In this study, we explored the application of Python programming for conducting and analyzing voltammetry tests using the IO Rodeo Potentiostat. Cyclic voltammetry (CV) and constant potential voltammetry (CPV) experiments were performed, and the acquired data were processed and visualized using Python scripting. The integration of Python allowed for real-time data acquisition, precise control of experimental parameters, and efficient post-experiment data analysis. For cyclic voltammetry, potential scans were conducted over a defined voltage range, and the resulting current responses were recorded and plotted to reveal the redox behavior of the electroactive species. Additionally, constant potential voltammetry experiments provided insights into the electrochemical behavior under steady-state conditions.

Graphical representations of the voltammetry data were generated using Matplotlib, showcasing clear and interpretable plots of current versus potential. The flexibility of Python facilitated customization of data visualization and streamlined the analysis process. This research demonstrates the feasibility and advantages of utilizing Python programming with the IO Rodeo potentiostat for electrochemical investigations. The presented approach enhances experimental control, data handling, and visualization, opening avenues for further advancements in electrochemistry research and education.