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A FFLUX Water Model: Flexible, Polarizable and with a Multipolar Description of Electrostatics.

Zak E HughesEmmanuel RenJoseph C R ThackerBenjamin C B SymonsArnaldo F SilvaPaul L A Popelier
Published in: Journal of computational chemistry (2019)
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. © 2019 The Authors. Journal of Computational Chemistry published by Wiley Periodicals, Inc.
Keyphrases
  • molecular dynamics simulations
  • machine learning
  • mass spectrometry
  • high performance liquid chromatography
  • systematic review
  • single molecule
  • deep learning
  • artificial intelligence
  • solar cells
  • virtual reality