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Entropy of Simulated Liquids Using Multiscale Cell Correlation.

Hafiz Saqib Ali1,2, Jonathan Higham1,2, Richard H Henchman1,2

  • 1Manchester Institute of Biotechnology, The University of Manchester, 131 Princess Street, Manchester M1 7DN, UK.

Entropy (Basel, Switzerland)
|December 3, 2020
PubMed
Summary
This summary is machine-generated.

We developed a multiscale cell correlation (MCC) method to accurately calculate liquid entropy from molecular dynamics simulations. This new approach provides a clear decomposition of entropy contributions, improving understanding and accuracy for industrial liquids.

Keywords:
conformationcoordinationforcemolecular dynamics simulationprobability distributionstructurethermodynamicstorque

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Area of Science:

  • Physical Chemistry
  • Computational Chemistry
  • Materials Science

Background:

  • Calculating and understanding the entropy of liquids is crucial for many chemical and industrial processes.
  • Existing methods for calculating liquid entropy are limited in number and scope.
  • There is a need for methods that not only calculate entropy but also explain the origin of the calculated values.

Purpose of the Study:

  • To introduce and validate a novel multiscale cell correlation (MCC) method for calculating liquid entropy.
  • To apply the MCC method to a diverse set of 56 industrial liquids.
  • To provide a detailed decomposition of entropy contributions for better physical interpretation.

Main Methods:

  • Developed the multiscale cell correlation (MCC) method utilizing molecular dynamics simulations.
  • Incorporated forces, torques, and probability distributions at molecular and united-atom levels.
  • Introduced consistent treatment of mean-field approximations, separated covariance matrices, and included conformational correlations.

Main Results:

  • Achieved low unsigned errors of 8.7 J K⁻¹ mol⁻¹ (GAFF) and 9.8 J K⁻¹ mol⁻¹ (OPLS) compared to experimental entropies.
  • Demonstrated superior performance compared to the 2-Phase Thermodynamics method on common liquid systems.
  • Enabled decomposition of entropy into translational, rotational, vibrational, and topographical components at multiple scales.

Conclusions:

  • The MCC method offers a significant advancement in the accurate calculation of liquid entropies.
  • The method provides valuable insights into the origins of entropy, aiding in the understanding of liquid behavior.
  • MCC is a robust tool for studying a wide range of industrial liquids and informing process design.