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The European Physical Journal Special Topics

, Volume 225, Issue 8–9, pp 1347–1372 | Cite as

Parametrizing coarse grained models for molecular systems at equilibrium

  • E. Kalligiannaki
  • A. Chazirakis
  • A. Tsourtis
  • M.A. Katsoulakis
  • P. Plecháč
  • V. Harmandaris
Regular Article Methodological Aspects of Coarse Graining
Part of the following topical collections:
  1. Modern Simulation Approaches in Soft Matter Science: From Fundamental Understanding to Industrial Applications

Abstract

Hierarchical coarse graining of atomistic molecular systems at equilibrium has been an intensive research topic over the last few decades. In this work we (a) review theoretical and numerical aspects of different parametrization methods (structural-based, force matching and relative entropy) to derive the effective interaction potential between coarse-grained particles. All methods approximate the many body potential of mean force; resulting, however, in different optimization problems. (b) We also use a reformulation of the force matching method by introducing a generalized force matching condition for the local mean force in the sense that allows the approximation of the potential of mean force under both linear and non-linear coarse graining mappings (E. Kalligiannaki, et al., J. Chem. Phys. 2015). We apply and compare these methods to: (a) a benchmark system of two isolated methane molecules; (b) methane liquid; (c) water; and (d) an alkane fluid. Differences between the effective interactions, derived from the various methods, are found that depend on the actual system under study. The results further reveal the relation of the various methods and the sensitivities that may arise in the implementation of numerical methods used in each case.

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Copyright information

© EDP Sciences and Springer 2016

Authors and Affiliations

  1. 1.Department of Mathematics and Applied Mathematics University of CreteHeraklionGreece
  2. 2.Mathematical and Computer Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST)ThuwalSaudi Arabia
  3. 3.Department of Mathematics and StatisticsUniversity of Massachusetts at AmherstAmherstUSA
  4. 4.Mathematical Sciences, University of Delaware, NewarkDelawareUSA
  5. 5.Institute of Applied and Computational Mathematics, Foundation for Research and Technology Hellas, IACM/FORTH, G71110HeraklionGreece

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