Pulse voltammetry (PV) encompasses a range of electroanalytical techniques utilizing a series of voltage pulses to study electrochemical reactions. These techniques provide numerous advantages over other electroanalytical techniques such as cyclic voltammetry (CV) and impedance spectroscopy by providing high sensitivity and discrimination against charging currents. Critically, this enables a more quantitative analysis of the voltammogram than is typical. In conjunction with mathematical models, PV can provide valuable quantitative information on the reaction kinetics, thermodynamics, and consistency with a hypothetical mechanism. Regression of experimental PV data against simulations, as opposed to comparing a limited set of features such as peak heights or full width at half-height, also enables the researcher to evaluate statistical confidence in the model and estimated parameters.

The objective of this work is to develop a pulse voltammetry analysis toolkit (PVAT) to automate kinetic parameter estimation, determine confidence, and enable mechanism discrimination using PV experimental data. The desired toolkit will address multiple PV techniques including square wave voltammetry (SWV), one of the most popular pulse techniques, and other common waveforms including normal pulse (NPV) and staircase (SC). As different pulse waveforms are best suited for elucidating different physical phenomena, the ability to analyze several techniques simultaneously provides significant value. Additional objectives include providing statistical analysis and sensitivity to mechanism parameters. Evaluating sensitivity to the PV parameters (e.g. pulse width, pulse height) is also desired, so that the analyst can improve the experimental design to further reduce uncertainty in kinetic, transport, and thermodynamic parameters. A long-term goal is to extend and apply these techniques to porous electrodes, to enable quantitative evaluation of emerging electroactive materials in batteries and fuel cells.

This presentation will include examples demonstrating the application of the developed PV toolkit to quantitative analysis of several PV studies using both experimental and simulated data. Support for multiple techniques has been successfully enabled through a modular toolkit design. Applications of the toolkit in simulation mode, which simply outputs the predicted voltammogram for a user specified pulse profile and mechanism, will be presented to verify the toolkit against prior work. The focus will be on the toolkit application in parameter estimation mode, which utilizes experimental data to determine the kinetic and thermodynamic parameters (e.g. rate constants, half-wave potential) for one or more mechanisms which best fit the observed data. Examples of statistical evaluation of multiple mechanisms against voltammogram data will be shown, demonstrating quantitative comparison to determine the most applicable mechanism for a given system. Currently, PVAT can simulate a sequence of any number of sequential single step electron transfer reactions on a planar electrode, with or without homogeneous reactions affecting any of the intermediates. Analysis of multi-step mechanisms including surface adsorption/desorption coupled with surface-confined electron transfer reaction will also be presented.

An example application will show PVAT analysis of the oxidation of acetaminophen under acidic, neutral, and basic pH of cyclic using square wave experimental data. Acetaminophen oxidation was selected as a test case because the pH dependence of the mechanism provides a simple means to generate data with several reaction pathways. The estimated parameters were consistent with available literature data and statistical analysis was able to discriminate among the candidate mechanisms and the modeled voltammograms agreed well with experimental data, as shown in Figure 1.

The presentation will conclude with preliminary results for analysis of electrochemical reactions in porous electrodes. Development of a computationally efficient software to utilize PV experiments on porous electrodes will enable rapid characterization of novel candidate electrode materials in battery and fuel cell operations more efficiently and confidently than traditional cycling at various rates. The resulting kinetic, thermodynamic, and transport properties will provide critical input for models to accelerate the insertion of promising electrodes into prototype hardware. Ideally, the data obtained from PV experiments on porous electrodes will allow for prediction of battery and fuel cell behavior operating under a range of use conditions.

Acknowledgements

This material is based upon work supported by the Army Small Business Innovation Research (SBIR) Program Office under Contract Number: W911NF-17-C-0026.

Any opinions, findings and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the Army Small Business Innovation Research Program Office or the Army Research Office.

Figure 1: CSWV Net Voltammograms Comparing Experimental (Markers) and Model (Lines) Using CE-Mechanism of the Oxidation of Acetaminophen at pH1. The Square Wave Frequencies Ranged from 2.5 – 50 Hz.