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RESEARCH PAPER · Applied Physics Reviews · 2022

Discovering exceptionally hard and wear-resistant metallic glasses by combining machine-learning with high throughput experimentation

Suchismita Sarker, Robert Tang‐Kong, Rachel L. Schoeppner, Logan T. Ward, Naila Al Hasan, Douglas G. Van Campen, Ichiro Takeuchi, Jason R. Hattrick-Simpers, Andriy Zakutayev, Corinne E. Packard, Apurva Mehta

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Discovering exceptionally hard and wear-resistant metallic glasses by combining machine-learning with high throughput experimentationOriginalMechanical Alloying Integrated with Cold Spray Coating for Fabrication Cu50(Ti50−xNix), x; 10, 20, 30, and 40 at.% Antibiofilm Metallic Glass Coated/SUS304 Sheets8Rapid screening the mechanical properties of ZrNi-based metallic glasses by high-throughput combinatorial approach6Autonomous (AI-driven) materials science23AutoMat: Automated materials discovery for electrochemical systems16Designing durable, sustainable, high-performance materials for clean energy infrastructure12Data-driven prediction of the glass-forming ability of modeled alloys by supervised machine learning16Achieving Diamond‐Like Wear in Ta‐Rich Metallic Glasses23Coupling mixture designs, high-throughput experiments and machine learning for accelerated exploration of multinary systems11Materials genome strategy for metallic glasses19Diverse 3D auxetic unit cell inverse design with deep learning21In Pursuit of the Exceptional: Research Directions for Machine Learning in Chemical and Materials Science99Data driven development of iron-based metallic glasses using artificial neural networks10A micromechanical nested machine learning model for characterizing materials behaviors of bulk metallic glasses10Customized design of amorphous solids by generative deep learning6Manufacturing of metallic glass components: Processes, structures and properties162Bridging the gap between high-entropy alloys and metallic glasses: Control over disorder and mechanical properties of coatings4High-throughput development of tough metallic glass films10Data-driven discovery of ultrahigh specific hardness alloys6Correlation between nanoscale viscoelastic heterogeneous structure and mechanical behaviors in amorphous alloy0Efficient training of machine learning potentials for metallic glasses: CuZrAl validation0Convolutional neural network-based prediction of hardness in bulk metallic glasses with small data3Sliding wear behavior and mechanism of Zr-based bulk metallic glasses and metallic glass matrix composites6Bayesian exploration of the composition space of CuZrAl metallic glasses for mechanical properties10Real-time experiment-theory closed-loop interaction for autonomous materials science29Composition design and process optimization of refractory boride coatings based on high-throughput preparation and machine learning2Self-supervised learning for glass composition screening4Unveiling key descriptors for electrical resistivity of alloys using high-throughput experiments and explainable AI7Machine learning on glass-forming ability of metallic glasses guided by domain knowledge0Data-driven prediction of thin-film metallic glass forming ability via Bayesian classification and experimental verification in the Cu–Zr–Al system0Generative AI inversely designs amorphous alloys with customized properties0Attention-enhanced variational learning for physically informed discovery of exceptionally hard multicomponent bulk metallic glasses2High‐Throughput Development of Advanced Metallic Glasses via Compositionally Graded Thin‐Film Combinatorial Strategy0

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  1. Mechanical Alloying Integrated with Cold Spray Coating for Fabrication Cu50(Ti50−xNix), x; 10, 20, 30, and 40 at.% Antibiofilm Metallic Glass Coated/SUS304 Sheets

    Nanomaterials · 2022-05-14

    Ahmad Aldhameer, Mohamed Sherif El-Eskandarany, Mohamed Kishk, Fahad Al-Ajmi, Mohammad Banyan

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  2. Rapid screening the mechanical properties of ZrNi-based metallic glasses by high-throughput combinatorial approach

    Intermetallics · 2022-06-17

    Junhua Cao, Meng Jiao Gao, Yuanfei Cai, Jinlong Li, Ye Wang, Junqiang Wang, Juntao Huo

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  3. Autonomous (AI-driven) materials science

    Applied Physics Reviews · 2022-09-01

    Martin L. Green, Benji Maruyama, Joshua Schrier

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  4. AutoMat: Automated materials discovery for electrochemical systems

