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Multiscale Numerical Modeling for Prediction of Piezoresistive Effect for Polymer Composites with a Highly Segregated Structure.
Lebedev, Oleg V; Ozerin, Alexander N; Abaimov, Sergey G.
Afiliación
  • Lebedev OV; Center for Design, Manufacturing and Materials, Skolkovo Institute of Science and Technology, 143026 Moscow, Russia.
  • Ozerin AN; Moscow Institute of Physics and Technology, Institutsky Lane 9, Dolgoprudny, 141700 Moscow, Russia.
  • Abaimov SG; N.S. Enikolopov Institute of Synthetic Polymer Materials of RAS, Profsoyuznaya St. 70, 117393 Moscow, Russia.
Nanomaterials (Basel) ; 11(1)2021 Jan 10.
Article en En | MEDLINE | ID: mdl-33435220
In this work, the piezoresistive effect for a polymer nanocomposite with a highly segregated distribution of conductive filler was investigated. As a base polymer for the investigated nanocomposites, ultrahigh-molecular-weight polyethylene, processed in a solid state (below melting point), was used. Multiwalled carbon nanotubes (MWCNTs) were used as a nanofiller forming a highly segregated structure in between polymer particles. A numerical multiscale approach based on the finite element method was proposed to predict changes in the conductive structure composed of MWCNTs in response to uniaxial deformation of the material. At the nanoscale, numerical simulations were conducted for uniformly distributed MWCNTs providing confinement of the filler to a two-dimensional layer with a high volume fraction of the filler in between two polymer particles. At the microscale, the piezoresistive response to uniaxial deformation for the three-dimensional highly segregated structure reconstructed from experimental data was investigated numerically. The embedded element method was implemented to conduct a realistic and computationally efficient simulation of MWCNT behavior during deformation of the nanocomposite. The results of numerical simulations were compared with the experimental data to prove the correctness of assumptions used in the modeling.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Nanomaterials (Basel) Año: 2021 Tipo del documento: Article País de afiliación: Rusia Pais de publicación: Suiza

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Nanomaterials (Basel) Año: 2021 Tipo del documento: Article País de afiliación: Rusia Pais de publicación: Suiza