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Pressure-Consistent Iterative Boltzmann Inversion for Coarse-Grained Molecular Dynamics.

Zheng Yu1, Ryan J Szukalo1, Quinn M Gallagher2

  • 1Department of Chemistry, Princeton University, Princeton, New Jersey 08544, United States.

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|October 7, 2025
PubMed
Summary
This summary is machine-generated.

New coarse-graining methods, iterative range transformation (iRT) and iterative linear correction (iLC), improve pressure accuracy in molecular simulations. These approaches enhance thermodynamic consistency for better coarse-grained model development.

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Area of Science:

  • Computational chemistry
  • Materials science
  • Statistical mechanics

Background:

  • Bottom-up coarse-graining (CG) simulates complex molecular systems efficiently.
  • Existing methods often overestimate pressure due to thermodynamic representability issues, limiting NPT ensemble simulations.
  • Accurate pressure calculation is crucial for thermodynamic consistency in CG models.

Purpose of the Study:

  • To develop and analyze novel extensions of iterative Boltzmann inversion (IBI) for improved pressure calculation in CG models.
  • To introduce iterative range transformation (iRT) and iterative linear correction (iLC) as methods for pressure correction during CG potential optimization.
  • To evaluate the performance and transferability of iRT and iLC across various molecular systems and CG resolutions.

Main Methods:

  • Developed straightforward extensions of iterative Boltzmann inversion (IBI) incorporating pressure corrections.
  • Implemented iterative range transformation (iRT) and iterative linear correction (iLC) methods.
  • Evaluated CG model performance using structural features, radial distribution functions, densities, and isothermal compressibility across polymer melts and molecular liquids at different CG resolutions.

Main Results:

  • Both iRT and iLC retained structural fidelity while improving thermodynamic consistency.
  • The developed CG models accurately reproduced radial distribution functions, densities, and density fluctuations.
  • iRT demonstrated enhanced stability and faster convergence compared to standard methods.
  • Isothermal compressibility showed a resolution-dependent trend, deviating from atomistic behavior below a critical CG resolution.
  • Pressure transferability was found to be resolution-dependent, while temperature transferability remained largely independent of resolution.

Conclusions:

  • iRT and iLC are practical and transferable methods for constructing CG models with consistent thermodynamic behavior.
  • These methods offer significant improvements over traditional approaches by integrating pressure corrections directly into potential optimization.
  • The study provides valuable insights into the resolution-dependent limitations of CG model fidelity.