THERMAL CONTROLLED ELECTROCHEMICAL INSTRUMENTATION FOR PROTEIN ARRAY MICROSYSTEMS By Xiaowen Liu A THESIS Submitted to Michigan State University in partial fulfillment of the requirements for the degree of MASTER OF SICENCE Electrical Engineering 2011 ABSTRACT THERMAL CONTROLLED ELECTROCHEMICAL INSTRUMENTATION FOR PROTEIN ARRAY MICROSYSTEMS By Xiaowen Liu Understanding the structure and function of proteins has become increasingly important since the completion of the Human Genome Project and the sequencing of several other important genomes. In recent years, lab-on-a-chip systems have introduced some new capabilities for protein analyses. Rapid progress in the field of microsystems, miniaturized devices combining sensor and electronics, enable a new generation of miniaturized biosensor arrays integrating silicon CMOS chips that acquire and process bio-electrochemical signals. Such biosensor array microsystems could permit improved sensitivity, throughput and cost. Because many proteins exhibit temperature dependent activity, this thesis explores the opportunity to develop a thermal control microsystem for protein arrays biosensors. A CMOS microhotplate array was developed for thermoregulation of protein interfaces in a liquid sample environment. The microhotplates were shown to provide suitable thermal control for biosensor temperature ranges without the process complexity of most previously reported microhotplates. When combined with a CMOS analog thermal controller, the on-chip array was shown to set and hold temperatures for each protein site within ±1°C, and array elements were found to be almost completely thermally isolated from each other at distances beyond 0.4mm. Furthermore, a new compact, low power impedance analysis circuit was developed utilizing mixed-mode signal processing to extract real and imaginary impedance components for an on-chip protein interface. The compact size and low power of this circuit enable it to be combined with the thermal control structures and instantiated for every element in a sensor array to increase the interrogation throughput. The developed thermal control and readout microsystem could significantly advance proteomics research and progress in characterizing newly sequenced genomes. DEDICATION Dedicated to my family iii ACKNOWLEDGEMENT The work presented in this thesis would not have been possible without the support, contribution, and encouragement of many individuals that I have had the privilege of interacting with during my stay at Michigan State University. Indeed this is now a unique opportunity to acknowledge them, even though in a very small way. First, and foremost, I would like to express my deep gratitude to my advisor, Professor Andrew Mason, for his generous support. His broad vision and encouragement has always been a source of inspiration for me. His enthusiasm and wise criticism have had a tremendous influence on my professional development, which I am deeply grateful for. I am also grateful to Professor Tim Hogan and Professor Shantanu Chakrabartty for serving on my committees. They have always been an exceptional source of support for me at MSU. Their technical feedback and original ideas greatly expanded the scope of my research and its contributions. I am greatly indebted to all my colleagues and friends at MSU for their coaching and support in our joint entrepreneurial endeavors. Special thanks to Dr. Yang Chao, Dr. Huang, Yue, Dr. Awais M. Kamboh, Daniel Rairigh, Xiaoyi Mu, Haitao, Li, Yuning, Yang, Lin Li, Waqar A. Qureshi and Chenling Huang. My utmost gratitude, love and affection belong to my family. My parents always unconditionally love and support me and I thank them for everything they have given me. I would like to thank my husband, Yang Liu, who accompanied me through the past years at Michigan State University. This thesis is dedicated to them. iv TABLE OF CONTENTS LIST OF TABLES ...................................................................................................... vii LIST OF FIGURES ................................................................................................... viii LIST OF SYMBOLS .....................................................................................................x Chapter 1 ........................................................................................................................1 Introduction ....................................................................................................................1 1.1 Motivation ...........................................................................................................1 1.2 Challenges ...........................................................................................................3 1.3 Thesis Goals ........................................................................................................4 1.4 Thesis Outline .....................................................................................................5 Chapter 2 ........................................................................................................................6 Background ....................................................................................................................6 2.1 Protein Array Microsystems ...............................................................................6 2.2 On-Chip Thermal Control ...................................................................................7 2.2.1 Micro-hotplate Device .................................................................................7 2.2.2 On-chip Temperature Controller..................................................................8 2.3 Protein Detection Circuits ...................................................................................9 2.4 Architecture of Protein Microsystem ................................................................11 Chapter 3 ......................................................................................................................14 First Generation Micro-thermoelectric Control System ..............................................14 3.1 Thermal Control ................................................................................................14 3.1.1 Requirements .............................................................................................14 3.1.2 Architecture................................................................................................14 3.1.3 Microhotplate Array Design ......................................................................15 3.1.4 PID Thermal Controller .............................................................................20 3.2 Microsystem Packaging ....................................................................................20 3.3 Measurement Results and Analysis ..................................................................22 3.4 Summary and Analysis .....................................................................................26 Chapter 4 ......................................................................................................................29 Impedance Extraction Circuits for Protein Array ........................................................29 4.1 Architecture of Impedance Extraction Circuits ................................................30 4.2 Impedance Readout Circuit...............................................................................31 4.2.1 Theory of Operation ...................................................................................31 4.2.2 IDC Circuit Implementation ......................................................................33 v Chapter 5 ......................................................................................................................38 Second Generation Thermal Control Chip with Test Results ......................................38 5.1 Second Generation Thermal Control Chip Design ...........................................38 5.1.1 Ambient Temperature Sensor Design ........................................................39 5.1.2 Thermal Controller Circuit Design ............................................................41 5.2 Test Results .......................................................................................................46 5.2.1 Thermal Control Circuit Test Results ........................................................46 5.2.2 IDC Circuit Test Results ............................................................................48 5.2.2.1 Circuit Characterization .......................................................................48 5.2.2.2 Biosensor Measurements .....................................................................53 Chapter 6 ......................................................................................................................56 Summary and Future Work ..........................................................................................56 6.1 Summary ...........................................................................................................56 6.2 Future Work ......................................................................................................58 BIBLIOGRAPHY ........................................................................................................61 vi LIST OF TABLES Table 5-1. The performance of impedance-to-digital converter circuit .......................53 vii LIST OF FIGURES Figure 2.1. Schematic view and equivalent model of a two-electrode electrochemical site with a counter electrode (CE) and a gold working electrode (WE) coated with a tBLM. In the tBLM equivalent model, Rm and Cm represent the resistance and capacitance of the lipid bilayer membrane, respectively, while Rs is the resistance of the solution and Cdl describes the interfacial capacitance. .................................................................................10 Figure 2.2. Simplified schematic of a typical electrochemical potentiostat system. Normally three electrodes are employed: a working electrode, a reference electrode and a counter electrode ................................................................................................................11 Figure 2.3. Conceptual view of the microsystem platform for a membrane protein biosensor array on CMOS .................................................................................................12 Figure 3.1. Block diagram of the micro-thermoelectric control system ............................15 Figure 3.2. Cross section of the CMOS microhotplate for thermal control of on-chip biosensor arrays .................................................................................................................17 Figure 3.3. Thermal analysis simulations: (a) temperature probed on surface of the heater; (b) temperature probed on surface of chip .........................................................................19 Figure 3.4. Die photograph of the 1.5x1.5mm microhotplate 3x3 array ...........................21 Figure 3.5. Chip packaging flow: (a) chip in DIP40; (b) dispense SU8 2002 using a syringe; (c) soft baking, UV exposure and hard baking; (d) final SU8 reservoir; (e) PDMS cap on DIP40 package. Steps (b) and (c) are repeated 4 or 5 times until package is fully filled with SU8 ..........................................................................................................22 Figure 3.6. The 1.5x1.5mm wire bonded first thermal CMOS chip encapsulated with SU8 2002. There are 3x3 microhotplate array in the chip .........................................................23 Figure 3.7. Thermal step response of the microhotplate thermal control system for 3 °C steps....................................................................................................................................24 Figure 3.8. Temperature (at on-chip sensor) in air and in liquid at different heater voltages ..............................................................................................................................25 Figure 3.9. Current density of a NEST (NEST is a hydrophobic recombinant polypeptide comprising the catalytic domain (residues 727–1216) of neuropathy target esterase) biosensor at different temperatures ....................................................................................26 viii Figure 3.10. The sensor measured temperature vs. the distance from the heating source to the sensor ...........................................................................................................................27 Figure 4.1. IDC functional blocks derived from the FRA method. The circuit extracts the imaginary portion of admittance when S=1 and real portion when S=0 ...........................32 Figure 4.2. Simplified lock-in impedance-to-digital converter structure. φ is the reference square wave ........................................................................................................................35 Figure 5.1. The concept of the second generation thermal control chip. The ambient temperature sensor block detects the temperature of whole chip. Thermal control block controls the temperature of each protein site locally. The IDC circuit characterizes the activity of the protein interface ..........................................................................................39 Figure 5.2. The simplified schematic of the CMOS PTAT ambient temperature sensing circuit. ................................................................................................................................41 Figure 5.3. The schematic of second generation thermal controller. The comparator used to control switched is a hysteresis comparator to reduce thermal noise ............................43 Figure 5.4. The schematic of the amplifier used in the thermal controller ........................44 Figure 5.5. (a) Description of temperature indepdent reference voltage and current generator. (b) Schematic of the temperature independent reference generator. ................45 Figure 5.6. Die photograph of second generation thermal control chip ............................47 Figure 5.7 The test result of voltage (a) and current (b) reference with temperature for 10 ºC to 70 ºC..........................................................................................................................48 Figure 5.8. The deviation between set point temperature (Temp_set) and measured temperature for 25 ºC to 50 ºC with gain=2 setting measured 180 second .......................49 Figure. 5. 9. Test platform for the IDC chip with biosensor equivalent circuit model. .....50 Figure 5.10. The real (circles) and imaginary (squares) results from the IDC circuit for the test setup shown in Figure 5.9 along with theoretical (expected) curve for comparison. ............................................................................................................................................51 Figure 5.11. Measured DNL and INL curve of one IDC channel output when the sinusoid input amplitude was swept from 0 to 10nA. The maximum DNL and INL are 59.8dB and 50.2dB, respectively...........................................................................................................52 Figure 5.12. Response of an IDC readout channel as the phase of the input signal is varied from -180° to +180° degrees. Input amplitude (30nA) and frequency (100Hz) are kept constant. .....................................................................................................................52 ix Figure 5.13. The test setup for the biosensor measurements using the IDC circuit. .........54 Figure 5.14. tBLM amplitude and phase measured by a commercial instrument (CHI 660 B) and by the fabricated IDC circuit at different frequencies. ...........................................55 x LIST OF SYMBOLS PID Proportional integral derivative PTAT Proportional to absolute temperature tBLM Tethered bilayer lipid membrane xi Chapter 1 Introduction 1.1 Motivation Proteins are vital entities in human cells and are involved in nearly all body functions both in healthy and diseased individuals [1-3]. Proteins are used to support the skeleton, control senses, move muscles, digest food, and against infections and process emotions. Understanding the structure and function of gene products, that is proteins, has been increasingly emphasized since the completion of the Human Genome Project and the sequencing of several other important genomes. Because proteins are the targets for virtually all pharmaceutical drugs and for most diagnostics [1], proteins can be used in detecting disease and creating new treatments for health problems such as cancer, cardiovascular and neurological disorders. According to the American Cancer Society , there would be more than 7.6 million deaths caused by cancer in 2007 worldwide (about 20,000 cancer deaths a day) [4], deaths that could potentially be prevented by better understanding of proteins. To understand the role of proteins in biological operations, typically referred to as proteomics, the characterization of protein structure and function is critical. Protein characterization has been used widely in drug discovery, development of biosensors, clinical and forensic analysis, and many other biomedical applications [5-8]. According to 1 a statement by Front Line Strategic Consulting, Inc. (San Mateo, CA), published in February, the proteomics market reached around $2.68 billion in 2008, up 76% from an estimated $1.52 billion in 2003 [9]. In recent years, researchers have seen an increased interest and investment in a more personalized approach to medicine, aided by better understanding of human proteins. This approach means that doctors can detect disease at a much earlier stage and select the right treatment for each patient. Also, it will enable earlier and more precise diagnosis, a necessity for selecting patients that actually might benefit from expensive and very targeted drugs that only work for specific small groups of patients [1]. Recently, high-throughput protein array methods have begun to be considered as the next-generation evolution of DNA microarrays, which allow rapid, direct and quantitative detection of a wide range of bimolecules [10, 11]. Protein array technology takes advantage of the fact that a large number of targets can be analyzed in parallel measurements with low sample consumption. The reduction of sample volume is of great importance for all applications in which only minimal amounts of samples are available. Furthermore, it is possible to perform comparative analyses of several different samples within a single array chip. For example, in medical research, all relevant immune diagnostic parameters of interest can be analyzed in parallel, which save cost and time. Techniques for measuring protein activities and structure can be generally divided into two main groups, optical and electrochemical. Electrochemical biosensor is a molecular sensing device that intimately couples a biological recognition element to an electrode transducer. The principle for electrochemical biosensor transducers is that many chemical reactions produce or consume ions or electrons, causing some change in the 2 electrical properties of the solution, which can be sensed as measuring parameters. Electrochemical biosensors have played a major role in the move towards simplified testing, including home-use devices [12]. Furthermore, miniaturized, electrochemical biosensors hold great promise for minimizing size, and power in vital applications such as point-of-care diagnostics. In summary, electrochemical biosensors are promising candidates for the next generation of protein characterization platforms. 1.2 Challenges To minimize reagent cost, the high throughput protein array for multiple analyte concentration measurement should be built in a tiny chip, with size around 1cm2. This requires the size of on-chip electrodes have to be very small because there are up to hundreds of on-chip electrodes in the protein array chip. The miniature size of the electrodes caused the biosensor reaction signals are really weak (~aA - fA for sensing current), so it is hard to detect these sensing signals by off-chip instruments due to the low signal to noise ratio (SNR). The weak biosensor reaction signal is a main challenge for high throughput protein array microsystem. To solve the detection limitation, integrating the electrodes directly on the instrumentation chip could eliminate external connection noise, and through miniaturization, the limits of detection can be extended by improving the SNR [13]. Temperature plays a major role in sensitivity of protein-based sensors because protein activity typically doubles every 10˚C in its biological temperature window [14]. Furthermore, reliability and lifetime of protein interfaces and test reagents can be greatly improved by keeping them at low temperature as long as possible. However, to our best 3 knowledge, no protein array associated with thermal control microsystem was presented. The main challenge of this thermal controlled microsystem is to maintain the entire system, including valuable biomolecules, at a low temperature and only heat the protein site locally in liquid environment. To solve this challenge, an on-chip thermal control circuit, allowing temperature control each protein site individually, was expected. 1.3 Thesis Goals The primary goals of this research are to develop the thermal control capabilities and instrumentation circuits that will permit the realization of a single chip, high throughput protein array microsystem. These two areas are described in detail below. A: Thermal Control for Protein To keep the protein platform at a low temperature and only heat the sensor site locally in liquid, a thermal controlled protein microsystem was proposed. In this thermal control system, several requirements need to be considered. First, the on-chip heaters and sensors have to be compatible with a standard CMOS process. Second, thermal uniformity across the microhotplate is needed to ensure no local hot spots will degrade the biointerfaces. Third, a feedback controller is needed to allow individual array sites to be set for different temperatures simultaneously. Forth, an in-package encapsulation system was also needed to verify thermal control operations in liquid environment necessary for protein-based interfaces. B: Readout Circuits 4 Another circuit that is necessary in the protein array microsystem is the readout circuit that will sense and extract biosensor reaction signals. Because of the high level of integration in the microsystem, multi-channel readout circuits have to be hardware and power efficient. Furthermore, because the biosensor outputs are small signals, high resolution is another key requirement for the readout circuits. In summary, to support chip-scale microsystem applications, a very hardware efficient and low power solution is needed that combines accurate, low noise readout circuits with electronics capable of circumventing the heavy signal processing load involved in parallel sensing of a sensor array 1.4 Thesis Outline In this thesis, Chapter 2 covers the background of protein array microsystem, on-chip thermal control and biosensor signal readout circuits. Chapter 3 covers the first generation of thermal control chip for protein array microsystem. It introduces the design concept of the microhotplates in standard 0.5µm CMOS process and shows results that characterize the thermal performance in liquid. Chapter 4 describes a readout and impedance extraction circuit for protein characterization that introduces in a new structure for impedance extraction based on the frequency response analyzer (FRA) technique. Chapter5 covers the second generation thermal control and readout chip and summarizes the chip performance and test results with a bilayer lipid membrane protein biosensor. Chapter 6 summarizes the thesis work, contributions and outlines future work related to this research. 5 Chapter 2 Background 2.1 Protein Array Microsystems In recent years, miniaturized systems called lab-on-a-chip or micro total analysis systems (µ-TAS) have been introduced as new microsystems for biochemical analyses. These systems are expected to perform DNA, protein, and cell analyses for drug screening and development of novel therapies [15]. Microarray and microfluidic types of chip-scale devices (so-called biochips) have been developed using micro- and nanotechnology techniques [15, 16]. These miniaturized biosensor arrays provide tremendous advantages. To fully realize these advantages, a microsystem that combines the biosensor microarray with miniaturized interrogation instruments is of increasing interest. Several protein microsystems have been reported. In [17] an amperometric electrochemical microsystem for a miniaturized protein biosensor array was introduced. In [18], an integrated multi-channel impedance extraction circuit for biosensor arrays was developed, and a platform for detection of avian influenza was reported in [19]. However, none of these consider the environment temperature around the protein. To improve the sensitivity and reliability of the biosensor system, and reduce the cost, a new thermal controlled protein microsystem was developed, which was introduced in Section 2.4. 6 2.2 On-Chip Thermal Control An on-chip temperature-controllable platform is of great advantage in sensor research into temperature-dependent phenomena. Most of the known on-chip thermal control systems were built for gas sensor [20-24]. The standard on-chip thermal control system includes two parts, a micro-hotplate device and a thermal controller. 2.2.1 Micro-hotplate Device 0B Using CMOS technology to generate a resistive heating element and a temperature sensor is generally called a micro-hotplate. In the microhotplate, most of the existing heating elements work as a resistive heater where an electrical current is applied to control temperature. The heating element can be made of any conductive material such as metal layers [23], polysilicon layers [21, 22], or transistors [20] within a CMOS process. The temperature sensing element can be resistive thermometers or NPN transistors realized as parasitic devices in a standard CMOS process [25-27]. Beginning in the early 1990s, the silicon micromachining was used to fabricate microhotplates and arrays for gas sensors. Numerous micro-hotplates have been produced by both surface [28] and bulk etching of silicon [29, 30]. Most of gas sensors demand post-CMOS processing (bulk etching, etc.) to remove silicon beneath of the hotplate and improve thermal isolation in air [31-33]. Many papers reported how to fabricate suspended membranes or microbridge structures for thermal isolation [21, 33], which are necessary to achieve temperatures around hundreds of degree Celsius (~200-600 ºC). 7 However, in microhotplates designed for protein biosensor microsystems, the microhotplates will be heated in a liquid environment and the maximum temperatures are much lower, ~60 ºC, than gas sensors. The thermal conduction and convection of a microhotplate in fluid are totally different than one in gas (e.g. air) and are mainly determined by the geometry and material of microhotplates. In Chapter 3, how to improve the temperature gradient and the heat transfer of microhotplate in liquid will be discussed further. Moreover, because the maximum temperature for protein sensors is much lower than that of gas sensors, the post-CMOS etching steps to create thermal isolation of the microhotplate are not necessary. To our best knowledge, the only microhotplate designed for biological applications and used within liquid environments with no post-CMOS processing was reported for cell culture and incubation [21]. This device achieved a single fixed temperature of 37 ˚C on the back side of a CMOS chip. However, the protein array application requires programmable control of individual sites across a wide temperature range, which can not be achieved with the reported device. Thus, there are no reported devices suitable for the goals of this thesis research. 2.2.2 On-chip Temperature Controller 1B A classical temperature controller can be implemented using either analog or digital methods. In [33-36], temperature controllers were built based on the digital proportionalintegral-derivative (PID) technique. The drawback of this method is that it requires a 8 large amount of hardware because it requires analog-to-digital and digital-to-analog converters plus anti-aliasing and smoothing filters within the thermal controller [35]. Analog temperature controllers have been around for many years, and there is a great deal of literature, practical experience, and design methods available. In [24, 37], analog temperature controllers based on Wheatstone bridge were used to detect the small variations in the resistive value of a temperature sensor resistor. [38, 39] introduced other analog temperature controllers to directly detect the temperature sensor resistor. Compared to a digital temperature controller, the analog thermal controller is more sensitive to the process variations and temperature drifts, but it simpler and needs fewer components. 2.3 Protein Detection Circuits Impedance spectroscopy (IS) is a standard technique for protein identification and characterization. Protein bio-interfaces elicit responses that are measured by a change of impedance over a range of stimulus frequencies. The basic concept of the electrochemical IS (EIS) method is shown in Figure 2.1. A potentiostat imposes a desired command voltage between the solution and the working electrode while simultaneously measuring the current flowing between them those results from the applied voltage. The command voltage for impedance sensing is an AC excitation plus an optional DC offset, and the impedance is simply the ratio of the AC voltage to the AC response current. EIS analyzers are potentiostats designed especially for measuring AC impedance, and they have typical frequency ranges of 1 mHz – 100 kHz. 9 Figure 2.1. Schematic view and equivalent model of a two-electrode electrochemical site with a counter electrode (CE) and a gold working electrode (WE) coated with a tBLM. In the tBLM equivalent model, Rm and Cm represent the resistance and capacitance of the lipid bilayer membrane, respectively, while RS is the resistance of the solution and Cdl describes the interfacial capacitance. (For interpretation of the references to color in this and all other figures, the reader is referred to the electronic version of this dissertation.) Recently, some chip-level approaches for IS have been introduced [40, 41], but these lack the ability to extract real and imaginary impedance components. Impedance component extraction is necessary to identify sensing elements within the complex impedance (see model in Figure 2.1) and is essential for reducing the signal processing load in array implementations. A chip with impedance extraction and stimulus signal generation has been reported [42], but it utilizes an external DSP for output digitization and supports frequencies and current ranges that are not appropriate for membrane proteins. Electrochemical amperometry techniques, such as cyclic voltammetry, are also often employed to characterize protein properties. As shown in Figure 2.2, one of the basic components of this electrochemical system is the potentiostat, a circuit that controls the bias voltage between two conductive electrodes, i.e. reference electrode (RE) and 10 Figure 2.2. Simplified schematic of a typical electrochemical potentiostat system. Normally three electrodes are employed: a working electrode, a reference electrode and a counter electrode. working electrode (WE). The electrical current between the counter electrode (CE) and the WE is then measured using an amperometric readout circuit [43]. Both EIS and amperometry techniques can be implemented with CMOS instrumentation circuits. For example, CMOS readout electronics including a compact potentiostat that supports a very broad range of input currents, 6 pA to 10 µA, have been reported [17]. In another example, a CMOS bi-potentiostat and amperometric readout chip has been reported by our lab [44]. 