Literature DB >> 22583277

Evaluation of the grand-canonical partition function using expanded Wang-Landau simulations. I. Thermodynamic properties in the bulk and at the liquid-vapor phase boundary.

Caroline Desgranges1, Jerome Delhommelle.   

Abstract

The Wang-Landau sampling is a powerful method that allows for a direct determination of the density of states. However, applications to the calculation of the thermodynamic properties of realistic fluids have been limited so far. By combining the Wang-Landau method with expanded grand-canonical simulations, we obtain a high-accuracy estimate for the grand-canonical partition function for atomic and molecular fluids. Then, using the formalism of statistical thermodynamics, we are able to calculate the thermodynamic properties of these systems, for a wide range of conditions spanning the single-phase regions as well as the vapor-liquid phase boundary. Excellent agreement with prior simulation work and with the available experimental data is obtained for argon and CO(2), thereby establishing the accuracy of the method for the calculation of thermodynamic properties such as free energies and entropies.

Entities:  

Year:  2012        PMID: 22583277     DOI: 10.1063/1.4712023

Source DB:  PubMed          Journal:  J Chem Phys        ISSN: 0021-9606            Impact factor:   3.488


  2 in total

1.  The SAMPL6 SAMPLing challenge: assessing the reliability and efficiency of binding free energy calculations.

Authors:  Andrea Rizzi; Travis Jensen; David R Slochower; Matteo Aldeghi; Vytautas Gapsys; Dimitris Ntekoumes; Stefano Bosisio; Michail Papadourakis; Niel M Henriksen; Bert L de Groot; Zoe Cournia; Alex Dickson; Julien Michel; Michael K Gilson; Michael R Shirts; David L Mobley; John D Chodera
Journal:  J Comput Aided Mol Des       Date:  2020-01-27       Impact factor: 3.686

2.  Converging free energies of binding in cucurbit[7]uril and octa-acid host-guest systems from SAMPL4 using expanded ensemble simulations.

Authors:  Jacob I Monroe; Michael R Shirts
Journal:  J Comput Aided Mol Des       Date:  2014-03-08       Impact factor: 3.686

  2 in total

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