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Prediction of Thermal Conductivities of Rubbers by MD Simulations—New Insights

In this article, two main approaches to the prediction of thermal conductivities by molecular dynamics (MD) simulations are discussed, namely non-equilibrium molecular dynamics simulations (NEMD) and the application of the Green–Kubo formula, i.e., EMD. NEMD methods are more affected by size effects...

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Detalles Bibliográficos
Autores principales: Vasilev, Aleksandr, Lorenz, Tommy, Breitkopf, Cornelia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9146200/
https://www.ncbi.nlm.nih.gov/pubmed/35631927
http://dx.doi.org/10.3390/polym14102046
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author Vasilev, Aleksandr
Lorenz, Tommy
Breitkopf, Cornelia
author_facet Vasilev, Aleksandr
Lorenz, Tommy
Breitkopf, Cornelia
author_sort Vasilev, Aleksandr
collection PubMed
description In this article, two main approaches to the prediction of thermal conductivities by molecular dynamics (MD) simulations are discussed, namely non-equilibrium molecular dynamics simulations (NEMD) and the application of the Green–Kubo formula, i.e., EMD. NEMD methods are more affected by size effects than EMD methods. The thermal conductivities of silicone rubbers in special were found as a function of the degree of crosslinking. Moreover, the thermal conductivities of thermoplastic polyurethane as function of the mass fraction of soft segments were obtained by those MD simulations. All results are in good agreement with data from the experimental literature. After the analysis of normalized heat flux autocorrelation functions, it has been revealed that heat in the polymers is mainly transferred by low-frequency phonons. Simulation details as well as advantages and disadvantages of the single methods are discussed in the article.
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spelling pubmed-91462002022-05-29 Prediction of Thermal Conductivities of Rubbers by MD Simulations—New Insights Vasilev, Aleksandr Lorenz, Tommy Breitkopf, Cornelia Polymers (Basel) Article In this article, two main approaches to the prediction of thermal conductivities by molecular dynamics (MD) simulations are discussed, namely non-equilibrium molecular dynamics simulations (NEMD) and the application of the Green–Kubo formula, i.e., EMD. NEMD methods are more affected by size effects than EMD methods. The thermal conductivities of silicone rubbers in special were found as a function of the degree of crosslinking. Moreover, the thermal conductivities of thermoplastic polyurethane as function of the mass fraction of soft segments were obtained by those MD simulations. All results are in good agreement with data from the experimental literature. After the analysis of normalized heat flux autocorrelation functions, it has been revealed that heat in the polymers is mainly transferred by low-frequency phonons. Simulation details as well as advantages and disadvantages of the single methods are discussed in the article. MDPI 2022-05-17 /pmc/articles/PMC9146200/ /pubmed/35631927 http://dx.doi.org/10.3390/polym14102046 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Vasilev, Aleksandr
Lorenz, Tommy
Breitkopf, Cornelia
Prediction of Thermal Conductivities of Rubbers by MD Simulations—New Insights
title Prediction of Thermal Conductivities of Rubbers by MD Simulations—New Insights
title_full Prediction of Thermal Conductivities of Rubbers by MD Simulations—New Insights
title_fullStr Prediction of Thermal Conductivities of Rubbers by MD Simulations—New Insights
title_full_unstemmed Prediction of Thermal Conductivities of Rubbers by MD Simulations—New Insights
title_short Prediction of Thermal Conductivities of Rubbers by MD Simulations—New Insights
title_sort prediction of thermal conductivities of rubbers by md simulations—new insights
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9146200/
https://www.ncbi.nlm.nih.gov/pubmed/35631927
http://dx.doi.org/10.3390/polym14102046
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