0
8.0
9.0
7.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0

-1.19943
0.43162
-0.17642
0.77442
-1.32783
-0.91823
-2.69158
-0.47177
-1.35170
-1.50666
-2.68325
-2.78539
-3.51620
1.27082

-0.77697
0.08935
1.20365
2.08201
0.65982
2.23710
-1.51433
-1.42425
0.21199
-0.97550
-1.42893
-2.50283
-1.02590
0.45106

0.16278
-0.87921
-1.80374
-2.47123
-2.52223
-0.71203
0.94819
0.62582
0.56129
-0.85018
1.96554
0.71073
0.59484
-0.42114

MeiprFSA, C1, Energy: -916.03637
6.0
7.0
16.0
8.0
8.0
9.0
7.0
1.0
1.0
1.0
1.0
1.0
1.0
6.0
1.0
6.0
6.0
1.0
1.0
1.0
1.0
1.0
1.0

-0.55910
1.14889
0.58564
1.54941
-0.56224
-0.17324
-2.05491
0.16204
-0.71244
-0.82453
-2.05987
-2.15684
-2.86788
2.39504
2.42687
2.41952
3.61997
3.32047
1.54541
2.42414
4.53926
3.64292
3.58153

-0.57798
0.04259
0.93809
1.65973
0.27135
2.19275
-1.12119
-1.09370
0.47792
-0.99309
-0.83085
-2.13687
-0.70673
0.42408
-0.24845
1.85866
0.11669
2.02241
2.06661
2.57046
0.26129
0.77279
-0.91958

141

0.51173
-0.61079
-1.76348
-2.59026
-2.38087
-0.93185
1.38979
1.12841
0.66585
-0.44652
2.36895
1.35578
0.93005
0.07307
0.94370
0.59948
-0.78361
1.19983
1.22214
-0.22883
-0.20546
-1.65555
-1.13011

Table 49 - Methyl Acetate, Cs, Energy:
C
C
O
O
C
N
H
H
H
H
H
H
H
H
H

6.0
6.0
8.0
8.0
6.0
7.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0

2.71505
1.21986
0.83498
0.46339
-1.52119
-3.22174
3.29119
-1.01488
-3.90645
-3.38394
-3.38394
-1.55695
-1.55695
2.96968
2.96968

-0.28053
0.01855
1.21455
-1.02504
-0.37468
0.20938
0.64546
0.58559
-0.54807
0.78874
0.78874
-0.93747
-0.93747
-0.87697
-0.87697

-323.88097

0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
-0.82474
0.82474
-0.91937
0.91937
-0.88004
0.88004

Table 50 - Methyl Trifluoroacetate, Cs, Energy: -620.97437
C
C
O
O
C
N
H
H
H
H
H
H
F
F
F

6.0
6.0
8.0
8.0
6.0
7.0
1.0
1.0
1.0
1.0
1.0
1.0
9.0
9.0
9.0

-2.74774
-1.25478
-0.94712
-0.50185
1.43691
3.21694
1.02108
3.86299
3.41129
3.41129
1.48885
1.48885
-3.55230
-3.05977
-3.05977

0.29836
-0.07407
-1.27898
0.96265
0.36815
-0.16221
-0.62941
0.62802
-0.73166
-0.73166
0.91979
0.91979
-0.77981
1.03794
1.03794

142

0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
-0.82442
0.82442
-0.92412
0.92412
0.00000
-1.09021
1.09021

Table 51 - Methyl Cyanoformate, Cs, Energy: -376.72778
C
C
O
O
C
N
H
H
H
H
H
H
N

6.0
6.0
8.0
8.0
6.0
7.0
1.0
1.0
1.0
1.0
1.0
1.0
7.0

-2.69698
-1.24349
-0.93291
-0.49173
1.44202
3.24599
1.05365
3.87723
3.45214
3.45214
1.49444
1.49444
-3.85118

0.22415
-0.11266
-1.31631
0.92582
0.35379
-0.14958
-0.65397
0.65248
-0.71505
-0.71505
0.90351
0.90351
0.47500

0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
-0.82425
0.82425
-0.92510
0.92510
0.00000

Table 52 - Dimethylcarbonate, Cs, Energy: -398.92298
O
C
O
O
C
N
C
H
H
H
H
H
H
H
H
H

8.0
6.0
8.0
8.0
6.0
7.0
6.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0

2.03073
0.64754
0.14739
0.04691
-1.96009
-3.75966
2.59536
3.67574
-1.62111
-4.34362
-3.99559
-3.99559
-1.95109
-1.95109
2.29741
2.29741

0.31305
0.36460
1.50177
-0.77312
-0.40610
-0.03986
-0.99593
-0.84328
0.62333
-0.87706
0.51406
0.51406
-0.96455
-0.96455
-1.56072
-1.56072

143

0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
-0.82420
0.82420
-0.92205
0.92205
-0.88658
0.88658

Table 53 - Dimethylurethane, Cs, Energy: -379.04927
O
C
O
N
C
N
C
H
H
H
H
H
H
H
H
H
H

8.0
6.0
8.0
7.0
6.0
7.0
6.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0

2.02579
0.66684
0.34646
-0.15741
-2.18990
-3.75189
2.90179
3.91019
-1.53527
-4.55234
0.35677
-3.81515
-3.81515
-2.29337
-2.29337
2.75358
2.75358

0.47650
0.13493
-1.07929
1.16869
0.36842
-0.46730
-0.64678
-0.22906
-0.49858
0.16691
2.04827
-1.06606
-1.06606
0.92365
0.92365
-1.26953
-1.26953

0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
-0.82479
0.82479
-0.91858
0.91858
-0.88536
0.88536

Table 54 - Methyl Acetamide, Cs, Energy: -304.00329
N
O
C
C
H
H
H
C
H
H
H
N
H
H
H
H

7.0
8.0
6.0
6.0
1.0
1.0
1.0
6.0
1.0
1.0
1.0
7.0
1.0
1.0
1.0
1.0

0.36989
0.56626
1.08414
2.61143
0.95893
2.98632
2.98632
-1.74849
-1.16436
-1.79635
-1.79635
-3.38196
-4.12634
-3.49362
-3.49362
3.00807

0.72035
-1.56104
-0.40181
-0.34590
1.55229
-0.87554
-0.87554
0.13165
-0.79005
0.69735
0.69735
-0.55392
0.14517
-1.14575
-1.14575
0.67358

144

0.00000
0.00000
0.00000
0.00000
0.00000
0.87987
-0.87987
0.00000
0.00000
-0.91752
0.91752
0.00000
0.00000
-0.82443
0.82443
0.00000

Table 55 - Methyl Trifluoroacetamide, Cs, Energy: -601.10242
C
C
O
N
C
N
F
H
H
H
F
F
H
H
H
H

6.0
6.0
8.0
7.0
6.0
7.0
9.0
1.0
1.0
1.0
9.0
9.0
1.0
1.0
1.0
1.0

2.11981
0.58992
-0.01703
0.04913
-2.09064
-3.85725
2.76033
-1.71854
-4.45550
0.74265
2.55559
2.55559
-2.06198
-2.06198
-4.08151
-4.08151

-0.52278
-0.40223
-1.50505
0.80354
0.55890
0.17215
0.68086
-0.46030
0.99955
1.54876
-1.19283
-1.19283
1.11772
1.11772
-0.38651
-0.38651

0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
-1.08864
1.08864
-0.92160
0.92160
-0.82460
0.82460

Table 56 - Methylcyanoformamide, Cs, Energy: -356.85536
C
C
O
N
N
H
C
H
N
H
H
H
H
H

6.0
6.0
8.0
7.0
7.0
1.0
6.0
1.0
7.0
1.0
1.0
1.0
1.0
1.0

-2.13211
-0.65322
-0.22872
0.08105
-3.30421
-0.47753
2.15409
1.64901
3.85744
4.56232
2.20896
2.20896
4.00477
4.00477

0.05823
-0.13475
-1.31677
0.96986
0.21366
1.82290
0.41429
-0.54449
-0.21663
0.52203
0.96893
0.96893
-0.80038
-0.80038

145

0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
-0.92261
0.92261
-0.82462
0.82462

Table 57 - Methyl Succinimide, Cs, Energy: -455.08510
N
O
O
C
C
C
C
H
H
H
H
C
H
H
H
N
H
H
H

7.0
8.0
8.0
6.0
6.0
6.0
6.0
1.0
1.0
1.0
1.0
6.0
1.0
1.0
1.0
7.0
1.0
1.0
1.0

0.05261
2.33705
-2.23756
1.17102
-1.08350
0.76545
-0.75813
1.19813
1.19813
-1.21286
-1.21286
-0.35264
-1.34340
0.21388
0.21388
-0.80868
0.00960
-1.36974
-1.36974

1.01151
0.61253
0.72233
0.21489
0.26114
-1.26900
-1.23665
-1.75517
-1.75517
-1.70250
-1.70250
3.13048
2.69223
3.11421
3.11421
4.85024
5.46176
5.06521
5.06521

0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.87941
-0.87941
0.87953
-0.87953
0.00000
0.00000
-0.91761
0.91761
0.00000
0.00000
-0.82586
0.82586

Table 58 - 1,3-Propanesultone, C1, Energy: -796.52517
C
C
C
O
S
O
O
N
H
H
H
H
H
H
H
H
H

6.0
6.0
6.0
8.0
16.0
8.0
8.0
7.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0

-3.45351
-2.19091
-1.79074
-3.45727
-4.49739
-5.67323
-4.70828
-0.11650
-3.94260
-3.25237
-1.36522
-2.37547
-2.14297
-1.32008
-0.27813
0.32686
0.54204

0.75616
0.52215
-0.94950
-1.71120
-0.65306
-0.63998
-0.59716
-0.67549
1.69560
0.73939
1.11095
0.85603
-1.57827
-1.42299
-0.23260
-1.58056
-0.09379

146

0.30115
-0.52144
-0.57062
0.31553
-0.06605
0.80762
-1.52723
-1.48034
0.03500
1.37412
-0.10902
-1.54511
-1.37184
0.27731
-2.38518
-1.64854
-0.96046

Table 59 - N-Triflylpropanesultam, C1, Energy: -1660.59152
C
C
C
N
S
O
O
S
O
O
C
F
F
F
N
H
H
H
H
H
H
H
H
H

