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Kinetics of Ion Transport in Conducting Polymers

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Kinetics of Ion Transport in Conducting Polymers Kinetics of Ion Transport in Conducting Polymers Dissertation Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University By Vinithra Venugopal, B.E., M.S. Graduate Program in Mechanical Engineering The Ohio State University 2016 Dissertation Committee: Dr. Vishnu Baba Sundaresan, Advisor Dr. Carlos Castro Dr. Jose Otero Dr. Jonathan Song Dr. Vishwanath Subramaniam c Copyright by Vinithra Venugopal 2016 Abstract Conducting polymers (CPs) exhibit coupling between electrochemical and me- chanical domains, namely, reversible ion exchange with an electrolyte under an ap- plied electrical voltage causes volumetric changes in the polymer matrix. The goal of this dissertation is to develop precise quantification techniques to assess the kinetics of ion transport in CPs. These techniques are based on the mechanics of ion storage in polypyrrole doped with dodecylbenzene sulfonate (PPy(DBS)). In this work, it is postulated that CP response is dictated by the driving force for ion ingress and the accessible ion storage sites in the polymer. Two mechanis- tic models are founded on this premise: (1) A mathematical constitutive model is derived from the first law of thermodynamics to describe the chemomechanically cou- pled, structure dependent, input-output relationship in PPy(DBS). The uniqueness of this model is that mechanical expansion of the polymer is predicted without the incorporation of empirical coefficients. (2) A kinetic model is proposed to describe the current and charge response of PPy(DBS) to a step voltage input. The transfer- function based approach used to validate this model offers advantages over traditional lumped parameter models by quantifying the effect of polymer mass and morphology on the magnitude and rate of ion ingress. These metrics are valuable control variables for tuning the performance of CP based sensors, actuators and energy storage devices. ii This research leads to the development of a calibrated PPy(DBS) sensor for the determination of bulk electrolyte concentration. Additionally, a miniaturized sensor incorporated at the tip of an ultramicroelectrode demonstrates near-field sensing using scanning electrochemical microscopy (SECM) hardware. These electrodes are used in conjunction with shear force imaging to develop a novel imaging technique with potential applications in cell membrane biophysics. iii Acknowledgements Firstly, I would like to express my gratitude to my advisor and mentor, Dr. Vishnu Baba Sundaresan. His technical guidance and unwavering support have fueled my success in graduate school. During my time here, he gave me free rein to satisfy my intellectual curiosity and created several opportunities to conduct exciting, multi- disciplinary research. His passion for research has been an inspiration. I would like to thank my committee members Dr. Carlos Castro, Dr. Jose Otero, Dr. Jonathan Song and Dr. Vishwanath Subramaniam for their valuable advice and support. I have been envied by my colleagues for having such a warm and approachable committee. A big thank you to the Otero-Czeisler research group for taking me in as one of their own. Our collaborative project was truly a rewarding experience for me. I would especially like to thank Dr. Catherine Czeisler for spending her valuable time on setting up cell experiments and analyzing befuddling data with me. I deeply appreciate her friendship and kind words. Dr. Noriko Katsube, and my co-workers, Dr. Robert Northcutt and Travis Hery, have contributed immensely in honing my skills as a researcher through long and insightful discussions about my work. The assistance provided by my colleagues Vijay Venkatesh and Jacob Maddox has been instrumental in the success of several intricate experiments. iv I gratefully acknowledge financial support from National Science Foundation (CA- REER award 1325114) and Monte Ahuja graduate student fellowship for making my PhD work possible. The level of camaraderie among the members of the Sundaresan group facili- tated a fun and productive research environment. Having spent countless number of hours together, both, academically and socially, my fellow graduate researchers - Paul Gilmore, Srivatsava Krishnan, Travis Hery, Prasant Vijayaraghavan, Vijay Venkatesh, and Dr. Robert Northcutt - have become my second family. I will forever cherish their friendship. I would like to express my gratitude to my family and friends for their support and understanding over the past three years. My aunts, uncles and cousins, here in the US, for keeping my homesickness at bay; my parents, for putting their lives on hold and temporarily moving in with me on several occasions to take care of me; my sister, Varsha Venugopal, for her weekend visits from East Lansing and care packages; Andrew Bodratti for his daily phone calls and pep talks; Tess Zangrilli for our movie marathons; and finally, Matt Barr, for his patience and unconditional love, and for being the voice of reason during bleak times. They