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Liquid Water and Interfacial, Cubic, and Hexagonal Ice Classification through Eclipsed and Staggered Conformation Template Matching.

Golnaz RoudsariFarshad G VeshkiBernhard ReischlOlli H Pakarinen
Published in: The journal of physical chemistry. B (2021)
We propose a novel method based on template matching for the recognition of liquid water, cubic ice (ice Ic), hexagonal ice (ice Ih), clathrate hydrates, and different interfacial structures in atomistic and coarse-grained simulations of water and ice. The two template matrices represent staggered and eclipsed conformations, which are the building blocks of hexagonal and cubic ice and clathrate crystals. The algorithm is rotationally invariant and highly robust against imperfections in the ice structure, and its sensitivity for recognizing ice-like structures can be tuned for different applications. Unlike most other algorithms, it can discriminate between cubic, hexagonal, clathrate, mixed, and other interfacial ice types and is therefore well suited to study complex systems and heterogeneous ice nucleation.
Keyphrases
  • molecular dynamics simulations
  • machine learning
  • molecular dynamics
  • deep learning
  • molecularly imprinted
  • mass spectrometry