Literature DB >> 17629320

Relationships between self-diffusivity, packing fraction, and excess entropy in simple bulk and confined fluids.

Jeetain Mittal1, Jeffrey R Errington, Thomas M Truskett.   

Abstract

Static measures such as density and entropy, which are intimately connected to structure, have featured prominently in modern thinking about the dynamics of the liquid state. Here, we explore the connections between self-diffusivity, density, and excess entropy for two of the most widely used model "simple" liquids, the equilibrium Lennard-Jones and square-well fluids, in both bulk and confined environments. We find that the self-diffusivity data of the Lennard-Jones fluid can be approximately collapsed onto a single curve (i) versus effective packing fraction and (ii) in appropriately reduced form versus excess entropy, as suggested by two well-known scaling laws. Similar data collapse does not occur for the square-well fluid, a fact that can be understood on the basis of the nontrivial effects that temperature has on its static structure. Nonetheless, we show that the implications of confinement for the self-diffusivity of both of these model fluids, over a broad range of equilibrium conditions, can be predicted on the basis of knowledge of the bulk fluid behavior and either the effective packing fraction or the excess entropy of the confined fluid. Excess entropy is perhaps the most preferable route due to its superior predictive ability and because it is a standard, unambiguous thermodynamic quantity that can be readily predicted via classical density functional theories of inhomogeneous fluids.

Year:  2007        PMID: 17629320     DOI: 10.1021/jp071369e

Source DB:  PubMed          Journal:  J Phys Chem B        ISSN: 1520-5207            Impact factor:   2.991


  9 in total

1.  Using compressibility factor as a predictor of confined hard-sphere fluid dynamics.

Authors:  Jeetain Mittal
Journal:  J Phys Chem B       Date:  2009-10-22       Impact factor: 2.991

Review 2.  Protein-protein interactions in a crowded environment.

Authors:  Apratim Bhattacharya; Young C Kim; Jeetain Mittal
Journal:  Biophys Rev       Date:  2013-04-16

3.  Machine learning determination of atomic dynamics at grain boundaries.

Authors:  Tristan A Sharp; Spencer L Thomas; Ekin D Cubuk; Samuel S Schoenholz; David J Srolovitz; Andrea J Liu
Journal:  Proc Natl Acad Sci U S A       Date:  2018-10-09       Impact factor: 11.205

4.  Connection Between Thermodynamics and Dynamics of Simple Fluids in Pores: Impact of Fluid-Fluid Interaction Range and Fluid-Solid Interaction Strength.

Authors:  William P Krekelberg; Daniel W Siderius; Vincent K Shen; Thomas M Truskett; Jeffrey R Errington
Journal:  J Phys Chem C Nanomater Interfaces       Date:  2017-07-05       Impact factor: 4.126

5.  Structural predictor for nonlinear sheared dynamics in simple glass-forming liquids.

Authors:  Trond S Ingebrigtsen; Hajime Tanaka
Journal:  Proc Natl Acad Sci U S A       Date:  2017-12-15       Impact factor: 11.205

6.  Protein Solvent Shell Structure Provides Rapid Analysis of Hydration Dynamics.

Authors:  Jayangika N Dahanayake; Elaheh Shahryari; Kirsten M Roberts; Micah E Heikes; Chandana Kasireddy; Katie R Mitchell-Koch
Journal:  J Chem Inf Model       Date:  2019-03-22       Impact factor: 4.956

Review 7.  Bottom-up Coarse-Graining: Principles and Perspectives.

Authors:  Jaehyeok Jin; Alexander J Pak; Aleksander E P Durumeric; Timothy D Loose; Gregory A Voth
Journal:  J Chem Theory Comput       Date:  2022-09-07       Impact factor: 6.578

8.  Connection between water's dynamical and structural properties: Insights from ab initio simulations.

Authors:  Cecilia Herrero; Michela Pauletti; Gabriele Tocci; Marcella Iannuzzi; Laurent Joly
Journal:  Proc Natl Acad Sci U S A       Date:  2022-05-19       Impact factor: 12.779

9.  Excess Entropy Scaling Law for Diffusivity in Liquid Metals.

Authors:  N Jakse; A Pasturel
Journal:  Sci Rep       Date:  2016-02-10       Impact factor: 4.379

  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.