Your browser doesn't support javascript.
loading
A Molecular Dynamics Simulation for Thermal Activation Process in Covalent Bond Dissociation of a Crosslinked Thermosetting Polymer.
Yamada, Naoki; Oya, Yutaka; Kato, Nobuhiko; Mori, Kazuki; Koyanagi, Jun.
Afiliación
  • Yamada N; Department of Materials Science and Technology, Graduate School of Tokyo University of Science, Tokyo 125-8585, Japan.
  • Oya Y; Research Institute for Science & Technology, Tokyo University of Science, Tokyo 125-8585, Japan.
  • Kato N; Sience and Engineering Systems Division ITOCHU Techno-Solutions Corporation, Tokyo 105-6950, Japan.
  • Mori K; Sience and Engineering Systems Division ITOCHU Techno-Solutions Corporation, Tokyo 105-6950, Japan.
  • Koyanagi J; Department of Materials Science and Technology, Tokyo University of Science, Tokyo 125-8585, Japan.
Molecules ; 28(6)2023 Mar 17.
Article en En | MEDLINE | ID: mdl-36985707
A novel algorithm for covalent bond dissociation is developed to accurately predict fracture behavior of thermosetting polymers via molecular dynamics simulation. This algorithm is based on the Monte Carlo method that considers the difference in local strain and bond-dissociation energies to reproduce a thermally activated process in a covalent bond dissociation. This study demonstrates the effectiveness of this algorithm in predicting the stress-strain relationship of fully crosslinked thermosetting polymers under uniaxial tensile conditions. Our results indicate that the bond-dissociation energy plays an important role in reproducing the brittle fracture behavior of a thermosetting polymer by affecting the number of covalent bonds that are dissociated simultaneously.
Palabras clave

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Molecules Asunto de la revista: BIOLOGIA Año: 2023 Tipo del documento: Article País de afiliación: Japón Pais de publicación: Suiza

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Molecules Asunto de la revista: BIOLOGIA Año: 2023 Tipo del documento: Article País de afiliación: Japón Pais de publicación: Suiza