ElectroKitty: A Python Tool for Modeling Electrochemical Data Including Non-Langmuir Adsorption

Area of Science:

• Electrochemistry
• Computational Chemistry
• Materials Science

Background:

• Simulation and data analysis are increasingly vital in electrochemistry.
• Experimental electrochemical data often presents non-idealities due to adsorbed species.
• A need exists for accessible tools to simulate complex electrochemical systems.

Purpose of the Study:

• Introduce ElectroKitty, a novel Python package for simulating electrochemical reaction pathways.
• Incorporate corrections for non-idealities caused by adsorbed species in simulations.
• Demonstrate the package's versatility and advanced capabilities.

Main Methods:

• Developed ElectroKitty as a Python package for electrochemical simulations.
• Programmed corrections for non-ideal adsorbed species.
• Validated simulations against an established electrochemical simulator.
• Modeled Frumkin isotherm and OH adsorption on Pt(111).

Main Results:

• ElectroKitty successfully simulates complex reaction pathways.
• The package accurately reproduces the Frumkin isotherm.
• Simulations of OH adsorption on Pt(111) demonstrate advanced modeling capabilities.
• Validation confirmed the accuracy of ElectroKitty against established simulators.

Conclusions:

• ElectroKitty provides a versatile and accurate tool for electrochemical simulations.
• The package effectively handles non-idealities from adsorbed species.
• ElectroKitty facilitates the study of complex electrochemical phenomena and surface interactions.