(209a) Cyclic Voltammetry Simulations in a Python Notebook for Interactive Electrochemistry Laboratories

Electrochemistry has received increased attention from chemical engineering students, especially students who are motivated by the pressing societal need for decarbonization. There is an opportunity to more thoroughly involve electrochemistry in all levels of chemical engineering curricula, not only as a way to encourage the interests of motivated students, but also as a way to connect concepts from different core courses and related disciplines.

Cyclic voltammetry is the quintessential experimental technique for electrochemists. From a teaching standpoint, it provides conceptually rich case studies that can be used to teach electrochemistry at multiple levels of complexity in a variety of classroom settings. Given the centrality of the technique and given the recognized benefits of hands-on and experiential learning, we propose that hands-on cyclic voltammetry laboratories are a key component for electrochemistry curricula for chemical engineers. In practice, the widespread adoption of cyclic voltammetry labs is hampered by the use of specialized equipment and software, which limits the hands-on time each student gets to explore how different parameters influence results, and thereby limits the extent to which students are able to develop intuition and comfort with the technique. In this talk, we introduce CVsim, cyclic voltammetry simulation and data fitting software in an interactive Python laboratory notebook, with the goal of making cyclic voltammetry more accessible for both virtual and experimental laboratory experiences.

The format of CVsim in an interactive Python notebook is designed to provide students access to rapid exploratory simulations and streamlined processing of experimental data interleaved with reflective prompts. Our goal is to minimize obstacles that could take time and attention away from learning voltammetry - such as extended coding and debugging, or waiting for access to lab equipment or a shared computer. Without any background coding experience needed, students can run CVsim in-browser in Google Colab on their personal computers.

We will first describe the functionality of the cyclic voltammetry simulation software, including the effects of input parameters and reaction mechanisms on simulated results. Then, we demonstrate how the simulation software may be used for fitting of student experimental data as part of an undergraduate laboratory activity on redox active materials for flow batteries, an emerging technology for grid-scale storage of renewable electricity. Finally, we propose further activities that could utilize Python notebook-based cyclic voltammetry simulation across different chemical education contexts.