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RESEARCH PAPER · Computational Materials Science · 2024

Development of single-phase BCC refractory high entropy alloys using machine learning techniques

Lakkanaboina Venkata Naveen, Priyanka Umre, Poulami Chakraborty, M.R. Rahul, Sumanta Samal, Raghvendra Tewari

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42 direct citing works

Development of single-phase BCC refractory high entropy alloys using machine learning techniquesOriginalA Modern Approach to HEAs: From Structure to Properties and Potential Applications40Machine learning-driven insights into phase prediction for high entropy alloys18Recent machine learning-driven investigations into high entropy alloys: A comprehensive review37Machine learning-assisted design of Ti–V–Nb–Mo refractory high-entropy alloys with higher ductility and specific yield strength30Machine Learning-Driven Prediction of Wear Rate and Phase Formation in High Entropy Alloy Coatings for Enhanced Durability and Performance22Third-generation thermodynamic descriptions of MoNbTaWHfZr refractory high entropy alloys and their phase stability6Machine learning prediction and experimental validation of microhardness in high-entropy alloy reinforced aluminium composite1Intelligent design of Fe–Cr–Ni–Al/Ti multi-principal element alloys based on machine learning5Design and development of advanced Al-Ti-V alloys for beampipe applications in particle accelerators3Machine Learning-Based Temperature-Induced Phase Transformation Temperature Prediction of Ti-Based High-Temperature Shape Memory Alloy4Impact of CoCrFeNiMo High-Entropy-Alloy Doping on the Mechanical and Electrochemical Properties of B4C Ceramic5Design Approaches of High‐Entropy Alloys Using Artificial Intelligence: A Review27Machine learning-driven optimization of hardness and toughness in high-entropy alloy coatings based on composition and descriptor10Accelerated design of eutectic high-entropy alloys using high-throughput phase diagram calculations and machine learning14Beyond elemental intrinsic characteristics: Δ H mix B − F -driven solid solution phase structure modeling in HEAs2Design of refractory complex concentrated alloys combining good tensile strength and ductility at 22–1000 °C6Machine learning assisted phase prediction of refractory multi-component alloys based on data from low-, medium-, and high-entropy alloys10Accelerated computational design of BCC refractory high entropy alloys using metaheuristics, CALPHAD, and artificial neural networks7Computation- and process-based design for advanced structural high-entropy alloy development and analyses: A critical review32Predicting the formation of single-phase high-entropy alloys using the tight-binding approximation0An interpretable Kolmogorov-Arnold neural network for refractory high-entropy alloy phase prediction0Machine learning-assisted design of lightweight refractory high-entropy alloys: A comprehensive review50Designing refractory complex concentrated alloys for extreme environments2Linking Dislocation Mobility, Compatible Heterogeneity and Service Stability in NbTaV-Containing and Related BCC Refractory High- and Medium-Entropy Alloys0A new feature engineered machine learning prediction of high-temperature yield strength for MoTiWNbZr refractory high-entropy alloys0High-Temperature Oxidation Resistance of Advanced High-Entropy Alloys: Recent Advances and Mechanistic Insights0

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  1. A Modern Approach to HEAs: From Structure to Properties and Potential Applications

    Crystals · 2024-05-09

    Radu Nartiţă, Daniela Ioniță, Ioana Demetrescu

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  2. Machine learning-driven insights into phase prediction for high entropy alloys

    Journal of Alloys and Metallurgical Systems · 2024-09-24

    Reliance Jain, Sandeep Jain, Sheetal Kumar Dewangan, Lokesh Kumar Boriwal, Sumanta Samal

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  3. Recent machine learning-driven investigations into high entropy alloys: A comprehensive review

    Journal of Alloys and Compounds · 2024-11-28

    Yonggang Yan, Xunxiang Hu, Yalin Liao, Yanyao Zhou, Wenhao He, Ting Zhou

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  4. Machine learning-assisted design of Ti–V–Nb–Mo refractory high-entropy alloys with higher ductility and specific yield strength

    Journal of Materials Research and Technology · 2024-12-24

    Yan Li, Junjie Gong, Shilong Liang, Wu Wei, Yongxin Wang, Zheng Chen

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  5. Machine Learning-Driven Prediction of Wear Rate and Phase Formation in High Entropy Alloy Coatings for Enhanced Durability and Performance

    IEEE Access · 2025-01-01

    S. Sivaraman, Nachimuthu Radhika, Muhammad Abubaker Khan

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  6. Third-generation thermodynamic descriptions of MoNbTaWHfZr refractory high entropy alloys and their phase stability

    Tungsten · 2025-02-03

    Jing-Han Gao, Enkuan Zhang, Ying Tang, Lijun Zhang, Jian Ding, Xingchuan Xia

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  7. Machine learning prediction and experimental validation of microhardness in high-entropy alloy reinforced aluminium composite

    Physica Scripta · 2025-02-24

    Saravana Sundar A, Nachimuthu Radhika

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  8. Intelligent design of Fe–Cr–Ni–Al/Ti multi-principal element alloys based on machine learning

    Journal of Materials Research and Technology · 2025-03-01

    Kang Xu, Zhengming Sun, Jian Tu, Wenwang Wu, Huihui Yang

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  9. Design and development of advanced Al-Ti-V alloys for beampipe applications in particle accelerators

    Physical Review Accelerators and Beams · 2025-04-08

    Kamaljeet Singh, Kangkan Goswami, Raghunath Sahoo, Sumanta Samal

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  10. Machine Learning-Based Temperature-Induced Phase Transformation Temperature Prediction of Ti-Based High-Temperature Shape Memory Alloy

