Design of Refractory Alloys for Desired Thermal Conductivity via AI-Assisted In-Silico Microstructure Realization

A computational methodology based on supervised machine learning (ML) is described for characterizing and designing anisotropic refractory composite alloys with desired thermal conductivities (TCs). The structural design variables are parameters of our fast computational microstructure generator, wh...

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Detalles Bibliográficos
Autores principales: Seyed Mahmoud, Seyed Mohammad Ali, Faraji, Ghader, Baghani, Mostafa, Hashemi, Mohammad Saber, Sheidaei, Azadeh, Baniassadi, Majid
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9921970/
https://www.ncbi.nlm.nih.gov/pubmed/36770095
http://dx.doi.org/10.3390/ma16031088

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9921970/
https://www.ncbi.nlm.nih.gov/pubmed/36770095
http://dx.doi.org/10.3390/ma16031088

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