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Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry
12:11

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Published on: April 8, 2020

Mesoscale model parameters from molecular cluster calculations.

Reinier L C Akkermans1

  • 1Accelrys Ltd., 334 Cambridge Science Park, Cambridge CB4 0WN, United Kingdom. reiniera@accelrys.com

The Journal of Chemical Physics
|July 8, 2008
PubMed
Summary

We developed a new method to calculate interaction parameters for mesoscale simulations from molecular clusters. This approach accurately predicts phase behavior by including both energy and entropy contributions, improving upon energy-only calculations.

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Area of Science:

  • Computational chemistry
  • Materials science
  • Statistical mechanics

Background:

  • Mesoscale simulation methods like dissipative particle dynamics (DPD) and self-consistent field (SCF) theory require accurate interaction parameters.
  • Estimating these parameters from molecular simulations is crucial for predicting macroscopic material properties.

Purpose of the Study:

  • To present an efficient, systematic, and universal method for deriving interaction parameters for mesoscale simulations.
  • To explicitly calculate energy and entropy contributions to the free energy of mixing.

Main Methods:

  • Utilizing a generalized Flory-Huggins model based on van der Waals surface contacts.
  • Sampling the density of states of molecular clusters and employing histogram reweighting to compute free energy.
  • Calculating Flory-Huggins chi-parameter and its energetic/entropic components for binary mixtures.

Main Results:

  • The method successfully calculates explicit energy and entropy contributions to cluster free energy.
  • For hexane/nitrobenzene mixtures, including excess entropy of mixing improved phase behavior prediction accuracy.
  • Calculations based solely on average energy overestimated the chi-parameter in polymer blend simulations.

Conclusions:

  • The developed method provides accurate interaction parameters for mesoscale simulations by incorporating entropic effects.
  • This approach enhances the predictive power of DPD and SCF methods for phase behavior in mixtures and blends.
  • Accurate parameterization is essential for reliable simulation outcomes in materials science.