Machine Learned Fock Matrix.

ABSTRACT: This work introduces a novel machine learning integral-based self-consistent field method, called miSCF, designed for the efficient prediction of molecular electronic structures. By incorporating detailed information from the atomic information and geometric features to predict the molecular Fock matrix, this approach enhances data sharing among similar systems and facilitates effective data transfer within chemically analogous systems. This enables precise predictions of various electronic properties of the systems with only a small amount of training data, significantly reducing computational costs while maintaining high accuracy. Testing results on some representative small molecules, H₂ and H₂O chain as well as ice structures, demonstrate that miSCF

SUBMITTER: Liu H 

PROVIDER: S-EPMC12648309 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature