MANUFACTURE OF BIOBASED MONOMERS AND VALUE-ADDED
PRODUCTS FROM SOYBEAN OIL
By
Yanjie Zhao

A DISSERTATION
Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of
Chemical Engineering—Doctor of Philosophy
2015

ABSTRACT
MANUFACTURE OF BIOBASED MONOMERS AND VALUE-ADDED PRODUCTS
FROM SOYBEAN OIL
By
Yanjie Zhao
The depletion of non-renewable resources by modern societies and the need for a
sustainable chemical industry are major factors that contribute to an increasing interest to
study and develop new biobased polymers. The specific goal of this research was to study
the synthesis of biobased polymer building blocks through ozonolysis of soybean-oilbased fatty acid methyl esters (FAMEs), evaluate their purification feasibility by
distillation and evaluate their potential for biobased polymer applications.
Ozonolysis reactions were conducted in two different solvent systems, in both batch and
continuous reaction mode. In the first system, methanol was used both as solvent and
esterification reagent, while sodium methoxide was added as the esterification catalyst. In
the second system, water was used as solvent without catalyst addition. In the methanol
system ozone oxidizes the double bonds of unsaturated FAMEs, producing aldehydes
(around 50% molar yield) and methyl esters (less than 15% molar yield). With dimethyl
azelate as the target compound for biobased polyester building blocks, Oxone was used to
convert the aldehydes into methyl esters, improving their molar yields to between 65%
and 73%. In the water system, ozonolysis reactions yield aldehydes and carboxylic acids.
The products from water system were also primarily aldehydes including hexanal,
nonanal and methyl 9-oxononanoate with molar yields between 62% and 71%. For room
temperature assays in a continuous system, the optimal flow rate for maximizing product

formation during ozonolysis in methanol system was found to be 15 ml/min (ratio of
methanol to fame 2:1), while in water system was 40 ml/min (ratio of water to fame 3:1).
For purification of the ozonolysis products from both methanol and water systems, two
distillation processes were designed and evaluated using simulation results. A fractional
distillation was designed and simulated in Aspen Plus for products generated from the
two systems, and most of the purity of products was above 0.99 with recoveries higher
than 0.98. As some of the products are sensitive to temperature, an alternative distillation
method was evaluated using wiped film distillation (WFD). This system was modeled
using an equilibrium simulation with a flash separation module in Aspen Plus to predict
the separation efficiency of multiple components. When the operating pressure in WFD is
fixed, the study showed that modeling pressure in Aspen Plus is proportional to the
pseudo bubble pressure of the mixture under the heating oil temperature of WFD. Since
the WFD is similar to one-stage flash separation under a certain pressure, it is not
recommended for separation of complex products with close relative volatility, like in the
case of mixed products from ozonolysis of FAMEs.
To evaluate the usage of biobased aldehydes for polymer applications, polyvinyl acetals
were prepared during polymerization reactions of polyvinyl alcohol (PVOH) with three
aldehydes generated from ozonolysis of FAMEs in water system. Properties including
decomposition temperature, glass transition and melting temperature for various types of
biobased polyvinyl acetals were evaluated and compared with a commercial product
polyvinyl butyral (PVB). The above mentioned properties for polyvinyl hexanal (PVH)
are comparable to PVB, suggesting that biobased PVH could potentially become a
marketable green polyvinyl acetal polymer.

ACKNOWLEDGEMENTS
I would like to first of all thank my research advisor, Dr. Ramani Narayan, for his
guidance, support and understanding. I give my special thanks to my co-advisor Dr. Carl
Lira and to Dr. Susan Masten for their dedicated support and help. I also thank my Ph.D.
committee members Dr. Miller and Dr. Jackson for providing valuable suggestions to my
research and dissertation. I thank all of the colleagues from BMRG for their help and
providing me a pleasant work environment.
I would also like to express my special gratitude to my parents, my sisters and all my
family members for loving me and supporting me unconditionally.

iv

TABLE OF CONTENTS

LIST OF TABLES ......................................................................................................... viii
LIST OF FIGURES .......................................................................................................... x
Chapter 1: Introduction ................................................................................................... 1
1.1
Research Motivation and Rationale ..................................................................... 1
1.2
Biobased Polymers ............................................................................................... 2
1.3
Vegetable Oil Chemistry ...................................................................................... 4
1.4
Vegetable Oil Based Polymers............................................................................. 6
1.5
Organization of the dissertation ......................................................................... 10
Chapter 2: Method Implementation for Ozonolysis Product Characte rization and
Mass Balance Study ........................................................................................................ 14
2.1
Introduction ........................................................................................................ 14
2.1.1
Ozone chemistry ......................................................................................... 14
2.1.2
Ozonation of fatty acid group ..................................................................... 16
2.1.3
Ozonolysis of soybean-oil-based FAMEs .................................................. 20
2.1.4
Analysis method for ozonolysis products ................................................... 23
2.2
Experiment ......................................................................................................... 25
2.2.1
Materials...................................................................................................... 25
2.2.2
Continuous reaction .................................................................................... 25
2.2.3
Oxone treatment .......................................................................................... 27
2.2.4
GC analysis ................................................................................................. 28
2.2.5
GC-MS analysis .......................................................................................... 29
2.3
Results and Discussion....................................................................................... 29
2.3.1
Composition of reactants and products ....................................................... 29
2.3.2
Effective carbon number method for quantitative GC-FID analysis .......... 33
2.3.3
Ozonolysis in methanol system .................................................................. 37
2.3.4
Ozonolysis in water system ........................................................................ 41
2.4
Conclusions ........................................................................................................ 45
Chapter 3: Mass Transfer and Reaction Kinetics Study for Ozonation of FAMEs . 47
3.1
Introduction ........................................................................................................ 47
3.2
Experiment ......................................................................................................... 50
3.2.1
Ozone measurement .................................................................................... 50
3.2.2
GC analysis ................................................................................................. 52
3.2.3
Ozonolysis reaction..................................................................................... 52
3.2.4
Ozonolysis of FAMEs in methanol............................................................. 52
3.2.5
Ozonolysis of FAMEs in water................................................................... 53
3.2.6
Mass transfer model of ozone in methanol and water ................................ 53
3.2.7
Assumptions of model and Henry’s law constant measurement ................ 58
3.2.8
Extraction of organic products from solution after Oxone treatment ......... 59
3.3
Results and Discussion....................................................................................... 60
v

3.3.1
Reaction kinetics of ozonolysis in methanol system .................................. 60
3.3.1.1
Batch process ....................................................................................... 60
3.3.1.2
Continuous process .............................................................................. 65
3.3.2
Oxone treatment and extraction of ozonolysis products in methanol system
……………………………………………………………………………..69
3.3.3
Mass transfer study of ozone in methanol system ...................................... 73
3.3.4
Ozone mass transfer in water system .......................................................... 78
3.3.5
Ozone mass transfer under reaction in methanol system ............................ 79
3.3.6
Reaction kinetics of ozonolysis in water system ........................................ 82
3.3.6.1
Batch process ....................................................................................... 82
3.3.6.2
Continuous process .............................................................................. 86
3.4
Conclusion.......................................................................................................... 89
Chapter 4: Distillation Process Design to Separate Ozonolysis Products of FAMEs 92
4.1
Introduction ........................................................................................................ 92
4.2
Heuristic method to determine distillation sequence ........................................ 94
4.3
Distillation sequence for ozonolysis products.................................................... 95
4.4
Properties for main components......................................................................... 98
4.5
Distillation design ............................................................................................ 101
4.6
Results and discussion...................................................................................... 103
4.6.1
Distillation design for separation of products obtained from ozonolysis in
methanol .................................................................................................................. 103
4.6.2
Distillation design for products obtained from ozonolysis in water ......... 108
4.7
Conclusion........................................................................................................ 115
Chapter 5: Simulation of Wiped Film Distillation in Aspen Plus ............................ 116
5.1
Introduction ...................................................................................................... 116
5.2
Experiment ....................................................................................................... 120
5.2.1
Materials.................................................................................................... 120
5.2.2
Analytical methods ................................................................................... 120
5.2.3
Wiped film distillation .............................................................................. 121
5.2.4
Simulation in Aspen Plus .......................................................................... 123
5.3
Results and discussion...................................................................................... 124
5.3.1
Affecting factors in WFD ......................................................................... 124
5.3.2
Vapor pressure data comparison and regression....................................... 129
5.3.3
Simulation in Aspen for methanol and methyl hexanoate mixture ........... 132
5.3.4
Simulation in Aspen for ozonolysis product mixture ............................... 134
5.3.5
Simulation in Aspen for FAMEs mixture ................................................. 137
5.4
Conclusion........................................................................................................ 140
Chapter 6: Polyvinyl Acetal Synthesis and Characterization................................... 142
6.1
Introduction ...................................................................................................... 142
6.2
Experiments...................................................................................................... 145
6.2.1
Materials.................................................................................................... 145
6.2.2
Preparation of PVOH solution .................................................................. 146
6.2.3
Preparation of polyvinyl acetal in aqueous solution ................................. 146
vi

6.2.4
6.2.5
6.2.6
6.2.7

Preparation of polyvinyl hexanal in organic solution ............................... 147
Thermogravimetric analysis (TGA).......................................................... 147
Differential scanning calorimetry (DSC) .................................................. 148
Gel permeation chromatography (GPC) for molecular weight measurement
……………………………………………………………………….…...148
1
6.2.8
H NMR analysis ...................................................................................... 148
6.3
Results and Discussion..................................................................................... 149
6.3.1
Thermogravimetric analysis (TGA).......................................................... 149
6.3.2
Differential scanning calorimetry (DSC) .................................................. 154
6.3.3
Gel permeation chromatography (GPC) for molecular weight measurement
…………………………………………………………………………....157
1
6.3.4
H NMR analysis for PVH prepared in aqueous solution......................... 158
6.4
Conclusion........................................................................................................ 159
BIBLIOGRAPHY ......................................................................................................... 163

vii

LIST OF TABLES

Table 1.1 Properties and fatty acid compositions of the most common vegetable oils ...... 7
Table 2.1 Compositions of FAMEs .................................................................................. 31
Table 2.2 Identification of ozonolysis products formed in ethanol and water system, with
respective mass spectra reliability according to NIST databank. ..................................... 32
Table 2.3 Contributions to the Effective Carbon Number ................................................ 34
Table 2.4 Calculated Effective Carbon Numbers for main compounds ........................... 36
Table 2.5 Comparison between experimentally obtained ECN and calculated ECN ....... 37
Table 2.6 Yield for products from ozonolysis in methyl system ...................................... 39
Table 2.7 Yield for products after Oxone treatment ......................................................... 41
Table 2.8 Yield for products from ozonolysis in water system ........................................ 44
Table 2.9 Mass yield of products from ozonolysis in two systems .................................. 45
Table 4.1 Products generated from ozonolysis in methanol after Oxone treatment and
water extraction................................................................................................................. 96
Table 4.2 Molar ratio of compounds after removing water and methanol ....................... 97
Table 4.3 Products generated from ozonolysis in water ................................................... 98
Table 4.4 Properties for main products from ozonolysis ................................................ 100
Table 4.5 Distillation results for the products from ozonolysis of FAMEs in methanol 105
Table 4.6 Reboiler and condenser design specification for separating products from
ozonolysis of FAMEs in methanol ................................................................................. 107
Table 4.7 Distillation column design specification for separating products from
ozonolysis of FAMEs in methanol ................................................................................. 108
Table 4.8 Distillation result for products from ozonolysis in water ............................... 111
Table 4.9 Reboiler and condenser design specification for products from ozonolysis in
water................................................................................................................................ 112
Table 4.10 Distillation column design specification for products from ozonolysis in water
......................................................................................................................................... 113
viii

Table 4.11 Comparison of two distillation processes based on the same input of FAMEs
......................................................................................................................................... 114
Table 5.1 Dimensions of ICL-04 wiped film evaporator................................................ 122
Table 5.2 Modeling and experimental data comparison o f component flow rates in
distillate stream. .............................................................................................................. 133
Table 6.1 Average molar mass of PVH made in two different solvents ......................... 158

ix

LIST OF FIGURES

Figure 1.1 Structure of triglyceride..................................................................................... 5
Figure 2.1 Natural formation of O 3 ................................................................................... 14
Figure 2.2 Ozonation mechanisms in methanol and water system ................................... 17
Figure 2.3 Ozonolysis reaction in methanol system ......................................................... 21
Figure 2.4 Ozonolysis reaction in water system ............................................................... 22
Figure 2.5 Reaction process and equipments for ozonolysis. A: air cylinder; B: ozonator;
C: ozone analyzer; D: plug flow reactor; E: batch reactor; F: flow meter; G: dry ice trap;
H: potassium iodide trap; c: cooling water; g: gas; m: liquid material. ............................ 26
Figure 2.6 Oxone oxidization reaction mechanisms. ........................................................ 27
Figure 2.7 GC chromatograph for soybean oil FAMEs. 1: Methyl palmitate (C16:0); 2:
Methyl Stearate (C18:0); 3: Methyl oleate (C18:1); 4: Methyl linoleate (C18:2); 5:
Methyl linolenate (C18:3). ................................................................................................ 30
Figure 2.8 Chromatogram for products from ozonolysis in methanol system. A: Hexanal;
B: Methyl hexanoate; C: Nonanal; D: Methyl nonanoate; E: Methyl 9-oxononanoate; F:
Dimethyl azelate; G: Methyl palmitate; H: Methyl stearate. ............................................ 39
Figure 2.9 Chromatogram for products after oxone treatment. A: Hexanal; B: Methyl
hexanoate; C: Nonanal; D: Methyl nonanoate; E: Methyl 9-oxononanoate; F: Dimethyl
azelate; G: Methyl palmitate; H: Methyl stearate. ............................................................ 40
Figure 2.10 Chromatogram for products of ozonolysis in water system. A: Hexana l; B:
Nonanal; C: Methyl 9-oxononanoate; D: Methyl palmitate; E: Methyl stearate. ............. 42
Figure 2.11 Chromatogram for acid products of ozonolysis in water system. A: Hexanoic
acid; B: Nonanoic acid; C: Monomethyl azelate .............................................................. 43
Figure 3.1 GC chromatograms for FAMEs in methanol solution during ozonolysis in
semi-batch reactor. Oxygen/ozone gas mixture flow rate was 1 L/min, with 10 wt% of
ozone. A: Methyl palmitate; B: Methyl Stearate; C: Methyl oleate; D: Methyl linoleate;
E: Methyl linolenate; F: Hexanal; G: Nonanal; H: Methyl 9-oxononanoate; I: Dimethyl
azelate................................................................................................................................ 61
x

Figure 3.2 Ozonolysis of FAMEs in three cooling systems using methanol as solvent
system................................................................................................................................ 62
Figure 3.3 Molar yields of products from ozonolysis in methanol in plug flow reactor
under different flow rates. ................................................................................................. 66
Figure 3.4 Total molar yields for products obtained from the same reactants from
ozonolysis in methanol in plug flow reactor under different flow rates ........................... 67
Figure 3.5 Conversion of unsaturated FAMEs during ozonolysis in methanol in plug flo w
reactor under different flow rates...................................................................................... 68
Figure 3.6 Kinetics for Oxone treatment of ozonolysis products ..................................... 70
Figure 3.7 GC chromatograms for products before and after Oxone treatment. A:
Hexanal; B: Methyl hexanal; C: Nonanal; D: Methyl nonanoate; E: Methyl 9oxonoanoate; F: Dimethyl azelate; G: Methyl palmitate; H: Methyl stearate. ................. 71
Figure 3.8 Extraction of products after Oxone treatment using hexane. From batch 1 to 5,
the volumetric ratios of sample to extractant were 4:6, 4:4, 4:3, 4:2 and 4:1. .................. 72
Figure 3.9 Extraction of products after Oxone treatment using water. From batch 1 to 5,
the volumetric ratios of sample to extractant were 4:6, 4:4, 4:3, 4:2 and 4:1. .................. 73
Figure 3.10 Concentration of ozone in methanol under different solvent flow rate at 22 ℃
with total gas pressure 20.89 psi, flow rate 3.75 L/min and ozone mass fraction 10.95%.
........................................................................................................................................... 74
Figure 3.11 Gas phase NTU for ozone in methanol for PFR reactor under different
solvent flow rate at 22 ℃ with total gas pressure 20.89 psi, flow rate 3.75 L/min and
ozone mass fraction 10.95%. ............................................................................................ 75
Figure 3.12 Box plot of gas phase NTU for ozone mass transfer in methanol in PFR
reactor under different solvent flow rate at 22 ℃ with total gas pressure 20.89 psi, flow
rate 3.75 L/min and ozone mass fraction 10.95%............................................................. 76
Figure 3.13 Liquid phase NTU for ozone in methanol in PFR reactor under different
solvent flow rate at 22 ℃ with total gas pressure 20.89 psi, flow rate 3.75 L/min and
ozone mass fraction 10.95%. ............................................................................................ 77
Figure 3.14 Concentration of ozone in water with different solvent flow rate at 22 ℃ with
total gas pressure 20.89 psi, flow rate 3.75 L/min and ozone mass fraction 10.95%. ...... 79

xi

Figure 3.15 Ozone consumption and enhancement factor for ozone mass transfer with
ozonolysis in methanol in PFR reactor under different material flow rate at 22 ℃ with
total gas pressure 21.5 psi, flow rate 3.77 L/min and ozone mass fraction 10.11%. ........ 81
Figure 3.16 Temperature of solution during ozonolysis reaction ..................................... 83
Figure 3.17 pH change of water phase during reaction .................................................... 83
Figure 3.18 Ozonolysis of FAMEs in two solvent systems at room temperature ............ 85
Figure 3.19 Conversions of unsaturated FAMEs at different material flow rate for
ozonolysis in water in continuous reactor......................................................................... 87
Figure 3.20 Product yields at different material flow rate for ozonolysis in water in
continuous reactor. ............................................................................................................ 88
Figure 3.21 Total molar yields for products obtained from the same reactants from
ozonolysis in water in plug flow reactor under different flow rates. ................................ 89
Figure 4.1 Distillation design in Aspen Plus for separating FAME ozonolysis products in
methanol system. DIS1: methanol; DIS3: methyl hexanoate; RES3: methyl nonanoate;
DIS4: dimethyl azelate; RES4: methyl palmitate and methyl stearate. .......................... 104
Figure 4.2 Distillation design in Aspen Plus for products made in water using ozonolysis.
D2: hexanal; R2: nonanal; D3: methyl 9-oxononanoate; R3: methyl palmitate and methyl
stearate. ........................................................................................................................... 110
Figure 5.1 Wiped film evaporator and adjunctive facilities. A. Wiped film evaporator; A1. Rolling speed meter; A-2. Wiper; A-3. Heating area; A-4. Dry ice trap; A-5. Pressure
gage; A-6. Condenser; B. Oil heating system; C. Peristaltic Pump; D. Material container;
E. Vacuum pump; F. Water cooling system. .................................................................. 122
Figure 5.2 Effect of heating temperature on the ratio between distillate and feed using
ozonolysis product with input flow rate of 3 ml/min and wiper rolling speed of 250 rpm,
under still pressure of 2.7 kPa. ........................................................................................ 125
Figure 5.3 Effect of heating temperature on mass fraction of components using
ozonolysis product with input flow rate of 3 ml/min and wiper rolling speed of 250 rpm,
under still pressure of 2.7 kPa. A: Methyl hexanoate; B: Methyl nonanoate; C: Dimethyl
azelate; D: Methyl palmitate; E: Methyl stearate............................................................ 126

xii

Figure 5.4 Effect of feed material flow rate on ratio of distillate to feed using ozonolysis
product with wiper rolling speed of 250 rpm, heating temperature of 60 ℃ under pressure
of 2.7 kPa. ....................................................................................................................... 127
Figure 5.5 Effect of wiper rolling speed on ratio of distillate to feed using ozonolysis
product with feed flow rate of 3 ml/min, heating temperature of 60 ℃ under pressure of
2.7 kPa............................................................................................................................. 128
Figure 5.6 Comparison of vapor pressure for methyl esters from Aspen (continuous data)
and literature (discrete points). C7: methyl hexanoate; C10: methyl nonanoate; C11:
dimethyl azelate; C17: methyl palmitate; C19: methyl stearate. .................................... 130
Figure 5.7 Comparison of vapor pressure data for unsaturated fatty acid methyl esters
from Aspen and literature. (C18:1): methyl oleate; (C18:3): methyl linolenate. ............ 131
Figure 5.8 Comparison of vapor pressure data of methyl linoleate from Aspen (databank
and after regression) and literature.................................................................................. 132
Figure 5.9 Bubble pressure of mixture versus modeling pressure from Aspen. ............. 134
Figure 5.10 Comparison of component flow rate in distillate for experimental and
modeling data of saturated methyl ester mixture. METH: Methanol; C7: Methyl
hexanoate; C10: Methyl nonanoate; C11: Dimethyl azelate; C17: Methyl palmitate; C19:
Methyl stearate. ............................................................................................................... 136
Figure 5.11 Bubble pressure of mixture versus modeling pressure in Aspen for products
prepared through ozonolysis. Operating pressure was 1 atm, feed flow rate was 3 ml/min,
condenser temperature was 3 ℃, and the rolling speed of wiper was 250 rpm. ............. 137
Figure 5.12 Experimental and modeling data comparison of component flow rate in
distillate for separation of FAMEs. C17:0: Methyl palmitate; C19:0: Methyl stearate;
C18:1: Methyl oleate; C18:2: Methyl linoleate; C18:3: Methyl linolenate. ................... 139
Figure 5.13 Experimental pressure of WFD versus modeling pressure in Aspen for
FAMEs. Operating temperature was 170 ℃, feed flow rate was 3 ml/min, condenser
temperature was 3 ℃, and the rolling speed of wiper was 250 rpm. .............................. 140
Figure 6.1 Reactions for polyvinyl acetal polymer preparation. .................................... 143
Figure 6.2 TGA weight percentage change with temperature profiles of polyvinyl alcohol
and acetal polymers......................................................................................................... 150

xiii

Figure 6.3 TGA weight percentage change with temperature profiles of polyvinyl alcohol
and acetal polymers......................................................................................................... 152
Figure 6.4 DSC spectra of polyvinyl acetals. PVB: polyvinyl butyral provided by
Kuraray; PVOH: polyvinyl alcohol provided by Kuraray; PVH: polyvinyl alcohol
reacted with hexanal based on stoichiometry; PVH_2: polyvinyl alcohol reacted with
100% excess hexanal based on stoichiometry; PVH_1/2: polyvinyl alcohol reacted with
half amount of hexanal based on stoichiometry. ............................................................ 155
Figure 6.5 DSC spectra of polyvinyl acetals. PVB: polyvinyl butyral provided by
Kuraray; PVH: polyvinyl alcohol reacted with hexanal based on stoichiometry; PVN:
polyvinyl alcohol reacted with nonanal based on stoichiometry; PVHN: polyvinyl alcohol
reacted with hexanal and nonanal (molar ratio 1:1) based on stoichiometry; PVHN9:
polyvinyl alcohol reacted with hexanal and 9-oxononanoate (molar ratio 1:1) based on
stoichiometry................................................................................................................... 156
Figure 6.6 GPC spectrum of PVH made in two different solvents. ................................ 158
Figure 6.7 1 H NMR spectrum of PVH prepared in organic solvent ............................... 159

xiv

Chapter 1: Introduction

1.1 Research Motivation and Rationale
A polymer is a large molecule containing repeated subunits which is usually produced
from monomers. Polymers are widely used in many areas including textiles, packaging,
medicines, construction, etc. In 2013, the world’s plastic production was more than 299
billion kilograms [1], and it is predicted that the global production will surpass 300
million tons by 2015. Currently, most commercially available polymers are derived from
non-renewable resources and account for approximately 7% of the overall worldwide oil
and gas usage [2]. Since the early 20th century, petroleum has been the main resource for
world’s energy and chemical production, including polymer precursors. To satisfy energy
and chemicals demand, the world currently consumes about 14.26×106 m3 of petroleum
per day (by May 30, 2013, from US Energy Information Administration [3] ) and about
16% of this volume is consumed by the chemical industry. Due to intense consumption of
fossil energy, the conventional crude oil production has already reached a peak and is
depleting at a rate of 6.8% annually, according to the report from the International Energy
Agency's (IEA) 2010 World Energy Outlook [4]. On the other hand, fossil energy
consumption also has a strong impact on the environmental conservation. As is well
known, fossil carbons have been immobilized underground for millions of years and once
being released for energy or chemical production, more carbons will be exposed to the
surface of the planet. As a significant portion of the carbons are fully oxidized during
combustion of fossil fuel, they are released in the form of carbon dioxide, which is a key
factor responsible for the greenhouse effect and global warming. To alleviate or solve the

1

problem, the usage of renewable carbon for fuels and chemicals production is required. In
response to these environmental concerns, biobased polymers have been developed.
Biobased polymers, as renewable substitutes to traditional petroleum-based plastics, can
be derived from a wide range of feedstocks such as corn, soybeans, wood and crop stalks
[5]. Among the biobased polymer resources, soybean is the one of the best choices in
terms of availability and cost. US is the largest soybean producer in the world, producing
more than 100 million tons of soybeans in 2014 [6] and exporting about one third of the
production. Aiming to reduce the consumption of fossil resources and to explore the
industrial utilization of soybean, an environmentally friendly process for production of
polymer precursors and other value-added products from soybean oil was studied in this
work. Furthermore, the synthesis and characterization of a novel soybean oil based
polymer is presented in this study.
1.2 Biobased Polymers
Biobased polymers are polymers derived from renewable biomass resources, such as
vegetable fats and oils, corn or pea starch, wood, etc. Some biobased polymers are
designed to be biodegradable, but a biobased polymer is not necessarily biodegradable.
Biodegradable

polymers

such

as

polylactic

acid,

starch

plastics

and

polyhydroxyalkanoates, are defined as materials whose physical and chemical properties
undergo deterioration and completely degrade to form carbon dioxide, methane, and
water when exposed to microorganisms. Biobased polymers can be classified into
renewable resource based polymers and mixed sources (bio-/petro-) based polymers,
depending on the proportion of bioresource [7].

2

Biobased polymers still take a very small portion in the total global plastic market (less
than 1%) and it is expected that biobased polymers will account for just over 1% by 2015
[8]. However, as the bioeconomy develops and people become more environmentally
conscious, there will be an increasing demand for developing sustainable polymers,
derived from biomass, which can replace petroleum based polymers in various
applications.
The resources for biobased polymers were mainly from food products in the early
technological stages, and included potatoes, corn grain and any other starch-producing
crop. However, the usage of food products for polymer production and other
commodities raises ethical problems due to increase in food demand and price. Therefore,
the focus has been shifted to use non-edible biomass and organic waste for production of
biobased materials [9].
Since polymers are usually synthesized through the reaction of monomers, the
development of biobased polymers often starts from production of small molecules which
will constitute the macromolecule. There are three main methods to get the small
molecules for polymer building blocks from natural resources — extraction, fermentation
and chemical synthesis [10]. Biobased polymers that have the monomers derived from
the first method include starch, cellulose and lignin. The fermentation method is used to
produce polymers like some types of polyhydroxyalkanoates, while traditional chemical
synthesis method is more suitable for manufacturing some widely used polymers like
polylactic acid (PLA), polyethylene (PE), etc [10].

3

Biobased polymers are widely applied in many industrial areas such as food packaging,
medical material, clothing textiles, coating, etc. The reason for this is that most biobased
polymers share some properties with traditional petroleum-based polymers and, at the
same time, they have some distinctive characteristics. For example, PLA – one of the
most famous biobased polymers – is widely used in packaging because it is very similar
to polyethylene terephthalate (PET), except for a lower degradation temperature (60 ℃).
Unlike PET, PLA is also biodegradable [11] and therefore, it can be used in medical
materials like sutures, which need to degrade in a special condition after some time [12].
The main challenges for wider commercialization of biobased polymers are the
performance of these polymers and the manufacturing cost. The former challenge may be
reduced if fossil-based polymers can be slowly replaced by biobased polymers that have
been proved to meet performance parameters for certain applications, while at the same
time, new biobased polymers with superior properties for new applications can be
developed. The latter challenge will be reduced as fossil energy is depleted and the
demand for biobased polymer development increases.
1.3 Vegetable Oil Chemistry
Vegetable Oil is usually produced from plant components (typically from seeds), and two
different methods are mainly used to extract vegetable oil: 1) mechanical extraction with
a mill and 2) chemical extraction with a solvent [13]. The most popular mechanical
extraction method is expeller pressing, which is operated at high pressure to obtain the
maximum yield. This method can also be specified as cold pressing if it is operated at
temperatures lower than 120 ℃, otherwise it is designated as regular expeller pressing.
Besides the above two methods, there is also CO 2 extraction, in which carbon dioxide is
4

converted to liquid, making it a safe and effective solvent that allows all the desirable
active constituents of a plant to be collected without the risk of heat degradation [14].
Mechanical extraction is preferred in food industry, since it will not introduce other
chemicals into the product, while the chemical solvent extraction (e.g. hexane) is more
preferred in chemical industry, which uses vegetable oil as feedstock for the manufacture
of chemicals [13].
As shown in Figure 1.1, the main components of vegetable oil are triglycerides, which is
a group of compounds with a structure of three fatty acids linked to one glycerol
molecule. The length of carbon chain of those fatty acids as well as the number of
double-carbon bonds determines the physical and chemical properties of vegetable oil.
The number of carbons in saturated fatty acids varies from 8 to 24 and in unsaturated
fatty acids it varies from 16 to 24, while the number of double bonds in the main chain of
unsaturated fatty acids ranges from 1 to 3 [15]. Vegetable oil has a lower boiling point
than fat because it contains a higher percentage of unsaturated fatty acids. This structural
feature is an important advantage of vegetable oil over animal fat for its application in the
chemical and polymer industry. Vegetable oils have been used for manufacturing paints
and coatings for centuries and during the last decade, a variety of vegetable oil-based
fuels has been increasingly produced [16].
O
H 2C

O

C

HC

O

C

H 2C

O

C

Figure 1.1 Structure of triglyceride
5

O
O

R1
R2
R3

The chemical structure of triglycerides contains two reactive sites, which are the double
bonds in the unsaturated fatty acid chains and the ester groups that connect all the fatty
acid chains to the glycerol structure [17]. Most vegetable oil-based polymers were
synthesized using chemistry targeting those two reactive sites. For example,
biorenewable polymers can be prepared by hydrogenation, epoxidation, carboxylation,
oxidative cleavage or polymerization, taking advantage of the carbon–carbon double
bonds in the fatty acid chains [18]. Reactions targeting the ester linkages encompass
hydrolysis, transesterification, amide synthesis, etc [19]. Innovative design and synthesis
of new vegetable oil-based monomers and the incorporation of novel polymerization
methods will impel the development of novel vegetable oil derived polymeric materials
in the future.
1.4 Vegetable Oil Based Polymers
Based on the triglyceride structure, a great variety of vegetable-oil-based polymers have
been derived from reactions targeting double bonds, allylic positions and the ester groups.
There are many types of plants that can be used to produce vegetable oil. The main
difference among vegetable oils is determined by the fatty acids contained in the
triglyceride molecules. Different fatty acids have different length of carbon chain and
different number of double bonds. The carbon number of most fatty acids falls into the
range of 8 to 18 [2]. The five main fatty acids can make up to 94 wt% ~ 100wt% of the
commonly used vegetable oils (Table 1.1 [2]). For polymer synthesis depending on
double bond-related reactions, the presence of more double bonds will certainly lead to
higher yield of polymeric products. In Table 1.1, it is shown that soybean oil has higher
double bond ratio than most of the other listed vegetable oils. This fact supports the
6

choice of soybean oil as the starting material used in this project, besides the wide
availability and low price.
Table 1.1 Properties and fatty acid compositions of the most common vegetable oils

Vegetable oil

Double bondsa

Iodine valueb/mg per 100 g

Fatty acids (%)
Palmitic Stearic

Oleic

Linoleic

Linolenic

Palm
Olive
Groundnut
Rapeseed
Sesame
Cottonseed
Corn
Soybean
Sunflower
Linseed

1.7
2.8
3.4
3.8
3.9
3.9
4.5
4.6
4.7
6.6

44–58
75–94
80–106
94–120
103–116
90–119
102–130
117–143
110–143
168–204

42.8
13.7
11.4
4
9
21.6
10.9
11
5.2
5.5

40.5
71.1
48.3
56
41
18.6
25.4
23.4
37.2
19.1

10.1
10
31.9
26
43
54.4
59.6
53.3
53.8
15.3

—
0.6
—
10
1
0.7
1.2
7.8
1
56.6

a

4.2
2.5
2.4
2
6
2.6
2
4
2.7
3.5

Average number of double bonds per triglyceride.
The amount of iodine (mg) that reacts with the double bonds in 100 g of vegetable oil.

b

Polyurethane is one of most important polymeric materials that can be synthesized by
triglycerides. Polyurethanes are usually synthesized from reaction of polyols with multiisocyanate, and both reactants could be derived from triglycerides and their derivatives
[20]. Soybean oil triglycerides were used to synthesize soybean oil iodo isocyanate
through a reaction between double bonds from the fatty acids and iodine isocyanate [21].
Fatty acids, e.g. oleic acid could also be used to produce multi- isocyanates [22, 23], and it
was found that diesters were applied as the starting material for diisocyanate synthesis.
Vegetable oil based polyols could be synthesized through many methods including thiolene coupling reactions [24-26], ozonolysis [27, 28], epoxidation, ring-opening [29], etc.
The starting materials that have been reported include castor oil [30], sunflower oil,
canola oil, soybean oil and linseed oil .

7

Polyesters are another type of polymers that can be produced from vegetable oil.
Biobased polyesters could be synthesized through condensation polymerization of
monoglycerides with phthalic anhydride [31]. It was also found that polyesters could be
obtained by reacting epoxidized oils with dicarboxylic acid a nhydrides with tertiary
amines or imidazoles as catalyst [32]. The properties of polyesters are usually determined
by the structure of dicarboxylic anhydride, the dicarboxylic anhydride and epoxy reactant
ratio [31].
Due to the special structure of some free acids in vegetable oil, polyesters can be
synthesized directly from these fatty acids. For example, ricinoleic acid represents more
than 90% of castor oil composition, it contains both carboxyl and hydroxyl groups and
therefore provides the structural condition for self-polymerization and formation of
polyester [33]. Another important fatty acid is sebacic acid, which has also been used to
synthesize polyester [34]. This product has potential in biomedical applications due to its
shape- memory property.
By applying ozonolysis, part of the unsaturated fatty acids can be converted into diacids
since ozone can oxidize the double bond s into carboxylic groups [35]. Published work
includes ozonolysis on oleic acid, petroselinic acid and erucic acid [35]. Considering the
safety issue of ozone usage, a process using peracetic acid and ruthenium catalysts or
H2 O2 and Mo, W, or Re based catalysts has been proposed as an alternative oxidization
method, however, they only allowed diacid molar yields between 50 and 60% [35].
Epoxidized vegetable oils as starting materials will lead to the syntheses of another type
of vegetable-oil-based polymer, notably an epoxy resin. Epoxidation of soybean oil was
carried out in toluene with the presence of an ion exchange resin as the catalyst. It was

8

found that the reaction was first-order with respect to the double bond concentration and
very little amount of side products were produced during the reaction [36]. Epoxidized
vegetable oils including castor, soybean and linseed oils can be polymerized with
utilization of photo- initiators [37]. The research on catalytic epoxidation of methyl
linoleate, using methyltrioxorhenium and pyridine as catalysts in aqueous H2 O2 was also
reported, and it was observed that the epoxidation reaction completed within 4 hours
[38]. Ring-opening polymerization of epoxidized methyl oleate was studied with ioniccoordinative initiators present, and the molecular weight of the polymer could reach to
over 7000 g/mol [39].
Polyolefin with its known high chemical stability and biocompatibility has also been
considered as one of biobased polymers derived from vegetable oil. Similar to epoxy
resin, the target reactive group for polymerization is also the double bond. One method to
synthesize polyolefin is cationical polymerization in a supercritical dioxide medium with
the presence of boron trifluoride diethyl etherate [40], and products produced in this
process can be used as medical lubricants. Another approach that has been developed was
acyclic diene metathesis (ADMET) polymerization of double bonds in soybean oil by
using Grubbs' ruthenium catalyst, which gave a variety of polymeric materials ranging
from sticky oils to rubbers [41]. Moreover, norbornene-functionalized castor oil or
linseed oil could also be used to form thermosets by employing the unique ring-opening
metathesis polymerization (ROMP) pathway [42].
In this project, two types of soybean-oil-based polymers will be studied. Part of the study
is about the production of diester (dimethyl azelate) through ozonolysis, which can be
used as the starting material for polyesters. Another part of this project deals with the

9

manufacture of polyvinyl acetal polymer. Although much work has been done in the four
main types of soybean-oil-based polymers, this polymer does not belong to any of the
types mentioned above. The product will be formed through the reaction between
aldehydes (e.g. hexanal, nonanal and 9-oxo-nonanoate) generated from ozonolysis of
soybean FAMEs and polyvinyl alcohol in an aqueous system in the presence of sulfuric
acid. Although the polyvinyl alcohol used in the lab was petroleum based, it can also be
made from biobased resources as shown in previous research [43], which implies that this
polyvinyl acetal polymer can be made fully biobased.
1.5 Organization of the dissertation
This dissertation consists of 6 chapters. It starts with a general introduction about the
motivation of the project and some basic knowledge related to the subject of the study.
Moreover, the conclusion of the entire work and final considerations for future
advancements in this line of work will be addressed.
Chapter 1 discusses the research motivation and provides a thorough review about
biobased polymers, soybean oil reactions and soybean oil based polymers. It summarizes
the important studies related to biobased polymers using vegetable oil as raw material.
Four main types of polymers including polyurethane, polyester, epoxy resin and
polyolefin are discussed respectively.
Chapter 2 describes the experiments for ozonolysis reaction in both methanol and water
systems through continuous process. In the methanol system, ozonolysis was conducted
with soybean oil based FAMEs with the presence of sodium methoxide as catalyst, and
the consequential products were oxidized further by Oxone to convert aldehydes to

10

esters. In the water system, soybean oil based FAMEs were ozonated without using any
catalyst.

The composition, properties and yield of products generated from the two

reaction systems were examined. Analysis methods of both GC-MS and GC-FID were
used for qualitative and quantitative measurement of ozonolysis products. Since pure
compound samples are not available for all the compounds, in order to calculate the
concentration of some commercially unavailable compounds through GC chromatogram,
the Effective Carbon Number (ECN) method was applied to estimate the response factor.
Chapter 3 covers mass transfer and reaction kinetics for ozonolysis reactions. The
Number of Transfer Units (NTU) approach was used to measure the mass transfer of
ozone in methanol reaction system. Reaction kinetics was investigated in both batch and
continuous processes for the two solvent (methanol and water) systems. In the batch
process in methanol, the impact of temperature on reaction rate was compared for three
cooling conditions – water bath, ice/water bath and dry ice/acetone bath. In continuous
reaction, the product yields under different flow rates for FAMEs and methanol mixtures
were calculated and compared. Oxone treatment was applied to convert aldehydes to
methyl esters and a study on reaction rate between all- in-one load and multiple load
processes were conducted. In order to purify organic products, extraction was conducted
using water and hexane, and the results were compared between the two solvent systems.
For ozonolysis of FAMEs in the water system, temperature and pH change were
investigated in a batch process and the effect of flow rate of FAMEs and water mixture
on product composition and yield was studied in the continuous process.
Chapter 4 focuses on distillation simulation and design of ozonolysis products using
Aspen Plus. It elaborates the details of distillation column design based on consideration
11

of safety, product quality and energy and cost efficiency. Distillation sequence for all the
compounds was firstly determined by a heuristic method. Based on this distillation order,
specific column design was conducted for products generated using ozonolysis in both
water and methanol system. The operation temperature, pressure, column dimensions,
number of stages and input stages were all specified and optimized.
Chapter 5 demonstrates a model for predicting the separation profile of the ozonolysis
products from soybean oil derived FAMEs using wiped film distillation. Wiped film
distillation unlike fractional distillation cannot be simulated directly using existing
software. This means that given certain operation conditions, the separation results (e.g.
distillate rate and composition) cannot be easily calculated or estimated. On the other
hand, given target product purity, separation conditions can be determined by an
empirical method. In this chapter, wiped film distillatio n is modeled in Aspen Plus by
fitting an objective function. A correlation between the pseudo vapor pressure calculated
from the operating temperature in the wiped film separator and pressure in Aspen Flash
module is then examined.
Chapter 6 exhibits the syntheses of polyvinyl acetal polymers using aldehydes produced
through ozonolysis. The three aldehydes, hexanal, nonanal and 9-oxo- nonanoate as the
main products prepared through ozonolysis of FAMEs in water system, react with
polyvinyl alcohol, and form a series of polyvinyl acetal polymers. The thermal properties
of the these polymers were analyzed using TGA and DSC, the molecular weight was
calculated based on the data from GPC and the extent of reaction and polymer structure
was determined by 1 NMR. These characteristics were also compared to a well known

12

similar product in the market, polyvinyl butyral (PVB), to evaluate potential industrial
applications.

13

Chapter 2: Method Implementation for Ozonolysis Product Characterization and Mass
Balance Study
2.1 Introduction
2.1.1 Ozone chemistry
Ozone was first identified as a distinct chemical compound by Christian Friedrich
Schönbein in 1828 [44] and the molecular formula was determined by Soret in 1865 [44].
Ozone (or trioxygen) is an inorganic compound that contains three atoms of oxygen with
the chemical formula O 3 . According to experimental evidence from microwave
spectroscopy, ozone is a bent molecule, with C2v symmetry. The O - O distance is 127.2
pm (1.272 Å) and the O - O - O angle is 116.78° [45]. In high concentration ozone is a
bluish green gas. It has a very strong pungent smell which is noticeable even at very low
level (0.01 μmol/mol) in air [46]. Exposure in more than 0.1 μmol/mol of ozone may
cause headache, burning eyes and irritation to the respiratory passages [47].
The formation of ozone in the stratosphere is a natural photodissociation process (Figure
2.1) in which ultraviolet solar radiation breaks down the chemical bonds of atmospheric
O 2 molecules, and the free radical oxygen atoms combine with O 2 to form ozone.

hv
O 2 (g) 
 O  (g)  O  (g)

 O  (g )  O 2 (g ) 
 O 3 (g)

Figure 2.1 Natural formation of O 3
Traditional ways of producing ozone include 1) corona discharge and 2) ultraviolet light
methods [48, 49]. New generators may use 1) cold plasma or 2) electrolytic method [50].
14

The former method applies pure oxygen as the input source and this input gas is exposed
to plasma created by a dielectric barrier discharge. The molecular oxygen is therefore
split into single atoms and these free atoms recombine in triplets to form ozone. The
maximum concentration of ozone produced with this method is about 5%. The
electrolytic method can achieve a higher purity of 20 to 30% by using water as the source
of ozone production. Current ozone generators differentiate from each other by the design
of the electrodes. For a required production above 20 kg/hour, a gas/water tube heatexchanger will be installed, as ground electrode and tubular high- voltage electrodes will
be assembled on the gas-side [51].
Ozone is not as stable as oxygen, and it tends to decay into diatomic oxygen in a very
short time. This reaction proceeds more rapidly with increased temperature and increased
pressure, so ozone cannot be stored or transported and must be produced on site. Since
ozone is a powerful oxidizing agent, only a few materials can be used for handling or
storage, like stainless steel, titanium, aluminium, glass, polyvinylidene fluoride, etc.
Ozone has a very high oxidizability and reacts with many different types of compounds,
such as metals, nitrogen and carbon compounds, sulfur compounds, alkenes, alkynes, etc.
Because of this, ozone has a wide application in many areas in industry. For example,
ozone is used as disinfector in hospitals and food factories; ozone can also be used as
deodorizer for air and objects and sanitizer for swimming pools and spas; ozone is added
in dish washers to kill yeast, mold and bacteria; ozone is introduced to age rubber
samples and determine the useful life of a batch of rubber; ozone is also applied in
manufacture of chemical products [52].

15

2.1.2 Ozonation of fatty acid group
Biobased polymers have drawn attention of researchers because biobased resources are
widely available, renewable, environmentally friendly and relatively safe to human [53].
Among all the studies, the research on fatty acids derived from vegetable oil is one of the
major topics researched. A considerable amount of research related to the chemical
modification and polymerization of fatty acids on unsaturated bonds has been reported.
Generally, two main strategies can be adopted to convert fatty acids into monomers:
creating new reactive functional groups based on original structure; splitting the fatty acid
chains at the double bonds and generating new molecules. Ozonolysis is applied to follow
the second strategy.
In organic chemistry, ozonation is mainly applied to react with molecules containing
double or triple carbon bonds. During reaction, the carbon chain with unsaturated carbon
bonds will be cleaved by ozone and converted to aldehydes, ketones or peroxidic
derivatives of aldehydes and carboxylic acids. The type and composition of products are
usually determined by the reactant as well as the reaction conditions such as the solvent,
concentration of ozone, workup method or reagent, pH, etc.
The reaction of ozone with unsaturated carbon bonds in organic compounds was first
studied in 1905 [54], following which a 3-step mechanism (Figure 2.2) was proposed by
R. Criegee [55] to explain the ozonolysis reaction of alkenes. According to this
mechanism, ozone reacts with double bond and forms a five- membered-ring compound
called molozonide (primary ozonide). This intermediate compound decomposes to a
“carbonyl oxide” group and a carbonyl compound. The decomposed products are not

16

stable in the system and tend to combine with each other to generate a more stable
compound, similar to the primary ozonide, named ozonide (or secondary ozonide). If this
reaction occurs in methanol with alkaline catalyst, the “carbonyl oxide” group will react
with methanol and produce methyl esters. If this reaction happens in water, the “carbonyl
oxide” group will form acids and aldehydes (or ketones), and the dominant products will
be aldehyde (or ketones).

Figure 2.2 Ozonation mechanisms in methanol and water system
Due of the instability of primary ozonide generated in the intermediate step of the
reaction, ozonation is usually conducted at low temperature (typically around -78 ℃ [55])
to prevent the ozonide from decomposing before the workup process is applied.
However, in this project, the workup process was actually omitted, so the low
temperature condition was not applied in the experiment.

17

When ozone is applied to react with double bonds, many factors including temperature,
solvent and pH value should be well controlled to obtain the ideal products. Among all
the factors, solvent choice can affect the reaction the most. Ozone is a strong oxidant, and
the ozonation reaction usually produces a series of products, e.g. carboxylic acids,
ketones, aldehydes, alcohols, etc. As shown in Figure 2.2, ozone reacts with alkene via
cycloaddition and forms a primary molozonide which decomposes immediately into
aldehyde and carbonyl oxides. In an aprotic solvent, the products formed from
decomposition tend to react with each other to generate a more stable form of ozonide. If
ozonolysis is carried out in the presence of protic solvents such as alcohols, the outcome
products will consist of alkoxy hydroperoxides and/or peroxy hemi-acetals [56]. In
conclusion, solvent will affect the output of ozonolysis in two aspects: it affects the
amount of ozone available for the reaction (because of mass transfer efficiency), and also
exerts an influence on the yield and types of products due to side reactions.
The effect of several solvents such as halogenated hydrocarbons, n-pentane, acetic acid,
ethyl acetate, methanol, ethanol, and water used in ozonation has been studied by
Greenwood et al. [57]. The experiment was carried out under temperature from -42 to 25
℃ in different solvents, and the reaction time lasted from 5 mins to 2 hours. Based on the
standpoint about resistance to attack from ozone, the conclusion from this study was that
water, acetic acid, ethyl chloride, carbon tetrachloride, and monofluorotrichloromethane
were satisfactory solvents for ozonation. In a practical situation, the choice of solvent
should depend on the solubility of the material and the type of workup method applied.
Research on the kinetics of ozonolysis of canola oil in three different solvent systems
(ethyl acetate, alcohol and the mixture) under temperature from 0 to 4 ℃ was conducted
18

by Omonov et al. [56], with hexanal and nonanal as target compounds. The result showed
that the better solvent was the mixture of both aprotic (ethyl acetate) and protic (me thanol
or ethanol) solvents which guaranteed the full solubility of canola oil and the reactivity of
ozonide intermediates, thus provided a higher yield of products.
Besides the solvent, another factor that also plays an important role in ozonation is the
starting material. Some researcher chose vegetable oil as the raw material like Omonov et
al. [56] as described above. De Souza et al. [58] used corn oil to synthesize polyols by
applying epoxidation and ozonolysis and found that epoxidation led to the opening of
double bonds, while ozonolysis promoted the cleavage of double bonds and therefore
reduced the molar mass of the product. The experiment was conducted in ice bath and the
yield of product could reach to as high as 86%. Research on manufacture of 9hydroxynonanoic acid methyl ester via ozonolysis from soybean oil and castor oil has
also been published [59], and this compound could be used for polymer syntheses as a
potential industrial application. Some other publications have focused on the ozonolysis
of FAMEs (fatty acid methyl esters) instead of vegetable oil. For example, it was found
that by treating polyunsaturated fatty esters with ozone malonaldehyde acetals could be
obtained [60]. Moreover, unsaturated FAMEs were also used to produce alcohols [61].
Ozonolysis reactions on a single unsaturated FAME compound like methyl oleate were
also studied and the structure of the products were analyzed [62].
Substantial studies have been presented on ozonolysis of fatty acids and fatty acid esters,
however, no reference was found focusing on ozonation of three unsaturated fatty esters
derived from soybean oil as a mixture, either in methanol or in water system. In addition,

19

ozonolysis conducted in continuous process, which will be evaluated in this project, was
not mentioned in any previous work either.
2.1.3 Ozonolysis of soybean-oil-based FAMEs
The starting material used in this project is FAMEs derived from soybean oil, which
mainly consists of five methyl esters, which are methyl palmitate, methyl stearate, methyl
oleate, methyl linoleate and methyl linolenate. The former two esters are saturated and
the later three esters contain 1, 2, and 3 double bonds, respectively. The total amount of
the five esters takes up 97 wt% of the FAMEs, where 14 wt% are saturated and 83wt%
are unsaturated esters. During ozonolysis, only the three unsaturated esters participate in
the reaction and the saturated ester like methyl palmitate and methyl stearate remain
intact.
The composition of FAMEs is determined by the source of vegetable oil and even if the
FAMEs are made from the same type of oil, products from different batches can be
different. To keep the composition of reactant consistent, all the soybean-oil-based
FAMEs used in this project were acquired from the same container.
The efficiency of ozonation on FAMEs highly depends on solvent, therefore choosing a
proper solvent is the most critical step before starting the project. Some factors were
considered while choosing the solvent, for example, the target products, the difficulty of
separating the product and recycling the solvent, the cost of the solvent and the safety of
the reaction. Based on all the considerations, methanol and water were selected for the
following reasons: firstly, in these two solvents, the reaction initiates easily and proceeds
fast even at room temperature, which implies the cost for the cooling system will
20

relatively low; secondly, the two solvents are cheaper than most other solvents; thirdly,
methanol is volatile and therefore, solvent recycling will not be too difficult; fourthly, the
compositions of output products are not very complicated, which means not many
byproducts are generated, and this gives advantage to analysis and separation of products;
and lastly, water is not flammable and therefore is relatively safe to operate.
O
O

O
O

O

Nonanal
O3

CH3OH
Methyl Oleate

Methyl nonanoate

O

O

O

O

O

O

Methyl 9-oxononanoate

O

Dimethyl azelate
O

O
O
O

Methyl linoleate

CH3OH

O

Methyl linolenate

Methyl hexanoate

O
O

O
O

O
O

O

Methyl 9-oxononanoate

Figure 2.3 Ozonolysis reaction in methanol system

21

O

Dimethyl azelate

O
O

O

O

Methyl 9-oxononanoate

O3

O

Hexanal

O3
CH3OH

O

O
O

Dimethyl azelate

O
O

O
O

HO

Nonanal
O3
H2O

Methyl Oleate

Nonanoic acid

O

O

O

O

O

HO

O

Methyl 9-oxononanoate Monomethyl azelate
O
O
O
O

Methyl linoleate

H2O

O

Methyl linolenate

Hexanoic acid

O
O

O
O

O

HO

O

Methyl 9-oxononanoate Monomethyl azelate

O3

O

Hexanal

O3
H2O

HO

O
O

O
O

HO

O
O

Methyl 9-oxononanoate Monomethyl azelate

Figure 2.4 Ozonolysis reaction in water system
Ozone reacts with organic compounds by breaking down double bonds and generates
formyl or carboxyl groups. The ratio of the two types of products depends on the specific
reaction conditions. In methanol system, the prod ucts contain aldehydes and esters, which
is because the formed carboxyl groups will react with methanol immediately and generate
methyl esters. The main products are aldehydes. As shown in Figure 2.3, from the three
unsaturated esters, three aldehydes are produced. Ozonolysis of methyl oleate yields
nonanal and methyl nonanoate, while methyl linoleate yields hexanal and methyl
hexanoate. Since half of the structure is the same for all the three esters, after being split,
they share the same two products – methyl 9-oxononanoate and dimethyl ester. The
ozonolysis reaction products in water, as shown in Figure 2.4 are very similar to that in
methanol. The differences are that acids are formed instead esters and the yields of
22

aldehydes are much higher; also, no catalyst is used in water system while sodium
methoxide is added as catalyst in methanol system.
2.1.4 Analysis method for ozonolysis products
The main subject of this chapter is to analyze the products prepared from ozonolysis in
two solvents conducted in continuous process. The products will be firstly identified
using gas chromatography-mass spectroscopy (GC-MS) before quantitative analysis is
performed using gas chromatography, due to the complexity of ozonolysis products and
the uncertainty of the ozonation mechanism.
Gas chromatography with flame ionization detection (GC-FID) is a well known
characterization method for volatile (possessing an appreciable volatility below 350-400
°C) organic compounds. In gas chromatography, the separation unit is a glass, metal or
quartz column which contains the stationary phase and mobile phase. The stationary
phase is a microscopic layer of polymer on an inert solid support, and the mobile phase is
a carrier gas such as helium or nitrogen. The gaseous sample molecules enter into column
in mobile phase and interact with the stationary phase. Because the interaction behavior
for different compounds is different, each compound will elute at a different time, known
as the retention time. Comparison of retention times enables GC to do analytical work.
The technique of GC-MS as implied by the name is a combination for both GC and MS
analytical methods which is usually used to analyze unknown mixtures of chemicals. The
molecules are passed through and separated by the column by coming out at different
retention times, after this the mass spectrometer breaks each molecule into ionized
fragments and detects the fragments using the mass-to-charge ratio.
23

Since all the compounds in FAMEs and final products are relatively volatile, GC-FID can
be used as primary analysis tool. In GC-FID analysis, the concentration of a compound in
solution is linearly correlated with the area of the corresponding peak in chromatogram.
This correlation function, also known as calibration curve, is prepared by plotting data of
peak area against compound concentration from standard samples ( ideally made from
pure compounds). The calculated slope of the line for each compound is the response
factor, and for different compounds, the value of the factor is usually different. Once the
response factor is known, the concentration can be calculated by dividing the peak area
obtained from GC chromatogram by the response factor.
There is a limitation of GC analysis using the calibration curve method, because if the
standard samples for certain compounds are not available, the calibration curve cannot be
generated, and thus the concentration cannot be calculated. However, according to
Sternberg et al. [63], the response factor for GC-FID can be examined using the effective
carbon number (ECN) approach, which does not require standard samples for all
compounds in the mixture. In this project, we will use this method to quantify the
components for which the standard samples are not obtainable.
Another limitation for GC-FID is that samples in aqueous solution cannot be properly
analyzed by it. In fact, water should be avoided from samples, because water interacts
with stationary phase and may cause problems like high baseline noise or column bleed.
These problems reduce the analysis sensitivity and may decrease lifetime of the column.
To prevent these problems from happening, samples containing water should be extracted
or dried before being injected in the GC.

