A stochastic thermostat algorithm for coarse-grained thermomechanical modeling of large-scale soft matters : theory and application to microfilaments

Li, Tong & Gu, YuanTong (2014) A stochastic thermostat algorithm for coarse-grained thermomechanical modeling of large-scale soft matters : theory and application to microfilaments. Journal of Computational Physics, 263, pp. 177-184.

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Abstract

As all-atom molecular dynamics method is limited by its enormous computational cost, various coarse-grained strategies have been developed to extend the length scale of soft matters in the modeling of mechanical behaviors. However, the classical thermostat algorithm in highly coarse-grained molecular dynamics method would underestimate the thermodynamic behaviors of soft matters (e.g. microfilaments in cells), which can weaken the ability of materials to overcome local energy traps in granular modeling. Based on all-atom molecular dynamics modeling of microfilament fragments (G-actin clusters), a new stochastic thermostat algorithm is developed to retain the representation of thermodynamic properties of microfilaments at extra coarse-grained level. The accuracy of this stochastic thermostat algorithm is validated by all-atom MD simulation. This new stochastic thermostat algorithm provides an efficient way to investigate the thermomechanical properties of large-scale soft matters.

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ID Code: 67060
Item Type: Journal Article
Refereed: Yes
Keywords: Thermomechanical, Coarse-grained, Microfilaments, Actin, Soft matter
DOI: 10.1016/j.jcp.2014.01.021
ISSN: 0021-9991
Subjects: Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > BIOMEDICAL ENGINEERING (090300) > Biomechanical Engineering (090302)
Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > MATERIALS ENGINEERING (091200) > Materials Engineering not elsewhere classified (091299)
Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > MECHANICAL ENGINEERING (091300) > Numerical Modelling and Mechanical Characterisation (091307)
Divisions: Current > Schools > School of Chemistry, Physics & Mechanical Engineering
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Funding:
Copyright Owner: Copyright 2014 Elsevier Inc.
Copyright Statement: NOTICE: this is the author’s version of a work that was accepted for publication in Journal of Computational Physics. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Journal of Computational Physics, [Volume 263, (15 April 2014)] DOI: 10.1016/j.jcp.2014.01.021
Deposited On: 06 Feb 2014 22:25
Last Modified: 05 May 2016 04:28

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