An ensemble learning based amorphous state predictor for multicomponent alloys-Reference-Cited by-同舟云学术

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An ensemble learning based amorphous state predictor for multicomponent alloys

Published:2023-05 Issue: Volume:607 Page:122116
ISSN:0022-3093
Container-title:Journal of Non-Crystalline Solids
language:en
Short-container-title:Journal of Non-Crystalline Solids

Author:

Hu Jingyi,Xu Xiang,Cui Yongcheng,Xu Mingxian,Gao Xiaojin,Ji Xiaomei

Funder

Shandong Academy of Sciences

Publisher

Elsevier BV

Subject

Materials Chemistry,Condensed Matter Physics,Ceramics and Composites,Electronic, Optical and Magnetic Materials

Reference30 articles.

1. Non-crystalline structure in solidified gold–silicon alloys;Klement;Nature,1960

2. Bulk Metallic Glasses;Suryanarayana,2017

3. Machine learning in materials informatics: recent applications and prospects;Ramprasad;NPJ Comput. Mater.,2017

4. Accelerating materials development via automation, machine learning, and high-performance computing;Juan-Pablo;Joule,2018

5. Computational platform for manufacturing bulk metallic glasses based on GFA parameters;Kuthe;Trans. Indian Inst. Met.,2018

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1. Prediction of digital transformation of manufacturing industry based on interpretable machine learning;PLOS ONE;2024-03-29

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