6.0
6.0
6.0
7.0
16.0
8.0
8.0
16.0
8.0
8.0
6.0
9.0
9.0
9.0
7.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0

-6.80903
-6.26053
-5.04418
-4.41467
-5.48929
-5.20853
-5.78052
-3.17308
-3.27811
-2.80960
-1.83920
-2.15599
-0.68200
-1.67732
-5.31761
-7.12190
-7.64294
-7.06380
-5.98698
-4.08081
-5.05721
-5.41267
-4.49815
-6.13924

0.62350
1.05260
0.24503
0.07993
0.79614
2.23361
0.01902
-0.88152
-1.65929
-1.51850
0.33782
1.10961
-0.28928
1.12280
0.27377
-0.42435
1.25823
0.95190
2.11063
0.71275
-0.83451
1.22307
-0.15270
-0.25975

0.94358
2.30011
2.73049
0.77498
-0.25481
-0.36327
-1.45839
0.43702
-0.79036
1.70950
0.12987
-0.91644
-0.11858
1.21270
4.63129
0.93553
0.63005
3.03707
2.24992
2.84873
2.70811
4.99570
5.06855
4.92010

Table 60 - Methyl Chloride, C3v, Energy: -555.66764
C
H
H
H
H
H
H
Cl
N

6.0
1.0
1.0
1.0
1.0
1.0
1.0
17.0
7.0

0.00000
-0.53245
-0.53245
1.06490
0.47750
0.47750
-0.95501
0.00000
0.00000

0.00000
0.92223
-0.92223
0.00000
-0.82706
0.82706
0.00000
0.00000
0.00000

147

0.98077
1.13760
1.13760
1.13760
-1.18908
-1.18908
-1.18908
3.41809
-0.82697

MP2(full)/6-31G(d) Geometries and Energies of van der Waals complexes

Table 61 - Methyl Mesylate, C1, Energy: -758.58709
S
O
O
O
C
C
H
H
H
N
H
H
H
H
H
H

16.0
8.0
8.0
8.0
6.0
6.0
1.0
1.0
1.0
7.0
1.0
1.0
1.0
1.0
1.0
1.0

2.07553
1.98721
3.03576
2.26572
3.21452
0.47676
-0.23040
0.20090
0.54040
5.32093
3.39137
2.75180
4.13737
4.61506
6.21396
5.09539

0.51573
1.90663
0.15510
-0.44335
0.05729
-0.07754
0.14685
0.44264
-1.15053
1.83568
-0.79804
0.87475
0.39319
2.56859
2.29069
1.28412

0.18915
-0.25416
1.23078
-1.10417
-2.09851
0.65915
-0.13785
1.57712
0.83612
-0.17260
-2.74665
-2.65164
-1.62272
-0.20399
0.00351
0.65259

Table 62 - Dimethylsulfate, C1, Energy: -833.61240
C
O
S
O
C
O
O
N
H
H
H
H
H
H
H
H
H

6.0
8.0
16.0
8.0
6.0
8.0
8.0
7.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0

-0.53204
0.10826
1.70441
1.84848
3.02227
2.37762
1.96618
5.05312
-1.57531
-0.42705
-0.10311
2.96440
2.92959
3.92979
5.98747
4.39412
4.96133

-2.61811
-1.31517
-1.38677
0.16909
0.82869
-1.72019
-2.18795
-1.66836
-2.40567
-3.08419
-3.25026
1.83652
0.83798
0.31584
-1.86208
-2.11560
-2.16274

148

0.15498
0.15639
-0.06897
-0.38204
0.19709
1.17815
-1.25647
-0.70869
0.37460
-0.82454
0.93483
-0.20682
1.28227
-0.12212
-1.06196
-1.34245
0.17586

Table 63 - Methyl Triflate, C1, Energy: -1055.65367
S
O
O
O
C
C
F
F
F
N
H
H
H
H
H
H

16.0
8.0
8.0
8.0
6.0
6.0
9.0
9.0
9.0
7.0
1.0
1.0
1.0
1.0
1.0
1.0

2.20717
2.02832
2.91878
2.70847
3.12432
0.53321
-0.13890
-0.11248
0.61466
5.24527
3.34404
2.30471
4.00749
4.84718
6.24956
5.10327

0.60708
1.94149
0.36265
-0.42245
0.14170
-0.10498
-0.02905
0.60054
-1.37976
1.74614
-0.73845
0.71340
0.75565
2.67830
1.86479
1.29429

0.29261
-0.25910
1.53519
-0.82763
-2.11433
0.51115
-0.64295
1.44453
0.89367
-0.13154
-2.71390
-2.54797
-1.95000
-0.04216
-0.24715
0.76956

Table 64 - Methylfluorosulfonate, C1, Energy: -818.44356
S
O
O
O
C
F
N
H
H
H
H
H
H

16.0
8.0
8.0
8.0
6.0
9.0
7.0
1.0
1.0
1.0
1.0
1.0
1.0

-0.61956
-0.84288
0.00645
0.00621
0.23617
-2.06612
2.33568
0.60254
-0.69879
0.98718
2.06008
3.33331
2.22440

-0.01031
1.30202
-0.23924
-1.00722
-0.47692
-0.69736
1.16672
-1.33970
-0.11534
0.30629
2.14084
1.16487
0.74401

149

0.67213
0.11379
1.95035
-0.38821
-1.73065
0.77082
0.26904
-2.28119
-2.15655
-1.66285
0.37115
0.06705
1.18854

Table 65 - Methyl TFSI (anti) C1, Energy: -1919.72254
C
N
S
S
O
O
O
C
C
F
F
F
O
N
H
H
H
H
H
H
F
F
F

6.0
7.0
16.0
16.0
8.0
8.0
8.0
6.0
6.0
9.0
9.0
9.0
8.0
7.0
1.0
1.0
1.0
1.0
1.0
1.0
9.0
9.0
9.0

-0.26467
0.41561
1.61248
0.09380
1.22812
-0.55561
1.30838
3.08627
-1.22869
-1.63951
-0.76557
-2.25420
1.85204
-3.27319
0.28315
-0.28348
-1.28730
-4.03026
-3.70618
-2.73259
4.12992
3.34498
2.84185

-1.53625
-0.23126
-0.12976
1.03733
1.93340
0.44608
-1.15564
-0.74737
1.92895
2.95437
2.37600
1.09721
1.25943
-1.16026
-2.11954
-2.05745
-1.36089
-0.57455
-1.89622
-0.58672
-0.75323
0.02963
-1.99517

150

0.16484
0.39525
1.59217
-0.67679
-0.76902
-1.83700
2.57483
0.67435
0.24505
-0.50540
1.40824
0.46151
1.92381
-1.31664
-0.57529
1.11970
-0.17266
-0.97246
-1.87023
-1.96009
1.50371
-0.37464
0.25241

Table 66 - Methyl TFSI (gauche) C1, Energy: -1919.71949
C
N
S
S
O
O
O
O
C
F
F
F
C
F
F
F
N
H
H
H
H
H
H

6.0
7.0
16.0
16.0
8.0
8.0
8.0
8.0
6.0
9.0
9.0
9.0
6.0
9.0
9.0
9.0
7.0
1.0
1.0
1.0
1.0
1.0
1.0

-3.63764
-2.65002
-1.01329
-3.14598
-1.99525
-4.11198
-1.01995
-0.14290
-4.12482
-4.57789
-3.35292
-5.15961
-0.70179
-0.66844
0.47355
-1.66904
-6.71368
-3.31138
-3.70482
-4.61261
-7.42086
-7.21403
-6.27433

-2.16135
-1.06318
-1.43548
0.36419
1.22201
0.05443
-2.83780
-0.87986
1.12717
2.30616
1.30963
0.34697
-0.50135
0.80872
-0.90339
-0.78079
-1.52231
-3.04362
-2.38431
-1.84472
-0.98022
-2.22207
-0.89124

-0.08845
-0.28779
0.01436
-1.03111
-1.23136
-2.07359
0.39523
-1.00114
0.33468
-0.09650
1.40760
0.66462
1.57348
1.34499
2.06028
2.45442
-1.28563
-0.63577
0.97618
-0.46398
-0.79443
-1.82937
-1.95199

Table 67 - Methyl FSI, C1, Energy: -1445.30276
C
N
S
S
O
O
O
O
F
F
N
H
H
H
H
H
H

6.0
7.0
16.0
16.0
8.0
8.0
8.0
8.0
9.0
9.0
7.0
1.0
1.0
1.0
1.0
1.0
1.0

-0.83597
0.26057
1.77316
-0.00032
-1.25556
1.22415
2.37410
1.65240
-0.28041
2.55228
-3.11589
-0.53618
-0.97342
-1.73650
-3.37293
-3.98272
-2.63218

-0.92101
-0.15853
-0.83171
1.44807
1.82126
2.19124
-0.25542
-2.24543
1.33325
-0.22244
-0.02290
-1.96603
-0.57081
-0.78848
0.85147
-0.47669
0.23513

151

0.68570
0.03331
-0.20120
-0.33436
0.26870
-0.19725
-1.37424
0.05041
-1.91105
1.05854
-1.56959
0.68167
1.70872
0.08395
-1.11727
-1.84960
-2.42662

Table 68 - Methyl MSI (anti) C1, Energy: -1325.59716
C
N
S
S
O
O
O
C
C
H
H
H
O
N
H
H
H
H
H
H
H
H
H

6.0
7.0
16.0
16.0
8.0
8.0
8.0
6.0
6.0
1.0
1.0
1.0
8.0
7.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0

-0.91580
0.32220
1.12420
0.56593
1.98593
-0.04744
0.47362
2.75641
-0.38261
-0.20706
-0.02182
-1.43657
1.20009
-3.14985
-0.88738
-0.92754
-1.80401
-3.60934
-3.80087
-2.34570
3.33313
3.17675
2.68232

-0.53634
0.17719
1.14196
0.49089
0.79365
-0.64106
0.83134
0.45260
1.94798
2.19102
2.74552
1.71298
2.51767
0.06708
-1.52821
-0.61816
0.00133
0.41138
-0.58630
-0.47849
1.02151
0.55340
-0.59300