    Journal of Materials Engineering and Performance · 2025-04-25

    S. Sridharan, Ramamoorthy Velayutham, Sudhir Behera, Jayaprakash Murugesan

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  11. Impact of CoCrFeNiMo High-Entropy-Alloy Doping on the Mechanical and Electrochemical Properties of B4C Ceramic

    Applied Sciences · 2025-04-27

    Alberto Daniel Rico-Cano, Julia Claudia Mirza Rosca, Burak Çağrı Ocak, Gültekin Göller

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  12. Design Approaches of High‐Entropy Alloys Using Artificial Intelligence: A Review

    Advanced Engineering Materials · 2025-05-07

    Nour Mahmoud Eldabah, Ayush Pratap, Atul Pandey, Neha Sardana, Sarabjeet Singh Sidhu, Mohamed Abdel Hady Gepreel

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  13. Machine learning-driven optimization of hardness and toughness in high-entropy alloy coatings based on composition and descriptor

    Journal of Applied Physics · 2025-05-19

    Kehong Zhong, Shaoyu Wu, Siqian Liu, Juan Qi, Longwei Cheng, Dongmei Ai

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  14. Accelerated design of eutectic high-entropy alloys using high-throughput phase diagram calculations and machine learning

    Materials & Design · 2025-05-20

    Mingxu Wu, Bang Guan, J.X. Wang, Shubin Wang, Chao Yang, Chuan Zhang, Da Shu, Chengbo Xiao, Baode Sun

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  15. Beyond elemental intrinsic characteristics: Δ H mix B − F -driven solid solution phase structure modeling in HEAs

    Intermetallics · 2025-05-24

    K.X. Yin, Yijiala Yiliti, Songtao Li, Chengyu Zhang, Y.K. Zhou, Haifeng Zhang, Zhengwang Zhu

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  16. Design of refractory complex concentrated alloys combining good tensile strength and ductility at 22–1000 °C

    International Journal of Refractory Metals and Hard Materials · 2025-05-24

    N. Yurchenko, E. Mishunina, E. Kochura, Vladimir Mirontsov, D. Kapustin, Svetlana Anatolievna Shalnova, Stanislav A. Evlashin, Nikita Stepanov

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  17. Machine learning assisted phase prediction of refractory multi-component alloys based on data from low-, medium-, and high-entropy alloys

    International Journal of Refractory Metals and Hard Materials · 2025-05-30

    Yuehua Wang, Mingqing Liao, Nan Qu, Xizhen Li, Danni Yang, Zhonghong Lai, Yong Liu, Fengjiang Wang, Jingchuan Zhu

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  18. Accelerated computational design of BCC refractory high entropy alloys using metaheuristics, CALPHAD, and artificial neural networks

    Materials Today Communications · 2025-06-13

    R.S. Monzamodeth, V.A. Aranda, E. Hernández-Mecinas, S. Espinosa-Rangel, J. Villalobos, I.A. Figueroa, G. González

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  19. Computation- and process-based design for advanced structural high-entropy alloy development and analyses: A critical review

    Progress in Materials Science · 2025-07-15

    Zaigham Saeed Toor, Renhao Wu, Muhammad Raihan Hashmi, Jeong Ah Lee, Xiaoqing Li, Harada Yuji, Haiming Zhang, Hyoung Seop Kim

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  20. Predicting the formation of single-phase high-entropy alloys using the tight-binding approximation

    Journal of Physics Condensed Matter · 2025-07-28

    Jacques René Eone

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  21. An interpretable Kolmogorov-Arnold neural network for refractory high-entropy alloy phase prediction

    SSRN Electronic Journal · 2026-01-01

    Guixin Chen, Xiaoli Zheng, Ziyun Li, Yonggang Yan, Dong Wang, Yi Bing Zhao, Hui Li, Xunxiang Hu

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  22. Machine learning-assisted design of lightweight refractory high-entropy alloys: A comprehensive review

    Metals Advances · 2026-01-27

    Lei Chen, Gang Qin, Yao Chen, Qi Ming Wang, Liang Wang, Yanqing Su, Ruirun Chen

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  23. Designing refractory complex concentrated alloys for extreme environments

    Current Opinion in Solid State and Materials Science · 2026-02-05

    Quanfeng He, Xufeng Wang, Qing Wang, Hang Wang, Ruiqi Ding, Zhaoqi Chen, Ruochen Sun, Guangbao Mi, Jianfeng Gu, Yong Gang Yang

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  24. Linking Dislocation Mobility, Compatible Heterogeneity and Service Stability in NbTaV-Containing and Related BCC Refractory High- and Medium-Entropy Alloys

    Crystals · 2026-08-12

    Longchao Zhuo, Yingliang Zhang, Bingqing Chen, Jiacheng Sun, Hao Wang, Zhaozong Zhang

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  25. A new feature engineered machine learning prediction of high-temperature yield strength for MoTiWNbZr refractory high-entropy alloys

    International Journal of Refractory Metals and Hard Materials · 2026-09-15

    Huohong Tang, Junfei Xiong, Bao Shen, Junsheng Zhang, Shunhua Chen

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  26. High-Temperature Oxidation Resistance of Advanced High-Entropy Alloys: Recent Advances and Mechanistic Insights

    Materials Science and Engineering A · 2026-10-01

    Xulong An, Lipeng Shao, Wei Wei, Wenwen Sun

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