Senior Project Scientist (2021 - Present)
Research Area Accelerating the Discovery of g-C3N4-supported single atom catalysts for hydrogen evolution reaction
Area of Interest In light of H2 emerging as a promising alternative to the conventional fuels, our work focusses on finding suitable g-C3N4 based SAC’s for Hydrogen Evolution Reaction (HER). A three-tier screening based on formation energy, Gibbs free energy and band-gap is used to down select suitable candidates. Also, a robust machine learning model is built based on the data generated from DFT as well as the features of gas-phase atoms present in the chemical composition. As a part of model development, performance of Multivariate Linear Regression (MLR), Decision Tree Regression (DTR), and Random Forest Regression (RFR) are compared. In addition, feature importance analysis is employed to identify key descriptors for the HER.
Abraham M, Parey V, Jyothirmal MV, Singh JK "Tuning the structural properties and chemical activities of graphene and hexagonal boron nitride for efficient adsorption of steroidal pollutants "Applied Surface Science (2022)