(334bx) Catalyst Design for Oxygen Reduction Reaction Using Molecular Modeling

Fuel cell technologies are regarded as the key for clean and sustainable energy generation; however, their efficiency is limited by the cathodic oxygen reduction reaction (ORR). Pt supported on carbon black, Pt/C, has long been recognized as the standard bearer in this field; however, its high cost and scarcity really cause challenges in wide applications. Therefore, my research interest is to search, develop, and design stable and efficient catalysts for ORR using computer modeling. In this work, molecular dynamics (MD) and density functional theory (DFT) are combined to study and design complex, multifunctional catalytic materials. To understand the carbon-supported Pt electrocatalysts for both cathodic (ORR) and anodic (MOR) reactions, MD simulations were performed to show that nanoscale Pt particles can be effectively stabilized at the open edges of the vertically aligned carbon nanofibers (VACNF). DFT calculations were then carried out to determine and predict the overpotential and catalytic activities. Moreover, DFT calculations were used to reveal the electronic structures, i.e. bader charge, which can be used as a descriptor to tune ORR activity. Further, scaling relationship of electrochemical potentials versus adsorption energies on reaction intermediates or charges on the active sites can be established and employed as training set for machine learning to screen, search, and design catalysts that has higher activity for ORR.

Research Interests

My research interest is catalysts design using first-principle-based method, i.e. density functional theory, to achieve high activity for ORR. I'd like to focus on building reasonable molecular model, investigating reaction mechanism and thermodynamics, characterizing material properties, finding catalytic trend, and designing new catalyst materials.