2.4 Architecture of Protein Microsystem 11 Figure 2.3 illustrates the proposed protein-based electrochemical biosensor array microsystem that serves as the conceptual model for the work described in this thesis. A silicon chip with CMOS electrochemical instrumentation circuitry forms the substrate. The circuitry includes on-chip thermal control and readout circuits to detect the biosensor reaction signal. The electrodes are individually modified with protein interfaces using molecular self assembly processes [14]. The assembly and measurement of biointerfaces are supported by a top microfluidics layer that could take a variety of forms including fluidic channels or, as shown in Figure 2.3, fluidic reservoirs that are filled and emptied by a robotic fluid delivery system. This platform is versatile and also permits electrode modification with other types of interfaces, such as redox enzymes. To interface the chip with biosensors, the chip needs to be suitably packaged for use in a liquid environment. The post-CMOS fabrication process begins with formation of electrodes by depositing titanium/gold (50Å/1000Å) on the CMOS chip and patterning by wet etch. A robust and reliable packaging scheme for on-CMOS biosensors that is uniquely capable of providing Figure 2. 3. Conceptual view of the microsystem platform for a membrane protein biosensor array on CMOS. 12 both electrical insulation of a CMOS chip in a liquid environment and also protection from chemical and biological agents has been developed by our lab [45]. 13 Chapter 3 First Generation Microthermoelectric Control System 3.1 Thermal Control 3.1.1 Requirements 2B Most of the published microhotplates have been designed for gas sensing, where the temperature required several hundreds of degree Celsius. However, biological application have significantly different requirements including: lower temperature range suitable for protein characterization [46]; ability to control array sites to different individual temperatures; thermal uniformity across the microhotplate to ensure no local hot spots that would degrade the biointerfaces; no post CMOS thermal isolation; and a simple package that enables liquid to get to the chip surface without interfering with wire bond connections. This chapter describes efforts to develop a new thermal control system that will provide these functional characteristics. 3.1.2 Architecture 3B To control the temperature around a protein, an on-chip heater, temperature sensor, temperature controller, and protein-based interfaces are needed. A multi-channel thermal 14 control system, shown in Figure 3.1, was developed to characterize the performance of the on-chip microhotplate in a liquid environment. The microhotplate array utilizes a standard 0.5 µm CMOS process and requires only a 5V supply. A simple in-package encapsulation scheme was implemented to verify thermal control operations in a liquid environment necessary for protein-based interfaces. To individually control the temperature of biointerfaces on the surface of a CMOS chip, each channel includes microhotplate and a feedback network for temperature control. The microhotplate is composed of a resistive heater, a resistive temperature sensor, heater driver circuitry, and sensor readout circuitry. A temperature-independent current, Is, generates a proportional-to-temperature voltage that is read by an A/D converter. The proportional integral derivative (PID) thermal controller compares the expected Figure 3. 1. Block diagram of the micro-thermoelectric control system. 15 temperature with the sensor-measured temperature and adjusts the duty cycle of the pulse width modulator (PWM). The PWM controls the heater to deliver the average power necessary to maintain the desired temperature. Because the heater and sensor are very near the surface of the chip, the temperature of the surface biointerface can be well maintained. 3.1.3 Microhotplate Array Design 4B A microhotplate is a micro-scale structure consisting of a heater and a temperature sensor and has been widely employed in gas sensors [21, 22, 33] To adapt microhotplates to protein interfaces, significant prior work in modeling [47] and experimental design [48, 49] has been completed by past students in our lab. Building on these past efforts, to better understand the thermal behavior of this micro-scale thermal system, the microhotplates were modeled and simulated using the CoventorWare finite element analysis tool with the Electromagnetics and Heat Transfer modules. Design optimizations were performed based on the following requirements: ability to achieve temperatures near 45 ˚C, high thermal uniformity across the hotplate to prevent damage to biointerfaces, low power consumption, high thermal strength to increase robustness, and compatibility with a standard IC process. The finite element simulation results demonstrated that, when properly designed, a standard CMOS microhotplate 1) could be designed using two polysilicon layers for a heater resistor and a resistive temperature sensor as shown in Figure 3.2, and 2) could achieve the target temperatures (up to 45 ˚C) using only a 5V supply and without any post-CMOS etching of silicon beneath the microhotplate to improve thermal isolation. Furthermore, simulations showed that sufficiently high temperatures could be achieved even in the presence of a liquid environment. These 16 results are significant because they validate a new approach that has many potential advantages but has never been attempted or reported in the literature. The microhotplate array was designed in the standard AMI 0.5 µm 3-metal, 2-poly CMOS process. As shown in Figure 3.2, the poly1 layer was used as the heater because of its high thermal capacity than metal layers and lower resistance compared to the poly2 layer. A circular design was chosen to reduce the heat dissipation [46]. To decrease resistance, and thus increase the maximum power delivered for a fixed voltage, concentric rings were chosen rather than a single serpentine heater. For a typical 100 µm diameter heater, the nominal heater resistance was 140 , which provides sufficient heating using only a 5V supply. A thermal simulation of this structure is shown in Figure 3.3 (a). Notice the hotter areas where current density is higher. Due to the small diameter of the heater and the desire to keep resistance low, there is a limit to how well hot spots can be Figure 3.2. Cross section of the CMOS microhotplate for thermal control of onchip biosensor arrays. 17 controlled just by changes in the poly1 layout. However, it was determined that proper allocation of highly thermally conductive CMOS metal layers and via contacts between the heater and the surface electrode could minimize the lateral thermal gradient [46] and remove all local hot spots, as shown in Figure 3.3 (b). The final element of the microhotplate is the resistive temperature sensor, which was formed in poly2 because of its high sheet resistance and close proximity to the poly1 heater layer. The sensor resistor was laid out in a thin-wire serpentine pattern to average temperature across the heater area and produce a large resistance, nominally 300-400 k . 