Deep Learning-Assisted Investigation of Electric Field-Dipole Effects on Catalytic Ammonia Synthesis.

ABSTRACT: External electric fields can modify binding energies of reactive surface species and enhance catalytic performance of heterogeneously catalyzed reactions. In this work, we used density functional theory (DFT) calculations-assisted and accelerated by a deep learning algorithm-to investigate the extent to which ruthenium-catalyzed ammonia synthesis would benefit from application of such external electric fields. This strategy allows us to determine which electronic properties control a molecule's degree of interaction with external electric fields. Our results show that (1) field-dependent adsorption/reaction energies are closely correlated to the dipole moments of intermediates over the surface, (2) a positive field promotes ammonia synthesis by lowering the overall energetics and decreasin

SUBMITTER: Wan M 

PROVIDER: S-EPMC9241008 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature