Literature DB >> 25296830

The mold integration method for the calculation of the crystal-fluid interfacial free energy from simulations.

J R Espinosa1, C Vega1, E Sanz1.   

Abstract

The interfacial free energy between a crystal and a fluid, γcf, is a highly relevant parameter in phenomena such as wetting or crystal nucleation and growth. Due to the difficulty of measuring γcf experimentally, computer simulations are often used to study the crystal-fluid interface. Here, we present a novel simulation methodology for the calculation of γcf. The methodology consists in using a mold composed of potential energy wells to induce the formation of a crystal slab in the fluid at coexistence conditions. This induction is done along a reversible pathway along which the free energy difference between the initial and the final states is obtained by means of thermodynamic integration. The structure of the mold is given by that of the crystal lattice planes, which allows to easily obtain the free energy for different crystal orientations. The method is validated by calculating γcf for previously studied systems, namely, the hard spheres and the Lennard-Jones systems. Our results for the latter show that the method is accurate enough to deal with the anisotropy of γcf with respect to the crystal orientation. We also calculate γcf for a recently proposed continuous version of the hard sphere potential and obtain the same γcf as for the pure hard sphere system. The method can be implemented both in Monte Carlo and Molecular Dynamics. In fact, we show that it can be easily used in combination with the popular Molecular Dynamics package GROMACS.

Entities:  

Year:  2014        PMID: 25296830     DOI: 10.1063/1.4896621

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


  5 in total

1.  Breakdown of the law of rectilinear diameter and related surprises in the liquid-vapor coexistence in systems of patchy particles.

Authors:  Jorge R Espinosa; Adiran Garaizar; Carlos Vega; Daan Frenkel; Rosana Collepardo-Guevara
Journal:  J Chem Phys       Date:  2019-06-14       Impact factor: 3.488

2.  Machine learning coarse grained models for water.

Authors:  Henry Chan; Mathew J Cherukara; Badri Narayanan; Troy D Loeffler; Chris Benmore; Stephen K Gray; Subramanian K R S Sankaranarayanan
Journal:  Nat Commun       Date:  2019-01-22       Impact factor: 14.919

3.  Valency and Binding Affinity Variations Can Regulate the Multilayered Organization of Protein Condensates with Many Components.

Authors:  Ignacio Sanchez-Burgos; Jorge R Espinosa; Jerelle A Joseph; Rosana Collepardo-Guevara
Journal:  Biomolecules       Date:  2021-02-14

4.  Size conservation emerges spontaneously in biomolecular condensates formed by scaffolds and surfactant clients.

Authors:  Ignacio Sanchez-Burgos; Jerelle A Joseph; Rosana Collepardo-Guevara; Jorge R Espinosa
Journal:  Sci Rep       Date:  2021-07-27       Impact factor: 4.379

5.  RNA length has a non-trivial effect in the stability of biomolecular condensates formed by RNA-binding proteins.

Authors:  Ignacio Sanchez-Burgos; Jorge R Espinosa; Jerelle A Joseph; Rosana Collepardo-Guevara
Journal:  PLoS Comput Biol       Date:  2022-02-02       Impact factor: 4.475

  5 in total

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