18 (a) (b) Figure 3.3. Thermal analysis simulations: (a) temperature probed on surface of the heater; (b) temperature probed on surface of chip. 19 3.1.4 PID Thermal Controller 5B High precision in the thermal control system is desirable to ensure that all sensing processes on the microhotplate take place at the desired temperature throughout a measurement cycle. The PID controller is a well known structure that corrects the error between a measured variable and the desired setpoint. It calculates and then outputs a corrective signal to rapidly adjust the process and minimize error. By optimizing the P, I and D parameters for a microhotplate system, a high speed thermal controller with very small error was realized. In this prototype system, the PID controller was implemented in software. An analog feedback controller with similar functionality was designed for the next generation system described in Chapter 5. 3.2 Microsystem Packaging A 3×3 microhotplate array with on-chip drive and readout circuitry was fabricated in 0.5µm CMOS and is shown in Figure 3.4. The chip was wire bonded to a standard DIP40 package for electrical testing. A simple packaging scheme that circumvents photolithography and enables liquid to get to the chip surface without interfering with wire bond connections was developed by lab mate Lin Li [45, 50]. This packaging scheme was adopted to conduct thermal tests in a liquid environment. The area around the chip and inside the DIP40 package was filled with SU8 photoresist. SU8 is commonly used to construct microstructures because it can form thick layers and is available in a wide range of viscosities. Experiments were performed to determine which viscosity of SU8 provided 20 the ideal combination of uniform coverage of the large package volume with sufficient surface tension to deter spreading onto the surface of the chip. SU8 2002 was found to be most effective. SU8 also provides thermal insulation for the chip, resulting in reduced heat loss to the ambient air. The SU8 was applied through a syringe in several layers, soft baking on a hotplate and cross linking with UV light after each layer, as shown in Figure 3.5. After the final SU8 layer, isolated the wire bonds were isolated and created a reservoir of approximately 0.5 ml was formed above the chip, as shown in Figure 3.6. To extend the volume, a polymethylsiloxane (PDMS) cap was fabricated using an SU8 master and soft lithography standard for this the biocompatible PDMS material. The cap extended the height of the reservoir by about 400µm, increasing the volume to approximately 1ml. The PDMS structure on the SU8 chip package was found to seal well and hold the liquid sample during thermal testing. Figure 3. 4. Die photograph of the 1.5x1.5mm microhotplate 3x3 array. 21 Figure 3.5. Chip packaging flow: (a) chip in DIP40; (b) dispense SU8 2002 using a syringe; (c) soft baking, UV exposure and hard baking; (d) final SU8 reservoir; (e) PDMS cap on DIP40 package. Steps (b) and (c) are repeated 4 or 5 times until package is fully filled with SU8. 3.3 Measurement Results and Analysis A test board was developed to connect the thermal control array chip to a PC equipped ® with a data acquisition card, and a LabVIEW program was designed to track and record the sensor temperature. The chip was first placed in an environmental test chamber to determine the poly1 sensor resistor’s temperature coefficient of resistance (TCR). The poly1 resistance was found to decrease linearly with temperature from 27-80˚C, and a TCR of -1, 520 ~ -3, 220ppm/˚C was calculated, with similar results for all sensor 22 Figure 3. 6. The 1.5x1.5mm wire bonded first thermal CMOS chip encapsulated with SU8 2002. There are 3x3 microhotplate array in the chip. resistors on the chip. To improve the measurement precision, it is better to calibrate the TCR in every chip fabrication because TCR is sensitive to the process. After calibrating the PID controller, a step response test of the entire thermal control system was performed at room temperature by setting the desired temperature from 27 to 42˚C in 3 ˚C steps. The temperature was held constant for 60 seconds before each step. The results plotted in Figure 3.7 show that the thermal settling time increases with temperature, as expected, with about 14 seconds to step to 30˚C. Once the set point is reached, the temperature is held very stable by the feedback controller; extensive testing shows a maximum error of only 0.7 ˚C over the entire span of operation. 23 The heating potential of the on-chip microhotplate as a function of heater voltage was tested in both air and liquid environments. The results in Figure 3.8 show that, as expected, higher voltages generate higher maximum temperatures. Although the maximum temperature is slightly higher in air, the microhotplate in liquid was able to rise to nearly 45 ˚C with only a 5 V heater drive voltage. Because the heater drive voltage connects only to the heater resistor and not to CMOS devices, a higher voltage could be used to increase the temperature. However, 45 ˚C is sufficient to characterize most proteins or to maximize their reactivity for sensor applications. For example, our colleagues in Dr. R. Mark Worden’s lab have characterized the temperature dependence of NEST (NEST is a hydrophobic recombinant polypeptide comprising the catalytic domain (residues 727–1216) of neuropathy target esterase [51]), a catalytically active fragment of the membrane protein Neuropathy Target Esterase (NTE) found in human neurons. Figure 3.9 plots the NEST thermal characteristics in the range of 20 °C – 60 °C, Figure 3.7. Thermal step response of the microhotplate thermal control system for 3 ˚C steps. 24 showing a typical parabolic function with maximum activity at 31 °C after which activity irreversibly degrades. The microhotplate array microsystem is well suited to thermally control this and similar proteins. Finite element analysis simulations predicted that the heat from of each array element would be contained in very close proximity to the heating element, even without additional processing steps to improve the thermal isolation of each heater. This selfcontained heading would permit each array element to be set to a different temperature for simultaneous characterization at multiple temperatures. To test this prediction, an experiment was conducted where one array element was heated and the temperature sensors of several other array elements were monitored. Referring to labels in Figure 3.4, a 5 V source was applied to the heater in array element ‘A’ for more than 10 min to ensure the maximum temperature was reached. Microhotplate temperature sensor values at elements ‘A’ – ‘E’ were then recorded. Figure 3.10 plots the results as a function of the Figure 3.8. Temperature (at on-chip sensor) in air and in liquid at different heater voltages. 