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Van der Waals Perspective on Coarse-Graining: Progress toward Solving Representability and Transferability Problems.

Nicholas J H Dunn1, Thomas T Foley2, William G Noid1

  • 1Department of Chemistry, The Pennsylvania State University , University Park, Pennsylvania 16802, United States.

Accounts of Chemical Research
|December 21, 2016
PubMed
Summary
This summary is machine-generated.

This study resolves limitations in coarse-grained (CG) models by developing a "pressure-matching" method. This approach accurately reproduces both structural and thermodynamic properties of all-atom (AA) models, improving CG model transferability and representability.

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Area of Science:

  • Computational Chemistry
  • Materials Science
  • Statistical Mechanics

Background:

  • Coarse-grained (CG) models offer computational efficiency for large-scale simulations but face challenges in accurately representing physical forces and predicting properties.
  • "Bottom-up" CG models derived from all-atom (AA) simulations often struggle with the "transferability" and "representability" problems, limiting their predictive power across different thermodynamic states.
  • A key issue is the overestimation of pressure and poor compressibility description in conventional structure-based CG models.

Purpose of the Study:

  • To investigate the fundamental origins of the representability and transferability problems in CG modeling.
  • To develop a rigorous and practical method to overcome these limitations and improve the accuracy of CG models.
  • To demonstrate the capability of improved CG models to accurately predict structural and thermodynamic properties.

Main Methods:

  • Re-examination of the "exact coarse-graining" procedure to understand the role of thermodynamic information.
  • Development and application of a "pressure-matching" technique to address the density dependence of the potential of mean force (PMF).
  • Validation of the improved CG models against AA simulations for molecular liquids and mixtures.

Main Results:

  • The "pressure-matching" method effectively resolves the density dependence of the PMF, addressing the core of representability and transferability issues.
  • The resulting bottom-up CG models accurately reproduce structural properties, equilibrium density, compressibility, and the equation of state for molecular liquids.
  • Transferable potentials developed using this approach show high accuracy for heptane-toluene mixtures and predictive power for unseen concentrations.

Conclusions:

  • The representability and transferability problems in CG modeling are not fundamental limitations but arise from improper handling of thermodynamic information.
  • The "pressure-matching" approach provides a robust solution, enabling CG models to accurately capture both structural and thermodynamic behaviors.
  • This work suggests a "van der Waals" perspective on coarse-graining, integrating configurational and thermodynamic information for more predictive CG models.