152

1.16462
0.78978
1.95545
-0.86013
-1.01966
-1.55674
3.22596
1.96505
-1.20549
-2.25567
-0.55717
-1.04079
1.46588
-1.46265
0.71574
2.24960
0.82537
-2.30310
-1.03252
-1.76958
2.69684
0.96585
2.26269

Table 69 - Methyl MSI (gauche) C1, Energy: -1325.59135
C
N
S
S
O
O
O
O
C
H
H
H
C
H
H
H
N
H
H
H
H
H
H

6.0
7.0
16.0
16.0
8.0
8.0
8.0
8.0
6.0
1.0
1.0
1.0
6.0
1.0
1.0
1.0
7.0
1.0
1.0
1.0
1.0
1.0
1.0

-0.60345
0.45232
2.05582
0.15176
1.39961
-0.53097
1.90420
2.60600
-1.00596
-1.17828
-0.55225
-1.93882
2.94960
2.95473
3.96169
2.47171
-3.50273
-0.53690
-0.48537
-1.57386
-4.22919
-3.92916
-2.79154

-1.08454
-0.14910
-0.74612
0.54769
1.18592
-0.41034
-1.46530
-1.41060
1.81703
2.39382
2.44536
1.35809
0.75260
1.35276
0.44675
1.27101
-0.38157
-2.05073
-1.21652
-0.63630
0.10278
-1.23895
-0.66136

0.59308
0.13373
0.44523
-1.39986
-1.81604
-2.27242
1.70841
-0.73122
-0.95342
-1.86507
-0.18812
-0.62107
0.75408
-0.15314
1.02623
1.58440
-1.16961
0.08625
1.66603
0.37982
-1.69334
-0.82392
-1.84439

Table 70 - Methyl MSA, C1, Energy: -738.74012
C
N
H
S
O
O
C
N
H
H
H
H
H
H
H
H
H

6.0
7.0
1.0
16.0
8.0
8.0
6.0
7.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0

0.29660
1.38978
2.29714
1.11500
-0.12475
2.37835
0.78513
-2.38816
0.65278
-0.52779
-0.06246
-1.97799
-3.01130
-2.98534
0.64067
-0.12628
1.64863

-0.96040
-0.08339
-0.52363
1.08464
1.76307
1.80203
0.24371
-0.21797
-1.55062
-0.33386
-1.63047
0.62904
-0.59756
0.07760
1.01518
-0.34828
-0.36906

153

1.56476
1.14796
1.01630
0.00513
0.39542
-0.14314
-1.53005
-0.59323
2.41035
1.90183
0.77631
-0.20067
0.11641
-1.36256
-2.28888
-1.42339
-1.79255

Table 71 - Methyl FSA, C1, Energy: -798.60455
C
N
H
S
O
O
F
N
H
H
H
H
H
H

6.0
7.0
1.0
16.0
8.0
8.0
9.0
7.0
1.0
1.0
1.0
1.0
1.0
1.0

0.26599
1.39201
2.17771
1.07843
-0.04715
2.32591
0.50063
-2.33177
0.69834
-0.23563
-0.45537
-2.09204
-3.34480
-2.08991

-1.01034
-0.27619
-0.83197
0.95996
1.70599
1.54862
0.21460
-0.49680
-1.84642
-0.34657
-1.36198
0.43502
-0.57652
-0.50797

1.21145
0.60706
0.27763
-0.39351
0.12390
-0.81861
-1.72081
-0.91025
1.76055
1.91401
0.47071
-0.57764
-0.85746
-1.89789

Table 72 - MeiprFSA, C1, Energy: -916.11962
C
N
C
S
O
O
F
N
H
H
H
H
H
H
C
H
C
H
H
H
H
H
H

6.0
7.0
6.0
16.0
8.0
8.0
9.0
7.0
1.0
1.0
1.0
1.0
1.0
1.0
6.0
1.0
6.0
1.0
1.0
1.0
1.0
1.0
1.0

-0.14543
0.86069
2.25515
0.62201
-0.75302
1.74177
0.72827
-3.39035
0.10402
-0.15009
-1.14042
-2.81037
-4.06842
-3.91890
3.04897
2.08369
2.98864
3.91018
2.36910
3.24651
3.99002
3.28536
2.49994

-1.18621
-0.15360
-0.48284
0.65794
1.10258
1.53234
-0.52536
-0.39663
-2.13828
-1.31550
-0.86810
0.30312
0.10977
-0.86316
-1.24595
-1.15343
0.74177
0.42043
1.26838
1.42885
-1.59078
-0.60357
-2.11917

154

0.75151
0.43946
0.85894
-0.94614
-1.03469
-1.21453
-2.06457
-0.20120
0.27073
1.83470
0.43931
-0.65932
0.36340
-0.93464
-0.19605
1.70724
1.38628
1.88086
2.11572
0.58146
0.24163
-1.04622
-0.55669

Table 73 -

Methyl Acetate, C1, Energy: -323.95778

C
C
O
O
C
N
H
H
H
H
H
H
H
H
H

6.0
6.0
8.0
8.0
6.0
7.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0

-4.76330
-3.48640
-2.68648
-3.30869
-2.09098
-6.29875
-4.88517
-4.72516
-5.60502
-2.08778
-1.22546
-2.08180
-6.74213
-6.36621
-5.31062

-0.87502
-0.13526
-0.36043
0.86734
1.61402
2.16070
-1.65388
-1.32253
-0.17832
2.35558
0.95574
2.09519
2.36174
3.01098
2.00614

0.56099
0.29454
-0.59484
1.20657
1.02202
1.18625
-0.19018
1.55723
0.53898
1.81839
1.10386
0.04315
2.07912
0.63224
1.37478

Table 74 - Methyl Trifluoroacetate, C1, Energy: -621.03443
C
C
O
O
F
F
F
C
H
H
H
N
H
H
H

6.0
6.0
8.0
8.0
9.0
9.0
9.0
6.0
1.0
1.0
1.0
7.0
1.0
1.0
1.0

-1.75678
-0.37804
0.54553
-0.20424
-1.91152
-2.72629
-1.89017
1.91810
2.47950
2.21883
1.99973
1.48996
1.39698
1.46455
0.64837

-0.01532
0.65146
-0.29094
1.84151
-0.71456
0.89983
-0.87075
0.17812
-0.68333
0.49004
1.01833
-2.76366
-2.95790
-3.66566
-2.26680

155

0.44186
0.42408
0.23608
0.58277
1.58235
0.36481
-0.59275
0.20045
-0.14917
1.20088
-0.48857
-1.32055
-2.31484
-0.85089
-1.03817

Table 75 - Methyl Cyanoformate, Cs, Energy: -376.78433
C
C
O
O
N
C
H
N
H
H
H
H
H

6.0
6.0
8.0
8.0
7.0
6.0
1.0
7.0
1.0
1.0
1.0
1.0
1.0

-1.47301
-0.73161
0.57986
-1.27341
-2.11971
1.42222
2.43222
3.46108
2.47835
1.21412
1.21412
3.88029
3.88029

-0.77120
0.49697
0.24591
1.58460
-1.75893
1.43332
1.03286
-1.18080
-1.44492
2.02517
2.02517
-1.62369
-1.62369

0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
-0.89140
0.89140
-0.81425
0.81425

Table 76 - Dimethylcarbonate, C1, Energy: -398.99274
O
C
O
O
C
C
H
H
H
H
H
H
N
H
H
H

8.0
6.0
8.0
8.0
6.0
6.0
1.0
1.0
1.0
1.0
1.0
1.0
7.0
1.0
1.0
1.0

-1.71595
-0.66748
0.32101
-0.86388
-2.84908
0.23999
-3.54950
-0.08140
-3.29192
-2.56146
0.39780
1.14739
3.05507
3.27864
2.33736
3.88902

-1.64567
-0.81514
-1.11461
0.34335
-1.20995
1.27555
-2.04128
2.14169
-0.31311
-1.01547
1.54388
0.83630
-0.71645
-1.51546
-1.02664
-0.52819

156

-0.34681
-0.46796
-1.10910
0.18726
0.42601
0.08546
0.37647
0.65991
-0.00759
1.45935
-0.95969
0.49912
0.47509
1.06409
-0.17824
-0.07662

Table 77 - Dimethylurethane, C1, Energy: -379.16693
O
C
N
O
H
C
C
H
H
H
H
H
H
N
H
H
H

8.0
6.0
7.0
8.0
1.0
6.0
6.0
1.0
1.0
1.0
1.0
1.0
1.0
7.0
1.0
1.0
1.0

0.04191
-0.00425
-1.10517
1.10629
-0.99067
2.31080
-2.37522
-3.16768
-2.43288
-2.52691
3.09582
2.23378
2.51772
-0.20802
-0.07207
0.67082
-0.36983

1.63211
0.43002
-0.29066
-0.38819
-1.27314
0.31506
0.38138
-0.36787
0.92663
1.09372
-0.43990
0.76334
1.09990
-3.07216
-3.45435
-2.64108
-3.85984

0.12268
-0.10942
-0.40633
-0.08147
-0.67022
0.25469
-0.57605
-0.54944
-1.52439
0.23628
0.23699
1.24627
-0.47424
-1.02144
-1.95418
-0.74028
-0.39864

Table 78 - Methyl Acetamide, C1, Energy: -304.12207
C
C
O
N
C
N
H
H
H
H
H
H
H
H
H
H

6.0
6.0
8.0
7.0
6.0
7.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0

-0.58441
0.69427
1.74947
0.59695
1.76516
-1.99959
-0.83598
-0.40745
-1.42418
1.48857
2.57168
2.14185
-2.20075
-2.83095
-1.91824
-0.29005

-1.75116
-0.98409
-1.55792
0.36353
1.18265
1.82192
-2.33883
-2.45155
-1.10112
2.22927
0.92838
1.03875
1.79949
1.47116
2.80368
0.80918

157

-0.33760
-0.60803
-0.89954
-0.50903
-0.75155
0.20970
-1.22328
0.48152
-0.08357
-0.61446
-0.05857
-1.76797
1.20697
-0.26089
-0.04643
-0.26822

Table 79 - Methyl Trifluoroacetamide, C1, Energy: -601.21078
C
O
N
H
C
F
F
F
C
H
H
H
N
H
H
H

