Machine learning-based glass formation prediction in multicomponent alloys

被引:0
|
作者
Liu, Xiaodi [1 ]
Li, Xin [1 ]
He, Quanfeng [2 ]
Liang, Dandan [1 ,3 ]
Zhou, Ziqing [2 ]
Ma, Jiang [1 ]
Yang, Yong [2 ,4 ]
Shen, Jun [1 ]
机构
[1] Liu, Xiaodi
[2] Li, Xin
[3] He, Quanfeng
[4] 1,Liang, Dandan
[5] Zhou, Ziqing
[6] Ma, Jiang
[7] 2,Yang, Yong
[8] Shen, Jun
来源
Shen, Jun (junshen@szu.edu.cn) | 1600年 / Acta Materialia Inc卷 / 201期
基金
中国国家自然科学基金;
关键词
Backpropagation - Forecasting - Neural networks - Glass - Learning systems - Ternary alloys;
D O I
暂无
中图分类号
学科分类号
摘要
引用
收藏
页码:182 / 190
相关论文
共 50 条
  • [21] Prediction of glass forming ability in amorphous alloys based on different machine learning algorithms
    Liu, Xiaowei
    Long, Zhilin
    Yang, Lingming
    Zhang, Wei
    Li, Zhuang
    JOURNAL OF NON-CRYSTALLINE SOLIDS, 2021, 570
  • [22] Prediction of glass-forming ability in ternary alloys based on machine learning method
    Xu, Miaojie
    Wang, Jianfeng
    Sun, Yufeng
    Zhu, Shijie
    Zhang, Tao
    Guan, Shaokang
    JOURNAL OF NON-CRYSTALLINE SOLIDS, 2023, 616
  • [23] Machine learning-based prediction and generation model for creep rupture time of Nickel-based alloys
    Ma, Chang
    Tang, Yucheng
    Bao, Gang
    COMPUTATIONAL MATERIALS SCIENCE, 2024, 233
  • [24] Machine learning-based model of surface tension of liquid metals: a step in designing multicomponent alloys for additive manufacturing
    Mariam Assi
    Julien Favre
    Anna Fraczkiewicz
    Franck Tancret
    Journal of Materials Science, 2022, 57 : 13446 - 13466
  • [25] Machine Learning and Deep Learning-Based Students’ Grade Prediction
    Korchi A.
    Messaoudi F.
    Abatal A.
    Manzali Y.
    Operations Research Forum, 4 (4)
  • [26] Machine learning-based model of surface tension of liquid metals: a step in designing multicomponent alloys for additive manufacturing
    Assi, Mariam
    Favre, Julien
    Fraczkiewicz, Anna
    Tancret, Franck
    JOURNAL OF MATERIALS SCIENCE, 2022, 57 (28) : 13446 - 13466
  • [27] Prediction and design of cyclodextrin inclusion complexes formation via machine learning-based strategies
    Ma, Yiming
    Niu, Yue
    Yang, Huaiyu
    Dai, Jiayu
    Lin, Jiawei
    Wang, Huiqi
    Wu, Songgu
    Yin, Qiuxiang
    Zhou, Ling
    Gong, Junbo
    CHEMICAL ENGINEERING SCIENCE, 2022, 261
  • [28] Machine learning-based prediction models for formation energies of interstitial atoms in HCP crystals
    You, Daegun
    Ganorkar, Shraddha
    Kim, Sooran
    Kang, Keonwook
    Shin, Won-Yong
    Lee, Dongwoo
    SCRIPTA MATERIALIA, 2020, 183 : 1 - 5
  • [29] Machine Learning-Based Hardness Prediction of High-Entropy Alloys for Laser Additive Manufacturing
    Wenhan Zhu
    Wenyi Huo
    Shiqi Wang
    Łukasz Kurpaska
    Feng Fang
    Stefanos Papanikolaou
    Hyoung Seop Kim
    Jianqing Jiang
    JOM, 2023, 75 : 5537 - 5548
  • [30] Machine Learning-Based Hardness Prediction of High-Entropy Alloys for Laser Additive Manufacturing
    Zhu, Wenhan
    Huo, Wenyi
    Wang, Shiqi
    Kurpaska, Lukasz
    Fang, Feng
    Papanikolaou, Stefanos
    Kim, Hyoung Seop
    Jiang, Jianqing
    JOM, 2023, 75 (12) : 5537 - 5548