Speaker
Description
The transition to sustainable energy requires the rapid discovery of advanced materials for energy conversion, storage, carbon utilization and clean fuels. The vast materials space and complex structure–property relationships make conventional trial-and-error approaches costly and time-consuming. Computational materials physics, integrating Density Functional Theory (DFT), atomistic modelling, high-performance computing, thermodynamic analysis and data-driven methods, provides a powerful pathway for accelerated materials discovery.
This presentation highlights a computational framework for understanding and designing functional materials for CO₂ reduction, water splitting, hydrogen production and storage, catalysis and energy conversion. The approach combines electronic-structure calculations, reaction-pathway analysis, high-throughput screening and data-driven materials selection to establish relationships between composition, structure, defects, electronic properties and functional performance.
Selected studies demonstrate the approach. DFT investigations of Cu–Zn bimetallic surfaces reveal how chemically distinct active sites influence competing CO₂-reduction pathways and product selectivity. Complementary studies examine CO₂ reduction and water-splitting catalysts through adsorption energetics, reaction free energies and electronic-structure descriptors. Metal–organic frameworks (MOFs) are explored as tunable porous materials for hydrogen storage, while MoS₂-based systems provide molecular-level insights into hydrogenation and C–O bond activation through reaction pathways, charge redistribution and vibrational analysis.
Together, these studies demonstrate the evolution from individual first-principles calculations toward an integrated DFT–data–AI–experiment workflow, in which computation guides materials selection and experimental validation. The presentation concludes by highlighting opportunities to strengthen computational materials research through HPC, open materials data, AI-assisted modelling and experimental collaboration, accelerating the pathway from atoms to materials, materials to devices, and devices to clean-energy technologies.
Keywords: Computational Materials Physics; Density Functional Theory; Materials Discovery; CO₂ Reduction; Water Splitting; Hydrogen Storage; Metal–Organic Frameworks; Catalysis; Clean Energy.