worked tirelessly to keep my spirits up and cheered me on. I couldn't have done it without them. v Vita June 1, 1986 . .Born - Chennai, Tamil Nadu, India 2008 . .B.E. Chemical Engineering Visvesvaraya Technological University 2011 . .M.S. Chemical Engineering University at Buffalo, SUNY 2011 - 2012 . Research Associate, Virginia Commonwealth University 2013 - present . Graduate Research Associate, The Ohio State University Publications Journal Publications V. Venugopal, T. Hery, V. Venkatesh, and V.B. Sundaresan, \Mass and charge density effects on the saturation kinetics of polypyrrole doped with dodecylbenzene sulfonate". Journal of Intelligent Material Systems and Structures, Accepted With Minor Revisions, 2016. V. Venugopal and V.B. Sundaresan, \Polypyrrole based amperometric cation sensor with tunable sensitivity". Journal of Intelligent Material Systems and Structures, doi: 10.1177/1045389X15604233, 2015. V. Venugopal, H. Zhang, R. Northcutt, and V.B. Sundaresan, \A thermodynamic chemomechanical constitutive model for conducting polymers". Sensors and Actua- tors B: Chemical, 201:293-299, 2014. vi Conference Proceedings V. Venugopal, H. Zhang, and V.B. Sundaresan, \A chemo-mechanical constitu- tive model for conducting polymers." ASME 2013 Conference on Smart Materi- als, Adaptive Structures and Intelligent Systems, 2013:V002T06A021-V002T06A021, Sept. 2013. Fields of Study Major Field: Mechanical Engineering vii Table of Contents Page Abstract . ii Vita......................................... vi List of Tables . xi List of Figures . xii 1. Introduction . .1 1.1 History . .1 1.2 Electronic Conductivity . .3 1.3 Ion Transport . .6 1.4 Electrochemical Analysis . .8 1.4.1 Cyclic Voltammetry . .9 1.4.2 Chronoamperometry . 13 1.5 Mathematical Descriptions of Ion transport . 15 1.5.1 Transmission Line Models . 15 1.5.2 Propagating/Moving Front Models . 17 1.5.3 Electrochemically Stimulated Chain Relaxation Model . 19 1.6 Mechanical Response due to Volumetric Expansion . 20 1.7 Applications . 24 1.8 Document Overview . 28 2. Motivation . 30 2.1 Morphology dependent CP response . 30 2.2 Constitutive Models . 32 2.3 Kinetic Models . 33 2.3.1 Inconsistencies of ESCR model . 34 viii 2.4 Scanning Electrochemical Microscopy with Shear Force Imaging (SECM- SF) ................................... 36 2.4.1 Shear Force Imaging . 39 2.4.2 UME Modifications . 40 2.5 Scientific Goals and Research Objectives . 42 3. Constitutive Model for Conducting Polymers . 44 3.1 Introduction . 44 3.2 Constitutive model . 45 3.3 Materials and methods . 48 3.3.1 Experimental setup . 48 3.3.2 Application of constitutive model to a PPy(DBS) actuator in NaCl . 51 3.4 Results and discussion . 53 3.4.1 Effect of NaCl concentration . 53 3.4.2 Effect of polymer packing . 58 3.4.3 Chemomechanical coupling coefficient - Significance in actu- ation, sensing and energy storage applications . 61 3.5 Summary . 62 4. Saturation kinetics model for ion ingress in PPy(DBS) . 65 4.1 Introduction . 65 4.2 Mechanics of Ion Storage in PPy(DBS) . 66 4.3 Saturation Kinetics Model . 67 4.4 Methods . 70 4.5 Results and discussions . 71 4.5.1 Effect of electrolyte concentration . 71 4.5.2 Effect of equilibration . 73 4.5.3 Pole-residue analysis of transient currents . 75 4.6 Summary . 79 5. Mass and charge density effects on saturation kinetics in PPy(DBS) . 81 5.1 Introduction . 81 5.2 Materials and Methods . 81 5.3 Results and Discussion . 83 5.3.1 Pole-residue analysis of chronocoulometric response . 85 5.3.2 Effect of Number of Redox Sites . 88 5.3.3 Effect of Redox Site Accessibility . 89 5.4 Synopsis of the Saturation Kinetics Model . 94 ix 5.5 Summary . 96 6. Nanoscale Polypyrrole Sensors for Near-field Electrochemical Measurements 98 6.1 Introduction . 98 6.2 Material and Methods . 99 6.2.1 Setup Characterization . 100 6.2.2 Electropolymerization . 103 6.2.3 PPy(DBS) UME Characterization . 104 6.3 Results and Discussion . 105 6.3.1 Electropolymerization . 105 6.3.2 Effect of distance from the substrate . 108 6.3.3 Effect of bulk electrolyte concentration . 114 6.4 Summary . 115 7. Conclusions . 118 7.1 Research Summary . 118 7.2 Significant Results . 119 7.2.1 Constitutive Model . 119 7.2.2 Saturation Kinetics Model . 120 7.2.3 PPy(DBS) Cation Concentration Sensor . 120 7.2.4 SECM-SF imaging with PPy(DBS) modified UMEs . 121 7.3 Contributions . 122 7.4 Future Directions . 123 Appendices A. Synthesis of PPy(DBS) . 126 A.1 Electropolymerization . 126 A.2 Equilibration . 128 B. Polypyrrole sensors on silicon nitride substrates . 130 C. Potentiostatic deposition of PPy(DBS) on Pt UMEs . 133 Bibliography . 135 x List of Tables Table Page 1.1 Electrochemical quartz crystal microbalance data for dopant ion trans- port in PPy . .7 1.2 PPy for actuator, sensor and energy storage applications . 24 1.3 PPy substrates for cell stimulation . 27 2.1 Morphology dependent charge transport in CPs as a function of poly- mer deposition conditions . 31 2.2 Summary of models predicting coupled response in CPs . 33 2.3 UME tip modifications for improving selectivity during SECM imaging 41 3.1 Constitutive model parameters .
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