Multiphase-based predictive framework construction of abrasive wear performance in C–V–Cr–Mo alloys Article Swipe
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· 2025
· Open Access
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· DOI: https://doi.org/10.1016/j.jmrt.2025.09.250
Abrasive wear persists as the dominant failure mechanism in crushing equipment, driving the demand for predictive models to guide wear-resistant alloy design and equipment lifespan assessment. Conventional models (e.g., Archard's law) relying on macrohardness alone prove inadequate for alloys with intricate microstructures. To address this limitation, this study established a novel multiphase-based predictive framework that integrated phase-specific characteristics (carbide types, distribution) and impact toughness to accurately forecast abrasive wear in C–V–Cr–Mo alloys. By synergizing thermodynamic calculations (CALPHAD), empirical martensitic transformation models, and orthogonal experimentation, the predictive framework achieved a matrix hardness prediction error of 5.2 % (32.58 HV) and 91.52 % accuracy in wear loss prediction—22.11 % superior to Archard's model. Experimental validation across three alloy variants confirmed a minimal 4.0 % deviation (3.18 mg), demonstrating the model's reliable prediction fidelity. This framework provides precise predictions of abrasive wear performance for C–V–Cr–Mo alloys, and offers a reference for establishing predictive frameworks for the wear resistance of other alloy systems.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1016/j.jmrt.2025.09.250
- OA Status
- gold
- References
- 84
- OpenAlex ID
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Raw OpenAlex JSON
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https://openalex.org/W4414571912Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1016/j.jmrt.2025.09.250Digital Object Identifier
- Title
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Multiphase-based predictive framework construction of abrasive wear performance in C–V–Cr–Mo alloysWork title
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articleOpenAlex work type
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enPrimary language
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2025Year of publication
- Publication date
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2025-09-27Full publication date if available
- Authors
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Tao Jiang, Xuke Yao, Ma Min, Hua Yu, Junjie Sun, Yu Liu, Xiaozhi Hu, Chong Chen, Chengshuai Lei, Xiaodong WangList of authors in order
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-
https://doi.org/10.1016/j.jmrt.2025.09.250Publisher landing page
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YesWhether a free full text is available
- OA status
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goldOpen access status per OpenAlex
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https://doi.org/10.1016/j.jmrt.2025.09.250Direct OA link when available
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0Total citation count in OpenAlex
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84Number of works referenced by this work
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