Data‐Driven Design of Electrically Conductive Nanocomposite Materials: A Case Study of Acrylonitrile–Butadiene–Styrene/Carbon Nanotube Binary Composites

The field of polymer‐based nanoscience has always been of significant interest in the search for polymer/carbon nanotube (CNT) nanocomposites with optimized material properties for new applications. Herein, it is demonstrated that data collected from the online literature can be used to develop an e...

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Autors principals:	Changrok So, Young-Shin Kim, Jong Hyuk Park, Gwan-Yeong Kim, Daniel Cha, Jong Hwan Ko, Boseok Kang
Format:	Artigo
Idioma:	Inglês
Publicat:	Wiley 2023-02-01
Col·lecció:	Advanced Intelligent Systems
Matèries:	acrylonitrile–butadiene–styrene carbon nanotubes deep learning deep neural network machine learning Monte Carlo simulation
Accés en línia:	https://doi.org/10.1002/aisy.202200399
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