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Reverse Monte Carlo modeling of liquid water with the explicit use of the SPC/E interatomic potential.

Ildikó PethesLászló Pusztai
Published in: The Journal of chemical physics (2018)
Reverse Monte Carlo (RMC) modeling of liquid water, based on one neutron and one X-ray diffraction data set, applying also the most popular interatomic potential for water, extended simple point charge (SPC/E), has been performed. The strictly rigid geometry of SPC/E water molecules had to be loosened somewhat, in order to be able to produce a good fit to both sets of experimental data. In the final particle configurations, regularly shaped water molecules and straight hydrogen bonding angles were found to be consistent with diffraction results. It has been demonstrated that the explicit use of interatomic potentials in RMC has a role to play in future structural modeling of water and aqueous solutions.
Keyphrases
  • monte carlo
  • electronic health record
  • machine learning
  • high resolution
  • data analysis
  • artificial intelligence
  • deep learning