Evolutionary Monte Carlo of QM Properties in Chemical Space: Electrolyte Design.

ABSTRACT: Optimizing a target function over the space of organic molecules is an important problem appearing in many fields of applied science but also a very difficult one due to the vast number of possible molecular systems. We propose an evolutionary Monte Carlo algorithm for solving such problems which is capable of straightforwardly tuning both exploration and exploitation characteristics of an optimization procedure while retaining favorable properties of genetic algorithms. The method, dubbed MOSAiCS (Metropolis Optimization by Sampling Adaptively in Chemical Space), is tested on problems related to optimizing components of battery electrolytes, namely, minimizing solvation energy in water or maximizing dipole moment while enforcing a lower bou

SUBMITTER: Karandashev K 

PROVIDER: S-EPMC10720348 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature