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Predicting of tunneling resistivity between adjacent nanosheets in graphene-polymer systems.
Zare, Yasser; Gharib, Nima; Nam, Dong-Hyun; Chang, Young-Wook.
Afiliação
  • Zare Y; Biomaterials and Tissue Engineering Research Group, Department of Interdisciplinary Technologies, Breast Cancer Research Center, Motamed Cancer Institute, ACECR, Tehran, Iran. y.zare@aut.ac.ir.
  • Gharib N; College of Engineering and Technology, American University of the Middle East, Egaila, 54200, Kuwait.
  • Nam DH; Department of Materials Science and Chemical Engineering, BK21 FOUR ERICA-ACE Center, Hanyang University ERICA, Ansan, 15588, Korea.
  • Chang YW; Department of Materials Science and Chemical Engineering, BK21 FOUR ERICA-ACE Center, Hanyang University ERICA, Ansan, 15588, Korea. ywchang@hanyang.ac.kr.
Sci Rep ; 13(1): 12455, 2023 Aug 01.
Article em En | MEDLINE | ID: mdl-37528228
In this work, the tunneling resistivity between neighboring nanosheets in grapheme-polymer nanocomposites is expressed by a simple equation as a function of the characteristics of graphene and tunnels. This expression is obtained by connecting two advanced models for the conductivity of graphene-filled materials reflecting tunneling role and interphase area. The predictions of the applied models are linked to the tested data of several samples. The impressions of all factors on the tunneling resistivity are evaluated and interpreted using the suggested equation. The calculations of tunneling resistivity for the studied examples by the model and suggested equation demonstrate the same levels, which confirm the presented methodology. The results indicate that the tunneling resistivity decreases by super-conductive graphene, small tunneling width, numerous contacts among nanosheets and short tunneling length.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article