    MRS Bulletin · 2022-10-01

    Emil Jonathan Annevelink, Rachel C. Kurchin, Eric S. Muckley, Lance Kavalsky, Vinay I. Hegde, Valentin Sulzer, Shang Zhu, Jiankun Pu, David Farina, Matthew S. Johnson, Dhairya Gandhi, Adarsh Dave, Hongyi Lin, Alan S. Edelman, Bharath Ramsundar, James E. Saal, Christopher Rackauckas, Viral B. Shah, Bryce Meredig, Venkatasubramanian Viswanathan

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  5. Designing durable, sustainable, high-performance materials for clean energy infrastructure

    Cell Reports Physical Science · 2022-12-16

    Jason R. Hattrick-Simpers, Kangming Li, Michael Greenwood, Robert W. Black, Julia Witt, Mark Kozdras, Xin Pang, Özlem Özcan

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  6. Data-driven prediction of the glass-forming ability of modeled alloys by supervised machine learning

    Journal of Materials Informatics · 2023-01-01

    Yuan-Chao Hu

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  7. Achieving Diamond‐Like Wear in Ta‐Rich Metallic Glasses

    Advanced Science · 2023-05-21

    Fucheng Li, Mingxing Li, Liwei Hu, Jiashu Cao, Chao Wang, Yitao Sun, Weihua Wang, Yanhui Liu

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  8. Coupling mixture designs, high-throughput experiments and machine learning for accelerated exploration of multinary systems

    Materials & Design · 2023-06-02

    Elise Garel, Jean-Luc Parouty, Hugo Paul Van Landeghem, M. Verdier, F. Robaut, Stéphane Coindeau, Raphaël Boichot

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  9. Materials genome strategy for metallic glasses

    Journal of Material Science and Technology · 2023-06-20

    Zhichao Lu, Yibo Zhang, Wenyue Li, Jinyue Wang, Xiongjun Liu, Yuan Wu, Hui Wang, Dong Ma, Zhaoping Lü

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  10. Diverse 3D auxetic unit cell inverse design with deep learning

    Applied Physics Reviews · 2023-07-17

    Xi Fang, Hui‐Shen Shen, Hai Wang

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  11. In Pursuit of the Exceptional: Research Directions for Machine Learning in Chemical and Materials Science

    Journal of the American Chemical Society · 2023-09-27

    Joshua Schrier, Alexander J. Norquist, Tonio Buonassisi, Jakoah Brgoch

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  12. Data driven development of iron-based metallic glasses using artificial neural networks

    Journal of Alloys and Compounds · 2023-11-19

    Kirsten Bobzin, H. Heinemann, E. Burbaum, Lukas Martin Johann, J. Seßler, J. Gärtner

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  13. A micromechanical nested machine learning model for characterizing materials behaviors of bulk metallic glasses

    Journal of Non-Crystalline Solids · 2023-11-21

    Moustafa Sahnoune Chaouche, Hani K. Al-Mohair, Shavan K. Askar, Barno Sayfutdinovna Abdullaeva, Naseer Ali Hussien, Ahmed Hussien Alawadi

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  14. Customized design of amorphous solids by generative deep learning

    The Innovation Materials · 2024-01-01

    Yinghui Shang, Ziqing Zhou, Rong Han, Hang Wang, Xiaodi Liu, Yong Gang Yang

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  15. Manufacturing of metallic glass components: Processes, structures and properties

    Progress in Materials Science · 2024-03-13

    Sajad Sohrabi, Jianan Fu, Luyao Li, Yu Zhang, Xin Li, Fei Sun, Jiang Ma, Wei Hua Wang

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  16. Bridging the gap between high-entropy alloys and metallic glasses: Control over disorder and mechanical properties of coatings

    Materials Today Communications · 2024-10-05

    Alessandro Troglia, Cyrian Leriche, Mike L. van de Poll, Christoph Burghard Morscher, Gert H. ten Brink, Bart Jan Kooi, Bart Weber, Roland Bliem

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  17. High-throughput development of tough metallic glass films

    Materials Horizons · 2024-10-22

    Yuzhou Wu, Yue Huang, Yebei Wang, Fuchao Wang, Yunhe Gao, Yingying Sun, Meichen Jian, Lijian Song, Yu Tong, Yan Zhang, Chao Wang, Yanhui Liu, Junqiang Wang, Juntao Huo, Meng Jiao Gao

