Solid-liquid phase transition temperature prediction of alloys based on machine learning key feature screening-Reference-Cited by-同舟云学术

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Solid-liquid phase transition temperature prediction of alloys based on machine learning key feature screening

Published:2024-02 Issue: Volume:36 Page:102007
ISSN:2352-9407
Container-title:Applied Materials Today
language:en
Short-container-title:Applied Materials Today

Author:

Fang Jiheng,Yang Shangrong,Xie Ming,Hu Jieqiong,Sun Hongsheng,Liu Guohua,Zhao Shangqiang,Chen Yongtai,Yang Youcai,Ning Dekui,He Xingqun,Jin Qinglin

Publisher

Elsevier BV

Subject

General Materials Science

Reference73 articles.

1. Brazing filler metals[J];Way;Int. Mater. Rev.,2020

2. Current review on the research status of cemented carbide brazing: filler materials and mechanical properties[J];Yin;Met. Mater. Int.,2021

3. Microstructure and mechanical properties of Al2O3/Cu joints brazed with Ag-Cu-Ti+Zn composite fillers[J];Fan;Ceram. Int.,2022

4. Effect of bonding temperature on isothermal solidification rate during transient liquid phase bonding of Inconel 738LC superalloy[J];Idowu;Mater Sci Eng A Struct Mater,2005

5. Selecting metal alloy electric contact materials for MEMS switches[J];Coutu;J. Micromech. Microeng.,2004

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Optimized design of composition and brazing process for Cu-Ag-Zn-Mn-Ni-Si-B-P alloy brazing material based on machine learning strategy to improve brazing properties;Materials Today Communications;2024-06

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