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

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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Bibliographic Details
Main Authors: Seyed Mohammad Ali Seyed Mahmoud, Ghader Faraji, Mostafa Baghani, Mohammad Saber Hashemi, Azadeh Sheidaei, Majid Baniassadi
Format: Article
Language:English
Published: MDPI AG 2023-01-01
Series:Materials
Subjects:
microstructure identifications
machine learning
thermal characterization
Fast Fourier Transform (FFT) homogenization
Online Access:https://www.mdpi.com/1996-1944/16/3/1088

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https://www.mdpi.com/1996-1944/16/3/1088

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