6.0
8.0
7.0
1.0
6.0
9.0
9.0
9.0
6.0
1.0
1.0
1.0
7.0
1.0
1.0
1.0

-0.82875
-0.80045
-1.85164
-1.77164
0.38976
1.35475
0.05156
0.90633
-3.06416
-3.77324
-3.50126
-2.85776
-1.40375
-1.44356
-0.42197
-1.87974

-0.56153
-1.77822
0.26359
1.27590
0.16714
-0.68472
0.89101
1.04679
-0.27987
0.53671
-1.03572
-0.74710
3.13233
3.29561
3.19100
3.91178

0.15288
-0.03209
-0.11855
0.05920
0.73801
1.08379
1.83585
-0.16086
-0.69897
-0.83466
-0.04201
-1.66533
0.42482
1.42829
0.16428
-0.02372

Table 80 - Methylcyanoformamide, Cs, Energy: -356.96347
N
C
C
O
N
C
H
H
N
H
H
H
H
H

7.0
6.0
6.0
8.0
7.0
6.0
1.0
1.0
7.0
1.0
1.0
1.0
1.0
1.0

-1.83570
-0.74073
0.63723
1.62091
0.63991
1.90428
-0.26184
1.69447
-2.10406
-2.60719
-2.42393
-2.42393
2.49159
2.49159

-1.50407
-1.06034
-0.51063
-1.25131
0.83336
1.54385
1.33637
2.61327
1.92527
1.03890
2.44214
2.44214
1.28779
1.28779

158

0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
-0.81642
0.81642
-0.88526
0.88526

Table 81 - Methyl Succinimide, C1, Energy: -455.18368
C
C
N
C
C
O
O
C
N
H
H
H
H
H
H
H
H
H
H

6.0
6.0
7.0
6.0
6.0
8.0
8.0
6.0
7.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0

0.52917
1.76042
1.38135
0.02188
-0.61973
-0.52583
2.90039
2.31425
4.66504
0.70344
0.40072
-1.38283
-1.13219
1.71974
2.93544
2.95198
4.30095
4.64012
5.64806

-1.26291
-0.83202
0.14771
0.45676
-0.44200
1.30054
-1.25874
0.81389
-1.64816
-1.07043
-2.34246
-1.05258
0.18323
1.38143
0.07381
1.49530
-1.62965
-2.61819
-1.39265

-0.86215
-0.08551
0.81472
0.76478
-0.27780
1.45442
-0.22177
1.71023
2.40933
-1.92439
-0.74822
0.21272
-1.01348
2.42535
2.21649
1.14227
1.45794
2.71474
2.35189

Table 82 - 1,3-Propanesultone, C1, Energy: -796.58767
C
C
C
O
S
O
O
N
H
H
H
H
H
H
H
H
H

6.0
6.0
6.0
8.0
16.0
8.0
8.0
7.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0

-3.84229
-2.58632
-1.99255
-3.07688
-4.53908
-5.30841
-5.08698
-6.48769
-4.58130
-3.62600
-1.87349
-2.85960
-1.44270
-1.34769
-7.38886
-6.39456
-6.55907

0.75631
0.41009
-0.81172
-1.58382
-0.86358
-0.98887
-1.34937
1.37912
1.35214
1.18153
1.23697
0.15626
-1.46802
-0.51631
1.55983
0.36670
1.72724

159

-0.06952
-0.85058
-0.13710
0.44439
0.19264
1.42085
-1.07484
-1.88668
-0.61505
0.91458
-0.87655
-1.87649
-0.81361
0.69471
-1.45017
-1.95086
-2.84003

Table 83 - N-Triflylpropanesultam, C1, Energy: -1660.66338
C
C
C
N
S
O
O
S
O
O
C
F
F
F
N
H
H
H
H
H
H
H
H
H

6.0
6.0
6.0
7.0
16.0
8.0
8.0
16.0
8.0
8.0
6.0
9.0
9.0
9.0
7.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0

-6.53875
-5.68805
-4.38491
-4.08139
-5.42434
-5.21655
-5.69217
-2.78151
-3.01004
-2.32875
-1.54199
-1.96431
-0.37569
-1.38165
-5.52432
-6.80796
-7.40418
-6.18426
-5.49594
-3.56541
-4.52252
-5.44561
-4.61498
-6.17549

0.69446
1.16524
0.37091
0.30374
0.80259
2.20223
-0.19595
-0.57133
-1.08554
-1.40146
0.77269
1.65378
0.25072
1.39053
-2.52894
-0.36070
1.32330
0.97369
2.23828
0.86521
-0.64286
-2.32132
-2.89066
-3.30831

1.10123
2.26912
2.17801
0.73124
-0.28481
-0.64154
-1.31100
0.21035
-1.12846
1.32047
0.03454
-0.87233
-0.35214
1.21390
0.86250
1.19574
0.88038
3.22347
2.18494
2.70334
2.55743
-0.13276
1.14725
0.94198

Table 84 - Methyl Chloride, C3v, Energy: -555.73069
C
H
H
H
H
H
H
Cl
N

6.0
1.0
1.0
1.0
1.0
1.0
1.0
17.0
7.0

0.00000
-0.51302
-0.51302
1.02604
0.47000
0.47000
-0.94000
0.00000
0.00000

0.00000
0.88858
-0.88858
0.00000
-0.81406
0.81406
0.00000
0.00000
0.00000

160

1.91852
1.56196
1.56196
1.56196
-1.71285
-1.71285
-1.71285
3.70220
-1.32406

MP2(full)/6-31G(d) Geometries and Energies of Methyl Transfer Agents

Table 85 - Methyl Mesylate, Cs, Energy: -702.21914
S
O
C
C
H
H
H
H
H
H
O
O

16.0
8.0
6.0
6.0
1.0
1.0
1.0
1.0
1.0
1.0
8.0
8.0

-0.48793
0.74189
2.05024
-1.78750
-2.72724
2.75493
-1.70452
-1.70452
2.17258
2.17258
-0.48327
-0.48327

0.59518
-0.48079
0.14658
-0.60331
-0.04971
-0.68149
-1.21272
-1.21272
0.75409
0.75409
1.32550
1.32550

0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
-0.89869
0.89869
-0.89797
0.89797
-1.26391
1.26391

Table 86 - Dimethylsulfate, C1, Energy: -777.24377
C
O
S
O
C
O
O
H
H
H
H
H
H

6.0
8.0
16.0
8.0
6.0
8.0
8.0
1.0
1.0
1.0
1.0
1.0
1.0

-1.94327
-1.26787
0.29230
0.41024
1.78363
1.08668
0.45285
-2.95766
-1.93144
-1.46981
1.69338
2.25226
2.34201

-1.54122
-0.26138
-0.32041
1.27809
1.75545
-0.78435
-0.95375
-1.34542
-1.85542
-2.28940
2.82986
1.52071
1.31405

161

0.02882
0.16975
-0.21263
-0.33405
-0.32370
0.91383
-1.51198
0.36629
-1.01440
0.66698
-0.46080
0.63166
-1.15122

Table 87 S
O
O
O
C
C
F
F
F
H
H
H

Methyl Triflate, C1, Energy: -999.28488
16.0
8.0
8.0
8.0
6.0
6.0
9.0
9.0
9.0
1.0
1.0
1.0

0.25159
0.07720
0.96943
0.81877
0.71707
-1.42711
-2.08031
-2.09407
-1.34499
1.21648
-0.32836
1.22784

0.41701
1.75046
0.13787
-0.58589
-0.15875
-0.29711
-0.24174
0.41557
-1.56608
-0.95207
-0.08190
0.79245

0.83473
0.28263
2.05924
-0.29120
-1.68227
1.03422
-0.13658
1.94346
1.43089
-2.23302
-1.97734
-1.81832

Table 88 - Methylfluorosulfonate, C1, Energy: -762.07625
S
O
O
O
C
F
H
H
H

16.0
8.0
8.0
8.0
6.0
9.0
1.0
1.0
1.0

-0.60047
-0.88595
0.30024
-0.27758
0.14692
-2.00395
0.32409
1.05819
-0.65152

0.32365
1.67695
-0.05308
-0.48448
-1.86719
-0.37244
-2.22029
-1.89960
-2.43862

162

1.04387
0.65859
2.10684
-0.28811
-0.10985
1.39800
-1.12209
0.48505
0.36382

Table 89 - Methyl TFSI (anti) C1, Energy: -1863.35495
N
S
S
O
O
O
O
C
F
F
F
C
F
F
F
C
H
H
H

7.0
16.0
16.0
8.0
8.0
8.0
8.0
6.0
9.0
9.0
9.0
6.0
9.0
9.0
9.0
6.0
1.0
1.0
1.0

0.17552
0.43900
-1.01820
-0.59558
-1.40403
1.17721
-0.77508
-2.41875
-3.45702
-2.05184
-2.74842
1.65825
1.12524
2.02968
2.72495
1.11958
0.54846
1.79542
1.67563

0.23493
-1.37755
0.70063
1.99214
-0.41878
-1.34640
-2.13839
1.03803
1.46415
1.99210
-0.06349
-1.89764
-1.81351
-3.15258
-1.08941
1.28464
2.14726
1.57006
0.87380

0.17590
0.62715
-0.93931
-1.45403
-1.77282
1.87842
0.42166
0.20971
-0.50953
1.07545
0.87714
-0.65200
-1.86777
-0.40263
-0.57754
0.63431
0.97208
-0.17071
1.47449

Table 90 - Methyl FSI, C1, Energy: -1388.93439
N
S
S
O
O
O
O
F
F
C
H
H
H

7.0
16.0
16.0
8.0
8.0
8.0
8.0
9.0
9.0
6.0
1.0
1.0
1.0

0.12598
0.17991
-1.35861
-1.09995
-2.21553
-0.96600
1.54614
-1.88279
-0.04132
1.24220
1.17936
2.17296
1.17679

0.85721
-0.74351
1.54537
2.82832
0.52898
-1.06044
-0.98483
1.85606
-1.46132
1.74979
2.63172
1.22368
2.03019

163

-0.43711
0.10271
-0.78570
-1.38785
-1.33205
0.91471
0.49304
0.69869
-1.30164
-0.04756
-0.68081
-0.24244
1.00543

Table 91 - Methyl MSI (anti) C1, Energy: -1269.22819
N
S
S
O
O
O
O
C
H
H
H
C
H
H
H
C
H
H
H