24

2.2 Experiment
2.2.1 Materials
Soybean oil FAMEs were bought from Zeelend Farm Services; methanol (99.9%),
hexane (99.9%), standards for GC analysis including hexanal (99%), nonanal (98%),
methyl hexanoate (99%), methyl nonanoate (98), dimethyl azelate (80%), methyl
palmitate (99%), methyl stearate (99%), methyl oleate (99%), methyl linoleate (99%) and
methyl linolenate (99%) were all purchased from Sigma-Aldrich (St. Louis, MO).
2.2.2 Continuous reaction
Ozone was generated by a CFS-3A ozone generator from Ozonia North America LLC.
Oxygen and Ozone gas mixture flow rate was 3 L/min, with weight fraction of ozone
10%. A plug flow reactor made of steel and sealed in a PVC jacket was used. The space
between the jacket and the external wall of reactor was occupied with cooling water to
guarantee safety during exothermic reactions between ozone and FAMEs. Both gas and
liquid feeds passed injected into the reactor through two separated lines. The bottom of
the reactor was equipped with a sparger to supply the ozone/oxygen gas bubbles and the
internal pathway of the reactor was packed with static mixers to increase gas- liquid mass
transfer during reaction. The total height of the reactor was 131 cm, the external diameter
of the jacket was 12.6 cm and the internal diameter of the reactor 2.7 cm. The
ozone/oxygen gas and the FAMEs solution were fed into the column via separated feed
lines passing through the cooling jacket to maintain a lower temperature, and then into
the reactor from the bottom inlet concurrently.

25

Before entering the reactor, the gas feed was first passed through a Mini-Hicon ozone
analyzer by which weight fraction (usually 9-13%), pressure (15-24 psi), and gas
temperature (36-38 ℃) were monitored. The flow rate (L/min) was measured by a flow
meter (model: FM-11-10) designed by Ozone Solutions Inc.

Figure 2.5 Reaction process and equipments for ozonolysis. A: air cylinder; B: ozonator;
C: ozone analyzer; D: plug flow reactor; E: batch reactor; F: flow meter; G: dry ice trap;
H: potassium iodide trap; c: cooling water; g: gas; m: liquid material.
For reactions in the methanol system, 500 g of FAMEs, 1000 g o f methanol and 0.25
wt% (of FAMEs) sodium methoxide were added together to be supplied to the plug flow
reactor by a peristaltic pump with a flow rate of 10 ml/min. For reactions in the water
system, the ratio between FAMEs and water was the same as the methanol system
26

(excluding the catalyst) and the liquid mixture flow rate was also 10 ml/min. Products
were collected after 15 min counting from the first drop of liquid coming out the reactor
when it reached steady state.
2.2.3 Oxone treatment
As shown in the reaction mechanism (Figure 2.3), ozonolysis products formed in
methanol system consist of both aldehydes and methyl esters, where aldehydes are
dominant products. The target products in this process are methyl esters, thus a further
oxidation step is needed to convert the aldehydes into esters. The oxidant chosen to
accomplish the goal is Oxone. Oxone is a trade name for the triple potassium salt
Potassium peroxymonosulfate (2KHSO 5 •KHSO 4•K2 SO4 ) produced by DuPont. Figure
2.6 shows that the formyl group is oxidized to carboxyl group by combining one oxygen
atom which originally connected to sulfur in Oxone. Due to the generation of KHSO 4 ,
H2 SO 4 and water as byproducts during the reaction, the pH value is usually reduced to 23 after the reaction is complete.
O

O
2H+

O

S

O

O

H

O

S

O

+

H

2e
O

O

(R 2)R 1

(R2)R 1
Oxone

O

O
CH 3OH
H 3CO

H

Figure 2.6 Oxone oxidization reaction mechanisms.

27

H 2O

The reasons for choosing Oxone as the oxidant are as follows: firstly, unlike other water
soluble oxidants (e.g. hydrogen peroxide), Oxone is distributed in the solution as solid
suspension, due to the fine particle size, it contacts with organic compounds better than
liquid- liquid system; secondly, Oxone is relatively cheap compared to other strong
reactants; thirdly, the separation of final products is simple – the main byproduct is
potassium salt which precipitates to the bottom of the vessel, and can be filtered out
easily; trace of dissolved salt and sulfuric acid can be further removed by extraction of
the products.
Oxone was added to the sample immediately after ozonation, with amount of 50% with
respect to the mass of FAMEs. At room temperature, the reaction was maintained for 72
hours under constant stirring.
2.2.4 GC analysis
To quantify the composition of reactant material as well as the products, GC analysis was
conducted in a GC-2010 Plus gas chromatograph made by Shimadzu. This machine was
equipped with a Shimadzu SHRXI-5MS capillary column (15m×0.25mm×0.25μm, 60℃~330/350℃) and an FID detector. Helium was used as carrier and makeup gas at a
flow rate of 30 mL/min. H2 and air were maintained at 40 mL/min and 400 ml/min
respectively. The injector and detector were set up at 250 ℃, and the column temperature
started at 50 ℃ holding for 2 mins and then increased at the rate of 10 ℃/min to 250 ℃
and then held for 5 mins. The injection volume of each sample was 1.0 μL with a split
ratio of 70. This method was applied to the analysis of FAMEs, the products after
ozonolysis and the mixture after Oxone treatment.
28

2.2.5 GC-MS analysis
A JEOL AX-505H double- focusing mass spectrometer (JEOL, USA) was connected to a
Hewlett-Packard 5890J gas chromatograph used to detect the ionized molecules of
selected samples. A DB-WAX (the stationary phase is polyethylene glycol) capillary
polar column (30m×0.25 mm×0.20 μm) from Restek Corporation (Bellefonte, PA) was
installed to separate the aldehydes, short-chain esters and fatty esters compounds.
Column temperature was started from 50 °C holding for 2 mins, and then increased with
a rate of 10 °C/min to a final 250 °C, and it was kept for another 2 mins. An ionization
voltage of 70 eV over the mass range of 45-500 amu was used to break the molecules
into ionized fragments. Helium was chosen as carrier gas and the injection volume of
each sample was 1.0 μL with a split ratio of 200. The injector temperature was 250 °C,
with interface and ion source temperature maintained at 240 ℃ and 200 °C, respectively.
A NIST/EPA/NIH Mass Spectral Library databank was used to search and identify
compounds.
2.3 Results and Discussion
2.3.1 Composition of reactants and products
Compositions of FAMEs produced from different vegetable oils can vary significantly. In
this project the FAMEs used were prepared from soybean oil. To eliminate the
experimental error caused by the inconsistence of FAMEs content, all the FAMEs
samples were prepared from the same batch provided by Zeeland Inc. and analyzed by
GC in triplicates.

29

uV(x100,000)
8.0
7.0
6.0

4

5.0
4.0

1

3

3.0
2.0

5

2

1.0
0.0
5.0

10.0

15.0

20.0

min

Figure 2.7 GC chromatograph for soybean oil FAMEs. 1: Methyl palmitate (C16:0); 2:
Methyl Stearate (C18:0); 3: Methyl oleate (C18:1); 4: Methyl linoleate (C18:2); 5:
Methyl linolenate (C18:3).
From Figure 2.7, the five main compounds in soybean FAMEs can be easily observed,
with methyl palmitate (C16:0) as the most volatile and methyl linolenate (C18:3) as the
least volatile. In ozonolysis reaction, only the three unsaturated methyl esters react with
ozone. According to Table 2.1, the three components have mass fraction of 22.85%,
54.66% and 5.89% respectively. The saturated esters C16:0 and C18:0 will remain the
same before and after reaction and thus act as perfect internal standards for yield
calculations. Other components take up 3.36wt% of the total FAME and consist of minor
fatty acid methyl esters and some other types of compounds [64].

30

Table 2.1 Compositions of FAMEs

Component

Peak No.

wt%

mol%*

C16:0

1

9.59

10.35

C18:0

2

3.66

3.58

C18:1

3

22.85

22.52

C18:2

4

54.66

54.24

C18:3

5

5.89

5.88

Others

--

3.36

3.43

*Molecular mass of soybean FAMEs was assumed as 292.2 g/mol

Ozone breaks olefinic bonds while generating formyl group s and carbonyl groups. The
reaction products are mainly dependent on the position of the double bonds in the
reactants. Different solvent can also lead to different compositions of prod ucts. In water
system, the main products were aldehydes and trace amount of acids, while in methanol
system both aldehydes and a little amount of methyl esters were formed. According to the
reaction shown in Figure 2.3 and Figure 2.4, there is one main common product derived
from all the three unsaturated esters, i.e. dimethyl azelate in methanol system and methyl
9-oxononanoate in water system, because all of the three compounds form a C9 chain
after being broken by ozone. All the mass spectra were identified and compared with the
NIST databank. The mass spectra results showed very high (mostly higher than 90%)
reliability (Table 2.2) for most of the products detected after ozonolysis reaction in both

31

ethanol and water system. Some small compounds were not detected either due to its high
volatility or low quantity (like propanal and methyl propanoate).
Table 2.2 Identification of ozonolysis products formed in ethanol and water system, with
respective mass spectra reliability according to NIST databank.

No.

Ozonolysis Product

Reactant resource

Molecular formula

Reliability (%)
(GC-MS)

1

Propanal

C18:3

C3 H6O

N/A*

2

Methyl Propanoate

C18:3

C4 H8O2

N/A*

3

Dimethyl Malonate

C18:3

C5 H8O4

91

4

Hexanal

C18:2

C6 H12 O

94

5

Methyl 3,3dimethoxypropionate

C18:3

C6 H12 O4

78

6

Methyl Hexanoate

C18:2

C7 H14 O2

91

7

Nonanal

C18:1

C9 H18 O

97

8

Methyl Nonanoate

C18:1

C10 H20 O2

94

9

Methyl 9-oxononanoate

C18:1, C18:2,
C18:3

C10 H18 O3

91

10

Dimethyl Azelate

C18:1, C18:2,
C18:3

C11 H20 O4

91

11

Methyl Palmitate

Unreacted

C17 H34 O2

99

12

Methyl Stearate

Unreacted

C19 H38 O2

99

* Not observed in GC chromatogram

32

2.3.2 Effective carbon number method for quantitative GC-FID analysis
The response factor for GC analyses using FID is crucial for calculating analyte
concentration. Usually, absolute response factor (Equation 2.1) is acquired through the
calibration curve made from a series of standard solutions of known concentration;
however, if pure sample for certain compound is not available, a relative response factor
can provide concentration estimations (Equation 2.2 and Equation 2.3). One of the
convenient methods of calculating relative response factor is using effective carbon
number (ECN).
RF  Acomp / Ccomp

RF ' 

RF ' 

AcompC ref
Aref Ccomp

ECN comp MWref
ECN ref MWcomp

33

(Equation 2.1)

(Equation 2.2)

(Equation 2.3)

Table 2.3 Contributions to the Effective Carbon Number

Atom

Type

ECN contribution

C

Aliphatic

1

C

Aromatic

1

C

Olefinic

0.95

C

Acetylenic

1.3

C

Carbonyl

0

C

Carboxyl

0

C

Nitrile

0.3

O

Ether

-1

O

Primary alcohol

-0.5

O

Secondary alcohol

-0.75

O

Tertiary alcohol

-0.25

N

Amine

As 0 in alcohols

Cl

2+-Aliphatic

-0.12 per chlorine

Cl

On olefinic C

0.05

The concept of ECN was originally published to explain flame ionization responses
obtained from the analysis of isomeric or homologous series of organic compounds [65].
As displayed in Table 2.3 [63], some atoms appeared in different groups will give
different ECN contribution. For example, a carbon in acetylenic group has the highest
ECN contribution of 1.3, while an oxygen atom in ether will give an ECN contribution as
low as -1. Based on Equation 2.3, the relative response factor can be calculated by known
ECN for both new compound and reference compound.

34

By applying the data in Table 2.3, the ECN values for all the main compounds in this
project were calculated and shown in Table 2.4 and corresponding ECN/MW were given
in the next column. With reference to Equation 2.3, given a reference compound, the
relative response factor for a new compound is calculated by dividing the ECN/MW
value of the new compound by the ECN/MW value of reference compound. To evaluate
the accuracy of this method, the relative response factor from experimental results were
compared with the theoretical values in Table 2.5. Among the 6 compounds (hexanal,
methyl hexanoate, nonanal, methyl nonanoate, dimethyl azelate and methyl palmitate)
chosen for comparison, the biggest error corresponded to methyl hexanoate which was
12.9% and the lowest error was associated to methyl palmitate with the value of 1.02%.

35

Table 2.4 Calculated Effective Carbon Numbers for main compounds

Compound

Molecular Formula

MW
(g/mol)

ECN

ECN/MW

Methanol

CH4 O

32.04

0.52*

0.01623

Hexanal

CH3 (CH2 )4CHO

100.16

5

0.04992

Hexanoic acid

CH3 (CH2 )4COOH

116.16

5

0.04304

Methyl hexanoate

CH3 (CH2 )4COOCH3

130.2

5.5

0.04224

Nonanal

CH3 (CH2 )7CHO

142.24

8

0.05624

Nonanoic acid

CH3 (CH2 )7COOH

158.23

8

0.05056

Methyl 3,3-dimethoxypropionate

(CH3 O)2 CHCH2CO2CH3

148.16

2.5

0.01687

Methyl nonanoate

CH3 (CH2 )7COOCH3

172.3

8.5

0.04933

Dimethyl Malonate

CH3 OOCCH2 COOCH3

132.11

2

0.01514

Methyl 9-oxononanoate

CH3 OOC(CH2 )7CHO

186.25

7.5

0.04027

Monomethyl azelate

CH3 OOC(CH2 )7COOH

202.25

7.5

0.03708

Dimethyl azelate

CH3 OOC(CH2 )7COOCH3

216.3

8

0.03699

Methyl palmitate

CH3 (CH2 )14 COOCH3

270.5

15.5

0.05730

Undecanedioic acid,1-methyl
ester

CH3 OOC(CH2 )9COOH

230.3

9.5

0.04125

CH3 (CH2 )16 COOCH3

298.5

17.5

0.05863

Methyl stearate
* According to [66]

With the application of ECN method, concentration for all the compounds that were
indicated in GC chromatogram could be calculated. As a result, the yields for the main
products could be obtained, taking methyl stearate as the internal standard to estimate the
original amount of FAMEs reacted.

36

Table 2.5 Comparison between experimentally obtained ECN and calculated ECN

Compound

Relative factor
(experiment)

Relative factor
(calculated)

Error (a) (%)

Hexanal

0.7834

0.8515

+8.69

Hexanoic acid (b)

--

0.7342

--

Methyl hexanoate

0.8273

0.7205

-12.90

Nonanal

0.8887

0.9593

+7.95

Nonanoic acid (b)

--

0.8623

--

--

0.2878

--

0.8983

0.8415

-6.33

--

0.2582

--

--

0.6869

--

--

0.6324

--

Dimethyl azelate

0.6906

0.6309

-8.64

Methyl palmitate

0.9675

0.9774

+1.02

Undecanedioic acid,1-methyl ester (b)

--

0.7036

--

Methyl stearate

1

1

--

Methyl 3,3-dimethoxypropionate

(b)

Methyl nonanoate
Dimethyl Malonate

(b)

Methyl 9-oxononanoate (b)
Monomethyl azelate

(b)

(a) Obtained by dividing absolute value of difference between experimental relative factor and
calculated relative factor by experimental relative factor;
(b) Commercial standard sample is not available

2.3.3 Ozonolysis in methanol system
The profile for ozonolysis products in methanol system is shown in Figure 2.8. As
estimated by the height of the peaks, the main outputs are aldehydes with only very little

37

amount of esters formed (Table 2.6). The sum of the molar yields of ester and aldehydes
derived from ozonolysis of methyl oleate (C18:1) show a relatively good molar balance
closure, indicating that approximately 49% of the double bonds were cleaved during
ozonolysis. The selectivity of this reaction was more favorable toward aldehyde
formation than ester formation in both sides of the double bond. Similarly, a very small
molar yield of methyl hexanoate ester (3.5%) was also achieved by ozonolysis of methyl
linoleate, compared to the aldehyde product hexanal (32.74%). The C3 product of this
reaction is highly volatile and could not be recovered for this study.
Even though the molar yields are lower than 50 % for the ozonolysis products, there was
no evidence of the presence of any unreacted unsaturated FAMEs, suggesting the
presence of ozonides or other derivatives that could not be detected by the GC method
used in this study. This implies that the fresh product solution after ozonolysis should be
taken care of with caution as it might contain high amount of unstable ozonides.

38

uV(x1,000,000)
1.50

1.25

E

1.00

G
0.75

A
C

0.50

0.25

B

F

H

D

0.00
5.0

10.0

15.0

20.0

min

Figure 2.8 Chromatogram for products from ozonolysis in methanol system. A: Hexanal;
B: Methyl hexanoate; C: Nonanal; D: Methyl nonanoate; E: Methyl 9-oxononanoate; F:
Dimethyl azelate; G: Methyl palmitate; H: Methyl stearate.
Table 2.6 Yield for products from ozonolysis in methyl system

Compound

Yield (%)

Hexanal

32.74

Methyl hexanoate

3.50

Nonanal

45.44

Methyl nonanoate

3.59

Methyl 9-oxononanoate

39.53

Dimethyl azelate

10.13

Methyl palmitate

Unreacted

Methyl stearate

Unreacted

39

uV(x1,000,000)
3.0

2.5

F
2.0

1.5

B
D

1.0

0.5

G
H

A

E

C

0.0
0.0

5.0

10.0

15.0

20.0

min

Figure 2.9 Chromatogram for products after oxone treatment. A: Hexanal; B: Methyl
hexanoate; C: Nonanal; D: Methyl nonanoate; E: Methyl 9-oxononanoate; F: Dimethyl
azelate; G: Methyl palmitate; H: Methyl stearate.
In order to convert the aldehydes to methyl esters, Oxone was added to the solution
immediately after ozonolysis. After 72 hours of reaction under constant stirring, the main
products changed from aldehydes to methyl esters as shown in Figure 2.9. The yield in
Table 2.7 also indicated that most of aldehydes have been converted to esters. For
example, the yield of Methyl 9-oxononanoate was only 4.39% in contrast with 72.38%
for the yield of dimethyl azelate after Oxone workup. Some acids were also detected as
byproducts, and this may be due to the existence small amounts of water generated from
Oxone oxidization according to Figure 2.6. The summation of yield for compounds
derived from the same reactant is slightly smaller than 100%. This may indicate that
some intermediate products (e.g. ozonides) didn’t decompose completely and could not

40

be detected by GC or could also be partially attributed to uncertainties in the
quantification method, notably ECN.
Table 2.7 Yield for products after Oxone treatment

Compound

Yield (%)

Hexanal

5.40

Hexanoic acid

7.32

Methyl hexanoate

65.12

Nonanal

7.61

Nonanoic acid

6.93

Methyl nonanoate

70.12

Methyl 9-oxononanoate

4.39

Monomethyl azelate

8.77

Dimethyl azelate

72.38

Methyl palmitate

Unreacted

Methyl stearate

Unreacted

2.3.4 Ozonolysis in water system
Reaction in water system shows a significantly different profile in terms of the types of
products compared to the methanol system, as displayed by the GC chromatogram in
Figure 2.10. Firstly, the peaks are clearer and not many small peaks are shown, indicating
that there is less formation of byproducts. Secondly, the peaks are “taller” compared to
the peaks for the same compounds in methanol system, using methyl stearate peak as the
reference. This can be more obviously seen in Table 2.8. The yields for the three

41

aldehydes are significantly higher. The byproducts are also different from those in
methanol system after Oxone treatment, as only acids were generated instead of esters.
This result was expected, because there was no alcohol in the solvent to promote
esterification.
uV(x1,000,000)
1.50

C

1.25

A
1.00

0.75

B

D

0.50

E

0.25

0.00
5.0

10.0

15.0

20.0

25.0

min

Figure 2.10 Chromatogram for products of ozonolysis in water system. A: Hexanal; B:
Nonanal; C: Methyl 9-oxononanoate; D: Methyl palmitate; E: Methyl stearate.
Another clear difference between the water system and methanol system is that the
summation of the yield for products derived from the same reactant is much higher with
respect to the products from ozonolysis in methanol before Oxone treatment. This
indicates that water system is more effective in completing the cleavage of the double
bonds, quickly decomposing ozonides (or any other intermediate compounds) and
therefore it can help reduce the potential hazard during reaction. This factor is extremely
important, especially when designing processes for industrial applications.

42

uV(x100,000)
2.00
1.75
1.50
1.25
1.00
0.75

A
A

0.50
0.25

C
A

B
A

0.00
5.0

10.0

15.0

20.0

min

Figure 2.11 Chromatogram for acid products of ozonolysis in water system. A: Hexanoic
acid; B: Nonanoic acid; C: Monomethyl azelate
The peaks for acids cannot be seen from Figure 2.10, however, by enlarging the
chromatogram, the three broad peaks for hexanoic acid, nonanoic acid and monomethyl
azelate can be easily indentified (Figure 2.11). The yield of these acid byproducts can be
highly affected by the retention time of the reaction, which means, more acid tends to be
generated if the time for reactants contact with ozone is increased. A trade-off between
the conversion of the reactants and the generation of byproducts should be made to
optimize the reaction for achieving the highest possible yields of the desired compounds.

43

Table 2.8 Yield for products from ozonolysis in water system

Compound

Yield (%)

Hexanal

62.14

Hexanoic acid

8.34

Nonanal

70.11

Nonanoic acid

7.85

Methyl 9-oxononanoate

66.53

Monomethyl azelate

9.89

Methyl palmitate

Unreacted

Methyl stearate

Unreacted

The overall mass yields of main products from ozonolysis in methanol (after Oxone
treatment) and in water were compared in Table 2.9. In terms of mass, the aldehyde
products obtained from water system were about 20% to 30% less than the corresponding
methyl ester products from methanol system, this was due to 1) the molecular weights of
aldehydes are lower than corresponding methyl esters, 2) the molar yield of aldehydes
were also lower than methyl esters derived from the same unsaturated FAMEs. For
example, the molar yield of hexanal was 62.14% and methyl 9-oxononanoate was
66.53%; while the molar yield of methyl hexanoate and dimethyl azelate were 65.12%
and 72.38% respectively. One reason for this may be that in water system, since the
reaction happened in two phases, some aldehyde products may have dissolved in water
phase and therefore were lost. Another reason might be that more acids were generated
and also dissolved in water phase.

44

Table 2.9 Mass yield of products from ozonolysis in two systems

Methanol system

Water system

Product

Mass yield
(Kg/100 Kg
FAMEs)

Product

Mass yield
(Kg/100 Kg
FAMEs)

Methyl hexanoate

15.74

Hexanal

11.55

Methyl nonanoate

9.31

Nonanal

7.69

Dimethyl azelate

44.28

Methyl 9-oxononanoate

35.04

Methyl palmitate

9.58

Methyl palmitate

9.58

Methyl stearate

3.66

Methyl stearate

3.66

2.4 Conclusions
The chapter reviewed the background for ozone chemistry, ozonolysis on fatty acid
groups and ozonolysis conducted on soybean-oil FAMEs. Analytical method GC-FID
and GC-MS were introduced to determine the composition of soybean-oil FAMEs and
the respective products of ozonation in methanol and water system. The effective carbon
number (ECN) method, as an estimation for compounds that do not have commercial
standards available, was proposed and implemented. The good reliability of this method
was proved by comparing the calculated relative response factors with known
experimental data.
Ozonolysis were carried out in both methanol and water system and, for each system, a
continuous process was applied. The GC-MS results showed that the products given by
ozonolysis in methanol are highly consistent with the anticipated outputs derived based
on the reaction mechanism. The GC-FID analysis indicated that the conversion of the

45

three unsaturated esters in FAMEs was 100% in all the reactions. The yields for the main
compounds in each process were also calculated. The products obtained from ozonolysis
in methanol after Oxone treatment were methyl esters with yields between 65% and 73%.
The products formed from ozonolysis in water were mainly aldehydes and the yields fell
between 62% and 71%.
On average, the unknown compounds are around 10% of the products for both of the
reactions in two systems. The fact that the mass balance did not close for the ozonolysis
reactions performed in this study, implies that undetected ozonides formed during
ozonolysis in both systems may not be completely decomposed to product. Also, this
observation could also be partially attributed to the uncertainties in the GC quantification
method by ECN.

46

Chapter 3: Mass Transfer and Reaction Kinetics Study for Ozonation of FAMEs
3.1 Introduction
In the previous chapter we mainly focused on identifying the products of ozonolysis of
soybean-oil FAMEs. In this chapter, we will study the mass transfer and reaction kinetics
parameters that govern this reaction, as well as the impact of processing conditions on its
efficiency.
The ozonolysis of FAMEs conducted in both methanol and water are heterogeneous
reactions. A heterogeneous reaction is one that takes place between two or more distinct
states of matter. In the case of this study, the methanol reaction system contains a liquid
and a gaseous phase, and the water reaction system consists of two immiscible liquid
phases (aqueous and organic) and a gaseous phase. One of the key characteristics of a
heterogeneous reaction is that it can only take place where the surfaces of the different
states of matter are in contact. Because of this property, the rate of heterogeneous
reactions is usually controlled by two factors: the mass transfer of one matter going
through the other and the reaction kinetics. In such circumstances, either factor can be the
limiting step of reaction.
Mass transfer of ozone in aqueous system has been extensively studied due to the wide
application of ozone in wastewater treatment [67]. In 1970, it was found that the mass
transfer of ozone was controlled within a liquid film closely adjacent to the gas-liquid
interface, and therefore the overall mass transfer coefficient could be approximated to the
local liquid mass transfer coefficient [68]. Furthermore, the liquid-side overall mass
transfer coefficient (k La) was measured in a contactor equipped with a gas sparger [69]

47

and a mathematical model related to the gas flow rate was developed. Similar mass
transfer studies were also performed for drinking water treatment [70, 71]. Correlations
between k La values and the superficial gas velocity for the design and operation of fine
bubble ozone contactors were established [72] and supported [73, 74]. These correlations
combined with ozone decay kinetics have also been incorporated into various
hydrodynamic models to describe ozonation processes [75, 76]. Additionally, it was
found that reactions of ozonolysis may accelerate the mass transfer of ozone from gas
phase into liquid phase [68]. To explain this phenomenon, two general kinetic
mechanisms were proposed including 1) slow kinetic regime and 2) fast kinetic regime,
depending on the relative rates of ozone physical absorption to ozone chemical reactions.
It was stated that the slow kinetic regimes occur when the ozonolysis reactions are slower
and the reaction only reduced the concentration of dissolved ozone in the bulk liquid. For
higher rate of reactions, the mass transfer of ozone may occur in the fast kinetic regime.
When this happens, dissolved ozone is completely depleted within the liquid film
adjacent to the gas- liquid interface. The apparent rate of ozone mass transfer may even
exceed the maximum rate of gas- liquid mass transfer of ozone. An enhancement factor
“E” was defined as the actual rate of mass transfer with ozone reactions divided by the
maximum rate of physical absorption without any reaction [77]. To demonstrate the
enhancement of the presence of chemical reactions on ozone gas- liquid mass transfer,
three types of water samples, including deionized water, tap water and pulp mill effluents
were investigated by Zhou et al. [67].
In previous reports, the mass transfer of ozone in aqueous solutions has been the focus of
theoretical and practical interest, however this interest is not observed for ozonolysis in
48

organic solvents. Despite the solubility of ozone in water and other organic solvents was
studied [78, 79], no previous work has been reported about solubility of ozone in
methanol.
Besides mass transfer, reaction kinetics is also an important factor in heterogeneous
systems. However, reaction kinetics of ozonolysis on fatty acids esters has not been
extensively studied in the literature compared to the large amounts of reports on ozone
mass transfer. While most researchers were focusing on the analysis of products under
different reaction conditions [80, 81], some general examinations on ozonolysis kinetics
of fatty acid derivatives were reported without calculating the reaction rate parameters
[56]. One of the few thorough reports in this field can be found in a manuscript about
aerosols, where ozonolysis of methyl oleate monolayers at the air-water interface was
carried out and a second order reaction model was established, with a reaction rate
parameter of (5.7±0.9) × 10-10 cm2 molecule -1 s-1 [82].
In this project we applied the theory of number of transfer units (NTU) into mass transfer
study of ozone in methanol and water. This theory is usually used for gas-liquid
absorption column mass transfer calculation. By applying this model, the reactor system
is simplified and the number of parameters related to the mass transfer coefficient
equation is also reduced. The limitation of this model is that the mass transfer coefficient
obtained from this study is applicable for the specific reactor in use. Also, we only
focused on the ozone mass transfer in a pure solvent without considering the reaction
kinetics, assuming mass transfer is the limiting step of reaction as an approximation for
the ozonolysis model. The goal of the study is to evaluate the performance of FAME

49

ozonolysis in methanol and provide some preliminary data for reactor design which may
be useful for scale-up production in the future, given a similar reaction system.
The apparent reaction kinetics for ozonolysis in both methanol and water solvent systems
was also examined, which included the combined effect of mass transfer and reaction
kinetics. This part of the study focused on ozonolysis in batch and continuous reactions,
which were conducted for both solvent systems. The effect of temperature was studied in
batch reactions with methanol and water as solvents, while the effect of pH was also
evaluated for the aqueous system. For the continuous reaction, the impact of flow rate of
reactants on the reaction rate was determined for both solvents.
Oxone treatment after ozonolysis in methanol was carried out using batch and fed-batch
strategies to evaluate their impact on the oxidation of aldehydes formed during
ozonolysis in methanol. Optimal reaction conditions determined by the overall results of
this study for both solvent systems will be recommended.
3.2 Experiment
3.2.1 Ozone measurement
The main equipment used for ozone concentration measurement was a Unico 2800 UVvis spectrophotometer. Direct measurement method was applied to determine the
concentration of ozone in solvent (water or methanol), in which the absorbance value
under ultra- violet light at 258 nm wave length was measured and converted to
concentration by using an extinction coefficient of 3,000 M -1 cm-1 [83]. To maintain the
linear correlation between the absorbance and concentration, the original solution was

50

diluted 50 times in order to achieve absorbance values between 0 and 1.0. In each
measurement, the same blank solvent was used as the control sample.
Ozone concentration in the gaseous phase was measured with two methods. The simpler
method was by direct analysis using a Mini-Hicon ozone analyzer. However, the
drawback of this instrument is that it is sensitive to other chemical vapors and therefore,
it is not proper for accurate outlet gas measurement. The secondary method used was the
modified indigo method. Indigo solution was prepared based on a standard published in
1981 [84]. The indigo reagent (I) could be used in this study because the ozone
concentration in the experiments was around 5-10 wt%. The measurement was performed
by adding 20 ml of indigo reagent into a 30 ml cuvette, sealed with a rubber cap,
followed by adding 5 ml of a gas sample collected with a syringe. After gentle agitation
for 1 min, the reagent solution was measured in the UV- vis spectrophotometer under 600
nm wave length with original indigo reagent as reference. The absolute value of the
absorbance was recorded for calculating ozone concentration using the following
equation:

mg O3 / L 

100  A
f  b V

where:
A = difference in absorbance between sample and blank,

b = path length of cell, cm,
V = volume of sample, mL (normally 90 mL), and
f = 0.42.