25 sensor’s distance from the one active heater, ‘A’. As expected, as distance increases the thermal isolation improves, and at only 0.4mm from the heater the induced temperature change is less than 1˚C. Although the thermal isolation was not as strong as predicted by simulations, these results verify that it is feasible to simultaneously set individual elements of the array to different temperatures. Even on the tiny 1.5×1.5 mm chip tested here, a highly isolated 2×2 array could easily be formed. 3.4 Summary and Analysis Figure 3.9. Current density of a NEST (NEST is a hydrophobic recombinant polypeptide comprising the catalytic domain (residues 727–1216) of neuropathy target esterase) biosensor at different temperatures. 26 Figure 3.10. The sensor measured temperature vs. the distance from the heating source to the sensor. A complete thermal control microsystem for protein characterization and sensing was developed and tested. The CMOS hotplate design ensures good spatial uniformity with no local hotspots. The chip was fabricated in a standard CMOS process and packaged using layering of SU8 for use in a liquid environment. A maximum temperature of 45 ˚C was achieved in liquid with a 5V supply. The thermal control microsystem can set and hold temperatures within 0.7 ˚C, and array elements were found to be almost completely thermally isolated from each other at distances beyond 0.4 mm. These test results proved our designed thermal microsystem is suitable for the protein characterization. However, the thermal controller was implemented using an off-chip PID controller, the chip did not include a sensor to monitor the ambient temperature, and the chip did not include any readout circuits. To achieve a fully integrated protein thermal control system, these elements are very important. Building on the efforts described in this 27 chapter, the second generation thermal controlled protein characterization chip, introduced at Chapter 5, implements these improvements . 28 Chapter 4 Impedance Extraction Circuits for Protein Array Traditionally, impedance spectroscopy measurements require complex and bulky electronics or utilize digital signal processing algorithms that require extensive computer hardware. To support chip-scale microsystem applications, a very hardware efficient and low power solution is needed that combines accurate, low noise impedance measurement circuits with electronics capable of extracting real and imaginary signal components and circumvents the heavy signal processing load incurred by parallel impedance extraction of a sensor array [52, 53]. Some impedance measurement systems have been built for miniaturized biomedical and biochemical systems [53-55], but they either lack the integration of measurement, extraction, and digitization functions or they fail to support multi-channel array-based systems. In this chapter, a compact, high-sensitivity lock-in impedance-to-digital converter (IDC) circuit for sensor array microsystems is presented. The lock-in IDC cell is based on a delta-sigma structure and can be instantiated for each sensor element to enable massively parallel interrogation, including analog domain impedance extraction and local digitization. Its low power consumption extends the battery-life for portable applications and protects on-chip sensors from overheating. It also provides high sensitivity to read 29 the very weak responses characteristic of miniaturized sensor elements. Compared to prior works in our lab [56], the new impedance measurement circuit presented here adds DC impedance readout capability and implements design modifications that reduce power and area, thus improving the utility of the circuit in array-based microsystems. 4.1 Architecture of Impedance Extraction Circuits There are three main concerns for integrating on a single chip all of the instrumentation functions for multi-channel impedance extraction. First, the heavy signal processing load must be simplified, which is especially true for multi-channel arrays. Second, the circuit area per channel must be minimized to maximize the potential array density in support of high throughput characterization goals. Finally, the power must be minimized to support portable applications and ensure no local heating that could degrade on-chip biointerfaces. To support these goals, an impedance extraction front-end instrumentation circuit based on the frequency response analyzer (FRA) method was developed. The FRA method processes the response of one frequency point at a time. It is a pure technique that gives rise to very stable, repeatable measurements, can be realized with compact analog circuits, and is able to minimize the effects of noise and distortion. Moreover, if all of the analog circuits can operate in the weak inversion region, static power consumption can be minimized and noise performance can be improved. 4.2 Impedance Readout Circuit 30 The IS measurement circuit presented here is based on a delta-sigma structure and will be referred to as the lock-in IDC, as defined in prior work in our lab [53]. Utilizing the FRA method, the lock-in IDC scheme simultaneously computes and digitizes the real or imaginary response components, sharing hardware required for these operations to minimize the power and area of the circuit. 4.2.1 Theory of Operation 6B The derivation of lock-in IDC operation was reported in [53] and was repeated here for clarity. To describe FRA method and the operation of the lock-in IDC, consider a sensor interface stimulated by a sinusoidal voltage, sin(ωt), and producing a current response IX such that IX=Asin( ωt+θ )=asin( ωt)+bcos( ωt) (4-1) where A and θ represent the amplitude and phase, of the sensor’s impedance, respectively. Here a=Acos(θ) is the real portion and b=Asin(θ) is the imaginary portion of the sensor’s admittance (the reciprocal of impedance). The values of a and b over a wide frequency range are sufficient to fully describe the sensor’s impedance response. To extract the values of a and b, a multiplying integrator was designed for the lockin IDC. As shown in Figure 4.1, the multiplier is driven by a square wave, φ(t). When control signal S in Figure 4.1 is set to 0, φ(t) is in phase with sin(ωt) and is described by 31 nT ≤ t