My project is titled "DFT and machine learning simulation of the electrode/electrolyte interface". In this project, I am trying to accurately describe the interactions and dynamics at the electrode - electrolyte interface. The goal is to accurately model the reaction process of CO2 reduction, as well as the structure of an electric double layer on a metal surface with the help of Neural Network Potentials (NNPs). The usage of NNPs allows for accurate long - timescale simulations of such reaction processes and along with enhanced sampling methods such as metadynamics, these processes can be studied to a much greater extent. Currently, my work has started by trying to create an NNP that works across different metal surfaces in the presence of water. Experimental collaborators such as Marc Koper and Huib Bakker will also be involved in both data generation for conditioning of the model, as well as experimental validation of the results.
