Invariant Molecular Representations for Heterogeneous Catalysis.

ABSTRACT: Catalyst screening is a critical step in the discovery and development of heterogeneous catalysts, which are vital for a wide range of chemical processes. In recent years, computational catalyst screening, primarily through density functional theory (DFT), has gained significant attention as a method for identifying promising catalysts. However, the computation of adsorption energies for all likely chemical intermediates present in complex surface chemistries is computationally intensive and costly due to the expensive nature of these calculations and the intrinsic idiosyncrasies of the methods or data sets used. This study introduces a novel machine learning (ML) method to learn adsorption energies from multiple DFT functionals by using invariant molecular representations (IMRs). To do th

SUBMITTER: Chowdhury J 

PROVIDER: S-EPMC10806804 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature