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Modeling of Electrical Conductivity for Polymer–Carbon Nanofiber Systems

There is not a simple model for predicting the electrical conductivity of carbon nanofiber (CNF)–polymer composites. In this manuscript, a model is proposed to predict the conductivity of CNF-filled composites. The developed model assumes the roles of CNF volume fraction, CNF dimensions, percolation...

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Detalles Bibliográficos
Autores principales: Khalil Arjmandi, Sajad, Khademzadeh Yeganeh, Jafar, Zare, Yasser, Rhee, Kyong Yop
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9571830/
https://www.ncbi.nlm.nih.gov/pubmed/36234382
http://dx.doi.org/10.3390/ma15197041
Descripción
Sumario:There is not a simple model for predicting the electrical conductivity of carbon nanofiber (CNF)–polymer composites. In this manuscript, a model is proposed to predict the conductivity of CNF-filled composites. The developed model assumes the roles of CNF volume fraction, CNF dimensions, percolation onset, interphase thickness, CNF waviness, tunneling length among nanoparticles, and the fraction of the networked CNF. The outputs of the developed model correctly agree with the experimentally measured conductivity of several samples. Additionally, parametric analyses confirm the acceptable impacts of main factors on the conductivity of composites. A higher conductivity is achieved by smaller waviness and lower radius of CNFs, lower percolation onset, less tunnel distance, and higher levels of interphase depth and fraction of percolated CNFs in the nanocomposite. The maximum conductivity is obtained at 2.37 S/m by the highest volume fraction and length of CNFs.