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Fast Screening of Corrosion Trends in Metallic Glasses
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    Fast Screening of Corrosion Trends in Metallic Glasses
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    • Jingbei Liu
      Jingbei Liu
      Department of Mechanical Engineering and Materials Science, Yale University, New Haven, Connecticut 06511, United States
      More by Jingbei Liu
    • Naijia Liu
      Naijia Liu
      Department of Mechanical Engineering and Materials Science, Yale University, New Haven, Connecticut 06511, United States
      More by Naijia Liu
    • Meng Sun
      Meng Sun
      Department of Chemical and Environmental Engineering, Yale University, New Haven, Connecticut 06520, United States
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    • Jinyang Li
      Jinyang Li
      School of Materials Science and Engineering, Southwest Jiaotong University, Chengdu 610031, China
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    • Sungwoo Sohn
      Sungwoo Sohn
      Department of Mechanical Engineering and Materials Science, Yale University, New Haven, Connecticut 06511, United States
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    • Jan Schroers*
      Jan Schroers
      Department of Mechanical Engineering and Materials Science, Yale University, New Haven, Connecticut 06511, United States
      *E-mail: [email protected]
      More by Jan Schroers
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    ACS Combinatorial Science

    Cite this: ACS Comb. Sci. 2019, 21, 10, 666–674
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    https://doi.org/10.1021/acscombsci.9b00073
    Published September 17, 2019
    Copyright © 2019 American Chemical Society

    Abstract

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    Corrosion trends in the bulk metallic glass forming alloy system Zr–Cu–Al are studied through a fast screening visual characterization method of thin film alloy libraries prepared by magnetron co-sputtering. Significant distinct brightness changes are present within the Zr–Cu–Al system when the thin film library is immersed in 3.5 wt % NaCl. Through additional quantification of corrosion current density, a correlation between change in brightness and corrosion current density is revealed, suggesting an effective rapid screening of corrosion simply by a visual method. For materials discovery with optimized multiproperties, we utilize the corrosion fast screening results and superimpose them on the composition dependence of the glass forming ability. This allows us to rapidly identify alloys with the best combination of glass forming ability and corrosion resistance, which we then confirm in bulk form.

    Copyright © 2019 American Chemical Society

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    Supporting Information

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    The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acscombsci.9b00073.

    • Figures of phases, polarization curves, and correlation (PDF)

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    Cited By

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    This article is cited by 10 publications.

    1. Yuzhou Wu, Yue Huang, Yebei Wang, Fuchao Wang, Yunhe Gao, Yingying Sun, Meichen Jian, Lijian Song, Yu Tong, Yan Zhang, Chao Wang, Yanhui Liu, Jun-Qiang Wang, Juntao Huo, Meng Gao. High-throughput development of tough metallic glass films. Materials Horizons 2025, 57 https://doi.org/10.1039/D4MH00815D
    2. Khadijah M. Emran, Noureddine Ouerfelli. Effect of acid proticity on the thermodynamic parameters of charge transfer resistance in corrosion and passivation of nickel based glass alloy. Scientific Reports 2024, 14 (1) https://doi.org/10.1038/s41598-024-52036-0
    3. Weijie Xie, Weihua Wang, Yanhui Liu. On the application of high‐throughput experimentation and data‐driven approaches in metallic glasses. Materials Genome Engineering Advances 2023, 1 (1) https://doi.org/10.1002/mgea.8
    4. Li Jiang, Mianyu Bao, Yanmao Dong, Yan Yuan, Xing Zhou, Xiangkang Meng. Processing, production and anticorrosion behavior of metallic glasses: A critical review. Journal of Non-Crystalline Solids 2023, 612 , 122355. https://doi.org/10.1016/j.jnoncrysol.2023.122355
    5. Jian Luo, Liping Huang, Yunfeng Shi, Binghui Deng. The dynamics of shear band propagation in metallic glasses. Acta Materialia 2023, 248 , 118787. https://doi.org/10.1016/j.actamat.2023.118787
    6. Xinyun Wang, Mao Zhang. Performance of oxidized metallic glasses. 2023, 231-246. https://doi.org/10.1016/B978-0-323-90997-6.00009-2
    7. Junhua Cao, Meng Gao, Yuanfei Cai, Jinlong Li, Ye Wang, Jun-Qiang Wang, Juntao Huo. Rapid screening the mechanical properties of ZrNi-based metallic glasses by high-throughput combinatorial approach. Intermetallics 2022, 148 , 107640. https://doi.org/10.1016/j.intermet.2022.107640
    8. Ming-Xing Li, Yi-Tao Sun, Chao Wang, Li-Wei Hu, Sungwoo Sohn, Jan Schroers, Wei-Hua Wang, Yan-Hui Liu. Data-driven discovery of a universal indicator for metallic glass forming ability. Nature Materials 2022, 21 (2) , 165-172. https://doi.org/10.1038/s41563-021-01129-6
    9. Daniel B. Miracle, Mu Li, Zhaohan Zhang, Rohan Mishra, Katharine M. Flores. Emerging Capabilities for the High-Throughput Characterization of Structural Materials. Annual Review of Materials Research 2021, 51 (1) , 131-164. https://doi.org/10.1146/annurev-matsci-080619-022100
    10. Cheng Zhang, Di Ouyang, Simon Pauly, Lin Liu. 3D printing of bulk metallic glasses. Materials Science and Engineering: R: Reports 2021, 145 , 100625. https://doi.org/10.1016/j.mser.2021.100625
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    ACS Combinatorial Science

    Cite this: ACS Comb. Sci. 2019, 21, 10, 666–674
    Click to copy citationCitation copied!
    https://doi.org/10.1021/acscombsci.9b00073
    Published September 17, 2019
    Copyright © 2019 American Chemical Society

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