Machine learning the electric field response of condensed phase systems using perturbed neural network potentials.

ABSTRACT: The interaction of condensed phase systems with external electric fields is of major importance in a myriad of processes in nature and technology, ranging from the field-directed motion of cells (galvanotaxis), to geochemistry and the formation of ice phases on planets, to field-directed chemical catalysis and energy storage and conversion systems including supercapacitors, batteries and solar cells. Molecular simulation in the presence of electric fields would give important atomistic insight into these processes but applications of the most accurate methods such as ab-initio molecular dynamics (AIMD) are limited in scope by their computational expense. Here we introduce Perturbed Neural Network Potential Molecular Dynamics (PNNP MD) to push back the accessible time and length scales of s

SUBMITTER: Joll K 

PROVIDER: S-EPMC11411082 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature