Convolutional neural networks for approximating electrical and thermal conductivities of Cu-CNT composites

This article explores the deep learning approach towards approximating the effective electrical and thermal conductivities of copper (Cu)-carbon nanotube (CNT) composites with CNTs aligned to the field direction. Convolutional neural networks (CNN) are trained to map the two-dimensional images of st...

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Detalles Bibliográficos
Autores principales: Ejaz, Faizan, Hwang, Leslie K., Son, Jangyup, Kim, Jin-Sang, Lee, Dong Su, Kwon, Beomjin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9365832/
https://www.ncbi.nlm.nih.gov/pubmed/35948586
http://dx.doi.org/10.1038/s41598-022-16867-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9365832/
https://www.ncbi.nlm.nih.gov/pubmed/35948586
http://dx.doi.org/10.1038/s41598-022-16867-z

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