51

(Equation 3.1)

3.2.2 GC analysis
The GC equipment and analysis method are as described in 2.2.4.
3.2.3 Ozonolysis reaction
In the batch reactions, ozone was produced by a CFS-3A ozone generator from Ozonia
North America LLC. Oxygen/Ozone gas mixture flow rate was 1 L/min, with a weight
fraction of 10% ozone. Compressed oxygen was used as input gas to generate ozone.
The reactor was modified from a dry ice trap cylinder with diameter of 3.8 cm and length
of 32 cm. The inlet gas was injected in the reactor through a deep-tube, submerged into
the liquid-phase during reaction. The deep-tube was equipped with a spray nozzle on the
tip to create small bubbles and increase the mass transfer efficiency during reaction.
During reaction, the outlet gas passed through a KI solution (1M), to trap the unreacted
ozone. The reaction was conducted independently using either methanol or water as
solvents. In methanol, 20 g of FAMEs, 40 g of methanol and 0.25 wt% sodium
methoxide (based on the added FAMEs) were added into reactor. In water system, the
reactants consisted of 20 g of FAME and 40 g of water without any added catalyst. The
reaction duration time was between 45 minutes to 1 hour under temperature controlled
conditions by cooling water. The continuous reaction was performed as described in
2.2.2.
3.2.4 Ozonolysis of FAMEs in methanol
Ozonolysis was conducted in both batch and continuous reactors. In batch reactor, the
cooling condition was varied as under room temperature (~ 22 ℃), ice bath (~ 0 ℃) and

52

dry ice bath (~ -75 ℃). In continuous reactor, the cooling system was constantly flowing
water with change of flow rate of material from 3 to 27 ml/min.
3.2.5 Ozonolysis of FAMEs in water
Ozonolysis in water was similar to ozonolysis in methanol and the reaction details are
also shown in 2.2.2 and 3.2.2. The difference between ozonation reaction in water and in
methanol are the following: 1) in methanol system, 0.25 wt% of sodium methoxide was
added as catalyst while in water solvent no other chemical was introduced except for
FAMEs and water; 2) the FAMEs-to-solvent mass ratio in water system was 1:3 while in
methanol system was 1:2 for both of the two reaction conditions. Based on preliminary
data, the effect of FAMEs-to-solvent mass ratio was not significant to the reaction rate,
however, the reason we chose different mass ratio in water system was mainly based on
safety considerations, because more water will absorb more heat generated by the
reaction, and also based on the fact that more water will provide better emulsification as
the reactants were in two phases.
3.2.6 Mass transfer model of ozone in methanol and water
The mass transfer study of ozone in customized plug flow reactor was conducted based
on the method of transfer units, which is usually applied in mass transfer studies for gasliquid absorption columns. The biggest difference that needs to be noticed is that in
absorption columns, the gas flow and liquid flow are usually countercurrent, however, in
our model the mass transfer happens in concurrent flow, since both gas and liquid
reactants enter into the reactor from the same side.

53

In this method, the height of packing in the column (in our case, the length of reactor) can
be evaluated either based on the gas phase or the liquid phase using the following
formula:
Z = NTU × HTU

(Equation 3.2)

where,
Z = the length of the reactor, m
NTU = the number of transfer units, dimensionless
HTU = the height of transfer units, m
NTU is the theoretical number of trays required for a trayed column in the absorption
column calculation. Similarly, here NTU can be considered as the theoretical number of
unit length of the PFR reactor. The height of a transfer unit (HTU) can be considered as
the unit length of the reactor for mass transfer.
For gas- liquid mass transfer, Equation 3.2 can be applied to both liquid and gas phases,
and the calculated value for reactor length Z will be the same, which can be expressed as
Z = NTU

gas

× HTU gas = NTU

liquid

× HTU liquid. In this project, we mainly studied the

mass transfer in gas phase, since we assumed that with ozonolysis reaction, the mass
transfer in liquid phase will be much faster compared to gas phase, thus the mass transfer
efficiency in gas phase will determine the overall speed.
The model is described by these equations combined with Equation 3.2:

( y  y*) LM 

( y o  y o* )  ( y e  y e* )
ln ( y o  y o* ) /( y e  y e* )





54

(Equation 3.3)

NTU gas 

( yo  ye )
( y  y*)LM

(Equation 3.4)

where:

NTU gas = Gas phase number of transfer units

y = Mole fraction of ozone

y* = Mole fraction of ozone in equilibrium with liquid flow
y o = Mole fraction of ozone in inlet gas flow
y o* = Mole fraction of ozone in equilibrium with inlet liquid flow (=0)
y e = Mole fraction of ozone in outlet gas flow
y e* = Mole fraction of ozone in equilibrium with outlet liquid flow
Similarly, the equations for liquid phase mass transfer calculation are shown as follows :

( x *  x )LM

( x o*  x o )  ( x e*  x e )

ln ( x o*  x o ) /( x e*  x e )



NTU liquid 



( xo  xe )
( x  x*)LM

where:

NTU liquid = Liquid phase number of transfer units
55

(Equation 3.5)

(Equation 3.6)

x = Mole fraction of ozone
x* = Mole fraction of ozone in equilibrium with gas flow
x o = Mole fraction of ozone in inlet liquid flow (=0)
x o* = Mole fraction of ozone in equilibrium with inlet gas flow
x e = Mole fraction of ozone in outlet liquid flow
x e* = Mole fraction of ozone in equilibrium with outlet gas flow
After NTU gas is calculated, inputting into Equation 3.2, HTU gas can also be calculated.
To further determine the gas phase mass transfer coefficient, the following equations will
be used:

HTU gas 

( 1  y )*LM 

G
K Y a( 1  y )*LM

(Equation 3.7)

( 1  y o )  ( 1  y o* )
ln ( 1  y o ) /( 1  y o* )





where:

HTU gas = Gas phase height of transfer units
G = Gas flow rate, mol/m2 s
K Y = Overall gas-phase mass transfer coefficient, mol/m2 s

56

(Equation 3.8)

2
3
a = Packing parameter, m /m

The only unknown variables are K Y and a , and they are usually combined as a single
parameter K Y a (mol/m3 s).
Similarly, for liquid phase, the equations turn to be:

HTUliquid 

( 1  x )*LM 

L
K X a( 1  x )*LM

(Equation 3.9)

( 1  x o )  ( 1  x o* )
ln ( 1  x o ) /( 1  x o* )





(Equation 3.10)

where:

HTUliquid = Liquid phase height of transfer units
L = Liquid flow rate, mol/m2 s
K X = Overall liquid-phase mass transfer coefficient, mol/m2 s
2
3
a = Packing parameter, m /m

Once the mass transfer coefficient is known, the rate of mass transfer can be calculated
using this equation:

Q  Ka( y  y* )V

where:

57

(Equation 3.11)

Q = Rate of mass transfer, mol/s
K = Overall mass transfer coefficient, mol/m2 s

V = Volume of reactor, m3
3.2.7 Assumptions of model and Henry’s law constant measurement
By applying the above equations, we assumed that there is no decay of ozone in the
whole process including both the reaction process and the measurement process. To
evaluate the validity of this assumption, we took a methanol or water solution containing
ozone and measured the concentration of ozone with time. The result showed that in 6
minutes the concentration of ozone dropped by less than 1.5% percent in both methanol
and water solution and in 10 mins the concentration decreased less than 2.5%, which can
be considered an acceptable error range. It was also assumed that oxygen does not
interfere with the absorbance of ozone at 258 nm and the absorbance of ozone in water
and methanol system obeys Beer-Lambert Law.
The third assumption is the solubility of ozone abbeys Henry’s law. In order to calculate
the mole fraction of ozone in equilibrium with outlet liquid flow ( y e* ), we need to
determine Henry’s law constant. In water system, the constant was calculated as 5846.7
atm/(mol fraction) through this equation [85]:

K H  3.842 107 [OH  ]0.035 exp[2428 /(T / K )]
where:

58

(Equation 3.12)

K H = Henry’s law constant (atm/mole fraction)
[OH  ] = Concentration of OH  (mol/L)
T = Temperature (K)
In methanol system, the Henry’s law constant was measured by passing ozone and
oxygen gas mixture into methanol in a semi-batch reactor for more than 40 minutes until
the solution was saturated with ozone (determined by measuring the change of
concentration value constantly), with the overall gas pressure and ozone mole fraction
known. By dividing the value of ozone partial pressure by the maximum mole fraction of
ozone in solution, the average Henry’s law constant was obtained as 771.17 atm/(mol
fraction) which is much smaller compared to that in water system. This indicates that
solubility of ozone is higher in methanol than in water given the same partial pressure
and temperature.
3.2.8 Extraction of organic products from solution after Oxone treatment
Upon completion of the reaction, the excess salt from Oxone was filtered out, and the
product was neutralized by adding KOH (85%) until the pH reached to 4-5. Under this
pH value, the esters are relatively stable, while under higher pH we observed some
decomposition of esters by analyzing with GC. More salt precipitated after the
neutralization process which occurred in 1 to 2 hours. When the solution became clear,
the sediment was filtered out. In order to remove the dissolved salt, extraction was carried
out with hexane and water. Extractant was put directly into 10 ml sample vial with certain
amount of sample, after 30 s shaking, the vial put on the bench standing for 24 hours.
59

Two layers formed with a clear boundary and then were separated. The organic layer was
weighed and the composition was analyzed by GC. Five batches with different sample to
extractant ratios were conducted, from number 1 to 5, the ratios were 4:6, 4:4, 4:3, 4:2
and 4:1. Experiments under the same condition were repeated twice and the mean value
was calculated as final result.
3.3 Results and Discussion
3.3.1 Reaction kinetics of ozonolysis in methanol system
3.3.1.1 Batch process
Ozonolysis of FAMEs in methanol was initially carried out in a semi-batch reactor for 45
min with continuous supply of ozone going through constant amount of reactant solution.
The reaction condition was described in 3.2.3 and ice/water batch was applied to keep the
reaction under lower temperature. The course of reaction was monitored by GC after
every 10 mins. The GC chromatograms for the solution before and after reac tion were
compared in Figure 3.1. The starting material contains five peaks which are the five
methyl esters derived from soybean oil, with the first two being saturated and last three
being unsaturated.
When the reaction started, the last three peaks started decreasing, as only the unsaturated
compounds react with ozone. At the time of 10 mins after reaction started, the only
obvious peak that can be seen from the GC chromatogram was peak H which was for
Methyl 9-oxononanoate. After reaction continued for another 10 mins, all the 4 main
product peaks showed up and all the reactant peaks could also be observed from the

60

figure, however, when reaction was carried out for 30 mins, the peak for methyl
linolenate almost disappeared from the chromatogram which indicated that the
conversion of this compound was close to complete. By the end of reaction, all the
reactant peaks disappeared from the chromatogram which means the conversions were
100% complete.

uV(x1,000,000)

F

6.0

H

G

A
I

B

40 min

5.5
5.0

30 min

4.5
4.0

20 min

3.5
3.0
2.5

10 min

2.0
1.5

D

1.0

C

0.5

A
B

0.0
-0.5
0.0

2.5

5.0

7.5

10.0

12.5

15.0

17.5

E
0 min
20.0

22.5

min

Figure 3.1 GC chromatograms for FAMEs in methanol solution during ozonolysis in
semi-batch reactor. Oxygen/ozone gas mixture flow rate was 1 L/min, with 10 wt% of
ozone. A: Methyl palmitate; B: Methyl Stearate; C: Methyl oleate; D: Methyl linoleate;
E: Methyl linolenate; F: Hexanal; G: Nonanal; H: Methyl 9-oxononanoate; I: Dimethyl
azelate.

61

o

Water bath (22 C)
100
80
60
40
20
0

0

5

10

15

20

25

30

35

40

45

50

15

20

25

30

35

40

45

50

o

Ice bath (0 C)

Conversion (%)

100
80
60
40
20
0

0

5

10

o

Dry ice bath (-78 C)

100
80
60
40

Methyl oleate (C18:1)
Methyl linoleate (C18:2)
Methyl linolenate (C18:3)

20
0

0

5

10

15

20

25

30

35

40

45

50

Time (min)

Figure 3.2 Ozonolysis of FAMEs in three cooling systems using methanol as solvent
system.

62

Ozonolysis is an exothermal reaction, thus it should be carried out at low temperatures to
avoid the heat accumulation for safety concerns. To examine the effect that temperature
causes on reaction rate, we conducted the reaction under three cooling regimes in a semibatch reactor, which were room temperature, ice-water bath and dry ice-acetone bath with
22 ℃, 0 ℃ and -78 ℃ at starting temperature, respectively. During the reaction, the
temperature of reactants kept at room temperature conditions increased to 42-45 ℃, while
the other reactions occurred in ice-water bath and ice-acetone bath kept a relatively
constant temperature.
Comparing the results from three conditions (Figure 3.2), it is observed that the reaction
rate increases with decreasing temperature. As known, given no mass transfer obstacle,
increasing the temperature usually improves reaction rate because of the increase of
number of high energy collisions which lead to reaction. However, the experimental
result does not follow this theory, suggesting that mass transfer is the limiting step for
ozonolysis in methanol. The rate of mass transfer of ozone in methanol is proportional to
the mass transfer coefficient, the difference of ozone concentration between the gas phase
and equilibrium concentration in gas phase to the liquid phase, and the bubble surface
area:

Q  K c a  ( CO3  CO* 3 )  V
where:
Q = Rate of mass transfer of ozone, mol/s;

K c a =Combined mass transfer coefficient, s-1;
63

(Equation 3.13)

CO3 =Molar concentration of zone in gas phase, mol/L;
CO* 3 =Molar concentration of ozone in equilibrium with liquid phase, mol/L;

V = Bubble size, L;
Temperature can affect all the three parameters. The input gas phase temperature is
around 32 ℃ for all the three conditions, and gas bubble passes through the liquid in a
very high speed, so we can assume that the transfer coefficient is not affected much by
the liquid temperature. We assume CO* 3 =0 because the reaction consumes ozone in the
liquid phase instantly, so the driving force is proportional to 1/R3 (R is the radius) which
increases when temperature decreases, since the bubbles shrink; while the area of the
bubble, which is proportional to R2 , will decrease due to the shrinkage of the bubble.
Considering the overall effect, the rate of mass transfer will increase under lower
temperature, because it is proportional to 1/R, which agrees with the result of the
experiment.
By the end of 30 mins, the ozonolysis reaction for C18:2 and C18:3 under -78 ℃ was
almost complete, while for C18:1 was about 95% converted. For the reaction conducted
under 22 ℃ at the end of 30 mins, when conversion of C18:3 was almost 100%, C18:2
was about 95% complete and C18:3 was about 86%. The reaction rate for all the three
unsaturated FAMEs showed a decreasing order: C18:3 > C18:2 > C18:1. This result is
consistent with that shown in Figure 3.1. This phenomenon may be explained by the
difference of double bond number per molecule among different unsaturated esters, as the
more double bonds present in the molecule, the more reactive the compound seems to be.
64

3.3.1.2 Continuous process
A continuous reaction was conducted in a vertical plug flow reactor embedded in a
cooling jacket. The flow rate of feed (containing solvent and catalyst) varied from 3 to 27
ml/min. The pressure of input gas was around 21.5 psi with overall flow rate of 3.77
L/min and weight percentage of ozone of around 10.11%.
The yields of products under different flow rates are shown in Figure 3.3. Since the flow
rate will affect the retention time of the materials, the yields of products under different
flow rates varied significantly. With flow rate increasing from 3 to 15 ml/min, the yield
of all the three aldehydes (hexanal, nonanal and methyl 9-oxononanoate) increased
rapidly, almost twice of the starting value. However, a descending trend was observed for
the aldehyde yields at flow rates higher than 15 ml/min. The change of yields for esters
(methyl hexanoate, methyl nonanoate and dimethyl azelate) displayed a different feature
compared to the change of aldehydes. Increase of flow rate resulted in a gradual decline
of the yields for methyl esters, and when the flow rate approached a higher value (around
18 ml/min), the yields tended to be steady.

65

60
Hexanal
Nonanal
Methyl 9-oxononanoate
Methyl hexanoate
Methyl nonanoate
Dimethyl azelate

55
50
45
40

Yield (%)

35
30
25
20
15
10
5
0

0

3

6

9

12

15

18

21

24

27

Flow rate (ml/min)

Figure 3.3 Molar yields of products from ozonolysis in methanol in plug flow reactor
under different flow rates.
The total yields for parallel products obtained from the same reactants also showed a
slight variation by increasing the flow rate of feed (Figure 3.4). Similar to the trend
observed in Figure 3.3, the maximum product yields also appeared at a flow rate of 15
ml/min. However, when measuring the amount of individual unsaturated FAMEs (Figure
3.5) and calculating their conversion profile as a function of feed flow rate, it is clear that
at the flow rates between 3 and 12 ml/min, the reaction achieves maximum conversion
(around 100% for most cases) and drops significantly for flow rates below 12 ml/min.
This result is not consistent to the product formation profiles from Figure 3.3 and Figure
3.4, suggesting that at low liquid feed rates, where the ratio of ozone to FAMEs is higher,
reaction intermediates (e.g. ozonides) did not decompose to final product. From the GC
analysis it was not possible to observe the formation of byproducts of FAME oxidation,
66

such as carboxylic acids, or ozonolysis intermediate s in the methanol system. One
hypothesis is that high ozone concentrations may stabilize ozonide intermediates, which
are not detectable by GC, avoiding it to break into measurable product. However,
additional work that is beyond the scope of this study should be performed to prove this
hypothesis.
70

Hexanal+Methyl hexanoate
Nonanal+Methyl nonanoate
Methyl 9-oxononanoate+Dimethyl azelate

65
60
55
50

Yield (%)

45
40
35
30
25
20
15
10
5
0

0

3

6

9

12

15

18

21

24

27

Flow rate (ml/min)

Figure 3.4 Total molar yields for products obtained from the same reactants from
ozonolysis in methanol in plug flow reactor under different flow rates

67

C18:1
C18:2
C18:3

100
90

Conversion (%)

80
70
60
50
40
30
0

5

10

15

20

25

30

Flow rate (ml/min)

Figure 3.5 Conversion of unsaturated FAMEs during ozonolysis in methanol in plug flow
reactor under different flow rates
At the higher flow rates, the retention time for reaction is shorter and therefore, a
decrease in conversion and on product formation was observed (Figure 3.4 and Figure
3.5). The aldehydes that are formed and some unreacted ozonides can be converted to
esters by an extra conversion step with Oxone, as previously mentioned. However, to
avoid extensive Oxone usage, it is important for the reaction system that we can achieve
high product formation levels after the ozonolysis step. With the aim of optimizing the
flow rate for maximizing both product formation and conversion of FAMEs into
aldehydes or esters, the flow rate of 15 ml/min is recommended for the methanol system.

68

3.3.2 Oxone treatment and extraction of ozonolysis products in methanol system
Further Oxone oxidization of the ozonolysis product mixture was conducted at room
temperature (22 ˚C) under constant magnetic stirring at 500 rpm. Room temperature was
chosen because the residual peroxides generated from ozonolysis are less reactive at low
temperatures but high temperatures could also potentiate uncontrolled exothermal
reactions and therefore, room temperature can help to accelerate their decomposition
safely.
Two samples were prepared using product obtained from the continuous ozonolysis
process, with the yields of 57% 9-oxononanoate and 18% dimethyl azelate. Oxone was
added to the sample in two distinct loading processes: one-time batch load and a fedbatch load. In the first sample, 30 g of Oxone was added initially to 180 g of ozonolysis
product, and the reaction was maintained for 19.30 hrs in total. During this period, 0.5 ml
of sample was collected for GC analysis every 1-4 hrs without disturbing the reaction.
For the fed-batch process, Oxone was added in 10 g aliquots every 5 hours for three times
and analyzed in the same way as the first sample. After 15 hours, an extra 10 g of Oxone
was added into sample under agitation for another 5 hrs, allowing the conversion to reach
85%. At the beginning of the 21st hr, the addition of same amount of Oxone boosted the
conversion to 90%. With no further increase in conversion the reaction was in balance.
The results are displayed in Figure 3.6. With the fed-batch loading, the conversion over
time was almost linear, while for the batch loading, the rate of conversion decreased after
2 hrs of reaction time. After 15 hrs of reaction, the total amount of Oxone consumed by
both of the two processes was the same (30 g), however, the conversion was notably
different. The interrupted process showed a conversion of around 70 %, with a tendency
69

for further increase, while the uninterrupted process reached a conversion of 50% and the
curve almost reached to a platform. This demonstrated that the more efficient loading
technique for Oxone is fed-batch addition. The reason that this could happen may be
because of the decomposition of Oxone, according to DuPont, the time for 50% of active
oxygen in Oxone (3 wt% solution at 32 ℃) to decompose is around 2.5 hrs under 7.0 pH
value [86].
100

Conversion of 9-oxononanoate (%)

90
80
70
60
50
40
30
20

One-time Feeding
Multi-batch Feeding

10
0

0

5

10

15

20

25

t (hr)

Figure 3.6 Kinetics for Oxone treatment of ozonolysis products
The GC analysis for products before and after Oxone treatment (using fed-batch load) is
displayed in Figure 3.7. The result showed that most aldehydes were converted to methyl
esters, with only trace amounts (less than 10% molar ratio) left in the final product
solution. Peak G and H denote the two saturated FAMEs which are methyl palmitate and
methyl stearate. Since they do not react during the whole process, including ozonolysis

70

and Oxone treatment, they can be used as a reference to evaluate the overall yield for
products.
uV(x100,000)
6.5

5.5
5.0

E

Products after ozonolysis in methanol

6.0

F

C

A

G
H

D

B

4.5
4.0

F

Products after Oxone treatment

3.5
3.0
2.5

B

2.0

G

D

1.5

H

1.0
0.5

A

E

C

0.0
5.0

7.5

10.0

12.5

15.0

17.5

20.0

22.5

25.0

27.5

min

Figure 3.7 GC chromatograms for products before and after Oxone treatment. A:
Hexanal; B: Methyl hexanal; C: Nonanal; D: Methyl nonanoate; E: Methyl 9oxonoanoate; F: Dimethyl azelate; G: Methyl palmitate; H: Methyl stearate.
After reacting the ozonolysis products with Oxone, an extraction step was required to
separate Oxone reaction products from the dissolved salt. When using hexane as the
extraction agent (Figure 3.8), the recovery for all of the organic material decreased
steadily with the decreasing of ratio of hexane to sample solution. The best recovery
observed among the 5 batches was 80% for dimethyl azelate and 90-100% for the other
organic compounds except methanol, which was less than 20%. Compared with
extraction by hexane, better results were obtained during water extraction (Figure 3.9).
The recovery of the five methyl esters reached to a peak in batch 2, while the recovery of
71

methanol showed the highest value in batch 6. The best results, indicated in batch 2,
showed recoveries of methyl hexanoate, methyl nonanoate, dimethyl azelate and methyl
palmitate of around 90%. Only methyl stearate showed a slightly lower recovery (80%).
Comparing both solvent systems for extraction of Oxone reaction products, water is
preferred as it is more economical and safer to use in the industrial setup than hexane.
The salt content was analyzed by drying a trace amount of material in an oven at 200 ˚C
and taking the weight difference, the content dropped from 0.4% to 0.01%.

100

Recovery (%)

80

Methanol
Methyl hexanoate
Methyl nonanoate
Dimethyl azelate
Methyl palmitate
Methyl stearate

60

40

20

0

1

2

3

4

5

Batch

Figure 3.8 Extraction of products after Oxone treatment using hexane. From batch 1 to 5,
the volumetric ratios of sample to extractant were 4:6, 4:4, 4:3, 4:2 and 4:1.

72

100

Recovery (%)

80

60

Methanol
Methyl hexanoate
Methyl nonanoate
Dimethyl azelate
Methyl palmitate
Methyl stearate

40

20

0

1

2

3

4

5

Batch

Figure 3.9 Extraction of products after Oxone treatment using water. From batch 1 to 5,
the volumetric ratios of sample to extractant were 4:6, 4:4, 4:3, 4:2 and 4:1.
3.3.3 Mass transfer study of ozone in methanol system
In methanol system, the pure solvent was passed through the reactor with flow rate varied
from 10 ml/min to 40 ml/min, and the conditions of gas phase are described in Figure
3.10. The concentration of ozone in methanol was measured in the reactor outlet as a
function of solvent flow rate. As demonstrated in the figure, the concentration of ozone
decreased significantly with increase of flow rate. This result suggests that the higher
flow rate of solvent will reduce the contact time between the liquid and gas phases, thus
the absorption of ozone into the liquid phase was lower. The duplicates of each
experiment did not show good consistency, perhaps due to the fact that the sample

73

needed to be diluted 25 times before each measurement (to keep the absorbance between
0.0 and 1.0), where some operating errors may be introduced.
0.20
0.18
0.16

Concentration (g/L)

0.14
0.12
0.10
0.08
0.06
0.04
0.02
0.00

10

15

20

25

30

35

40

Flow rate (ml/min)

Figure 3.10 Concentration of ozone in methanol under different solvent flow rate at 22 ℃
with total gas pressure 20.89 psi, flow rate 3.75 L/min and ozone mass fraction 10.95%.
The value NTU of reactor calculated based on Equation 3.3 under different flow rates
falls between 0.0011 and 0.002 without significant variation, as shown in Figure 3.11.
This observation indicates that the gas phase NTU remains constant, at certain
temperature, for the same absorption liquid in the experimental flow rate range (10-40
ml/min).

