Speaker
Description
Transitioning to sustainable clean energy requires efficient electrocatalysts to drive the cathodic hydrogen evolution reaction (HER) and anodic oxygen evolution reaction (OER) in water splitting. In this presentation, we will report computational results based on the combination of density functional theory calculations, the computational hydrogen electrode framework, and machine learning methods to screen and design high-performance electrocatalytic materials. We explore a broad materials space, including iridium-based surfaces, defect-engineered transition metal clusters supported on two-dimensional MoS2 (TM4@MoS2), multi-metal MXenes, and non-precious bimetallic alloys. The results show how local coordination, d-band center shifts, and synergistic active sites govern intermediate adsorption energetics. In particular, IrO2 outperforms metallic Ir for OER, Fe4@MoS2 demonstrates superior HER activity, and structural fluxionality from metastable configurations substantially promotes catalytic performance in sub-nanometer clusters. These atomistic insights deliver predictive design principles to advance materials discovery for green hydrogen and power-to-X technologies