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  18. Data-driven discovery of ultrahigh specific hardness alloys

    Journal of Materials Research and Technology · 2024-11-01

    Taeyeop Kim, Wook Ha Ryu, Geun Hee Yoo, Donghyun Park, Ji Young Kim, Eun Soo Park, Dongwoo Lee

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  19. Correlation between nanoscale viscoelastic heterogeneous structure and mechanical behaviors in amorphous alloy

    Zhongguo kexue. Wulixue Lixue Tianwenxue · 2024-11-27

    Yebei Wang, Yizhou Liu, Yue Huang, Fu XU, Meng GAO

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  20. Efficient training of machine learning potentials for metallic glasses: CuZrAl validation

    SSRN Electronic Journal · 2025-01-01

    Antoni Wadowski, Anshul D. S. Parmar, F. Kaśkosz, Jesper Byggmästar, Jan S. Wróbel, Mikko J. Alava, Silvia Bonfanti

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  21. Convolutional neural network-based prediction of hardness in bulk metallic glasses with small data

    Journal of Non-Crystalline Solids · 2025-02-19

    Chunghee Nam

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  22. Sliding wear behavior and mechanism of Zr-based bulk metallic glasses and metallic glass matrix composites

    Journal of Non-Crystalline Solids · 2025-04-06

    Jiaxiang Wu, Zhong Lin Wang, Huijun Yang, Junwei Qiao

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  23. Bayesian exploration of the composition space of CuZrAl metallic glasses for mechanical properties

    npj Computational Materials · 2025-04-07

    Tero Mäkinen, Anshul D. S. Parmar, Silvia Bonfanti, Mikko J. Alava

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  24. Real-time experiment-theory closed-loop interaction for autonomous materials science

    Science Advances · 2025-07-02

    Haotong Liang, C Wang, Heshan Yu, Dylan J. Kirsch, Rohit Kumar Pant, Austin McDannald, Aaron Gilad Kusne, Ji‐Cheng Zhao, Ichiro Takeuchi

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  25. Composition design and process optimization of refractory boride coatings based on high-throughput preparation and machine learning

    Journal of Materials Science · 2025-08-23

    Binyuan Jia, Wenhui Ma, Qiang Wan, Cai Lu, Qiwen Wei, Bing Yang, Yangyi Xiao

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  26. Self-supervised learning for glass composition screening

    Acta Materialia · 2025-09-23

    Meijing Chen, 斌 刘, Ying Liu, Tianrui Li

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  27. Unveiling key descriptors for electrical resistivity of alloys using high-throughput experiments and explainable AI

    npj Computational Materials · 2025-10-10

    Taeyeop Kim, Dongwoo Lee

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  28. Machine learning on glass-forming ability of metallic glasses guided by domain knowledge

    Transactions of Nonferrous Metals Society of China · 2025-11-01

    Hong BO, Xu-dong CHEN, Li-bin LIU, Xiao-gang FANG, Jian-liang HU, Li-min WANG

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  29. Data-driven prediction of thin-film metallic glass forming ability via Bayesian classification and experimental verification in the Cu–Zr–Al system

    RSC Advances · 2026-01-01

    Xuliang Luo, Tero Mäkinen, Wenyi Huo, Silvia Bonfanti, Zhehao Chen, Kenichiro Mizohata, Kostas Sarakinos, Mikko J. Alava

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  30. Generative AI inversely designs amorphous alloys with customized properties

    Science China Technological Sciences · 2026-01-01

    Shaochun Li, Junzhi Cui, Jingli Ren

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  31. Attention-enhanced variational learning for physically informed discovery of exceptionally hard multicomponent bulk metallic glasses

    Nature Communications · 2026-05-12

    Anurag Bajpai, Jaemin Wang, Barak Ratzker, Bilgehan Murat Şeşen, Florian Kark, Dierk Raabe

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  32. High‐Throughput Development of Advanced Metallic Glasses via Compositionally Graded Thin‐Film Combinatorial Strategy

    Rare Metals · 2026-08-01

    Yizhou Liu, Yebei Wang, Jinning Xie, Meichen Jian, Yunhe Gao, Yue Huang, Yan Li, Wenlin Liu, Fu Xu, Juntao Huo, Junqiang Wang, Meng Gao

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