Multi-objective optimization for high-performance Fe-based metallic glasses via machine learning approach-Reference-Cited by-同舟云学术

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Multi-objective optimization for high-performance Fe-based metallic glasses via machine learning approach

Published:2023-10 Issue: Volume:960 Page:170793
ISSN:0925-8388
Container-title:Journal of Alloys and Compounds
language:en
Short-container-title:Journal of Alloys and Compounds

Author:

Zhang Yu-Xing,Xie She-Juan,Guo Wei,Ding Jun,Poh Leong Hien,Sha Zhen-Dong

Funder

State Key Laboratory of Nonlinear Mechanics, Chinese Academy of Sciences

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Materials Chemistry,Metals and Alloys,Mechanical Engineering,Mechanics of Materials

Reference75 articles.

1. Bulk metallic glasses with functional physical properties;Wang;Adv. Mater.,2009

2. Bulk metallic glasses: At the cutting edge of metals research;Greer;MRS Bull.,2007

3. Metallic glasses as structural materials;Ashby;Scr. Mater.,2006

4. Bulk glassy alloys: Historical development and current research;Inoue;Engineering,2015

5. New Fe‐based soft magnetic alloys composed of ultrafine grain structure;Yoshizawa;J. Appl. Phys.,1988

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4. Deep learning-based prediction of saturation magnetic flux density in Fe-based metallic glasses via transfer learning;Materials Chemistry and Physics;2024-03

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