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Conditional reversible work method for molecular coarse graining applications.

Emiliano Brini1, Valentina Marcon, Nico F A van der Vegt

  • 1Center of Smart Interfaces-TU Darmstadt, Petersenstr. 32, 64287 Darmstadt, Germany.

Physical Chemistry Chemical Physics : PCCP
|May 5, 2011
PubMed
Summary
This summary is machine-generated.

We introduce conditional reversible work (CRW) potentials for coarse-grained models, enhancing chemical and thermodynamic transferability. This method offers a straightforward, automatable approach for developing more physically significant effective potentials.

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Area of Science:

  • Computational chemistry
  • Materials science
  • Statistical mechanics

Background:

  • Coarse-grained (CG) models are essential for simulating complex fluids but often lack chemical and thermodynamic transferability.
  • Developing effective potentials with clear physical significance is crucial for improving CG model transferability.

Purpose of the Study:

  • Introduce conditional reversible work (CRW) potentials for pair-level nonbonded interactions in CG models.
  • Demonstrate the implementation and automization of CRW potentials.
  • Assess the temperature-transferability of CRW potentials for liquid phase density.

Main Methods:

  • Developed conditional reversible work (CRW) potentials for pair interactions.
  • Applied the method to 3-site models of hexane and toluene.
  • Investigated temperature-transferability of liquid phase density and compared with iterative Boltzmann inversion (IBI) potentials.

Main Results:

  • Successfully derived CRW potentials for hexane and toluene models.
  • Demonstrated the straightforward implementation and automization of the CRW method.
  • Evaluated the temperature-transferability of liquid phase density, showing comparable results to IBI potentials.

Conclusions:

  • CRW potentials offer a promising route to enhance the transferability of CG models for complex fluids.
  • The method is readily extendable for hydration contributions in implicit-solvent models.
  • CRW potentials provide a physically significant and automatable alternative to existing methods.