Effective subgrouping enhances machine learning prediction in complex materials science phenomena: Inoue's subgrouping in discovering bulk metallic glasses-Reference-Cited by-同舟云学术

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Effective subgrouping enhances machine learning prediction in complex materials science phenomena: Inoue's subgrouping in discovering bulk metallic glasses

Published:2024-02 Issue: Volume:265 Page:119590
ISSN:1359-6454
Container-title:Acta Materialia
language:en
Short-container-title:Acta Materialia

Author:

Liu Guannan,Sohn Sungwoo,O'Hern Corey S.,Gilbert Anna C.,Schroers Jan

Funder

National Science Foundation

Division of Materials Research

Publisher

Elsevier BV

Subject

Metals and Alloys,Polymers and Plastics,Ceramics and Composites,Electronic, Optical and Magnetic Materials

Reference64 articles.

1. Microscopic mechanisms of equilibrium melting of a solid;Samanta;Science,2014

2. Machine learning for alloys;Hart;Nat. Rev. Mater.,2021

3. A framework to predict binary liquidus by combining machine learning and CALPHAD assessments;Deffrennes;Mater. Des.,2023

4. Compositional dependence of the fragility in metallic glass forming liquids;Kube;Nat. Commun.,2022

5. Size-dependent deformation behavior in nanosized amorphous metals suggesting transition from collective to individual atomic transport;Liu;Nat. Commun.,2023

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