74

0.0030

0.0025

NTU

0.0020

0.0015

0.0010

0.0005

0.0000

10

15

20

25

30

35

40

Flow rate (ml/min)

Figure 3.11 Gas phase NTU for ozone in methanol for PFR reactor under different
solvent flow rate at 22 ℃ with total gas pressure 20.89 psi, flow rate 3.75 L/min and
ozone mass fraction 10.95%.
Considering the entire sample results for the different liquid flow rates, a box plot was
applied and the result is shown in Figure 3.12. The mean value and median value of NTU
for ozone mass transfer in methanol are both around 0.0015.

75

0.0022
0.0020
0.0018

NTU

0.0016
0.0014
0.0012
0.0010
0.0008
Methanol

Figure 3.12 Box plot of gas phase NTU for ozone mass transfer in methanol in PFR
reactor under different solvent flow rate at 22 ℃ with total gas pressure 20.89 psi, flow
rate 3.75 L/min and ozone mass fraction 10.95%.
Using the median value of 0.00148 for gas phase NTU, the gas phase HTU was
calculated as 74.07 meters using Equation 3.2. Applying Equation 3.7 and Equation 3.8,
the resulting mass transfer coefficient K X a was 0.138 mol/m3 s.

76

0.9
0.8
0.7
0.6

NTU

0.5
0.4
0.3
0.2
0.1
0.0

10

15

20

25

30

35

40

Flow rate (ml/min)

Figure 3.13 Liquid phase NTU for ozone in methanol in PFR reactor under different
solvent flow rate at 22 ℃ with total gas pressure 20.89 psi, flow rate 3.75 L/min and
ozone mass fraction 10.95%.
The NTU under different flow rates of methanol in liquid phase was also calculated using
concentration data from Figure 3.10. Unlike in the gas phase, the value of NTU drops
from 3.66 to 1.7 with flow rate increasing from 10 to 40 ml/min as indicated in Figure
3.13. This result shows that the mass transfer efficiency in the liquid phase is affected
more significantly by the speed of liquid flow. Applying Equation 3.2 and using the
average value of NTU from Figure 3.13, the liquid phase HTU was calculated as 0.34 m.
By inputting this number into Equation 3.9 and Equation 3.10, the corresponding mass
transfer coefficient K X a was obtained as 21.313 mol/m3 s. Since the calculated mass
transfer coefficient in the gas phase is much lower than that in the liquid phase, we use

77

the gas-phase value as the approximate overall mass transfer coefficient to simplify the
process.
3.3.4 Ozone mass transfer in water system
Mass transfer in the same PFR reactor using water as solvent was also evaluated under
the same condition as using methanol. Water was fed into reactor with flow rate changing
from 10 ml/min to 60 ml/min and the concentration of ozone in outlet liquid phase was
measured under each flow rate. Unlike the result shown above for methanol system, the
concentration of ozone in solvent did not change significantly with the increase of water
flow rate. This happened was because the water solution was already saturated by ozone
under the experiment condition: ozone partial pressure was around 1.58 psi, and
according to Henry’s law and the known Henry’s law constant of 85922.55 psi/(mol
fraction), the equilibrium concentration of ozone should be 0.049 g/L, which is highly
consistent with result shown in Figure 3.14.

78

0.07

0.06

Concentration (g/L)

0.05

0.04

0.03

0.02

0.01

0.00

10

15

20

25

30

35

40

45

50

55

60

Flow rate (ml/min)

Figure 3.14 Concentration of ozone in water with different solvent flow rate at 22 ℃ with
total gas pressure 20.89 psi, flow rate 3.75 L/min and ozone mass fraction 10.95%.
Since the solution was saturated with ozone for almost all the flow rate conditions, the
NTU calculated for corresponding flow rate is now dependent on the flow rate, and the
NTU value in this circumstance is not accurate anymore, thus, it is not possible to
continue the study for mass transfer calculation in water system.
3.3.5 Ozone mass transfer under reaction in methanol system
According to the previous study, the mass transfer of ozone between gas phase and liquid
phase will be enhanced by the reaction [77], and this enhancement factor “E” is defined
as the actual rate of mass transfer with ozone reactions divided by the maximum rate of
physical absorption without any reactio n. In this section, we will calculate the
enhancement factor for ozonolysis of FAMEs in methanol.
79

As observed from Figure 3.2, the reaction rate of ozonolysis is controlled by ozone mass
transfer between gas and liquid phase in methanol system. Therefore, we used the data
for conversion of unsaturated FAMEs during ozo nolysis from Figure 3.5 and calculated
the ozone required under different flow rates based on stoichiometry. Because the
reaction is mass transfer driven, we assume that if the conversion is not 100%, it is
because the ozone obtained from the liquid already reaches to the limit amount. Based on
this assumption we obtained the actual rate of ozone mass transfer for flow rates under
which conversions of FAMEs were less than 100%. As shown in Figure 3.15, these flow
rates are from 15 to 27 ml/min. It is also displayed that the rates of mass transfer actually
reached to maximum value with flow rate of 15 ml/min or higher.

80

0.050

5

Ozone Consumption
Enhancement Factor

0.045

4

0.035
0.030

3

0.025
0.020

2

0.015
0.010

Enhancement Factor E

Ozone Consumption (mol/min)

0.040

1

0.005
0.000

0

5

10

15

20

25

0
30

Flow rate (ml/min)

Figure 3.15 Ozone consumption and enhancement factor for ozone mass transfer with
ozonolysis in methanol in PFR reactor under different material flow rate at 22 ℃ with
total gas pressure 21.5 psi, flow rate 3.77 L/min and ozone mass fraction 10.11%.
The rates of mass transfer for ozone without any reaction was calculated using Equation
3.11, where y* was assumed 0, because with presence of ozone reaction, ozone in liquid
phase is assumed to be consumed instantly due to the high reaction rate compared to
mass transfer rate. Also we assumed the value of K Y a was constant, because the
temperature change during reaction was not very high – the input gas phase temperature
was around 32 ℃ and the input and output temperatures of liquid phase was 22 ℃ and
33-36 ℃, respectively. The enhancement factor values were calculated by applying the
definition, as shown in Figure 3.15 with an average value of 3.44. This value is

81

comparable to the result reported by Zhou, et al. [67] , which was between 1 and 9 under
different ozone reactions in water.
3.3.6 Reaction kinetics of ozonolysis in water system
3.3.6.1 Batch process
Ozonolysis in water system was carried out in the same experimental setup as in the
methanol system described above. The batches of 20 g of FAMEs were diluted in 60 g of
distilled water without adding any catalyst. Before the reaction, materials were left in the
ice bath for 1 hour to be cooled down to near 0 ℃. After the reaction started, the
temperature increased steadily from 2 ℃ to more than 50 ℃ (Figure 3.16) and this trend
lasted for 39 mins. When the temperature stopped increasing, it indicated that the reaction
was complete. As a contrast, the pH value of the mixture was decreasing during the
process and at the end of the reaction, the pH value reached to about 2 (Figure 3.17). The
temperature change shows that ozone reaction is exothermal and needs to be applied with
cooling system to control the temperature in a lower range. The decrease of pH value
should be caused by the generation of acids that are slightly soluble in water.

82

65
60
55
50
45

o

T ( C)

40
35
30
25
20
15
10
5
0

0

5

10

15

20

25

30

35

40

45

40

45

t (min)

Figure 3.16 Temperature of solution during ozonolysis reaction
7.5
7.0
6.5
6.0
5.5

pH

5.0
4.5
4.0
3.5
3.0
2.5
2.0
1.5

0

5

10

15

20

25

t (min)

Figure 3.17 pH change of water phase during reaction
83

30

35

Figure 3.18 shows the comparison between kinetics for ozonolysis in water and methanol
system. Under the same flow rate of reactant solution, gas pressure and mass
concentration of ozone, the reaction for all three unsaturated FAMEs in water was
finished in 45 mins, while reaction in methanol proceeded slightly faster (about 5 mins)
than that in water. The reason for this observation could be that the reaction in water is
occurring between three phases, rather than two phases as in methanol, which exerts
more resistance to mass transfer. Similar to the methanol system ozonolysis kinetics, the
higher rate of conversion was also observed for FAMEs containing more double bonds
(e. g. C18:3 > C18:2 > C18:1).

84

In methanol

100

Conversion (%)

80

60

40

20

0

C18:1
C18:2
C18:3
0

10

20

30

40

50

t (min)
In water

100

Conversion (%)

80

60

40

20

0

C18:1
C18:2
C18:3
0

10

20

30

40

50

t (min)

Figure 3.18 Ozonolysis of FAMEs in two solvent systems at room temperature

85

3.3.6.2 Continuous process
In the continuous reaction mode, FAMEs and water with a mass ratio of 1:3 were added
to a conical flask and mixed under high speed agitation. A peristaltic pump was used to
supply the material into the reactor at constant flow rate. The flask stored with material
was connected to the reactor through a tube containing a static mixer, which can keep the
material emulsified. The pressure of input gas was around 21.7 psi at a flow rate of 4.72
L/min with the weight percentage of ozone around 11.07%. Cooling water was applied to
keep the reactor as well as the ozonator under lower temperature. The only variable was
the material flow rate, which was changed from 20 L/min to 50 L/min while conducting
different batches of experiments. The purpose of this experiment was to examine the
effect of material flow rate on the yield and profile of products, so that an optimal flow
rate can be recommended.
Figure 3.19 displays the conversions of 3 unsaturated FAMEs obtained under different
flow rates. The products formed under flow rate equal or lower than 30 ml/min showed
100% conversions of FAMEs, while under 50 ml/min the conversions dropped
significantly, especially for C18:1 and C18:2. The reactor volume is 0.75 L, so the
retention times for each flow rate from 20 ml/min to 50 ml/min are 37.5, 25, 18.75 and 15
min, the stoichiometric flow rates of ozone for each material flow rate are 2.34, 3.51,
4.67 and 4.69 L/min with the same gas pressure and ozone mass fraction as described
above.
The specific yields for all the products are displayed in Figure 3.20. From these results
we can see that the production of acids consistently decrease as the flow rate increases,

86

while aldehydes show a peak of yield at 40 ml/min, similarly to what was observed for
the methanol system.
C18:1

C18:2

C18:3

100

Conversion (%)

80

60

40

20

0

20

30

40

50

Flow rate (ml/min)

Figure 3.19 Conversions of unsaturated FAMEs at different material flow rate for
ozonolysis in water in continuous reactor.
The overall molar yields of products, including both aldehydes and acids contributed by
the same unsaturated FAMEs are plotted in Figure 3.21. Unlike the yield profiles for
aldehydes in Figure 3.20, the peak for overall yield of methyl 9-oxononanoate and
monomethyl azelate was obtained at 30 ml/min, for nonanal and nonanoic acid shows at
20 ml/min, and for hexanal and hexanoic acid the difference is not obvious between flow
rate of 20 ml/min and 30 ml/min. This can be explained as follows: under flow rate that is
higher than 40 ml/min the reactants were not completely consumed (as shown in Figure
3.19), so the increase of flow rate will cause the increase of overall product yields; once
the flow rate is lower than 40 ml/min, since the conversion of FAMEs was 100% or very
87

close to it, more reaction time will cause the generation of more acids from aldehydes,
which results in a decrease of aldehydes and increase of acids. Since the target products
for this reaction were aldehydes, from Figure 3.20 we can conclude that the optimal
material flow rate is around 40 ml/min.
100
Hexanal
Nonanal
Methyl 9-oxononanoate
Hexanoic acid
Nonanoic acid
Monomethyl azelate

90
80
70

Yield (%)

60
50
40
30
20
10
0

20

30

40

50

Flow rate (ml/min)

Figure 3.20 Product yields at different material flow rate for ozonolysis in water in
continuous reactor.

88

100

Hexanal + Hexanoic acid
Nonanal + Nonanoic acid
Methyl 9-oxononanoate + Monomethyl azelate

90
80

Yield (%)

70
60
50
40
30
20
10
0

20

30

40

50

Flow rate (ml/min)

Figure 3.21 Total molar yields for products obtained from the same reactants from
ozonolysis in water in plug flow reactor under different flow rates.
3.4 Conclusion
Ozonation of FAMEs produced from Soybean oil using methanol as solvent and sodium
methoxide as catalyst was carried out in both semi-batch and continuous processes to
study reaction kinetics. Using dry- ice-acetone cooling system to control the temperature
at -78˚C showed to be the best method to achieve the highest conversion rates, however,
the reaction rate difference among different temperatures was not highly significant. The
optimal flow rate for the continuous process was suggested to be around 15 ml/min,
where the production of esters and aldehydes were maximized. The kinetics also
indicated that the most unsaturated ester (C18:3) had the highest reaction rate, followed
by C18:2 and C18:1, which can be explained by the highest number of double bonds per
FAME molecule. Complete unsaturated FAMEs conversion was obtained for liquid flow
89

rates between 3 and 15 ml/min, decreasing significantly for flow rates higher than 15
ml/min. This observation and the fact that aldehyde and ester yields peaked at 15 ml/min
in the continuous reaction, suggests that the higher concentrations of ozone, which are
obtained at lower FAME solution flow rates, may promote the stabilization of reaction
intermediates that cannot be detected using GC methodology and could not be quantified.
Further studies beyond the scope of this work should address this topic to understand the
effect of ozone concentration in the inhibition of aldehyde and ester formation during
ozonolysis in solvents like methanol.
As the target products from ozonolysis in methanol are methyl esters, the oxidation from
aldehydes to esters was accomplished by Oxone treatment. A best conversion of 88% for
9-oxononanoate, was reached according to the experiment results and the total yield of
dimethyl azelate was 68%. In order to remove the salt residues from the product solution,
extraction using both hexane and water was conducted. Based on the comparison of
recovery of organic compounds water performed better than hexane.
Mass transfer of ozone in pure methanol was studied by applying the number of transfer
units (NTU) theory, which is a simplified model for studying gas-liquid mass transfer. It
was found that the NTU value for the gas phase of ozone mass transfer in methanol is
around 0.0015. Also, the combined mass transfer coefficient K Y a for gas phase
calculated based on NTU value for methanol system is 0.0087 mol/m3 s.
Ozonolysis of FAMEs in water without catalyst was also conducted in both semi-batch
reactor and continuous reactor. It was found that the reaction was highly exothermal,

90

generating increase in reaction temperature even under cooling conditions, and formed
acids that caused the pH value to decrease during the course of reaction.
The conversion rate of FAMEs during ozonolysis in water and in methanol was also
compared. The results show that the conversion rate is slightly higher in the methanol
system than in water. The observed difference may be due to the fact that in water system
there are three phases present while in methanol, the reaction takes place in two phases.
The optimal material flow rate in continuous reaction for the water solvent system was
found to be around 40 ml/min, given a constant ozone gas input 21.5 psi at a flow rate of
4.72 L/min with the weight percentage of ozone around 11.07%. Higher flow rate will
cause incomplete conversion of reactants and lower flow rate will generate higher molar
yield of acids and therefore reduce the aldehydes yield.

91

Chapter 4: Distillation Process Design to Separate Ozonolysis Products of FAMEs
4.1 Introduction
During last chapter we discussed the reaction kinetics in methanol system and water
system. Multiple products were formed from the reactions including aldehydes and
methyl esters. In addition to the newly formed compounds, the two saturated methyl
esters (methyl palmitate and methyl stearate) also remained in the systems; therefore, the
compositions of the product solutions are quite complex. The project objective is to
develop and produce biobased polymer building blocks which would be dimethyl azelate
from the methanol system and the aldehydes (hexanal and nonanal) from water system,
probably also methyl 9-oxononanoate from both systems depending on the performance
of the derived polymer from this compound. According to the polymer theory, high
purity of monomers increase the degree of polymerization and thus provides higher
molecular weight and often better polymer properties. Therefore, purification of the
products is very important for polymer application. Besides, even for the other output
chemicals that will not be used to produce biobased polymers, such as methyl hexanoate
and methyl nonanoate, a higher purity will always increase the marketing value of the
products.
Distillation is the most widely used technology in the chemical industry to separate and
purify chemicals. Fractional distillation was developed by Tadeo Alderotti in the 13 th
century [87], and since then, the simulation study on distillation became increasingly
efficient. One of the most powerful software used by engineers to conduct distillation
simulation is Aspen Plus.

92

Aspen Plus is a chemical process optimization software created in the 1980’s and has
been used by the chemical, biochemical and polymer industries to simulate their
processes. It supports design, operation, and optimization for both manufacturing and
separation processes. It also contains batch simulation, dynamic simulation and economic
evaluations [88].
Aspen Plus is a very powerful software, given proper input values and assumptions, it can
provide very accurate results. In order to properly develop a simulation for distillation
process, there are several factors that should be taken into consideration. The first and
most important factor is the physical properties of the components of the mixture, such as
VLE data and enthalpy of evaporation of components. Most data for the properties of
compounds related to this project is reliably provided in the modern version of Aspen.
However, for some components that are not included in ASPEN database (e.g. 9-oxononanoate), thermodynamic properties can be estimated using group contribution method
by UNIFAC functional groups in the data properties module of Aspen Plus. Parameters
estimated by Aspen include: 1) ideal gas heat capacity coefficients; 2) Antoine liquid
vapor pressure coefficient; 3) DIPPR liquid heat capacity coefficients; 4) Watson heat of
vaporization parameters; 5) DIPPR liquid thermal conductivity coefficients; 6) Andrade
liquid viscosity coefficients; 7) DIPPR vapor viscosity coefficients; 8) DIPPR surface
tension coefficients.
Another concern before starting the distillation design is the separation sequence. In this
project the sequence was determined by the heuristic method. In this method, the
volatility, corrosivity and reactivity were fully considered to assign different priorities to
components. Separation order is important because it can significantly impact on the

93

separation cost especially in terms of energy cost. For example, in an improper design,
some components would be repeatedly heated up and cooled down before leaving the
system.
The third consideration in distillation modeling is to decide operating pressure and
temperature. The pressure of distillation column is normally determined based on the
temperature of cooling medium at the reflux condenser. Generally, it is desirable to
operate the column at as low a pressure as possible, to maximize the relative volatility,
this is to facilitate the better separation, because the relative volatility goes on increasing
as we reduce the separation pressure. The two factors pressure and temperature are highly
correlated and should be determined also based on equipment cost considerations.
Stability of products should also be evaluated, for instance, some components may
decompose or get oxidized under higher temperature. In this case, the cost of energy or
equipment should be given secondary importance.
In this chapter we addressed all the issues mentioned above and eventually proposed the
distillation design for products generated through ozonolysis in both methanol and water
system, as described in chapter 3. The dimensions of equipments and operation
conditions will also be specified based on the simulation results.
4.2 Heuristic method to determine distillation sequence [89]
a. If there are only two products in a mixture and all of the components in one
product are more volatile than all of the components in the other product, then
separate the components into two products first;
b. If a component is corrosive, unstable, reactive or otherwise hazardous, then
remove this component from bulk stream first;
94

c. If the most volatile component in the mixture is >~20 mol% of the feed, and it has
the largest mole fraction in the feed, the second-largest-mole- fraction component
is less than 90% of the most volatile component, and the proposed separation is
one of the easiest separations remaining, then split off the most volatile
component as distillate;
d. If the least volatile component in the mixture is >~20 mol% of the feed, and it has
the largest mole fraction in the feed, the second-largest-mole- fraction component
is less than 90% of the most volatile component, and the proposed separation is
one of the easiest separations remaining, then split off the least volatile
component as bottom;
e. If a separation has a distillate-to-bottom molar ratio of ~40:60 to 60:40 and the
proposed separation is one of the easiest separations remaining, then the next
separation should be the one closest to 50:50 distillate-to-bottom ratio;
f.

If none of the above apply, then the next separation to be done should be the
easiest, i.e. the one with the highest separation coefficient, S, defined as S = (α-1)
*(D/B) for D/B < 1, and S = (α-1)*(B/D) for D/B > 1, where α is the ratio of
relative volatility of adjacent components, D is the molar flow rate of the
distillate, B is the molar flow rate of the bottoms.

4.3 Distillation sequence for ozonolysis products
Products prepared from ozonolysis in methanol after being dried using molecular sieves
contain 6 main components with a little amo unt of unknown impurities (< 0.3% mass
ratio). To simplify the design, the portion of unknown compounds was added as methyl
palmitate and methyl stearate, with the assumption that they are mainly heavy
95

compounds. As shown in Table 4.1 (products were prepared by continuous ozonolysis
reaction in methanol, with gas flow rate of 3.75 L/min containing 10.91 wt% ozone, and
liquid reactants flow rate of 12 ml/min; FAMEs to methanol mass ratio was 1:2), the
most abundant compound is methanol, which takes up 83.96% of molar ratio in the total
mixture. The second most abundant compound is dimethyl azelate, which has a molar
ratio of 7.46%, and this is also the most important product. All the other compounds are
relatively low in molar quantity.
Table 4.1 Products generated from ozonolysis in methanol after Oxone treatment and
water extraction

Index

Component

mol%

1

Methanol

83.96

2

Methyl hexanoate

5.04

3

Methyl nonanoate

2.11

4

Dimethyl azelate

7.46

5

Methyl palmitate

1.06

6

Methyl stearate

0.4

Examining the heuristic rules in 4.2, a and b do not apply, since we have more than two
products to purify; according to c, methanol should be separated first. After methanol is
separated from the mixture, the composition and volatilities for each compound are given
below in Table 4.2. The remaining three products that are of interest are methyl
hexanoate, methyl nonanoate and dimethyl azelate. Rule c and d also do not apply,

96

because neither methyl hexanoate nor methyl stearate has the largest mole fraction,
whereas dimethyl azelate has.
The next rule e is the one we should follow. The reason is if we split methyl hexanoate
and methyl nonanoate as the distillate stream, and the remaining compounds as the
bottom stream, the molar ratio between the two mixtures is 44.5:55.5 which is quite close
to 50:50. Thus, these two methyl esters were chosen to be distilled first as a mixture, and
then separated in the next column. Dimethyl azelate will be separated from the heavy
compounds in the consequential process, using another parallel column. The overall
process diagram will be displayed in the design section.
Table 4.2 Molar ratio of compounds after removing water and methanol

Product

Component

Concentration
mol%

Bp, at 0.3 atm.
℃

Adjacent
relative
volatility

Separation
coefficient

1

Methyl hexanoate

31.36

113

7.91

1.9603466

2

Methyl nonanoate

13.13

169

16.9

7.55132743

3

Dimethyl azelate

46.42

171 (0.04 atm)

6.69

2.43857143

Methyl palmitate

6.60

211 (0.04 atm)

Methyl stearate

2.49

234 (0.04 atm)

4

The distillation sequence for the second set of products (all the products in Table 4.2) can
also be determined similarly. These products were made by applying ozonolysis in water
and then were dried for 24 hrs using molecular sieves (3 A beads purchased from SigmaAldrich) after reaction. This mixture consists of five compounds, which are listed in
Table 4.3 with the corresponding molar fractions for each component. The most abundant
97

compound in this mixture is methyl 9-oxononanoate, which takes up more than 46% in
molar ratio. The second most abundant product in this mixture is hexanal, with molar
ratio of 28.48% followed by nonanal with 13.32%. Saturated esters including methyl
palmitate and methyl stearate will be separated as a mixture product.
Table 4.3 Products generated from ozonolysis in water

Index

Component

mol%

1

Hexanal

28.48

2

Nonanal

13.32

3

Methyl 9-oxononanoate

46.42

4

Methyl palmitate

8.75

5

Methyl stearate

3.02

Compounds in this mixture have similar structures and compositions compared to
products from ozonolysis in methanol, therefore a similar separation order should be
implemented. In this case, rule a, b, c, d do not apply, and according to rule e, hexanal
and nonanal will be separated together as distillate in first the column, with the other
compounds coming from bottom. This split gives a molar ratio of 41.8:51.2, which is also
close to 50:50. Because no solvent needs to be removed in the water system, this
distillation process consists of three columns.
4.4 Properties for main components
Properties for the main products prepared by ozonolysis using methanol and water
systems are displayed in Table 4.4. Most of the properties were obtained from Aspen Plus

98

databank, however for some compounds that could not be found in the databank, online
resources and literature was used. According to the boiling point data, separation for
methyl 9-oxononanote and dimethyl azelate requires high temperature and therefore, in
order to prevent the products from decomposing, vacuum distillation would be applied.
Among all the properties, vapor pressure and heat of evaporation are the most important
data for distillation simulation, because in distillation design, all the calcula tions are
based on these data, and if they are not accurate, the consequential design could be very
unrealistic. For all the ozonolysis products, the compounds that cannot be found in the
databank are methyl 9-oxononanoate and dimethyl azelate. The properties for this
compound were estimated by Aspen Properties. For this purpose, the chemical structure
and functional groups were added to the software for group contribution method and
UNIFAC functional groups were applied. Property estimation can also be conducted
using regression method, if experimental data of thermodynamic properties for these
compounds is available from literature. However, no data was found for methyl 9oxononanoate and dimethyl azelate and therefore, the estimation only relied on theory.

99

Table 4.4 Properties for main products from ozonolysis

Properties

Formula

Molar weight Density

Signs

---

Mw

ρi

Units

---

g/mol

Water

H2O

Methanol

Molar volume Boiling point Heat of evap. Vapor Pressure Viscosity
Tb

ΔHi

P 0*

kg/m3(at 25 oC) 10-3m3/mol

o

kJ/mol

kPa (at 25 oC) cP(mPa·s)

18.02

1000

0.018

100

39.5n

3.17

0.89 (25 oC)

CH4O

32.04

791.8

0.0405

65

35.28g

13.02

0.521 (30 oC)n

Hexanal

C6H12O

100.161

833.5

0.1237

131

31.65

1.51

0.69(20 oC)

Nonanal

C9H18O

142.24

826.4

0.1744

191

43.49

0.0493

---

Methyl Hexanoate

C7H14O2

130.185

884.6

0.1472

151

48.7

0.072

0.525 (25 oC)n

Methyl Nonanoate

C10H20O2

172.268

875a

0.1969

213.5c

63.2h

0.0257

0.68 (25 oC)n

Methyl 9-oxononanoate C10H18O3

186.248

958

0.1944

249.4d

48.66d

3.07E-03d

---

e

e

Vi

C

vi

Dimethyl Azelate

C11H20O4

216.27

1007

0.2148

294.4

51.45

6.55E-04

---

Methyl Palmitate

C17H34O2

270.46

852

0.3174

417n

62.42n

1.99E-05

0.403 (126 oC)n

Methyl Stearate

C19H38O2

0.3554
4.13E-06
840b
443f
64.99n
http://www.wolframalpha.com/entities/chemicals/methyl_nonanoate/zx/sv/zd/
http://www.chemicalbook.com/ChemicalProductProperty_EN_CB6409834.htm
http://webbook.nist.gov/cgi/cbook.cgi?ID=C1731846&Units=SI&Mask=4#Thermo-Phase
http://www.lookchem.com/Nonanoic-acid-9-oxo--methyl-ester/
http://webbook.nist.gov/cgi/cbook.cgi?ID=C1732101&Units=SI&Mask=4#Thermo-Phase
http://www.chemicalland21.com/lifescience/foco/METHYL%20STEARATE.htm
http://webbook.nist.gov/cgi/cbook.cgi?Name=Methanol
http://webbook.nist.gov/cgi/cbook.cgi?ID=C1731846&Units=SI&Mask=4#Thermo-Phase
http://app.knovel.com/web/data-search.v

0.359 (139 oC)n

a
b
c
d
e
f
g
h
n

298.51

100

4.5 Distillation design
The flow rates of feed materials were calculated based on the desired production and
the mole fraction of each component. Materials were input into the system at room
temperature under 1 atm. Operation pressure for each column was mainly determined
based on the consideration of product thermal stability and condenser energy cost.
Shin et al. [90] found that all FAMEs remained stable at 325 ℃ or below and FAME
with shorter chain length or less double bound has higher thermal stability. However,
the thermal stability data of dimethyl azelate and methyl 9-oxononanoate was not
found from previous studies. Dimethyl azelate has a shorter chain length than main
components of FAMEs, but has one more methyl group, therefore the comparison of
thermal stability is not straight forward. Based on lab-scale distillation records, when
the highest temperature reached to 195 ℃, dimethyl azelate was still stable. Taking all
these aspects into consideration, it was assumed that all the compounds remain stable
under 280 ℃.
For industrial vacuum distillation, the pressure can be as low as 10 mmHg [91] and
therefore, this is the lower pressure limit for our distillation design. According to Cai
et al. [92], in a trayed column the minimum dynamic pressure drop for a tray is in the
order of 25 mmH2 O (0.036 psi). In this study, some data for pressure drop of
hydrocarbon system from industrial distillation columns was presented, with the
highest pressure drop of 0.16 psi. Based on this study, a pressure drop of 0.1 psi was
assumed for the following design.
In Aspen Plus, RadFrac module was used to conduct distillation simulation. The stage
number and feed stage for each column were initially assigned an estimated value.
After these parameters are fixed, there are only two degrees of freedom left for
calculation. We chose distillate rate and reflux ratio as the two parameters that need to

101

be specified. The starting value for distillate rate was the same as the mass flow rate
of the target material from the feed stream, which means the recovery rate for product
from distillate was 100%. The reflux ratio was given a temporary value 2.
Once the calculation was converged, we used “Design Specifications/Vary” function
under each block to optimize the distillate rate and reflux ratio. Two parameters were
input as design objectives which were usually the mass purity of the main product and
the mass purity of the adjacent compound (in terms of volatility) in the product
stream. The former input value was between 0.99 and 0.999, and the later value was
around 0.001 to 0.01 depending on the separation difficulty for the product. The two
unknown variables were distillate rate and reflux ratio. After the calculation was
converged, the optimal values were output under each block.
The number of stage of a column and the reboiler reflux ratio are highly correlated.
Once a column reaches to the minimum number of stages, the value of reflux ratio
will turn to be infinity; therefore, the minimum number of stages can be calculated
based on this theory. While slowly decreasing the stage number of each column, the
“Vary” function for reflux ratio value would eventually output a very large number
(e.g. bigger than 100), and that means the stage already reached to minimum. Two
times of the minimum stage number was chosen for the final design of the column,
and based on that, feed stage was optimized. This was determined by varying the feed
stage starting from the middle of the column and choosing the one that leads to the
lowest heat duty for condenser.

