Application of Quantum Chemical Topology Force Field FFLUX to Condensed Matter Simulations: Liquid Water.

ABSTRACT: We present here the first application of the quantum chemical topology force field FFLUX to condensed matter simulations. FFLUX offers many-body potential energy surfaces learnt exclusively from ab initio data using Gaussian process regression. FFLUX also includes high-rank, polarizable multipole moments (up to quadrupole moments in this work) that are learnt from the same ab initio calculations as the potential energy surfaces. Many-body effects (where a body is an atom) and polarization are captured by the machine learning models. The choice to use machine learning in this way allows the force field's representation of reality to be improved (e.g., by including higher order many-body effects) with little detriment to the computational scaling of the code. In this man

SUBMITTER: Symons BCB 

PROVIDER: S-EPMC9476653 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature