Prediction of mechanical properties of high-entropy ceramics by deep learning with compositional descriptors-Reference-Cited by-同舟云学术

Prediction of mechanical properties of high-entropy ceramics by deep learning with compositional descriptors

Published:2023-06 Issue: Volume:35 Page:105949
ISSN:2352-4928
Container-title:Materials Today Communications
language:en
Short-container-title:Materials Today Communications

Author:

Nam Chunghee^ORCID

Funder

National Research Foundation of Korea

Ministry of Science, ICT and Future Planning

Publisher

Elsevier BV

Subject

Materials Chemistry,Mechanics of Materials,General Materials Science

Reference52 articles.

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3. High-entropy high-hardness metal carbides discovered by entropy descriptors;Sarker;Nat. Commun.,2018

4. Designing high-entropy ceramics via incorporation of the bond-mechanical behavior correlation with the machine-learning methodology;Tang;Cell Rep. Phys. Sci.,2021

5. Bulk high‑entropy nitrides and carbonitrides;Dippo1;Sci. Rep.,2020

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