102

4.6 Results and discussion
4.6.1 Distillation design for separation of products obtained from ozonolysis in
methanol
The design for the distillation process was based on the dimethyl azelate production
of 4 tons/day, using four columns in total. Dimethyl azelate was chosen as the main
target product in accordance with the primary research goal which is to develop
biobased polymer, and dimethyl azelate can be used to synthesize biobased
polyesters. According to the separation sequence as mentioned in section 4.3,
methanol is separated from the top of the first column, while methyl hexanoate and
methyl nonanoate is distilled as a mixture in the second column, with dimethyl azelate
and the rest of the components coming from the bottom. The two parallel columns
following the second column are responsible for separating all the other products
including methyl hexanoate, methyl nonanoate and dimethyl azelate. The saturated
esters and unknown compounds are separated together as a byproduct.
As shown in Figure 4.1, methanol comes out of the top of column B1 as DIS1 and its
mass fraction is 0.999 with recovery of 0.999 according to Table 4.5. Methyl
hexanoate and methyl nonanoate are separated from column B3 as distill and residue
streams respectively, with purities of 0.99 and 0.981, recovery of 0.985 and 0.99.
Column B4 purified dimethyl azelate with a mass fraction of 0.995 and recovery of
0.998 from the top stream. The purity for these products is specified in the “Design
Specification” module, by automatically varying the value of distillate rate and reflux
ratio, if the calculation in Aspen could converge, the design objective will be satisfied.
When it doesn’t converge after several trials, the purity requirement has to be
decreased slightly until conversion is achieved.

103

B3
DIS3

B1
DIS1

V1
FEEDA

DIS2B
FEEDB

DIS2A

V2
RES1A

RES3

V3

B2

RES1B

RES2A
B4
DIS4
V4
RES2B

RES4

Figure 4.1 Distillation design in Aspen Plus for separating FAME ozonolysis products in methanol system. DIS1: methanol; DIS3:
methyl hexanoate; RES3: methyl nonanoate; DIS4: dimethyl azelate; RES4: methyl palmitate and methyl stearate.

104

Table 4.5 Distillation results for the products from ozonolysis of FAMEs in methanol*
DIS1
B1
LIQUID
Substream: MIXED
Mole Flow mol/hr
1-HEX-01
1-NON-01
METHA-01
METHY-01
METHY-02
DMA
Mole Frac
1-HEX-01
1-NON-01
METHA-01
METHY-01
METHY-02
DMA
Mass Flow kg/hr
1-HEX-01
1-NON-01
METHA-01
METHY-01
METHY-02
DMA
Mass Frac
1-HEX-01
1-NON-01
METHA-01
METHY-01
METHY-02
DMA
Total Flow mol/hr
Total Flow kg/hr
Total Flow cum/hr
Temperature C
Pressure atm
Vapor Frac
Liquid Frac
Solid Frac
Enthalpy Btu/lbmol
Enthalpy Btu/lb
Enthalpy Btu/hr
Entropy Btu/lbmol-R
Entropy Btu/lb-R
Density lbmol/cuft
Density lb/cuft
Average MW
Liq Vol 60F cum/hr

DIS2A
V3
B2
LIQUID

DIS2B
B3
V3
MIXED

DIS3

DIS4

B3
LIQUID

B4
LIQUID

FEEDA
V1
LIQUID

FEEDB
B1
V1
LIQUID

RES1A
V2
B1
LIQUID

RES1B
B2
V2
MIXED

RES2A
V4
B2
LIQUID

RES2B
B4
V4
MIXED

RES3

RES4

B3
LIQUID

B4
LIQUID

3.245856
1.23E-11
10135.86
2.31E-32
1.96E-39
9.76E-28

605.7756
254.5184
10.1458
2.97E-08
5.80E-12
0.52241

605.7756
254.5184
10.1458
2.97E-08
5.80E-12
0.52241

599.7179
1.980124
10.14564
8.62E-28
1.13E-35
3.42E-11

4.22E-07
0.681747
0
2.757977
3.47E-05
900.5842

609.0214
255.2001
10146.01
127.9322
44.2197
902.008

609.0214
255.2001
10146.01
127.9322
44.2197
902.008

605.7756
255.2001
10.1458
127.9322
44.2197
902.0081

605.7756
255.2001
10.1458
127.9322
44.2197
902.0081

4.22E-07
0.681752
7.28E-19
127.9322
44.2197
901.4857

4.22E-07
0.681752
7.28E-19
127.9322
44.2197
901.4857

6.057714
252.5383
1.65E-04
2.97E-08
5.80E-12
0.52241

2.06E-14
4.72E-06
0
125.1742
44.21967
0.901497

3.20E-04
1.21E-15
0.99968
2.28E-36
1.94E-43
9.63E-32

0.695525
0.292227
0.011649
3.41E-11
6.66E-15
6.00E-04

0.695525
0.292227
0.011649
3.41E-11
6.66E-15
6.00E-04

0.980182
3.24E-03
0.016582
1.41E-30
1.86E-38
5.59E-14

4.67E-10
7.54E-04
0
3.05E-03
3.84E-08
0.996195

0.050397
0.021118
0.839596
0.010587
3.66E-03
0.074642

0.050397
0.021118
0.839596
0.010587
3.66E-03
0.074642

0.311408
0.131189
5.22E-03
0.065765
0.022732
0.46369

0.311408
0.131189
5.22E-03
0.065765
0.022732
0.46369

3.93E-10
6.35E-04
6.77E-22
0.119082
0.041161
0.839123

3.93E-10
6.35E-04
6.77E-22
0.119082
0.041161
0.839123

0.023378
0.974605
6.38E-07
1.14E-10
2.24E-14
2.02E-03

1.21E-16
2.77E-08
0
0.735042
0.259665
5.29E-03

0.325107
1.75E-12
324.7749
6.25E-33
5.86E-40
1.82E-28

60.6749
36.20303
0.325093
8.02E-09
1.73E-12
0.097299

60.6749
36.20303
0.325093
8.02E-09
1.73E-12
0.097299

60.06815
0.281655
0.325088
2.33E-28
3.39E-36
6.37E-12

4.23E-08
0.096973
0
0.745911
1.04E-05
167.7348

61
36.3
325.1
34.6
13.2
168

61 60.6749 60.6749 4.23E-08
36.3
36.3
36.3 0.096973
325.1 0.325093 0.325093 2.33E-20
34.6
34.6
34.6
34.6
13.2
13.2
13.2
13.2
168
168
168 167.9027

4.23E-08
0.096973
2.33E-20
34.6
13.2
167.9027

0.606745
35.92137
5.30E-06
8.02E-09
1.73E-12
0.097299

2.06E-15
6.71E-07
0
33.85409
13.19999
0.167905

1.00E-03
5.39E-15
0.999
1.92E-35
1.80E-42
5.59E-31
10139.11
325.1
0.436919
64.54242
1
0
1
0
-1.01E+05
-3144.77
-2.25E+06
-54.6065
-1.70305
1.448699
46.45104
32.06397
0.409224

0.623584
0.372075
3.34E-03
8.25E-11
1.78E-14
1.00E-03
870.9622
97.30032
0.132459
111.7358
0.5
0
1
0
-1.25E+05
-1119.95
-2.40E+05
-150.178
-1.34429
0.410485
45.85768
111.7159
0.118702

0.623584
0.372075
3.34E-03
8.25E-11
1.78E-14
1.00E-03
870.9622
97.30032
2.842926
105.7677
0.4
0.04066
0.95934
0
-1.25E+05
-1119.95
-2.40E+05
-150.167
-1.34418
0.019126
2.136623
111.7159
0.118702

0.99
4.64E-03
5.36E-03
3.84E-30
5.58E-38
1.05E-13
611.8437
60.6749
0.080712
87.42967
0.3
0
1
0
-1.19E+05
-1197.33
-1.60E+05
-133.647
-1.34769
0.473241
46.93003
99.16732
0.074217

2.51E-10
5.75E-04
0
4.42E-03
6.15E-08
0.995
904.0239
168.5777
0.167436
203.7664
0.2
0
1
0
-2.74E+05
-1471.11
-5.47E+05
-199.048
-1.06742
0.337063
62.85384
186.4748
0.136304

0.095581
0.056879
0.509401
0.054215
0.020683
0.26324
12084.39
638.2
0.746372
30
1.4
0
1
0
-1.23E+05
-2325.14
-3.27E+06
-81.959
-1.5519
1.010761
53.38024
52.81194
0.71862

1.96E-10
4.49E-04
1.08E-22
0.160334
0.061168
0.778049
1074.319
215.7997
6.669589
239.4114
0.5
0.072696
0.927304
0
-2.69E+05
-1338.72
-6.37E+05
-210.447
-1.04767
0.010056
2.019905
200.8711
0.190695

0.016566
0.980777
1.45E-07
2.19E-10
4.73E-14
2.66E-03
259.1185
36.62542
0.051851
152.8729
0.361241
0
1
0
-1.40E+05
-988.777
-79839.1
-193.018
-1.36557
0.311973
44.09618
141.3462
0.044484

4.37E-17
1.42E-08
0
0.716914
0.279531
3.56E-03
170.2954
47.22199
0.07943
278.9174
0.308874
0
1
0
-2.74E+05
-986.84
-1.03E+05
-313.362
-1.13007
0.133843
37.11396
277.2946
0.05439

0.095581
0.056879
0.509401
0.054215
0.020683
0.26324
12084.39
638.2
0.746379
30.00667
1.2
0
1
0
-1.23E+05
-2325.14
-3.27E+06
-81.958
-1.55188
1.010752
53.37978
52.81194
0.71862

0.193788
0.115937
1.04E-03
0.110508
0.042159
0.53657
1945.282
313.1
0.386715
174.8753
1.095264
0
1
0
-2.09E+05
-1299.54
-8.97E+05
-186.785
-1.16049
0.31403
50.54419
160.9536
0.309396

0.193788
0.115937
1.04E-03
0.110508
0.042159
0.53657
1945.282
313.1
14.97589
161.9659
0.6
0.12846
0.87154
0
-2.09E+05
-1299.54
-8.97E+05
-186.715
-1.16005
8.11E-03
1.305177
160.9536
0.309396

1.96E-10
4.49E-04
1.08E-22
0.160334
0.061168
0.778049
1074.319
215.7997
0.251177
247.7904
0.629287
0
1
0
-2.69E+05
-1338.72
-6.37E+05
-210.469
-1.04778
0.267013
53.63523
200.8711
0.190695

* 1-HEX-01: Methyl hexanoate; 1-NON-01: Methyl nonanoate; METHA-01: Methanol;
METHY-01: Methyl palmitate; METHY-02: Methyl stearate; DMA: Dimethyl azelate.

105

Operating pressure for column B1 is the highest among all the columns, which is about 1
atm. The reason is methanol is much more volatile than methyl hexanoate, so it can be
separated under atmospheric pressure and at lower temperatures. Pressure for column B2
is around 0.5 atm, and B3 is between 0.3 and 0.36 atm. This design was based on the
consideration of the lower volatility of methyl hexanoate and methyl nonanoate, as at
lower pressure the operation temperature is also lower, it will reduce the energy cost for
the condenser. Since dimethyl azelate as well as the other two heavier saturated FAMEs
are less stable than the other products separated in previous columns, the column for
separating dimethyl azelate (B4) is run under the lowest pressure which is between 0.2
and 0.3 atm.
Table 4.6 shows the simulation results for reboiler and condenser. As indicated by the
table, column B1 has the highest heat duty value. The reason for this is that methanol
takes more than 60% in molar ratio in the total mixture and therefore it requires much
more energy to be removed. The distillation rate for column B1, B3 and B4 are almost
equal to the feed rate of methanol, methyl hexanoate and methyl nonanoate, which
indicates that the products were recovered with high rate. Reflux ratio is related to the
number of stages and will increase if the stage number is decreased. In this design since
twice of the minimum number of stages was chosen as the specification, the reflux ratio
was determined by that.

106

Table 4.6 Reboiler and condenser design specification for separating products from
ozonolysis of FAMEs in methanol

Reboiler
Name

Temperature

Heat duty

Distillate rate

Reflux rate

Reflux ratio

Units

℃

Btu/hr

mol/hr

mol/hr

B1

64.542419

-396828.13

10139.1075

1725.44119

0.170176832

B2

111.735738

-51219.8979

870.962411

294.894087

0.338584172

B3

87.429614

-39455.7231

611.843845

453.059307

0.740481924

B4

203.76638

-84399.1429

904.023843

591.083631

0.65383633

Boilup ratio

Condenser
Name

Temperature

Heat duty

Bottoms rate

Boilup rate

Units

℃

Btu/hr

mol/hr

mol/hr

B1

174.875332

517311.533

1945.28156

10709.717

5.50548425

B2

247.790382

71106.5553

1074.31924

1277.80933

1.18941305

B3

152.872912

39694.8148

259.118566

841.015965

3.24568007

B4

278.917162

71826.9239

170.295402

1038.05137

6.09559248

The number of stages will reflect the difficulty for separation given the requirement for
the purity of products. In this process, the higher number of stages appears in column B2
and column B4. B2 is used to separate methyl hexanoate and methyl nonanoate from
dimethyl azelate and B4 is designed to separate dimethyl azelate from methyl palmitate.
Both of the two separations are more difficult than the other ones by simply comparing
the boiling point data in Table 4.4.

107

Table 4.7 Distillation column design specification for separating products from
ozonolysis of FAMEs in methanol

Name

Stages

Feed Stage

Tray Spacing

Height

Diameter

m

m

m

Units
B1

15

10

0.2

3.12

0.4925

B2

20

9

0.2

4.32

0.2262

B3

10

6

0.2

1.92

0.1976

B4

17

12

0.2

3.6

0.2969

Feed stage was optimized by choosing the one that gives the minimum cooling duty for
the condenser. The initial guess for the feed stage was the middle stage of the column,
while varying the number by increasing or decreasing it the minimum cooling duty
appeared after several trials. As listed in Table 4.7, the optimal feed stage is close to but
not always the middle stage. Since the amount of production specified in this study is not
very high, a small spacing was defined so the column will not be too tall and thin.
4.6.2 Distillation design for products obtained from ozonolysis in water
Design for the distillation for separating products obtained from ozonolysis of FAMEs in
water system is simpler than that for the methanol system products. The reason is that no
solvent is present in this mixture, so only 3 columns are required instead of 4. As
indicated in Figure 4.2, the first column separates hexanal and nonanal from the rest of
the materials. Following the first column, two parallel columns separate hexanal, nonanal
and methyl 9-oxononanoate respectively and leave the two saturated esters as a byproduct
108

mixture. This design was based on hexanal productivity of 1 ton/day. The reason for this
assumption is that based on the same amount input of FAMEs, the ratio of mass yield of
dimethyl azelate from methanol system to that of hexanal from water system is about
3.8:1; since dimethyl azelate and hexanal are primary products from the two reactions
respectively and dimethyl azelate productivity was assumed 4 tons/day in the previous
design, production of hexanal was chosen as 1 ton/day for comparison.
The separation results are shown in Table 4.8. The product hexanal came from column
C2 as D2 with a mass fraction of 0.999 with recovery of 0.993, and nonanal was
separated from the same column as R2 with a lower mass purity of 0.966 and recovery of
0.992. Column C3 was responsible for the purification of methyl 9-oxononanoate which
was recovered with a mass ratio of 0.99 and recovery of 0.993. The purity of nonanal is
relatively lower because we wanted to guarantee the purity of methyl 9-oxononanoate,
however, at the same time more methyl 9-oxononanoate was also lost in the nonanal
stream. As shown in Table 4.8, the mass fraction of methyl 9-oxononanoate was 0.025 in
stream R2.
Low pressure was also applied for this distillation process, for example, C1 was under
pressure 0.3 atm, C2 under 0.2 atm and C1 under around 0.1 atm. The pressure for
downstream columns is lower than upstream for two reasons: 1) to save the cost from
using pumps (because the pressure of output stream from the previous column will be
higher than the operating pressure of feed stage in the next column so no pump is needed
to increase the pressure of feed stream) and to reduce the separation temperature so that
heavy compounds can be protected from decomposing.

109

C2

V2

C1

D1B

D1A

R2

V1
FEED1

D2

FEED2
V3
R1A

R1B

D3

C3
R3

Figure 4.2 Distillation design in Aspen Plus for products made in water using ozonolysis. D2: hexanal; R2: nonanal; D3:
methyl 9-oxononanoate; R3: methyl palmitate and methyl stearate.

110

Table 4.8 Distillation result for products from ozonolysis in water*
D1A
V2
C1
LIQUID
Substream: MIXED
Mole Flow kmol/hr
1-HEX-01
1-NON-01
M-9OXO
M-PALM
M-STEA
Mole Frac
1-HEX-01
1-NON-01
M-9OXO
M-PALM
M-STEA
Mass Flow kg/hr
1-HEX-01
1-NON-01
M-9OXO
M-PALM
M-STEA
Mass Frac
1-HEX-01
1-NON-01
M-9OXO
M-PALM
M-STEA
Total Flow kmol/hr
Total Flow kg/hr
Total Flow l/min
Temperature C
Pressure bar
Vapor Frac
Liquid Frac
Solid Frac
Enthalpy cal/mol
Enthalpy cal/gm
Enthalpy cal/sec
Entropy cal/mol-K
Entropy cal/gm-K
Density mol/cc
Density gm/cc
Average MW
Liq Vol 60F l/min

D1B
C2
V2
MIXED

D2

D3

C2
LIQUID

C3
LIQUID

FEED1
V1
LIQUID

FEED2
C1
V1
LIQUID

R1A
V3
C1
LIQUID

R1B
C3
V3
MIXED

R2

R3

C2
LIQUID

C3
LIQUID

0.416331 0.416331 0.4135592 4.04E-12 0.416331 0.416331 4.04E-12 4.04E-12 2.77E-03 2.32E-19
0.1935185 0.1935185 2.92E-04 1.22E-03 0.1947395 0.1947395 1.22E-03 1.22E-03 0.193227 7.97E-09
3.75E-03 3.75E-03 5.03E-17 0.6742244 0.6786536 0.6786536 0.6748993 0.6748993 3.75E-03 6.75E-04
3.26E-11 3.26E-11 3.76E-39 4.05E-03 0.1279322 0.1279322 0.1279322 0.1279322 3.26E-11 0.123885
4.47E-15 4.47E-15 5.01E-49 6.16E-07 0.0442197 0.0442197 0.0442197 0.0442197 4.47E-15 0.044219
0.6785013 0.6785013 0.9992956 5.94E-12 0.2847923 0.2847923 4.76E-12 4.76E-12 0.0138761 1.38E-18
0.3153801 0.3153801 7.04E-04 1.80E-03 0.133212 0.133212 1.44E-03 1.44E-03 0.9673288 4.72E-08
6.12E-03 6.12E-03 1.22E-16 0.9922461 0.4642347 0.4642347 0.7956164 0.7956164 0.018795 4.00E-03
5.32E-11 5.32E-11 9.10E-39 5.96E-03 0.0875123 0.0875123 0.150815 0.150815 1.63E-10 0.7340073
7.29E-15 7.29E-15 1.21E-48 9.07E-07 0.0302485 0.0302485 0.0521291 0.0521291 2.24E-14 0.2619939
41.7
41.7 41.42237 4.05E-10
27.52633 27.52633 0.0414643 0.1736737
0.6992568 0.6992568 9.37E-15 125.575
8.82E-09 8.82E-09 1.02E-36 1.094577
1.33E-12 1.33E-12 1.50E-46 1.84E-04
0.5963483
0.3936517
0.01
1.26E-10
1.91E-14
0.6136039
69.92558
1.539877
88.36302
0.20265
0
1
0
-71957.75
-631.4364
-12264.88
-157.0764
-1.378361
6.64E-03
0.7568307
113.9588
1.417068

0.5963483
0.3936517
0.01
1.26E-10
1.91E-14
0.6136039
69.92558
1.540002
88.36302
0.20265
8.26E-08
0.9999999
0
-71957.75
-631.4364
-12264.88
-157.0764
-1.378361
6.64E-03
0.7567696
113.9588
1.417068

0.999
1.00E-03
2.26E-16
2.46E-38
3.61E-48
0.4138507
41.46384
0.892541
61.83982
0.101325
0
1
0
-67406.44
-672.784
-7748.946
-138.7853
-1.385217
7.73E-03
0.7742658
100.1903
0.8451901

3.19E-12
1.37E-03
0.99
8.63E-03
1.45E-06
0.6794931
126.8435
1.9403
139.3845
0.020265
0
1
0
-1.58E+05
-846.744
-29834.43
-212.4984
-1.138342
5.84E-03
1.089552
186.6737
1.711824

41.7
27.7
126.4
34.6
13.2
0.1711823
0.113711
0.5188834
0.1420361
0.0541871
1.461876
243.6
4.282013
30
0.303975
0
1
0
-1.30E+05
-777.2402
-52593.26
-223.9689
-1.344067
5.69E-03
0.9481522
166.6352
3.99096

41.7 4.05E-10 4.05E-10 0.2776255 2.33E-17
27.7 0.1736749 0.1736749 27.48486 1.13E-06
126.4 125.7007 125.7007 0.6992568 0.1257007
34.6
34.6
34.6 8.82E-09 33.50542
13.2
13.2
13.2 1.33E-12 13.19982
0.1711823
0.113711
0.5188834
0.1420361
0.0541871
1.461876
243.6
4.282013
30.00001
0.303975
0
1
0
-1.30E+05
-777.2402
-52593.26
-223.9689
-1.344067
5.69E-03
0.9481522
166.6352
3.99096

2.33E-12
1.00E-03
0.7237724
0.1992234
0.0760042
0.8482721
173.6744
3.236708
226.3106
0.3336504
0
1
0
-1.52E+05
-740.8897
-35742.66
-224.918
-1.098559
4.37E-03
0.8942956
204.739
2.573892

2.33E-12
1.00E-03
0.7237724
0.1992234
0.0760042
0.8482721
173.6744
354.0339
210.1464
0.20265
0.1264302
0.8735698
0
-1.52E+05
-740.8897
-35742.66
-224.8554
-1.098254
3.99E-05
8.18E-03
204.739
2.573892

9.75E-03
0.9656774
0.0245683
3.10E-10
4.69E-14
0.1997532
28.46174
0.6527915
134.6971
0.1909568
0
1
0
-80644.74
-565.9893
-4474.734
-197.4914
-1.386055
5.10E-03
0.7266675
142.4846
0.5718774

4.97E-19
2.42E-08
2.68E-03
0.7154548
0.281861
0.168779
46.83094
1.086376
269.6369
0.0823178
0
1
0
-1.52E+05
-547.6892
-7124.667
-337.795
-1.217415
2.59E-03
0.718458
277.469
0.8620683

* 1-HEX-01: Hexanal; 1-NON-01: Nonanal; M-9OXO: Methyl 9-oxononanoate; M-PALM:
Methyl palmitate; M-STEA: Methyl stearate.

111

Table 4.9 Reboiler and condenser design specification for products from ozonolysis in
water

Reboiler
Name

Temperature

Heat duty

Distillate rate

Reflux rate

Reflux ratio

Units

℃

Btu/hr

mol/hr

mol/hr

C1

88.363021

-2209.78869

0.613603904

0.070668387

0.115169389

C2

61.8398209

-1380.98729

0.413850746

0.105092911

0.253939159

C3

139.384487

-3639.2395

0.679493113

0.178110906

0.262123195

Boilup ratio

Condenser
Name

Temperature

Heat duty

Bottoms rate

Boilup rate

Units

℃

Btu/hr

mol/hr

mol/hr

C1

226.310557

6795.50243

0.848272141

1.67028069

1.96903872

C2

134.697143

1422.18368

0.199753158

0.418675701

2.09596536

C3

269.636922

2422.80584

0.168779028

0.372716149

2.20830842

The heat duty for this distillation process (Figure 4.9) is significantly lower compared to
the one designed to separate products of ozonolysis of FAMEs in the methanol system.
Firstly, this observation can be explained by the fact that the mass productivity for this
process is much lower (almost 25% of the previous process for ozonolysis products
obtained in methanol system). Secondly, there is no solvent that needs to be separated,
which constituted a substantial fraction of the feed in the methanol system. Besides,
reflux ratio can also affect the heat duty, since lower reflux means less material will go
back to the column and thus less heat will be spent on repeatedly heating or cooling.

112

Compared to the previous process the reflux ratios for the reboiler in this process are
much lower, so the heat duty was also reduced.
The stage number was also determined by doubling the number of minimum stages and
feed stage was optimized by the same method. Tray spacing was also the same as the
former process. Table 4.10 shows that column C1 has the highest stage number and C3
has the lowest, this may be because the difference between boiling point of nonanal and
methyl 9-oxononanoate (58.4 ℃) is slightly smaller than that between hexanal and
nonanal (60 ℃), and between methyl 9-oxononanoate and methyl palmitate (167.6 ℃).
Table 4.10 Distillation column design specification for products from ozonolysis in water

Name

Stages

Feed Stage

Tray Spacing

Height

Diameter

m

m

m

Units
C1

20

8

0.2

4.32

0.2975

C2

14

9

0.2

2.88

0.1742

C3

10

5

0.2

1.92

0.3699

The profiles from both of the two distillation processes based on the same hourly input of
FAMEs (360.7 Kg/hr) were summarized and compared in Table 4.11 in terms of purity,
mass yield, recovery and the heat duty of reboilers and condensers. It is shown that most
final products have a very high purity (> 0.99) except methyl nonanoate (0.981) and
nonanal (0.966). This happened was because we gave higher priority of purity to
dimethyl azelate than methyl nonanoate and to methyl 9-oxononanoate than nonanal
when separating the neighbor compounds, as we assumed the two products may be more

113

valuable. The recoveries of the products are all between 0.98 and 0.999, which means
that most of the product was recovered during the distillation. The biggest d ifference
resides in the heat duty of the reboilers and the condensers. The heat duty of the methanol
system distillation process is more than 70 times of the water system process. This was
caused by the existence of the methanol in the first system, and if we exempt the heat
duty from the columns for separating methanol (column B1), the heat duty ratio of the
first distillation process to the second process dropped to about 20 : 1. From this we
conclude that the distillation cost for the water system ozono lysis products cost much less
in terms of the energy consumption, and considering the number of distillation column
required for the methanol system products is also larger than the water system products,
the overall cost of the separation of water system products is much more advantageous.

Table 4.11 Comparison of two distillation processes based on the same input of FAMEs*

Systems

Methanol

Water

Products

Product
purity

Product flow
rate (Kg/hr)

Mass yield
(Kg/100 Kg)

Recovery

Methyl hexanoate

0.990

60.07

14.02

0.985

Methyl nonanoate

0.981

35.92

8.30

0.990

Dimethyl azelate

0.995

167.73

39.45

0.998

Hexanal

0.999

41.42

11.46

0.993

Nonanal

0.966

27.48

7.63

0.992

Methyl 9-oxononanoate

0.990

125.58

34.76

0.993

* Input flow rate of FAMEs was 360 Kg/hr, which was 8.6 tons/day.

114

Heat duty
(Btu/hr)

1271842.72

17870.51

4.7 Conclusion
In this chapter two distillation processes for separating two sets of ozonolysis products
were designed for a small industrial operation and evaluated with simulation results.
Distillation sequence was firstly determined by heuristic method by taking in
consideration the molar fraction, thermal stability and the reactivity of the materials.
Based on this sequence, the distillation columns were designed with specification of stage
number, dimension, operating temperature and pressure, reflux ratio and the optimal feed
stage. Most of the purity of products from the two distillation processes are higher than
0.99, except for methyl nonanoate (0.981) in methanol system and nonanal (0.966) in
water system. Recovery of main products are also satisfactorily higher than 0.98.
Comparing the two processes, it was found that the heat duty spent on separating
ozonolysis products from water system was much lower than that for products from
methanol system, even after considering the difference between the productions. The
reason was that the products from the water system do not contain solvent and also the
compounds were more volatile in average.
Considering the yields of reaction, as well as the separation result and energy
consumption of distillation for both ozonolysis process in methanol and water, the water
system is more economical as far as separations is concerned and should be
recommended for industrial development.

115

Chapter 5: Simulation of Wiped Film Distillation in Aspen Plus
5.1 Introduction
Molecular distillation, according to G. Burrows (1960), is a type of short-path distillation
under a high vacuum [93]. High vacuum is applied to reduce the obstruction exerted by
the air, and the short path between the central condenser and the surrounded heating
surface is used to ease the condensation process for the product vapor molecules.
However, high vacuum for molecular distillation is not always applied and it depends on
the materials, for example, in this project the pressure was set between 0.03 atm and 1
atm.
There are three different types of molecular evaporators, which differ by the way the film
is formed. These are 1) falling film evaporator, 2) centrifugal film evaporator and 3)
wiped film evaporator. Falling film evaporator was the first to be introduced among the
three types. Falling film evaporators work using gravity that drives the feed down along
the evaporator wall. During this process, a film is naturally formed on the internal surface
of the jacket. However the disadvantage of this evaporator is that the film is not evenly
spread, especially for high-viscosity material. To compensate this drawback of falling
film evaporator, the wiped film evaporator was designed and patented in the 1960s [94].
The modification was done by installing a wiper, which consists of several tubes or
blades fastened on a circular frame nested inside the column. When the wiper rotates, the
liquid material will be evenly spread on the wall.
Wiped film distillation (WFD) is widely used to separate many materials in industry
especially for sensitive materials, such as natural pigment, vitamins, essential oil and

116

polyunsaturated fatty acids, because it has a short reside nce time, high heat transfer
efficiency and good ability in handling viscous fluids [95].
WFD has been used for more than half century, however, simulation study on it is still
not mature. Most of the available research was conducted on falling film distillation,
because it is easier to describe with numerical equations [96]. However, according to
former studies on wiped film distillation, two ways were applied to set up the model. One
is a numerical method, which was firstly developed by Kern and Karakas (1958), who
developed the design equations based on heat and mass transfer, hydrodynamics and
rheology principles to explain wiped film distillation [97]. Later, Li et al. (2006) studied
the fluid mass transfer and heat transfer in wiped film evaporator using a 2 dimensional
model solved numerically [98]. More recently, in S. Zeboudj’s research, the liquid flow
in a wiped film evaporator was represented by the model of a series of paralleled mixed
cells with dead zone, and the model was developed using the DTS Pro software [99]. The
alternative non-numerical approach is to simulate WFD in a flash evaporator. G. Gruber
in 1989 modeled the separation of a complex final product with ASPEN by assuming it
as a multiple-stage flash [100]. By inputting Fortran code into Aspen, the author was able
to predict the purity and recovery of the product. However, no detailed results showed
how good the model can fit the experimental data, neither the effect from the operating
conditions. In general, a body of study has been done in this area for tens of years, which
could not satisfy the correspondence of experimental data and universality in application.
Moreover, most studies were conducted based on 2 or 3 components in relatively simple
systems [101], which reduced the complexity of the model.

117

The aim of this study is to develop a model using ASPEN to simulate the separation
process of WFD for 3 different multi-component systems and then compare the modeling
result with experimental data to demonstrate the accuracy of the simulation and the
method.
Aspen Plus is a well know software for separation design, chemical processing
simulation and optimization, as well as property analysis and estimation, and it has been
widely used in industry for over 25 years. Since it is a well-developed simulation tool
with up-to-date databanks, it can be reliably integrated in a plant simulation along with
other unit operations.
Unlike fractional distillation, WFD is not an equilibrium process, and the system in the
column is not homogeneous either. Temperature on the wall side is much higher than that
on the condenser side and thus, the partial pressure for the material on different sides is
also different. Due to this difference, molecules are driven from the heating wall to the
condenser, and on the other hand, the driving force is also strengthened by the process of
condensation. However, according to Burrows [93], if we take the whole process of
continuous molecular distillation as an entity, it is similar to regular distillation (e. g.
flash separation) based on the fact that it follows Raoult’s law, which means the partial
vapor pressure of each component in the mixture is equal to the vapor pressure of the
pure component multiplied by its mole fraction in the mixture. No substantial literature
was found on equilibrium simulation of WFD, like the earliest study conducted by
Gruber [100] in 1989, who simulated WFE in Aspen Plus as a series of co-current flash
tanks, where the material were assumed following through a series of flash evaporators
successively until the calculated vapor and liquid composition reached to steady value.
118

The total amount of distillates exiting from all of the flash evaporators was eq ualed to the
vapor stream in original data. Liquid entrainment was described as a function of vapor
velocity, heat transfer coefficient as a function of hot oil flow rate and temperature, and
heat loss as a function of ambient temperature using Fortran code. However, as
mentioned previously, no comparison between modeling and experimental data was
shown in this publication, and no information about operating pressure was mentioned.
Jacinto Lopez- Toledo [101] also performed studies on equilibrium simulation of WFD
and assumed the wiped film evaporator as a one-stage flash separator. Corresponding
equations consisting of flash mass balance and heat transfer coefficient were developed
and an Excel-based program was built to do solve the equations. Three different 2component mixtures were used to verify the model, with relative errors that varied
between -20% and 20%. Similar to the study by Gruber [100], this paper also didn’t give
much emphasis to the impact of pressure on the separation efficiency. Chuaprasert
introduced a data reconciliation process of an agitated thin film evaporator using Aspen
Plus in 1999 [102], and this model consisted of one heat exchanger and one flash
separator, and an objective function containing multiple variables was cho sen to be
minimized. This model could increase the fit between measured values and the process
model by about 60%. The evaporator used in that study is different from what is
presented herein, as that study used an external condenser, and the evaporation
temperature and pressure were not included as independent variables.

119

5.2 Experiment
5.2.1 Materials
The two-component mixture was prepared by mixing methanol and methyl hexanoate (>
99.9% mass fraction) in two mass ratios: 27:73 and 51:49. Methyl ester mixture was
generated from ozonolysis of soybean FAMEs, in which 7 main components take up
more than 90% mass fraction. The composition in mass was: methanol: 21.4%, water
3.8%, methyl hexanoate 11.5%, methyl nonanoate 7.7%, dimethyl azelate 33.2%, methyl
palmitate 8.6%, methyl stearate 3.4% and impurity 10.4%. FAMEs were obtained from
Zeeland Inc., and the mass fraction for each component is: methyl palmitate 10.1%,
methyl stearate 4.2%, methyl oleate 21.9%, methyl linoleate 51.7%, methyl linolenate
6.8% and impurity 5.3%.
5.2.2 Analytical methods
Quantitative analysis was conducted using the same gas chromatography machine as
described in Chapter 2, with the same capillary column as well as the same carrier and
makeup gas. Sample prepared from ozonolysis was analyzed with this method: injector
and detector temperature were set up at 250 ℃; column temperature initially started at 50
℃, after 2mins, it slowly increased to 240 ℃ at a rate 5 ℃/min and stayed for 2 mins. For
methanol and methyl hexanoate system, a similar method was applied except for the
terminal temperature, which was 100 ℃ instead of 240 ℃. For FAMEs, the analysis was
run using EN14103 FAME content method (Agilent Technologies) [103].

120

5.2.3 Wiped film distillation
Wiped film distillation was carried out using ICL-04A wiped film evaporator (by InCon
Processing, L.L.C.). The flow rate of feed was varied between 0.1 and 2 L/hr;
temperature was set between room temperature (25 ℃) and 300 ℃ and the operating
temperature applied was in a range of 20 mmHg to 760 mmHg. As shown in Table 5.1
and Figure 5.1, the height of the evaporator (A) is 23.1 cm, and the inner diameter is 9.6
cm, with the total capacity of 0.987 L. The heating area (A-3) covered a height of 19.1
cm, which has the same height as the 3-tube wiper (A-2), while the condenser finger (A6) is about 2 cm shorter than them. The external diameters of the condenser and the wiper
are 2.3 cm and 1.3 cm respectively. According to Figure 5.1, material to be separated was
supplied by a peristaltic pump (C) into the column, and then it fell down under the force
of gravity, once the liquid reached to the area contacting with wipers, it was spread
evenly on to the inner surface of wall. At the same time, the mixture was heated up by the
internal wall that was in contact with circulating hot oil from the jacket (controlled by
Thermal H350 from Julabo Inc.). Some fraction of the mixture was evaporated and part
of the vapor molecules would be condensed when they reach the surface of the condenser
(operated by circulating cooling water). Condenser temperature was kept at 3 ℃
constantly to insure high condensation efficiency. Two flasks were connected to the
column to collect distillate and residue.

121

Table 5.1 Dimensions of ICL-04 wiped film evaporator

Element

Total Column

Dimension Height

Heating Area

Condenser

Wiper

V

ID

Height

Height

ED

Height

ED

Unit

cm

L

cm

cm

cm

cm

cm

cm

Value

23.1

0.987

9.6

19.1

17.2

2.3

19.1

1.3

No.

3

*ID: Inner diameter; ED: External diameter.

Figure 5.1 Wiped film evaporator and adjunctive facilities. A. Wiped film evaporator; A1. Rolling speed meter; A-2. Wiper; A-3. Heating area; A-4. Dry ice trap; A-5. Pressure
gage; A-6. Condenser; B. Oil heating system; C. Peristaltic Pump; D. Material container;
E. Vacuum pump; F. Water cooling system.

122

5.2.4 Simulation in Aspen Plus
In Aspen Plus, FLASH2 was used to set up a one-stage flash separation process to
simulate WFD, and the process was adiabatic. Since there are many parameters that can
affect separation result in WFD than in flash process, some parameters were fixed in
WFD. In this study, the volumetric flow rate, temperature and pressure of the feedstock
were fixed; the rolling speed of the wiper and cooling temperature in condenser were also
fixed. Detailed values for these parameters will be given in the next section. The only
variables that were studied were the heating temperature and pressure.
The flow rate and temperature of feed stream in Aspen was set up as the same as the one
used in WFD (and it is always a constant value). The flow rates of all the components
from the distillate stream were chosen with the objective to be matched for both the two
processes. An objective function (Equation 5.1) was derived for this system, which
should be minimized for fitting experimental data with the model predictions. The
weighting factor for each flow rate was reasonably assumed as 1 [104]. For each batch of
separation in WFD, Aspen had the same temperature fixed, while pressure was adjusted
iteratively. An optimum pressure under which the objective function reached to the
lowest value was recorded as the final result for that batch.
The optimal fitting pressure was found out using the function “Sensitivity” in Aspen,
which automatically calculates the distillation results for a series of different pressures.
To determine which pressure is the most adequate, Equation 5.1 was inputted into
Tabulate tab in Sensitivity module in Aspen.

123

2

n

FN   Ci M i  mi  / mi 

(Equation 5.1)

1

In this function (Equation 5.1), Ci is the weight factor, which equals to 1 for all the
elements; Mi (i=1, 2, … n) is the mass flow rate (lb/hr) of each component in distillate
stream based on Aspen simulation result, while mi (i=1, 2, … n) is the mass flow rate
(lb/hr) of each component in distillate stream from experimental WFD data. The sum of
flow rate of distillate and residue were assumed equal to the flow rate of input stream.
After calculation was finished in Aspen, pressure under which FN reached to the
minimum value was recorded. Usually this pressure was lower than the running pressure
in WFD.
5.3 Results and discussion
5.3.1 Affecting factors in WFD There are many factors that can affect the separation
results in WFD, and these include flow rate, temperature and pressure of feed stream,
temperature and pressure of column, rolling speed and blades number of wiper and
cooling temperature of condenser. To examine the effect of these factors on the
separation efficiency in WFD, we chose different conditions as the variables to run the
experiment, and the consequent results are shown in this section.

124

Mass Fraction of Distillate (%)

100

80

60

40

20

60

80

100

120

140

160

o

Oil Temperature ( C)

Figure 5.2 Effect of heating temperature on the ratio between distillate and feed using
ozonolysis product with input flow rate of 3 ml/min and wiper rolling speed of 250 rpm,
under still pressure of 2.7 kPa.
As shown in Figure 5.2, the mass fraction of distillate increased almost exponentially
with the increase of heating temperature, which means the heating temperature can affect
the separation results significantly. Composition of distillate also changed dramatically
with the variation of heating temperature (from 60 to 160 ℃) (Figure 5.3). At lower
temperature, the main component in distillate was methyl hexanoate, followed by methyl
nonanoate and dimethyl azelate, and this result was coincident with the order of boiling
point of the three components; however, when heating temperature was increased, the
mass fraction of dimethyl azelate in distillate started to increase gradually. After the
temperature was above 120 ℃, the main component in distillate was already dimethyl
azelate. This increasing tendency was kept steadily in the following batches which were
125

operated under even higher temperature. This indicates that on one hand, higher
temperature tends to increase the amount of distillate, but on the other hand it will also
reduce the separation efficiency. In order to get a product with certain purity, the
temperature must be chosen very carefully, and a tradeoff between the recovery and

Mass Fraction of Components in Distillate (%)

purity should be made based on the observation shown in Figure 5.3.

70

A
B
C
D
E

60
50
40
30
20
10
0
60

80

100

120

140

160

o

Oil Temperature ( C)

Figure 5.3 Effect of heating temperature on mass fraction of components using
ozonolysis product with input flow rate of 3 ml/min and wiper rolling speed of 250 rpm,
under still pressure of 2.7 kPa. A: Methyl hexanoate; B: Methyl nonanoate; C: Dimethyl
azelate; D: Methyl palmitate; E: Methyl stearate.

126

Mass Fraction of Distillate (%)

30

25

20

15

10

5

0

0

5

10

15

20

25

Feeding Material Flow Rate (ml/min)

Figure 5.4 Effect of feed material flow rate on ratio of distillate to feed using ozonolysis
product with wiper rolling speed of 250 rpm, heating temperature of 60 ℃ under pressure
of 2.7 kPa.
Feed flow rate can also affect the separation substantially, especially in the range from 0
to 15 ml/min. With the feeding flow rate varying from 2 to 15 ml/min, the mass ratio of
distillate to feed was decreased as much as 88% (Figure 5.3). This can be explained by
the principle of heat exchange: consider the jacket wall as a small heat exchanger, in
which the cold stream is the material needs to be separated and hot stream is the heating
oil inside the wall, since the higher flow rate will decrease the heat transfer efficiency, the
average temperature in the film turned to be lower than that with the lower flow rate, and
this difference in temperature caused the difference in separation. In Figure 5.4, if the
flow rate was arranged in the reversed order, the trend of the curve would be quite similar
to that in Figure 5.2, which means, the infect of material flow rate is indeed an indirect
127

effect of the heating temperature. Based on the result displayed in Figure 5.4 and
considering the productivity of the separation, we decided to choose 3 ml/min as the flow
rate to run all the future experiments.
20

Mass Fraction of Distillate (%)

18

16

14

12

10

8

6

0

100

200

300

400

Rolling Speed of Wiper (r/min)

Figure 5.5 Effect of wiper rolling speed on ratio of distillate to feed using ozonolysis
product with feed flow rate of 3 ml/min, heating temperature of 60 ℃ under pressure of
2.7 kPa.
Figure 5.5 demonstrated the impact of rolling speed of wiper on the separation result. The
wiper spreads the material evenly on the heating area therefore to increase the heat
transfer, and the faster it rolls, the more homogeneous the film is. The difference in
rolling speed would also affect the average temperature of the liquid, and eventually
affect the separation. It has been seen that with increase of rolling speed, the amount of
distillate also increased, however after the speed reached to 250 rpm, the mass fraction of

128

distillate turned to be steady, so we chose 250 rpm as the rolling speed for all the batches
of experiments.
There are also some other parameters which were not examined that can also affect the
separation result, such as the flow rate of heating oil, the temperature of condenser, etc.
In previous WFD study, some of these parameters have been investigated for the effect
on heat transfer coefficient [101]. Since changing these parameters has to do with
modifying the equipment, we will take them as fixed parameters in this project.
5.3.2 Vapor pressure data comparison and regression
Vapor liquid equilibrium data is the most important factor that can affect the simulation
in Aspen. The databank of Aspen has vapor pressure data for all the compounds that we
would use in this study except dimethyl azelate, which was estimated by molecular
structure using UNIFAC functional groups in group contribution method. To guarantee
the accuracy of the modeling, data obtained from experiment and Aspen databank was
plotted in the same figure for comparison. According to Antoine equation, if 1/T was
used as x axis, and lnP used as y axis, a linear relationship should be observed between
the two. All of the experimental data was obtained from literatures in Reaxys website
[105], and 300 to 500 K was chosen as the temperature range for this comparison, based
on the availability of the data and the operation condition of regular WFD.
As displayed in Figure 5.6, vapor pressure data of methyl hexanoate (C7), methyl
nonanoate (C10) and dimethyl azelate (C11) collected from Aspen fit the experimental
data very well, if not considering a few deviated points. For methyl palmitate (C17) and
methyl stearate (C19), not many experimental data points fell on the line, but on the
129

overall consideration, the fitting was still acceptable. So no regression was really needed
for the five saturated methyl esters.
T (K)
13

500

450

400

350

12

300

C7
C10
C11
C17
C19

11
10
9

lnP (Pa)

8
7
6
5
4
3
2
1
0.0020

0.0024

0.0028

0.0032

0.0036

1/T (1/K)

Figure 5.6 Comparison of vapor pressure for methyl esters from Aspen (continuous data)
and literature (discrete points). C7: methyl hexanoate; C10: methyl nonanoate; C11:
dimethyl azelate; C17: methyl palmitate; C19: methyl stearate.
The vapor pressure data curves for methyl oleate (C18:1) and methyl linolenate (C18:3)
were very close to each other (Figure 5.7). They firstly kept a small distance from each
other at lower temperature, and then joined together above temperature of about 500 K.
The experimental data for C18:1 was a little bit higher than the data curve, which means
C18:1 is more volatile in reality compared to the data in Aspen. However this difference
is not obvious, therefore we also didn’t make any change to the data in Aspen. The two

130

data points at about 640 K, which represent the vapor pressure for both of the two
compounds under 1 atm, fitted very well.
T (K)
650

600

550

500

450

400
C18:1 (literature)
C18:3 (literature)
C18:1 (Aspen)
C18:3 (Aspen)

12

10

lnP (Pa)

8

6

4

2

0

0.0016

0.0018

0.0020

0.0022

0.0024

0.0026

0.0028

1/T (1/K)

Figure 5.7 Comparison of vapor pressure data for unsaturated fatty acid methyl esters
from Aspen and literature. (C18:1): methyl oleate; (C18:3): methyl linolenate.
The most apparent deviation from Aspen estimations was observed in the data for methyl
linoleate (C18:2) (Figure 5.8). Regarding the original data curve obtained from Aspen,
only the experimental data points near 510~530 K fell on it. Most of the experimental
data showed an increasing trend along the temperature with a smaller slope than Aspen
data. Using experimental data, the new parameters for Antoine equation were regressed
and inputted into PLXANT parameter in Aspen. After this operation, the new vapor

131

pressure versus temperature curve was re-run, and the fitness was much better. New
parameter was saved and used for the following simulation calculations.
T (K)
14

650

600

550

500

450

400
Aspen
Literature
Regression

12

lnP (Pa)

10

8

6

4

2
0.0016

0.0018

0.0020

0.0022

0.0024

0.0026

1/T (1/K)

Figure 5.8 Comparison of vapor pressure data of methyl linoleate from Aspen (databank
and after regression) and literature.
5.3.3 Simulation in Aspen for methanol and methyl hexanoate mixture
Two mixtures with different compositions of methanol and methyl hexanoate were
separated using WFD, at temperature from 44 to 180 ℃ and constant pressure of 1atm.
Simulation in Aspen Plus was conducted in the same conditio n as WFD including feed
flow rate and operating temperature except pressure, thermodynamic method NRTL (all
the binary interaction parameters were left empty) and ideal gas phase was chosen in
project specification. Pressure was the only independent variable when running
132

Sensitivity in model analysis tools, and then the fitting pressure for each temperature was
obtained by minimizing objective function (Equation 5.1). Under optimal pressure, it was
found that the flow rates of distillate stream for both of the two components were very
close to the experimental data as shown in Table 5.2.
Table 5.2 Modeling and experimental data comparison of component flow rates in
distillate stream.
Batch 1 [1]
T (o C)

44
55
70
80
90
100
120
130
150
180

Component

M-hex
Meth.
M-hex
Meth.
M-hex
Meth.
M-hex
Meth.
M-hex
Meth.
M-hex
Meth.
M-hex
Meth.
M-hex
Meth.
M-hex
Meth.
M-hex
Meth.

Batch 2 [2]

Flow Rate of Distillate
Stream (lb/hr)
Aspen

Experiment

0.0279
0.0758
0.0714
0.0881
0.0765
0.0878
0.0952
0.0896
0.1145
0.0909
0.1480
0.0929
0.1509
0.0926
0.1673
0.0933
0.1848
0.0939
0.2326
0.0957

0.0270
0.0793
0.0729
0.0864
0.0761
0.0908
0.0952
0.0927
0.1140
0.0948
0.1475
0.0967
0.1531
0.0969
0.1652
0.0986
0.1834
0.1012
0.2366
0.0999

Relative Error
(%)
3.33
-4.41
-2.09
1.99
0.45
-3.36
0.02
-3.35
0.44
-4.06
0.36
-3.95
-1.45
-4.44
1.28
-5.40
0.79
-7.21
-1.71
-4.18

Flow Rate of Distillate
Stream (lb/hr)
Aspen

Experiment

0.0238
0.1456
0.0491
0.1606
0.0725
0.1657
0.0892
0.1682
0.0932
0.1683
0.1040
0.1693
0.1254
0.1713
0.1156
0.1699
0.1314
0.1714
0.1574
0.1739

0.0233
0.1509
0.0469
0.1574
0.0723
0.1675
0.0873
0.1785
0.0900
0.1695
0.1039
0.1714
0.1252
0.1720
0.1148
0.1739
0.1311
0.1762
0.1571
0.1783

Relative Error
(%)
2.37
-3.50
4.78
2.06
0.25
-1.09
2.20
-5.80
3.50
-0.74
0.15
-1.22
0.22
-0.42
0.70
-2.27
0.23
-2.69
0.17
-2.45

[1] Mass fraction of methyl hexanoate was 73%;
[2] Mass fraction of methyl hexanoate was 49%.

From Table 5.2 we can see that the simulation results obtained in Aspen fit the
experimental data very well with a range of relative error from -7.2% to 4.78%, and more
than 82% samples’ relative errors are between -4.0 % and 4.0%.

133

200

Batch1
Batch2

Modeling Pressure from Aspen (psi)

180
160
140

Y2 =-0.50383+0.39532 X2
120
100
80
60

Y1 =-0.11587+0.29959 X1

40
20
0

0

50

100

150

200

250

300

350

400

Pbub (psi)

Figure 5.9 Bubble pressure of mixture versus modeling pressure from Aspen.
In Figure 5.9, the modeling pressures from Aspen were plotted as Y-axis and the bubble
pressures of the mixture at the temperature of heating temperature were plotted as X-axis,
and as shown in the figure, the two pressures form a linear correlation. The slope of the
fitting line for batch 2 is higher than that for batch 1. This may be because the effective
pressure correlates with the distillate fraction, and higher distillate fraction will have a
higher effective pressure, so the more volatile mixture will have a higher effective
pressure. The sample mixture of batch 2 contains higher mass fraction of methanol, it is
therefore more volatile than batch 1 and led to a larger slope of the fitting line.
5.3.4 Simulation in Aspen for ozonolysis product mixture
A mixture prepared by ozonolysis and Oxone oxidization containing 5 methyl esters,
methanol and water was separated using WFD. Most of the compounds in this sample

134

could be identified and quantified, with only 11.2% (mass fraction) as unknown impurity.
Impurity components were defined as one PSEUDO component which as assumed
having the same properties as methyl stearate. Feed flow rate was 3 ml/min (0.3801
lb/hr), condenser temperature was 3 ℃, and the rolling speed of wiper was 250 rpm. For
each batch under different temperature, operation was repeated for 3 times, and the
average flow rate for each component was eventually applied. UNIFAC was chosen as
thermodynamic method, and missing parameters were estimated by Aspen based on the
chemical structures of components. Figure 5.10 shows a satisfactory qualitative
agreement of the results obtained from Aspen and experimental operation. The biggest
error rate did not exceed 10%. Inconformity in fitting may be caused by approximation of
the impurity and estimation of properties of some compounds.

135

0.08

0.08
Experimental
Modeling

0.06
0.05
0.04
0.03
0.02
0.01
0.00

METH WATER

C7

C10

C11

C17

Experimental
Modeling

0.07

Flow Rate (lbs/hr)

Flow Rate (lbs/hr)

0.07

0.06
0.05
0.04
0.03
0.02
0.01
0.00

C19

METH WATER

C7

o

C17

C19

0.08
Experimental
Modeling

0.07
0.06
0.05
0.04
0.03
0.02
0.01
METH WATER

C7

C10

C11

C17

Experimental
Modeling

0.07

Flow Rate (lbs/hr)

Flow Rate (lbs/hr)

C11

b. 90 C

0.08

0.00

C10
o

a. 70 C

0.06
0.05
0.04
0.03
0.02
0.01
0.00

C19

METH WATER

C7

C10

C11

C17

C19

o

o

d. 120 C

c. 100 C

Figure 5.10 Comparison of component flow rate in distillate for experimental and
modeling data of saturated methyl ester mixture. METH: Methanol; C7: Methyl
hexanoate; C10: Methyl nonanoate; C11: Dimethyl azelate; C17: Methyl palmitate; C19:
Methyl stearate.
As demonstrated in Figure 5.11, it still holds true for this multi-component system that
the modeling pressure in Aspen is linear related to the bubble pressure of the mixture,
however, the intercept for the fitting line is much higher than the two-component system
and the slope is much lower.

