Abstract
Key to progress in molecular simulation is the development of advanced models that go beyond the limitations of traditional force fields that employ a fixed, point-charge based description of electrostatics. Taking water as an example system, the FFLUX framework is shown capable of producing models that are flexible, polarizable and have a multipolar description of the electrostatics. The kriging machine learning methods used in FFLUX are able to reproduce the intramolecular potential energy surface and multipole moments of a single water molecule with chemical accuracy using as few as 50 training configurations. Molecular dynamics simulations of water clusters (25-216 molecules) using the new FFLUX model reveal that incorporating charge- quadrupole, dipole-dipole and quadrupole-charge interactions into the description of the electrostatics results in significant changes to the intermolecular structuring of the water molecules.
Original language | English |
---|---|
Pages (from-to) | 619-628 |
Number of pages | 10 |
Journal | Journal of Computational Chemistry |
Volume | 41 |
Early online date | 20 Nov 2019 |
DOIs | |
Publication status | Published - 2020 |