Zeng Research Group
AI/SI-Accelerated Computational Discovery, Design and Development of Catalysts and Interfaces
AI/SI-Accelerated Computational Discovery, Design and Development of Catalysts and Interfaces
Our research group harnesses advanced computational modeling to develop practical and sustainable energy solutions. We focus on enhancing the catalytic activity and durability of hydrogen fuel cells and water electrolysis through density functional theory (DFT) surface calculations and data-driven materials design.
By bridging quantum-level understanding with real-world applications, we aim to advance next-generation electrocatalysts and accelerate the global transition to a clean hydrogen economy.
By integrating machine learning with density functional theory (DFT) calculations through the Atomic Simulation Environment (ASE), our group models catalytic reactions under realistic operating conditions.
ASE: https://ase-lib.org/
Purdue's super-computing clusters allow us to carry out the complex calculations we need
Find out more: RCAC - Purdue