136

T (K)
340

Modeling Pressure from Aspen (psi)

10

350

360

370

380

390

400

8

Y =1.6808+0.0594 X
6

4

2

0

0

10

20

30

40

50

60

70

80

Pbub (psi)

Figure 5.11 Bubble pressure of mixture versus modeling pressure in Aspen for products
prepared through ozonolysis. Operating pressure was 1 atm, feed flow rate was 3 ml/min,
condenser temperature was 3 ℃, and the rolling speed of wiper was 250 rpm.
5.3.5 Simulation in Aspen for FAMEs mixture
In previous discussion, we have explored the linear correlation between the bubble
pressure of the mixture at heating temperature and the modeling pressure from Aspen
while separating under the same temperature and the operating pressure in WFD was
fixed at 1 atm. In this section, we would like to study on the relationship between the
modeling pressure and operating pressure while the heating temperature of WFD is fixed.
A mixture consisting of five fatty acid methyl esters (FAMEs) was used to study the
equilibrium simulation in Aspen for WFD. Similar to the saturated ester mixture, 5.33%

137

of mass fraction of the sample was impurity, and was defined as one PSEUDO
component, assumed with the same properties of methyl linolenate. Volumetric feed flow
rate was also 3 ml/min, condenser temperature was 3 ℃, and the rolling speed of wiper
was 250 rpm. This time the heating temperature was fixed at 170 ℃, and operating
pressure was varied from 0.493 psi to 7.802 psi. Thermodynamic activity coefficient
model was UNIFAC, and by evaluating the structures of the components the missing
parameters were estimated through group contribution method.
By fitting the distillation results from WFD into Aspen, the optimal pressure of flash
separator in response to each operating pressure of WFD was calculated. A satisfactory
qualitative agreement between the experimental data and Aspen simulation result was
shown in Figure 5.12. Relative error fell in to the range of -10% to 10%。

138

0.030

0.025

Flow Rate (lb/hr)

Flow Rate (lb/hr)

0.025

0.030
Experimental
Modeling

0.020
0.015
0.010
0.005
0.000

C17:0

C19:0

C18:1

C18:2

0.020
0.015
0.010
0.005
0.000

C18:3

Experimental
Modeling

C17:0

C19:0

f. 0.493 psi
0.030

0.025

0.020
0.015
0.010
0.005
0.000

C17:0

C19:0

C18:1

C18:2

C18:3

C18:2

C18:3

0.015
0.010
0.005
C17:0

C19:0

C18:1
c. 3.5 psi

0.030
Experimental
Modeling

0.025

Flow Rate (lb/hr)

Flow Rate (lb/hr)

C18:2

Experimental
Modeling

d. 1.953 psi

0.020
0.015
0.010
0.005
0.000

C18:3

0.020

0.000

C18:3

0.030
0.025

C18:2

0.030
Experimental
Modeling

Flow Rate (lb/hr)

Flow Rate (lb/hr)

0.025

C18:1
e. 1.189 psi

C17:0

C19:0

C18:1

C18:2

0.020
0.015
0.010
0.005
0.000

C18:3

b. 4.9 psi

Experimental
Modeling

C17:0

C19:0

C18:1
a. 7.802 psi

Figure 5.12 Experimental and modeling data comparison of component flow rate in
distillate for separation of FAMEs. C17:0: Methyl palmitate; C19:0: Methyl stearate;
C18:1: Methyl oleate; C18:2: Methyl linoleate; C18:3: Methyl linolenate.
The dependence of component distillate flow rate on operating pressure was obviously
indicated in Figure 5.13. As indicated by the data, operation pressure was much higher
than the simulation pressure in Aspen when operating pressure was higher than about 0.2
psi. The modeling pressure in Aspen increases exponentially with the increase of
operating pressure of WFD. In fact, the actual operating temperature in WFD column is
139

lower than the heating temperature, which is to say, the real temperature in WFD system
is lower than in Aspen. Even under this circumstance, to gain the same separation result
in the flash separator in Aspen it still needs higher vacuum than in WFD.

Modeling Pressure from Aspen (psi)

1.0

0.8

0.6

0.4

0.2

0.0
0

2

4

6

8

Experimental Pressure (psi)

Figure 5.13 Experimental pressure of WFD versus modeling pressure in Aspen for
FAMEs. Operating temperature was 170 ℃, feed flow rate was 3 ml/min, condenser
temperature was 3 ℃, and the rolling speed of wiper was 250 rpm.
5.4 Conclusion
Equilibrium simulation of WFD using one stage flash separation process in Aspen was
developed and evaluated. Feed flow rate and heating temperature for WFD were adopted
by flash separation, and only operating pressure was calculated. The optimum pressure
for flash separator that generates the similar separation results was found out by using
Sensitivity module in Aspen and minimizing the objective function defined in Tabulate

140

tab. Three different mixtures (methanol and methyl hexanoate, products of ozonolysis in
methanol and FAMEs mixture) were used to verify this modeling method, and different
operating conditions including temperature and pressure were applied to conduct
experiments. For all of the mixtures above, satisfactory quantitative agreement was
obtained between experimental and modeling result.
When operating pressure in WFD is fixed, the study showed that modeling pressure in
Aspen was proportional to the pseudo bubble pressure of the mixture at the heating
temperature of WFD, and the slope of the fitting straight line is higher for more volatile
mixture. When operating pressure of WFD increases, the modeling pressure from Aspen
also increases in a higher speed. For FAMEs mixture, it was found that when operating
pressure in WFD was higher than certain value (e. g. 0.2 psi), to have the same separation
result the required pressure in flash separator in Aspen was higher than that in WFD. This
study may contribute to the equilibrium simulation of WFD in the future, and in order to
simulate WFD without depending on preliminary data, further study on the relationship
between operating pressure in WFD and modeling pressure in Aspen is needed. For
example, more experiments using materials with different components and compositions
should be conducted; also more experiments using the same material under different
operating pressures should be carried out in order to examine the relationship between
operating pressure in WFD and modeling pressure in Aspen.

141

Chapter 6: Polyvinyl Acetal Synthesis and Characterization
6.1 Introduction
Polyvinyl acetal polymer (poly-(vinyl acetal)) is usually formed by the reaction of
aldehydes with polyvinyl alcohol (PVOH). During the reaction, adjacent alcohol groups
from PVOH react with one molecule of aldehyde and form an acetal ring. When the
aldehyde participating in the reaction is hexanal, nonanal or 9-oxononanoate, the
consequential polymer will be polyvinyl hexanal (PVH), polyvinyl nonanal (PVN) or
polyvinyl 9-oxononanoate (PVON), which will be the subject of the study in this chapter.
The reactions for the three aldehydes with PVOH respectively are shown in Figure 6.1:

142

*
n

2 *

O

*

+ n

=

*

n
O

OH

O

(A) Reaction for polyvinyl hexanal
*
n

2 *

O

*

+ n

=

*

n
O

OH

O

(B) Reaction for polyvinyl nonanal
*
n

2 *

O

*

+ n

=

*

n
O

OH

O

O
O

O
O

(C) Reaction for polyvinyl 9-oxononanoate
Figure 6.1 Reactions for polyvinyl acetal polymer preparation.
PVOH is a crystalline thermoplastic material which is highly polar and resistant to
hydrocarbons and hard to dissolve in almost any solvent except water. The solubility of
143

PVOH in water depends on the degree of hydrolysis and molecular weight [106].
Completely hydrolyzed PVOH are soluble only in hot water whereas partially hydrolyzed
grades (88 mol%) are soluble at room temperature [107]. In industry, PVOH is used to
make water-soluble films for packaging, barrier layers in multi- layer co-extrusions and
blow moulding containers [108].
In the group of polyvinyl acetal polymers, the most widely used material is polyvinyl
butyral (PVB), which is formed by reaction of butyraldehyde with PVOH. PVB is an
amorphous material which can be used as a safety glass interlayer such as windshield for
vehicles. PVB has this application is due to its high strength, low density, water
resistance, transparence and stickiness to glass. It is also used in adhesives and coatings
[109].
Preparation methods of polyvinyl acetal can be found in several patents [110], and most
methods include addition of acid catalyst such as hydrochloric acid, sulfuric acid, solid
acid, etc. In 1954, a patent from DuPont claimed a continuous process to prepare
polyvinyl acetal in a strong acid aqueous solution (pH 1.5 to 2.5) under 60-100 ℃ and
obtained 69-75% acetalized polyvinyl acetal product [111]. After two years, the above
method was modified by DuPont, in which the reaction of PVOH and aldehyde was
conducted in aqueous solution with the presence of a plasticizer under temperature of 2065 ℃ for 10-100 mins, and afterwards the slurry with product was formed [112]. In 2004,
a Japanese patent application introduced a method of acetalizing PVOH in aqueous
solution with a solid acid as catalyst with application of high pressure (8 MPa) under 100
℃ for 30 mins, the polymerization degree of polyvinyl acetal product was reported as 500
[113].

144

Another method published by Fitzhugh et al.[114] demonstrated the reaction of PVOH
with aldehyde in a mixture of solvents containing both ethanol and 1, 4-dioxane (mass
ratio 1:1) with sulfuric acid as catalyst under 80 ℃ for 9 hrs. After this reaction, the
product was precipitated by washing with water. Since polyvinyl acetal dissolves well in
this solvent, a higher degree of acetalization can be achieved compared to the aqueous
solution process. The disadvantages of this process are the long reaction time and high
cost, and thus it is less feasible for industrial production.
The preparation of PVH can be carried out through all the above mentioned methods,
however, considering the equipment availability and the economic due to usage of
expensive solvents that are not easily recoverable al feasibility of the process we will
only evaluate two methods in this chapter. Three aldehydes (hexanal, nonanal and 9oxononanonoate) obtained from ozonolysis of soybean FAMEs were chosen to react with
PVOH, and the resulting products were characterized and compared among each other as
well as with PVB, a commercial polyvinyl acetal. The properties examined include
decomposition temperature, glass transition and melting temperatures, molecular weight
and degree of acetalization.
6.2 Experiments
6.2.1 Materials
Hexanal (≥ 99%), nonanal (≥ 95%) and 1, 4-dioxane (≥ 99%) were purchased from
Sigma-Aldrich; 200 proof ethanol was purchased from KOPTEC; PVOH (hydroxylation
degree of 99 mol%) and polyvinyl butyral (PVB) were provided by Kuraray America Inc.
In some reactions, hexanal (95%), nonanal (93%) and 9-oxononanoate (88%) were
obtained from ozonolysis product purified through lab-scale fractional distillation.
145

6.2.2 Preparation of PVOH solution
Aqueous solution of PVOH with concentration of 5 wt% was prepared using the
following method: 50 g of PVOH were added slowly into 900 g of cold water (15-25 ℃)
with continuous stirring. At the same time, the slurry was heated until temperature
reached 97- 98 ℃. If PVOH was completely dissolved at this time, 50 g of hot water was
added and the preparation was completed. If not, stirring at this temperature was
continued and hot steam was passed through the slurry. The amount of steam should be
recorded and should not exceed 50 g. After PVOH is completely dissolved, the missing
amount of water between 50 g and the mass of injected steam was added.
6.2.3 Preparation of polyvinyl acetal in aqueous solution
Take 200 g of 5% PVOH aqueous solution, add 15 g of hexanal (or 21.3 g of nonanal or
corresponding weight of material based on 2:1 molar ratio between PVOH and aldehyde)
and 2 g of sulfuric acid, heat up the mixture and keep the reaction run at the temperature
of 75-80 ℃ with mechanical agitation and reflux for 30 mins to 1 hr.
Upon completion of the reaction, polyvinyl acetal will congeal to white lumps and float
on top of the solvent. Filter out the polymer using a Buchner funnel and wash the product
with 100 g of water (to remove PVOH) and 100 g of methanol (to remove aldehyde)
successively. Cut the lumps of polymer into small pieces and wash with water and
methanol one more time, and then put product into oven with temperature maintained at
50-60 ℃ for 24 hrs to dry out.

146

6.2.4 Preparation of polyvinyl hexanal in organic solution
Add 10 g of PVOH to 275 g of 1, 4- dioxane and ethanol mixture (weight ratio 1:1) and
preheat the mixture to 70 ℃ for 1 hr with stirring and then add 15 g of hexanal (or the
same molar amount of other aldehydes) and 2 g of sulfuric acid into this mixture.
Increase the temperature to 75 - 85 ℃ with mechanical agitation at a speed of 1800 rpm
under reflux.
Keep the reaction run for more than 5 hrs with the same temperature and agitation speed
maintained. Upon the completion of reaction, add water into reactor to precipitate the
polyvinyl acetal resin under continuous stirring, and then wash the product with 100 g of
water (to remove PVOH) and 100 g of ethanol (to remove aldehyde and 1, 4-dioxane)
successively. Keep the resin in 5% of KOH solution for 4.5 hrs to stabilize the polymer.
After stabilization, wash the product with water and cut the lumps of polymer into small
pieces, wash with water one more time and then put the product in oven at 50-60 ℃ for
24 hrs for drying.
6.2.5 Thermogravimetric analysis (TGA)
TGA was conducted with a TA Instruments Model TGA Q50 machine (New Castle, DE).
The sample was weighted between 5 and 15 mg and placed into an aluminum pan inside
a platinum pan to avoid contamination. The sample was firstly heated up to 550 ℃ at a
rate of 10 ℃/min with the supply of nitrogen, and when the temperature reached to 550, a
homothermal mode with a time period of 20 mins was applied and the gas was switched
from nitrogen to air to burn the materials completely. Since the material only contains

147

carbon, hydrogen and oxygen molecules, no residue was left in the pan and the final
weight reduced to 0.
6.2.6 Differential scanning calorimetry (DSC)
DSC analysis was carried out in a TA Instruments Model DSC Q20 machine (New
Castle, DE). The sample was weighted between 5 and 10 mg and placed into an
aluminum pan with a compatible lid. The sample was first heated up to 220 or 300 ℃ at a
rate of 20 ℃/min and then cooled down to -50 or -80 ℃ at a rate of 10 ℃/min. Starting at
the lowest temperature, the sample was heated up 220 or 300 ℃ again with 10 ℃/min.
The data from last run from -80 or -50 ℃ to 220 or 300 ℃ was chosen to be plotted in the
final result figure.
6.2.7 Gel permeation chromatography (GPC) for molecular weight measurement
Average molar mass of polyvinyl acetals from different reaction was determined by gel
permeation chromatography (GPC) equipped with a refractive index detector (Shimadzu,
Tokyo, Japan, RID-10A) and a combination of three columns (Waters Co., Israel).
Tetrahydrofuran was applied as mobile phase and the flow rate was set at 0.50 mL/min at
40 °C. Polystyrene was used as standard to obtain the calibration curve for average molar
mass calculation.
6.2.8
1

1

H NMR analysis

H NMR was conducted on a Unity Plus 500 MHz NMR spectrometer from Varian Inc.

(Palo Alto, CA, USA) to determine the acetalization degree of polyvinyl acetals. A

148

sample was dissolved in CDCl3 and the spectrum was recorded using the solvent peak as
the internal standard.
6.3 Results and Discussion
6.3.1 Thermogravimetric analysis (TGA)
TGA was conducted with a TA Instruments Model TGA Q50 machine (New Castle, DE).
The sample was weighted between 5 and 15 mg and placed into an aluminum pan inside
a platinum pan to avoid contamination. The sample was firstly heated up to 550 ℃ at a
rate of 10 ℃/min with the supply of nitrogen, and when the temperature reached to 550, a
homothermal mode with a time period of 20 mins was applied and the gas was switched
from nitrogen to air to burn the materials completely. Since the material only contains
carbon, hydrogen and oxygen molecules, no residue was left in the pan and the final
weight reduced to 0.

149

100
b
d

Weight Percentage (%)

80

c
a

e
f

g

60

a__ PVH_Org
b__ PVOH
c__ PVH
d__ PVB
e__ PVN
f__ PVHN
g__ PVHN9

40

20

0
0

100

200

300

400

500

o

Temperature ( C)

Figure 6.2 TGA weight percentage change with temperature profiles of polyvinyl alcohol
and acetal polymers.
PVOH: polyvinyl alcohol provided by Kuraray; PVB: polyvinyl butyral provided by
Kuraray; PVH: polyvinyl alcohol reacted with hexanal based on stoichiometry in water;
PVH_Org: polyvinyl alcohol reacted with hexanal based on stoichiometry in organic
solvent; PVN: polyvinyl alcohol reacted with nonanal based on stoichiometry; PVHN:
polyvinyl alcohol reacted with hexanal and nonanal (molar ratio 1:1) based on
stoichiometry; PVHN9: polyvinyl alcohol reacted with hexanal, nonanal and methyl 9oxononanoate (molar ratio of the three aldehydes: 1:1:1).
To determine the potential of the various aldehydes produced by ozonolysis of FAMEs
for polymer application, various polymers were synthesized using different solvent
150

systems (aqueous and organic) and different aldehyde combinations with PVOH. The
various polymers produced were initially tested for their thermal stability using
thermogravimetric analysis (TGA) and compared to the commercially available PVB and
PVOH as controls. The weight percentage change as a function of temperature for 6
different polyvinyl polymers and PVOH were plotted in Figure 6.2. It was observed that
the weight loss of PVHN9 started at the lowest temperature (< 100 ℃) among the
polymers tested herein, while PVHN showed the second lowest initial degradation
temperature, at around 140 ℃. PVN followed as the third compound that started
decomposing, at a similar temperature as PVHN, showing a lower initial drop in weight,
followed by a larger drop after 270 ℃ and a third instant drop at around 500 ℃. The
initial decomposition temperatures for PVH (organic solvent), PVOH, PVH and PVB are
much higher than PVN, PVHN and PVHN9, which generally start around 230 ℃.
Comparing the structure of the two groups of compounds, the differences reside in that
the side chains of former group of compounds are shorter than that of the latter group of
compounds. In addition, the latter group of compounds like PVHN and PVHN9 contain
more than one type of acetal side chains, which may also reduce the thermal stability of
the polymer and increase the number of decomposition stages as a function of
temperature due to their heterogeneity.
The decomposition temperatures of PVH and PVOH are very similar, at about 375 ℃,
and both are slightly higher than PVB. However, PVH made in organic solvent has an
observably higher decomposition temperature, at around 380-390 ℃. This difference may
be explained by the fact that the polymer was made in organic solvent, and unlike the
aqueous solvent system, the product was completely dissolved during the process. The
151

polymerization in homogeneous systems allows the reaction to occur in a larger extent,
creating a larger number of acetal side chains bound to the PVOH backbone. Usually,
more side chains homogeneously distributed should provide higher thermal stability and
this explains why the PVH made in organic solvent is more stable than the PVH made in
aqueous solvent. As PVH was the polymer that showed the highest thermal stability
among the various polymers tested in this study, including the commercial PVB, we
focused our study in the characterization of PVH.

100
b
d

Weight Percentage (%)

80

c
a

a__ PVH_Org
b__ PVOH
c__ PVH
d__ PVB
e__ PVH_2
f__ PVH_1/2

e
f
60

40

20

0
100

200

300

400

500

o

Temperature ( C)

Figure 6.3 TGA weight percentage change with temperature profiles of polyvinyl alcohol
and acetal polymers.
PVOH: polyvinyl alcohol provided by Kuraray; PVB: polyvinyl butyral provided by
Kuraray; PVH: polyvinyl alcohol reacted with hexanal based on stoichiometry in water;
152

PVH_Org: polyvinyl alcohol reacted with hexanal based on stoichiometry in organic
solvent; PVH_2: polyvinyl alcohol reacted with hexanal with 2 times of stoichiometric
amount of hexanal; PVH_1/2: polyvinyl alcohol reacted with hexanal with 0.5 times of
stoichiometric amount of hexanal.
To determine potential changes in thermal stability due to addition of hexanal in different
proportions to the reaction with PVOH, the polymer was synthesized with in water with a
stoichiometric ratio of hexanal to PVOH (PVH), with double the stoichiometric ratio of
hexanal to PVOH (PVH_2) and half the stoichiometric ratio of hexanal to PVOH
(PVH_1/2). TGA for the different polymers was obtained and compared with controls
such as PVOH, PVB and PVH produced in organic solvent (Figure 6.3). The results show
that the PVH_2 started decomposing at lower temperatures, around 130 ℃, which
coincides with the boiling point of hexanal. This suggests that unreacted hexanal trapped
into the polymer matrix, which could not be washed out, is evaporating from the sample
and is responsible for the initial weigh loss for PVH_2. If we would not take into account
this initial weight loss due to solvent evaporation, the thermal stability of the polymer
would be similar to the one showed by PVB. In the case of PVH_1/2, the weight loss
profile shows an early decomposition temperature of about 200 ℃, presenting a lower
slope compared to the controls. This observation suggests that the polymer is more
heterogeneous in terms of its building block units, which may also contribute to the lower
thermal stability of the product.
From the results of this experiment, it is clear that PVH produced using a stoichiometric
ratio of hexanal to PVOH shows better thermal stability than using lower hexanal to
PVOH ratios. Also, addition of higher hexanal content to the reaction mixture did not
153

show any improvements in the thermal stability of the product and may create processing
issues in the future for removal of excess hexanal from the polymer matrix. There fore, for
industrial production of PVH, the synthesis protocol using a stoichiometric ratio of
hexanal to PVOH is highly recommended in case of using water as solvent system.
6.3.2 Differential scanning calorimetry (DSC)
To evaluate the grass transition and melting temperatures of PVH produced using various
ratios of hexanal to PVOH in water, a DSC analysis was performed. Figure 6.4 shows the
DSC results of PVH produced using different hexanal-to-PVOH ratios and the respective
controls, notably PVOH and PVB. The results show that PVOH has a glass transition
temperature (Tg) of 85 ℃ and melting temperature (Tm) of 230 ℃. A clear Tg of PVB
shows up between 65-70 ℃ which is identical to the reported value provided by Kuraray
Inc. [115]. The Tg of PVH and PVH_2 appears at a temperature between 30 and 40 ℃
which is lower than that of PVB. This indicates that longer side chains of polyvinyl
acetals may contribute to lowering the Tg of polyvinyl acetal polymers. The Tg of
PVH_1/2 could be clearly determined by the DSC plot, which may have to do with the
high level of heterogeneity of this polymer. Unlike PVOH, all the polyvinyl acetals do
not show a melting point within the range of temperatures analyzed in this study.

154

a__ PVB
b__ PVH_2
c__ PVH
d__ PVH_1/2
e__ PVOH

Heat Flow (mW/mg)

0.0

-0.5

a
e

b
c
d

-1.0

-1.5
-100

-50

0

50

100

150

200

250

300

350

o

Temperature ( C)

Figure 6.4 DSC spectra of polyvinyl acetals. PVB: polyvinyl butyral provided by
Kuraray; PVOH:

polyvinyl alcohol provided by Kuraray; PVH: polyvinyl alcohol

reacted with hexanal based on stoichiometry; PVH_2: polyvinyl alcohol reacted with
100% excess hexanal based on stoichiometry; PVH_1/2: polyvinyl alcohol reacted with
half amount of hexanal based on stoichiometry.
Comparing the DSC results obtained for PVH with the other polyvinyl acetals that are
possible to produce from products of FAME ozonolysis (Figure 6.5), we can further
support the idea that the Tg is reduced by the increasing molecular weight of the acetal
side chains. For the mixed acetal polymers (i.e. PVHN and PVHN9), there is high
heterogeneity on the sample that does not allow the formation of a clear Tg gradient in

155

the DSC curves. Therefore, it is not possible to determine the Tg value for these polymer
samples.

a__ PVHN9
b__ PVHN
c__ PVN
d__ PVB
e__ PVH

Heat Flow (mW/mg)

0.0

-0.2

-0.4

a

c

b
d

-0.6

e

-100

-50

0

50

100

150

200

250

300

350

o

Temperature ( C)

Figure 6.5 DSC spectra of polyvinyl acetals. PVB: polyvinyl butyral provided by
Kuraray; PVH: polyvinyl alcohol reacted with hexanal based on stoichiometry; PVN:
polyvinyl alcohol reacted with nonanal based on stoichiometry; PVHN: polyvinyl alcohol
reacted with hexanal and nonanal (molar ratio 1:1) based on stoichiometry; PVHN9:
polyvinyl alcohol reacted with hexanal and 9-oxononanoate (molar ratio 1:1) based on
stoichiometry.

156

6.3.3 Gel permeation chromatography (GPC) for molecular weight measurement
The GPC analysis of PVH made in aqueous and organic solutions are compared in Figure
6.6 and the specific properties of both polymers are listed in Table 6.1. From these
results, PVH prepared in aqueous reaction has a higher average molecular weight and a
higher polydispersity index (PDI) value. This means that both the average molecular
weight and the range of degrees of polymerization present in the sample are higher for
PVH produced in water. The higher average weigh molecular weight (Mw) and average
number molecular weight (Mn) of PVH made in aqueous solution could be caused by the
fact that in water solution, once the polymer is formed, the product separates from the
aqueous phase immediately as solid, and in this way the reaction would be driven to the
direction towards forming the polymer. However, in organic solvent the polymer is
always dissolved in the same phase and thus the forward reaction encounters more
resistance from the reverse reaction during PVH production. The higher PDI value may
result from the same fact that the product separates from the reactants after being formed,
which provides less chance for the polymer to structure regularly. The Mn value for both
of the two PVH products is comparable to the highest reported Mn for PVB (around
100,000) in the Kuraray PVB Brochure [115].

157

PVH (organic solvent)
PVH (aqueous solvent)

1.0

Normalized Intensity

0.8

0.6

0.4

0.2

0.0
20

21

22

23

24

25

26

27

28

29

Time (min)

Figure 6.6 GPC spectrum of PVH made in two different solvents.
Table 6.1 Average molar mass of PVH made in two different solvents

6.3.4

1

Name

PVH (aqueous solvent)

PVH (organic solvent)

Mw

212,522

170,734

Mn

123,955

114,919

PDI

1.71

1.48

H NMR analysis for PVH prepared in aqueous solution

NMR analysis was performed on the PVH polymer to elucidate its structure and degree
of acetalization. The PVH used in this study was produced in organic solvent, as it was
158

not possible to totally re-dissolve the polymers produced in water system with CDCl3.
The 1 HNMR spectrum showed in Figure 6.7, confirms the structure of PVH as previously
described in this manuscript. To evaluate the level of acetalization of the PVH sample
prepared in organic solvent, the four protons from peak A and the three protons from
peak B were used. From the calculation, the degree of acetalization of PVH obtained after
polymerization was 76.5%. In comparison, the acetalization degree of commercial PVB
products from Kuraray Inc. is usually between 62% and 82% [115].
1.0 2013-02-09-yanjiePVH
0.9

B

A

0.8

Normalized Intensity

0.7
0.6

A

0.5

A
0.4
0.3

B

0.2
0.1
0

1.00
8

7

6

5

4
3
Chemical Shift (ppm)

2

0.65
1

0

-1

Figure 6.7 1 H NMR spectrum of PVH prepared in organic solvent
6.4 Conclusion
In this study, polyvinyl acetals were prepared by reacting PVOH with three aldehydes in
water solution with sulfuric acid as catalyst. PVH was also produced in organic solution
for comparison. The thermal decomposition properties of PVHAproduced in aqueous and
B

159

organic solvents were superior to the commercially available PVB. When higher
molecular weight aldehydes were used in the polymerization reaction, the decomposition
temperatures reduced significantly, as in the case of PVN. Also, by mixing various
aldehydes with different molecular weights, the thermal stability of the polymers was
further reduced, as observed for PVHN and PVHN9. From the perspective of vinyl acetal
polymer

production,

the

utilization

of

hexanal

seems

more

suitable

for

commercialization. Our studies revealed that synthesis of PVH using stoichiometric
ratios of hexanal and PVOH is the most suitable for better thermal stability of the
product. PVH synthesis in water with twice the stoichiometric amount of hexanal to
PVOH showed that excess aldehyde entrapped in the polymer matrix was not easily
removed and affected the thermal stability of the overall product. When the amount of
hexanal was reduced to half of the stoichiometric ratio to PVOH, the thermal stability of
the product was reduced due to heterogeneity in the sample.
DSC analysis showed that PVH has a lower Tg than the commercial polyvinyl acetal
PVB. Also, this analysis revealed that higher molecular weight acetal groups reduce the
Tg value of polyvinyl acetals.
The molecular weight distribution of PVH was determined by GPC and showed that the
polymer produced in water contains a higher average molecular weight and a higher PDI
than the same polymer produced in organic solvent. This difference may be related to the
fact that the PVH falls out of solution when produced in water, driving the reaction to
polymerization, but also allowing the product to be less regular. PVH formed in solvent
was further analyzed by 1 H NMR to elucidate the structure of the polymer and also
determine the level of acetalization. Our results agree to the structure of the targeted PVH

160

product and showed a degree of acetalization of 76.5% which is comparable to the
commercial product of PVB.

161

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