Internship project: Screening of dopants in V2O5 for enhanced electrochemical performance using machine learning-accelerated methods

Vanadium pentoxide (V2O5) is a widely studied material for electrocatalysis due to its redox properties and potential as an efficient catalyst for the oxyge¬¬n evolution reaction (OER). However, further improvements in its catalytic performance can be achieved by modifying its surface structure through the incorporation of dopants. This project aims to enhance the catalytic performance of V2O5 in OER by screening various dopant elements. Machine learning-accelerated Monte Carlo simulations will be employed to investigate the effects of dopants on surface reconstruction and controlled defect formation. After identifying promising candidates, density functional theory (DFT) calculations will be performed to create Gibbs free energy diagrams, offering insights into their electrocatalytic activity. The most promising candidates will then be synthesized and experimentally validated for water splitting performance.

Faculty Supervisor:

Bruno Pollet

Student:

Partner:

Massachusetts Institute of Technology

Discipline:

Physics

Sector:

Education

University:

Université du Québec à Trois-Rivières

Program: