Ontology highlight
ABSTRACT:
SUBMITTER: Zielinski F
PROVIDER: S-EPMC5634454 | biostudies-literature | 2017 Oct
REPOSITORIES: biostudies-literature
Zielinski François F Maxwell Peter I PI Fletcher Timothy L TL Davie Stuart J SJ Di Pasquale Nicodemo N Cardamone Salvatore S Mills Matthew J L MJL Popelier Paul L A PLA
Scientific reports 20171009 1
The geometry optimization of a water molecule with a novel type of energy function called FFLUX is presented, which bypasses the traditional bonded potentials. Instead, topologically-partitioned atomic energies are trained by the machine learning method kriging to predict their IQA atomic energies for a previously unseen molecular geometry. Proof-of-concept that FFLUX's architecture is suitable for geometry optimization is rigorously demonstrated. It is found that accurate kriging models can opt ...[more]