7.0
16.0
16.0
8.0
8.0
8.0
8.0
6.0
1.0
1.0
1.0
6.0
1.0
1.0
1.0
6.0
1.0
1.0
1.0

0.18569
-0.02526
-1.19470
-0.68432
-2.27211
-1.10049
1.31052
-1.63882
-2.51134
-0.79905
-1.87133
-0.59449
0.16590
-0.72473
-1.53800
1.39738
1.59453
1.28781
2.21657

0.23527
-1.44459
1.24290
2.59692
0.71724
-1.80835
-2.02036
1.02999
1.66215
1.35384
-0.02041
-1.68216
-1.30695
-2.75684
-1.15121
0.84298
1.77865
1.04332
0.14727

-0.72916
-0.89703
-0.57807
-0.77402
-1.41653
0.02067
-0.78488
1.12318
1.29904
1.73718
1.28927
-2.56249
-3.24863
-2.70243
-2.68209
-1.31282
-0.79397
-2.38254
-1.14029

Table 92 - Methyl MSA, C1, Energy: -682.37105
C
N
H
S
O
O
C
H
H
H
H
H
H

6.0
7.0
1.0
16.0
8.0
8.0
6.0
1.0
1.0
1.0
1.0
1.0
1.0

-0.46679
0.60191
1.51463
0.27618
-0.92965
1.54382
-0.15223
-0.14236
-1.33902
-0.73913
-0.39272
-1.02420
0.70035

-0.98040
-0.06732
-0.47669
1.19746
1.84720
1.90088
0.48393
-1.52469
-0.38197
-1.70185
1.30803
-0.16124
-0.07500

164

1.39584
1.00427
0.82176
-0.01451
0.49174
-0.18715
-1.59370
2.28386
1.65753
0.61542
-2.26707
-1.47872
-1.98104

Table 93 - Methyl FSA, C1, Energy: -742.23853
C
N
H
S
O
O
F
H
H
H

6.0
7.0
1.0
16.0
8.0
8.0
9.0
1.0
1.0
1.0

-0.47591
0.77742
1.15876
0.91353
0.46777
2.15882
-0.24927
-0.31366
-0.69531
-1.31405

-1.08472
-0.37593
-0.49957
1.17616
1.28713
1.69964
1.89708
-2.13860
-0.97950
-0.70311

0.63071
0.35091
-0.58501
0.83132
2.19914
0.32390
-0.04507
0.40637
1.69189
0.04073

Table 94 - MeiprFSA, C1, Energy: -859.75289
C
N
C
S
O
O
F
H
H
H
C
H
C
H
H
H
H
H
H

6.0
7.0
6.0
16.0
8.0
8.0
9.0
1.0
1.0
1.0
6.0
1.0
6.0
1.0
1.0
1.0
1.0
1.0
1.0

-1.80722
-0.79726
0.59710
-1.04159
-2.43176
0.05565
-0.86695
-1.59199
-1.80916
-2.78819
1.41497
0.43285
1.30135
2.23665
0.67519
1.52976
2.35797
1.64644
0.88618

-0.85772
0.15979
-0.15701
0.95216
1.33359
1.85854
-0.24180
-1.81629
-0.98511
-0.50207
-0.88805
-0.84411
1.07545
0.77053
1.56923
1.78580
-1.22087
-0.22725
-1.76480

165

0.47214
0.14298
0.57192
-1.25824
-1.36381
-1.51026
-2.35604
-0.01234
1.55533
0.16115
-0.48732
1.40886
1.12054
1.59903
1.86713
0.32701
-0.04512
-1.32439
-0.86857

Table 95 - Methyl Acetate, Cs, Energy: -267.59323
C
C
O
O
C
H
H
H
H
H
H

6.0
6.0
8.0
8.0
6.0
1.0
1.0
1.0
1.0
1.0
1.0

2.68274
1.23130
0.79414
0.44331
-0.96736
3.29585
-1.45462
-1.24089
-1.24089
2.90425
2.90425

-0.19511
0.19417
1.33134
-0.90962
-0.62359
0.70458
-1.59632
-0.05332
-0.05332
-0.80029
-0.80029

0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
-0.88859
0.88859
-0.88168
0.88168

Table 96 - Methyl Trifluoroacetate, Cs, Energy:
C
C
O
O
C
H
H
H
F
F
F

6.0
6.0
8.0
8.0
6.0
1.0
1.0
1.0
9.0
9.0
9.0

2.68783
1.21056
0.82365
0.45829
-0.96475
-1.42554
-1.24147
-1.24147
2.97136
2.97136
3.46795

-0.18717
0.21533
1.36512
-0.88853
-0.63202
-1.61614
-0.06886
-0.06886
-0.92258
-0.92258
0.89761

-564.66942

0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
-0.89130
0.89130
-1.09071
1.09071
0.00000

Table 97 - Methyl Cyanoformate, Cs, Energy: -320.41939
C
C
O
O
C
H
H
H
N

6.0
6.0
8.0
8.0
6.0
1.0
1.0
1.0
7.0

1.37723
0.01780
-0.21986
-0.87322
-2.25169
-2.83598
-2.45105
-2.45105
2.49554

-0.16951
0.38172
1.57342
-0.61542
-0.17089
-1.08702
0.42337
0.42337
-0.54781

166

0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
-0.89167
0.89167
0.00000

Table 98 - Dimethylcarbonate, Cs, Energy: -342.62576
O
C
O
O
C
C
H
H
H
H
H
H

8.0
6.0
8.0
8.0
6.0
6.0
1.0
1.0
1.0
1.0
1.0
1.0

1.32894
-0.01437
-0.67479
-0.51325
-1.95315
2.02034
3.07540
1.77468
1.77468
-2.20380
-2.34489
-2.34489

-0.45491
-0.45141
-1.46683
0.80765
0.84933
0.80664
0.54013
1.38405
1.38405
1.90791
0.35619
0.35619

0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.89158
-0.89158
0.00000
0.88966
-0.88966

Table 99 - Dimethylurethane, C1, Energy: -322.79444
O
C
N
O
H
C
C
H
H
H
H
H
H

8.0
6.0
7.0
8.0
1.0
6.0
6.0
1.0
1.0
1.0
1.0
1.0
1.0

-1.68705
-1.68319
-2.75114
-0.59305
-2.55723
0.57467
-3.98495
-3.99845
-4.82779
-4.08382
1.35224
0.85481
0.39661

2.70857
1.48714
0.69525
0.70542
-0.28473
1.45616
1.26905
1.35213
0.65521
2.26626
0.71044
2.14578
2.02120

-0.07422
-0.01669
0.27394
-0.26830
0.42707
-0.63476
0.76937
1.86158
0.44694
0.34329
-0.78915
0.16236
-1.55056

Table 100 - Methyl Acetamide, C1, Energy: -247.75036
C
C
N
O
C
H
H
H
H
H
H
H

6.0
6.0
7.0
8.0
6.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0

-2.63278
-1.32164
-0.21658
-1.26543
1.12159
-2.58313
-3.39653
-2.92879
-0.33358
1.69942
1.01750
1.65173

-0.41880
0.33824
-0.42195
1.54426
0.13121
-1.36572
0.21656
-0.62105
-1.41158
-0.25824
1.20998
-0.09100

167

-0.00008
-0.00008
0.25807
-0.24354
0.23094
0.54296
0.44900
-1.03287
0.42215
-0.61273
0.12255
1.16051

Table 101 - Methyl Trifluoroacetamide, Cs, Energy: -544.83515
C
C
O
N
F
H
F
F
C
H
H
H

6.0
6.0
8.0
7.0
9.0
1.0
9.0
9.0
6.0
1.0
1.0
1.0

0.49401
-1.03527
-1.58336
-1.66595
0.94330
-1.12087
0.99271
0.99271
-3.11718
-3.42912
-3.51399
-3.51399

-0.00687
0.07587
1.17432
-1.11551
-1.29065
-1.96561
0.59792
0.59792
-1.16451
-2.20812
-0.66427
-0.66427

0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
1.08865
-1.08865
0.00000
0.00000
0.88576
-0.88576

Table 102 - Methylcyanoformamide, Cs, Energy: -300.58450
C
C
O
N
N
H
C
H
H
H

6.0
6.0
8.0
7.0
7.0
1.0
6.0
1.0
1.0
1.0

2.61562
1.19688
0.86457
0.34474
3.76025
0.71669
-1.09068
-1.38667
-1.38667
-1.59166

-0.18309
0.22863
1.41048
-0.82117
-0.47562
-1.76205
-0.59470
-0.03003
-0.03003
-1.56190

0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
-0.88642
0.88642
0.00000

Table 103 - Methyl Succinimide, Cs, Energy: -398.81698
N
O
O
C
C
C
C
H
H
H
H
C
H
H
H

7.0
8.0
8.0
6.0
6.0
6.0
6.0
1.0
1.0
1.0
1.0
6.0
1.0
1.0
1.0

-0.02919
2.26482
-2.32393
1.14492
-1.18736
0.76407
-0.76528
1.20551
1.20551
-1.19543
-1.19543
-0.03046
-1.07105
0.48307
0.48307

0.96204
0.70480
0.63450
0.21891
0.18999
-1.25124
-1.26945
-1.72785
-1.72785
-1.75653
-1.75653
2.41152
2.73425
2.78389
2.78389

168

0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.87928
-0.87928
0.87916
-0.87916
0.00000
0.00000
-0.88801
0.88801

Table 104 - Methyl Chloride, C3v, Energy: -499.36908
C
H
H
H
Cl

6.0
1.0
1.0
1.0
17.0

0.00000
-0.51467
-0.51467
1.02934
0.00000

0.00000
0.89144
-0.89144
0.00000
0.00000

169

1.91773
1.56476
1.56476
1.56476
3.69460

MP2(full)/6-31G(d) Geometries and Energies of Anions

Table 105 - Mesylate (-) C3v, Energy: -662.53310
C
S
O
O
O
H
H
H

6.0
16.0
8.0
8.0
8.0
1.0
1.0
1.0

0.00000
0.00000
-0.72121
-0.72121
1.44242
0.51566
0.51566
-1.03132

0.00000
0.00000
1.24918
-1.24918
0.00000
-0.89315
0.89315
0.00000

0.15191
1.95361
2.31290
2.31290
2.31290
-0.20542
-0.20542
-0.20542

Table 106 - Methylsulfate (-) Cs, Energy: -737.57487
O
S
O
C
H
O
O
H
H

8.0
16.0
8.0
6.0
1.0
8.0
8.0
1.0
1.0

1.62257
0.50838
-0.81510
-2.05606
-2.83768
0.33447
0.33447
-2.15525
-2.15525

0.37580
-0.58274
0.48061
-0.21083
0.55435
-1.36721
-1.36721
-0.83840
-0.83840

0.00000
0.00000
0.00000
0.00000
0.00000
-1.24145
1.24145
-0.89199
0.89199

Table 107 - Triflate (-) C3v, Energy: -959.63081
C
S
O
O
O
F
F
F

6.0
16.0
8.0
8.0
8.0
9.0
9.0
9.0

0.00000
0.00000
-0.72210
-0.72210
1.44420
0.62744
0.62744
-1.25489

0.00000
0.00000
1.25071
-1.25071
0.00000
-1.08676
1.08676
0.00000

170

0.20921
2.04431
2.35488
2.35488
2.35488
-0.29674
-0.29674
-0.29674

Table 108 - Fluorosulfonate (-) C3v, Energy: -722.42035
F
S
O
O
O

9.0
16.0
8.0
8.0
8.0

0.00000
0.00000
-0.71849
-0.71849
1.43697

0.00000
0.00000
1.24445
-1.24445
0.00000

0.29520
1.95804
2.26366
2.26366
2.26366

Table 109 - TFSI (anti)(-) C2, Energy: -1823.69893
N
S
S
O
O
O
O
C
C
F
F
F
F
F
F

7.0
16.0
16.0
8.0
8.0
8.0
8.0
6.0
6.0
9.0
9.0
9.0
9.0
9.0
9.0

0.00000
1.41490
-1.41490
1.41448
-1.41448
2.42973
-2.42973
1.80301
-1.80301
2.98193
-2.98193
0.86056
-0.86056
1.90555
-1.90555

0.00000
0.02268
-0.02268
0.48851
-0.48851
0.52762
-0.52762
-1.76885
1.76885
-1.93558
1.93558
-2.42617
2.42617
-2.33443
2.33443

0.87210
0.11185
0.11185
-1.27785
-1.27785
1.03850
1.03850
-0.01609
-0.01609
-0.64993
-0.64993
-0.70840
-0.70840
1.19802
1.19802

Table 110 - FSI (-)C2, Energy -1349.28297
N
S
S
F
F
O
O
O
O

7.0
16.0
16.0
9.0
9.0
8.0
8.0
8.0
8.0

0.00000
1.34747
-1.34747
1.79459
-1.79459
1.19740
-1.19740
2.37985
-2.37985

0.00000
0.31716
-0.31716
-1.15425
1.15425
1.11481
-1.11481
0.65209
-0.65209

171

0.90199
0.10686
0.10686
-0.44979
-0.44979
-1.10277
-1.10277
1.07274
1.07274

Table 111 - MSI (anti)(-) C2, Energy: -1229.53832
N
S
S
O
O
O
O
C
C
H
H
H
H
H
H

7.0
16.0
16.0
8.0
8.0
8.0
8.0
6.0
6.0
1.0
1.0
1.0
1.0
1.0
1.0

0.00000
1.39569
-1.39569
1.36940
-1.36940
2.46813
-2.46813
1.63809
-1.63809
2.58701
-2.58701
0.80040
-0.80040
1.66567
-1.66567

0.00000
0.05051
-0.05051
0.93808
-0.93808
0.27777
-0.27777
-1.59984
1.59984
-1.61728
1.61728
-1.83034
1.83034
-2.29000
2.29000

1.19069
0.37946
0.37946
-0.80902
-0.80902
1.36210
1.36210
-0.26067
-0.26067
-0.80014
-0.80014
-0.91775
-0.91775
0.58283
0.58283

Table 112 - MSA (-) C1, Energy: -642.63252
N
H
S
O
O
C
H
H
H

7.0
1.0
16.0
8.0
8.0
6.0
1.0
1.0
1.0

0.57006
1.48921
0.38777
-0.62712
1.66059
-0.39514
-0.57377
-1.34108
0.26538

-0.10099
-0.50957
1.03873
2.02699
1.59170
0.32181
1.11028
-0.13545
-0.43491

0.96594
0.77668
-0.09430
0.34904
-0.65248
-1.56133
-2.29622
-1.26657
-1.99171

Table 113 - FSA (-) C1, Energy: -702.52414
N
H
S
O
O
F

7.0
1.0
16.0
8.0
8.0
9.0

0.56722
0.97222
0.52061
0.19381
1.54857
-0.85883

-0.19330
-0.42577
1.35184
1.84129
2.08606
1.81386

172

0.15548
-0.75429
0.22419
1.56672
-0.54186
-0.63337

Table 114 - Isopropyl FSA (-) C1, -820.03729
N
C
S
O
O
F
C
H
C
H
H
H
H
H
H

7.0
6.0
16.0
8.0
8.0
9.0
6.0
1.0
6.0
1.0
1.0
1.0
1.0
1.0
1.0

-1.16986
0.17441
-1.31598
-2.70600
-0.26330
-1.06232
1.10384
0.00632
0.84000
1.78322
0.16790
1.03613
2.03381
1.35160
0.61212

-0.12412
-0.43254
0.71546
1.11600
1.70878
-0.37167
-1.06709
-1.18778
0.77038
0.48393
1.18169
1.54388
-1.40766
-0.34254
-1.92015

0.10324
0.59246
-1.18332
-1.41984
-1.49458
-2.45844
-0.44532
1.37443
1.26476
1.74879
2.02338
0.52087
0.02768
-1.22369
-0.91840

Table 115 - Acetate (-) Cs, Energy: -227.85413
C
C
O
O
H
H
H

6.0
6.0
8.0
8.0
1.0
1.0
1.0

1.41889
-0.13047
-0.81068
-0.51302
1.70293
1.84816
1.84816

0.17015
-0.01033
1.05306
-1.21448
1.22674
-0.32279
-0.32279

0.00000
0.00000
0.00000
0.00000
0.00000
-0.87991
0.87991

Table 116 - Trifluoroacetate (-) Cs, Energy: -524.96954
C
C
O
O
F
F
F

6.0
6.0
8.0
8.0
9.0
9.0
9.0

-1.39578
0.15647
0.78477
0.51389
-1.96620
-1.96620
-1.85640

-0.13102
0.01014
-1.07386
1.21294
0.46561
0.46561
-1.41109

0.00000
0.00000
0.00000
0.00000
-1.08925
1.08925
0.00000

Table 117 - Cyanoformate (-) C2v, Energy: -280.73023
C
C
N
O
O

6.0
6.0
7.0
8.0
8.0

0.00000
0.00000
0.00000
0.00000
0.00000

0.00000
0.00000
0.00000
-1.14998
1.14998

173

-0.02555
1.51982
-1.20979
2.00991
2.00991

Table 118 - Methylcarbonate (-) Cs, Energy: -302.90805
O
C
O
O
C
H
H
H
Table 119 O
C
O
N
C
H
H
H
H

8.0
6.0
8.0
8.0
6.0
1.0
1.0
1.0

0.61675
-0.57910
-1.62139
-0.34730
1.82340
2.63345
1.92596
1.92596

0.77336
-0.07927
0.59762
-1.30903
0.04709
0.78836
-0.59811
-0.59811

0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
-0.88132
0.88132

Methylurethane (-) Cs, Energy: -283.02333
8.0
6.0
8.0
7.0
6.0
1.0
1.0
1.0
1.0

2.05993
0.62469
0.37929
-0.16535
2.90753
3.93531
0.44585
2.75986
2.75986

0.49488
0.13235
-1.09266
1.17891
-0.62959
-0.24415
2.00010
-1.26547
-1.26547

0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
-0.88135
0.88135

Table 120 - Acetamide (-) Cs, Energy: -207.96859
N
O
C
C
H
H
H
H

7.0
8.0
6.0
6.0
1.0
1.0
1.0
1.0

-0.02089
1.13446
0.06986
-1.22754
-1.02004
-1.21978
-1.21978
-2.16072

-1.42154
0.59077
-0.09681
0.76548
-1.65591
1.41923
1.41923
0.18718

0.00000
0.00000
0.00000
0.00000
0.00000
0.87947
-0.87947
0.00000

Table 121 - Trifluoroacetamide (-) Cs, Energy: -505.08677
C
C
O
N
F
H
F
F

6.0
6.0
8.0
7.0
9.0
1.0
9.0
9.0

-0.45772
1.09048
1.51171
1.75147
-1.02417
1.06639
-0.98781
-0.98781

-0.03591
0.00643
1.19540
-1.13304
-1.29038
-1.89247
0.59077
0.59077

174

0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
-1.08749
1.08749

Table 122 - Cyanoformamide (-) Cs, Energy: -260.84632
N
C
C
O
N
H

7.0
6.0
6.0
8.0
7.0
1.0

2.12924
0.94410
-0.58354
-1.08719
-1.16580
-0.42817

-0.00457
0.01128
-0.00423
-1.15456
1.18112
1.89250

0.00000
0.00000
0.00000
0.00000
0.00000
0.00000

Table 123 - Succinimide (-) C2v, Energy: -359.07164
N
O
O
C
C
C
C
H
H
H
H

7.0
8.0
8.0
6.0
6.0
6.0
6.0
1.0
1.0
1.0
1.0

0.00000
-2.29645
2.29645
-1.11121
1.11121
-0.75752
0.75752
-1.20887
1.20887
-1.20887
1.20887

0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.00000
0.88031
0.88031
-0.88031
-0.88031

175

0.34286
-0.07498
-0.07498
-0.44605
-0.44605
-1.95649
-1.95649
-2.42744
-2.42744
-2.42744
-2.42744

REFERENCES

176

REFERENCES

(1) Bruce, P.; Scrosati, B.; Tarascon, J. Angew. Chem. Int. Ed. 2008, 47, 2930 – 2946.
(2) http://web.mit.edu/newsoffice/2006/battery-hybrid.html
(3) Whittingham, M. S. Science, 1976, 192, 1126 -1127.
(4) Zhao, H. M. S. Thesis, Michigan State University, East Lansing, MI, 2012
(5) Shriver, M. A.; Ratner, D. F. Chem. Rev. 1988, 88, 109 – 124.
(6) Ahmad, S. Ionics 2009, 15, 309 – 321.
(7) Dias, F. B.; Plomp, L.; Veldhuis, J. B. L. Journal of Power Sources 2000, 88, 169 – 191.
(8) Atkins, P.; De Paula, J. Physical Chemistry, 7th ed. W. H. Freeman and Company: New York,
2002.
(9) Ratner, M. A.; Johansson, P.; Shriver, D. F. MRS Bull. 2000, 25, 31-37.
(10) Hayamizu, K.; Akiba, E.; Bando, T.; Aihara, Y. J. Chem. Phys. 2002, 117, 5929 – 5939.
(11) Druger, S. D.; Nitzan, A.; Ratner, M. A. J. Chem. Phys. 1983, 79, 3133 – 3141.
(12) Druger, S. D.; Ratner, M. A.; Nitzan, A. Phys. Rev. B 1985, 31, 3939 – 3947.
(13) Granek, R.; Nitzan, A.; Druger, S. D. Ratner, M. A. Solid State Ionics 1988, 28-30, 120 –
129.
(14) Nitzan, A.; Ratner, M. A. J. Phys. Chem. 1994, 98, 1765 – 1775.
(15) Lonergan, M. C.; Nitzan, A. Ratner, M. A.; Shriver, D. F. J. Chem. Phys. 1995, 103, 3253 –
3261.
(16) Paul, W.; Smith, G. D. Rep. Prog. Phys. 2004, 67, 1117 – 1185.
(17) Borodin, O.; Smith, G. D. J. Phys. Chem. B 2003, 107, 6801 – 6812.
(18) Borodin, O.; Smith, G. D.; Douglas, R. J. Phys. Chem. B 2003, 107, 6824 – 6837.
(19) Borodin, O.; Smith, G. D. Macromolecules 2006, 39, 1620 – 1629.

177

(20) Borodin, O.; Smith, G. D.; Geiculescu, O.; Creager, S. E.; Hallac, B.; DesMarteau, D. J.
Phys. Chem. B 2006, 110, 24266 – 24274.
(21) Diddens, D.; Heuer, A.; Borodin, O. Macromolecules, 2010, 43, 2028 – 2036.
(22) Strobl, G. The Physics of Polymers: Concepts for Understanding their Structure and
Behavior 2nd Ed. Springer-Verlag: Berlin, 1996; pp 257-277.
(23) Maitra, A.; Hueur, A. Phys. Rev. Lett. 2007, 98, 227802.
(24) Nugent, J. L.; Moganty, S. S.; Archer, L. A. Adv. Mater. 2010, 22, 3677 – 3680.
(X) Shi, J.; Vincent, A. Solid State Ionics 1993, 60, 11 – 17.
(25) Croce, F.; Curcini, R.; Martinelli, A.; Persi, L.; Ronci, F.; Scrosati, B. J. Phys. Chem. B
1999, 103, 10632 – 10638.
(26) Asfour, F. Ph.D. Thesis, Michigan State University, East Lansing, MI, 2003
(27) Hou, J.; Baker, G. L.; Chem. Mater. 1998, 10, 3311 – 3318.
(28) Walls, H. J.; Zhou, J.; Yerian, J. A.; Fedkiw, P. S.; Khan, S. A.; Stowe, M. K.; Baker, G. L.
Journal of Power Sources 2000, 89, 156 – 162.
(29) Moganty, S. S.; Jayaprakash, N.; Nugent, J. L.; Shen, J. Archer, L. A. Angew. Chem. Int.
Ed. 2010, 49, 1 – 5.
(30) Schaefer, J. L.; Moganty, S. S.; Yanga, D. A.; Archer, L. A. J. Mater. Chem. 2011,
(31) Mehta, M. A.; Fujinami, T.; Inoue, T. Journal of Power Sources, 1999, 724 – 728.
(32) Sun, X.; Kerr, J. B.; Reeder, C. L.; Liu, G.; Han, Y. Macromolecules 2004, 37, 5133 – 5135.
(33) Matsumoto, K.; Endo, T. J. Polymer Sci. Part A: Poymer Chem. 2011, DOI:
10.1002/pola.24614
(34) Chen, Y. Doctoral Thesis.
(35) Christie, A. M. Lilley, S. J.; Staunton, E.; Andreev, Y. G.; Bruce, P. G. Nature 2005, 433,
50 – 53.
(36) Zhang, C.; Staunton, E.; Andreev, Y. G.; Bruce, P. G. J. Am. Chem. Soc. 2005, 127, 18305 –
18308.
(37) Zhang, C.; Lilley, S. J.; Ainsworth, D.; Staunton, E.; Andreev, Y. G.; Slawin, A. M. Z.;
Bruce, P. G. Chem. Mater. 2008, 20, 4039 – 4044.

178

(38) Mays, J. M.; Macromolecules 1990, 23, 3530 – 3531.
(39) H. C. Kolb, Finn, M. G.; Sharpless, K, B. Angew. Chem. Int. Ed. 2001, 40, 2004 – 2021.
(40) Chandran, S. P.; Hotha, S.; Prasad B. L. V.; Current Sci. 2008, 95, 1327 – 1323.
(41) Qin, G.; Santos, C.; Zhang, W.; Li, Y.; Kumar, A.; Erasquin, U. J.; Liu, K.; Muradov, P.;
Trautner, B. W. ; Cai, C. J. Am. Chem. Soc. 2010, 132, 14632 – 14644.
(42) Shi, J.; Vincent, A. Solid State Ionics 1993, 60, 11 – 17.
(43) Johansson, P; Tegenfeldt, J.; Lindgren, J. Polymer 1999. 4399 – 4406.
(44) Hoyle, C. E.; Lowe, A. B.; Bowman, C. N. Chem. Soc. Rev. 2010, 39, 1355-1387.
(45) Binder, W. H.; Sachsenhofer, R. Macromol. Rapid Commun. 2008, 29, 952 – 981.
(46) Hua, Y.; Flood, A. H. Chem. Soc. Rev. 2010, 39, 1262-1271.
(47) Alabi, C. A.; Chen, Z.; Yan, Y. S.; Davis, M. E. Chem. Mater. 2009, 21, 4645–4652.
(48) Coᶊgun, S.; Çelik, S. Ü.; Baykal, A.; Bozkurt, A. Curr. Appl. Phys. 2010, 10, 133 – 137.
(49) Luo, J.; Hu, J.; Saak, W.; Beckhaus, R.; Wittstock, G.; Vankelecom, I. F. J.; Agert, C.;
Conrad, O. J. Mater. Chem. 2011, 21, 10426 – 10436.
(50) Choi, J.; Cho, B J. Polym. Sci. A Polym. Chem. 2011, 49, 2468-2473.
(51) Rodgers, M. T.; Armentrout, P. B. Int. J. Mass. Spec. 2007, 267, 167 – 182.
(52) Rodgers, M. T.; Armentrout, P. B. Int. J. Mass. Spec. 1999, 185/186/187, 359 – 380.
(53) Huang, H.; Rodgers, M. T. J. Phys. Chem. A 2002, 106, 4277 – 4289.
(54) Amunugama, R; Rodgers, M. T. Int. J. Mass Spec. 2000, 195/196, 439 – 457.
(55) Schmidt, W. M.; Baldidge, K. K. ; Boatz, J. A.; Elbert, S. T.; Gordon, M. S.; Jensen, J. H;
Koseki, S.; Matsunaga, N.; Nguyen, K. A.; Su, S. A.; Windus, T. L.; M, Dubuis; J.A.
Montgomery J. Comput. Chem. 1993, 14, 1347 – 1363.
(56) Curtiss, L. A.; Raghavachari, K. ; Redfern, P. C.; Rassolov, V., Pople, J. A. J. Chem. Phys.
1998, 109, 7764 – 7776.

179

(57) Curtiss, L. A.; Redfern, P. C.; Raghavachari, K.; Rassolov, V.; Pople, J. A. J. Chem. Phys.
1999, 110, 4703 – 4709.

(58) Gaussian 03, Revision C.02, Frisch, M. J.; Trucks, G. W.; Schlegel, H. B.; Scuseria, G. E.;
Robb, M. A.; Cheeseman, J. R.; Montgomery, Jr., J. A.; Vreven, T.; Kudin, K. N.; Burant, J. C.;
Millam, J. M.; Iyengar, S. S.; Tomasi, J.; Barone, V.; Mennucci, B.; Cossi, M.; Scalmani, G.;
Rega, N.; Petersson, G. A.; Nakatsuji, H.; Hada, M.; Ehara, M.; Toyota, K.; Fukuda, R.;
Hasegawa, J.; Ishida, M.; Nakajima, T.; Honda, Y.; Kitao, O.; Nakai, H.; Klene, M.; Li, X.;
Knox, J. E.; Hratchian, H. P.; Cross, J. B.; Bakken, V.; Adamo, C.; Jaramillo, J.; Gomperts, R.;
Stratmann, R. E.; Yazyev, O.; Austin, A. J.; Cammi, R.; Pomelli, C.; Ochterski, J. W.; Ayala, P.
Y.; Morokuma, K.; Voth, G. A.; Salvador, P.; Dannenberg, J. J.; Zakrzewski, V. G.; Dapprich,
S.; Daniels, A. D.; Strain, M. C.; Farkas, O.; Malick, D. K.; Rabuck, A. D.; Raghavachari, K.;
Foresman, J. B.; Ortiz, J. V.; Cui, Q.; Baboul, A. G.; Clifford, S.; Cioslowski, J.; Stefanov, B. B.;
Liu, G.; Liashenko, A.; Piskorz, P.; Komaromi, I.; Martin, R. L.; Fox, D. J.; Keith, T.; AlLaham, M. A.; Peng, C. Y.; Nanayakkara, A.; Challacombe, M.; Gill, P. M. W.; Johnson, B.;
Chen, W.; Wong, M. W.; Gonzalez, C.; and Pople, J. A.; Gaussian, Inc., Wallingford CT, 2004.
(59) Woon, D. E.; Dunning, T. H. J. Chem. Phys. 1995, 103, 4572 – 4585.
(60) Feller, D. J. Comp. Chem. 1996, 13, 1571 – 1586.
(61) Schuchardt, K.L.; Didier, B.T., Elsethagen, T.; Sun, L., Gurumoorthi, V.; Chase, J.; Li, J.;
Windus, T.L. J. Chem. Inf. Model. 2007, 3, 1045 – 1052.
(62) Keddie, D. J.; Grande, J. B.; Gonzaga, F.; Brook, M. A.; Dargaville, T. R. Org. Let. 2011,
13, 6006 – 6009.
(63) Chen, Y; Ding, Y.; Rabolt, J. F.; Baker, G. L. J. Am. Chem. Soc. 1999, 121, 6962-6963.
(66) Dienes, G. J. Appl. Phys. 1950, 21, 1189 - 1192.
(67) Wieczorek, W. Solid State Ionics 1992, 53-56, 1064 – 1070.
(68) Liu, L.; Guo, Q. Chem. Rev. 2001. 101. 673 – 695.
(69) Petrowski, M.; Frech, R. J. Phys. Chem. B 2009, 113, 5996 – 6000.
(70) Petrowsky, M.; Fleshman, A.; Bopege, D. N.; Frech, R. J. Phys. Chem. B 2012, 116, 93039309.
(71) Petrowsky, M.; Fleshman, A.; Ismail, M.; Glatzhofer, D. T.; Bopege, D. N.; Frech, R. J.
Phys. Chem. B 2012, 116, 10098 – 10105.
(72) Frech, R.; Petrowski, M. J. Phys. Chem. B 2014, 118, 2422 – 2432.

180

(73) Pogliani, L. New J. Chem. 2003, 27, 919 – 927.
(74) COSMO V1.61, Software for the CCD Detector Systems for Determining Data Collection
Parameters. Bruker Analytical X-ray Systems, Madison, WI (2009).
(75) APEX2 V2010.11-3. Software for the CCD Detector System; Bruker Analytical X-ray
Systems, Madison, WI (2010).
(76) SAINT V 7.68A Software for the Integration of CCD Detector System Bruker Analytical Xray Systems, Madison, WI (2010).
(77) SADABS V2008/2 Program for absorption corrections using Bruker-AXS CCD based on
the method of Robert Blessing; Blessing, R.H. Acta Cryst. A51, 1995, 33-38.
(78) Sheldrick, G.M. Acta Cryst. 2008, A64, 112-122.
(79) Dolomanov, O. V.; Bourhis, L. J.; Gildea, R. J.; Howard, J. A. K.; Puschmann H. J. Appl.
Cryst. 2009, 42, 339 – 341.
(80) Stirling, C. J. M. Acc. Chem. Res. 1979, 12, 198 – 203.
(81) Ayers, P. W.; Anderson, J. S. M.; Rodriguez, J. I.; Jawed, Z. Phys. Chem. Chem. Phys.
2005, 7, 1918 – 1925.
(82) Brockaert, L.; Moens, J.; Roos, G.; De Proft, F.; Geerlings, P. J. Phys. Chem. A 2008, 112,
12164-12171.
(83) Ormazábal-Toledo, R.; Campodónico, P. R.; Contreras, R. Org. Lett. 2011, 13, 822 – 824.
(84) Denegri, B.; Streiter, A.; Jurić, S.; Ofial, A. R.; Kronja, O.; Mayr, H. Chem. Euro. J. 2006,
12, 1648 - 1656.
(85) Bell, R.P.; Higginson, W.C.E. Pro. Royal Soc. 1949, 197, 141-159.
(86) DeChristopher, P. J.; Adamek, J. P.; Lyon, J. P.; Galante, J, J.; Haffner, H. E., Boggio, R. J.;
Baumgarten, R. J. J. Am. Chem. Soc. 1969, 91, 2384-2385.
(87) Hendrickson, J. B.; Bergeron, R.; Giga, A.; Sternbach, D. J. Am. Chem. Soc. 1973, 95,
3412-3413.
(88) Zhang, J.; Martin, G. R.; DesMarteau, D. D. Chem. Commun. 2003, 2334 – 2335.
(89) Arvai, R.; Toulgoat, F.; Langlois, B. R.; Sanchez, J.; Médebielle, Maurice Tetrahedron
2009, 65, 5361 – 5368.
(90) Shainyan, B. A.; Tolstikova, L. L. Chem. Rev. 2013, 113, 699 – 733.

181

(91) Armand, M.; Endres, F.; MacFarlane, D.; Ohno, H.; Scrosati, B. Nat. Mater. 2009, 8, 621 –
629.
(92) Welton, T. Chem. Rev. 1999, 99, 2071 – 2083.
(93) Castejon, H.; Wiberg, K. B. J. Am. Chem. Soc. 1999, 121, 2139 – 2146.
(94) Poater, J.; Solá, M.; Duran, M.; Fradera, X. J. Phys. Chem. A 2001, 105, 6249 – 6257.
(95) Bühl, M.; Schaefer, H. F.; J. Am. Chem. Soc. 1993, 115, 9143 – 9147.
(96) Xing, Y.; Xu, X.; Cai, Z.; Zhao, X. Cheng, J. Chem. Phys. 2004, 298, 125 – 134.
(97) Bento, P.; Bickelhaupt, F. M. J. Org. Chem. 2008, 73, 7290 – 7299.
(98) Yang, Z.; Ding, Y.; Zhao, D. J. Phys. Chem. A 2009, 113, 5432 – 5445.
(99) Su, P.; Ying, F.; Wu, W.; Hiberty, P. C.; Shaik, S. Chem. Phys. Chem. 2007, 8, 2603 –
2614.
(100) Gonzales, J. M.; Allen, W. D.; Schaefer, H. F. J. Phys. Chem. A 2005, 109, 10613 –
10628.
(101) Nowacki, A.; Dmochowska, B.; Jaczkowska, E.; Sikora, K., Wisniewski, A Comp. Theor.
Chem. 2011, 973, 53 – 61.
(102) Laerdahl, J. K.; Uggerud, E. Int. J. Mass. Spec. 2002, 214, 277 – 314.
(103) Curtiss, L.A.; Ragavachari, K.; Redfern, P. C.; Baboul, A. G.; Pople, J. A. Chem. Phys.
Lett. 1999, 314, 101 - 107.
(104) Wei, Y.; Singer, T.; Mayr, H.; Sastry, G. N.; Zipse, H. J. Comput. Chem. 2008, 29, 291 –
297.
(105) Shi, Z.; Boyd, R. J. J. Am. Chem. Soc. 1990, 112, 6789 – 6796.
(106) Bode, B. M.; Gordon, M. S.; J. Mol. Graphics and Modeling 1998, 16, 133 – 138.
(107) Fernández, I.; Frenking, G.; Uggerud, E. Chem. Euro. J. 2009, 15, 2166 – 2175.
(108) Wolfe, S.; Mitchell, D. J.; Schlegel, H. B. J. Am. Chem. Soc. 1981, 103, 7692 – 7694.
(109) Wolfe, S.; Mitchell, D. J.; Schlegel, H. B. J. Am. Chem. Soc. 1981, 103, 7694 – 7696.
(110) Shaik, S. S.; Schlegel, H. B.; Wolfe, S. J. Chem. Soc. Chem. Commun. 1988, 1322 – 1323.

182

(111) Shaik, S. S.; Schlegel, H. B.; Wolfe, S. J. Chem. Soc. Chem. Commun. 1988, 1322 – 1323.
(112) Bernasconi, C. F. Acc. Chem. Res. 1992, 25, 9-16.
(113) Shaik, S.; Shurki, A. Angew. Chem. Int. Ed. 1999, 38, 586 – 625.
(114) Shaik, S.; Duzy, E.; Bartuv, A. J. Phys. Chem. 1990, 94, 6574 – 6582.
(115) Piecuch, P.; Kucharski, S. A.; Kowalski, K.; Musial, M. Comp. Phys. Commun. 2002, 149,
71 – 96.
(116) Bentz, J. L.; Olson, R. M.; Gordon, M. S.; Schmidt, M. W.; Kendall, R. A. Compute. Phys.
Commun. 2007, 176, 589 – 600.
(117) Olson, R. M.; Bentz, J. L.; Kendall, R. A.; Schmidt, M. W.; Gordon, M. S. J. Comput.
Theoret. Chem. 2007, 3, 1312 – 1328.
(118) Denehy, E.; White, J. M.; Williams, S. J. Inorg. Chem. 2007, 46, 8871 – 8886.
(119) Bharatam, P. V.; Gupta, A. A.; Kaur, D. Tetrahedron 2002, 58, 1759 – 1764.
(120) Chardin, A.; Laurence, C.; Berthelot, M.; Morris, D. G. J. Chem. Soc. Perkin Trans. 2
1996, 1047 – 1051.
(121) Hoz, S.; Basch, H.; Wolk, J. L.; Hoz, T.; Rozental, E. J. Am. Chem. Soc. 1999, 121, 7724
– 7725.
(122) Yi, R.; Basch, H.; Hoz, S. J. Org. Chem. 2002, 67, 5891 – 5895
(123) Narita, A.; Shibayama, W.; Ohno, H. J. Mater. Chem. 2006, 16, 1475 – 1482.
(124) Yoshizawa, M.; Ohno, H. Ionics 2002, 8, 267-271.
(125) Shibayama, W.; Narita, A.; Matsumi, N.; Ohno, H. J. Organomet. Chem. 2009, 694, 1642
– 1645.
(126) Zhao, H. Ph.D. Thesis, Michigan State University, East Lansing, MI, 2012.
(127) Lee, J. W.; Jun, S. I.; Kim, K. Tetrahedron Lett. 2001, 42, 2709 – 2711.
(128) King et al. J. Am. Chem. Soc. 1982, 104, 7108.
(129) Askin et al. Org. Lett. 2003, 5, 4175 – 4177.
(130) Toulgoat, F.; Langlois, B. R.; Médebielle, M.; Sanchez, J. J. Org. Chem. 2008, 73, 5613 –
5616.
183

(131) Anselyn, E. V.; Dougherty, D. A.; Modern Physical Organic Chemistry. University
Science Books: Sausalito, 2006.
(132) Evans, J.; Vincent, C. A.; Bruce, P. G. Polymer 1987, 28, 2324 – 2328.

184