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Effect of fabrication techniques of high entropy alloys: A review with integration of machine learning

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dc.contributor.author Salam, Mohamed Yasin Abdul
dc.contributor.author Ogunmuyiwa, Enoch Nifise
dc.contributor.author Manisa, Victor Kitso
dc.contributor.author Yahya, Abid
dc.contributor.author Badruddin, Irfan Anjum
dc.date.accessioned 2025-11-25T14:03:53Z
dc.date.available 2025-11-25T14:03:53Z
dc.date.issued 2025-03
dc.identifier.citation Salam, M.Y. A., Ogunmuyiwa, E. N., Manisa, V. K., Yahya, A. and Badruddin, I. A. (2025) Effect of fabrication techniques of high entropy alloys: A review with integration of machine learning. Results in Engineering,25,104441. https://doi.org/10.1016/j.rineng.2025.104441 en_US
dc.identifier.issn 2590-1230
dc.identifier.uri https://repository.biust.ac.bw/handle/123456789/717
dc.description.abstract High Entropy Alloys (HEAs) are an emerging class of materials distinguished by equimolar or near-equimolar compositions of five or more principal elements. HEAs display exceptional mechanical properties, thermal stability, and wear resistance, making them suitable for advanced aerospace, biomedical, and automotive engineering applications. This review thoroughly explores various fabrication techniques for HEAs, including Vacuum Arc Melting (VAM), Hot Compression (HC), Laser Cladding (LC), and Spark Plasma Sintering (SPS). Each method's advantages, limitations, and impacts on microstructural properties are discussed in detail. Additionally, the integration of Machine Learning (ML) techniques in HEA research is highlighted, demonstrating their potential for optimizing fabrication parameters and predicting phase stability, microstructure evolution, and mechanical properties. The review concludes by identifying challenges in HEA fabrication, such as data availability and sustainability, and proposes future research directions to address these gaps. This work aims to provide researchers and engineers with a consolidated resource for advancing the development and application of HEAs. en_US
dc.description.sponsorship Deanship of Research and Graduate Studies at King Khalid University , Grant number RGP2/309/46. en_US
dc.language.iso en en_US
dc.publisher Elsevier Ltd en_US
dc.subject High entropy alloys en_US
dc.subject Machine learning en_US
dc.subject Vacuum arc melting en_US
dc.subject Spark plasma sintering en_US
dc.subject Laser cladding en_US
dc.subject Hot compression en_US
dc.subject Microstructure en_US
dc.title Effect of fabrication techniques of high entropy alloys: A review with integration of machine learning en_US
dc.description.level phd en_US
dc.description.accessibility unrestricted en_US
dc.description.department cme en_US


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