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RESEARCH PAPER · Intermetallics · 2025

Machine learning for obtaining values of thermomechanical processing parameters of high-entropy alloys with desirable strength and ductility

Zolfaghar Ali Akhlaghi, Hamed Shahmir, Ahmad R. Sharafat

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Machine learning for obtaining values of thermomechanical processing parameters of high-entropy alloys with desirable strength and ductilityOriginalMulti-objective grey wolf optimization of selective laser melting process parameters for the fabrication of Al0.2CuFeMnNi high entropy alloy and evaluation of mechanical, tribological and corrosion behaviour1Superior strength-ductility synergy in metastable high-entropy alloys: The crucial role of FCC to BCC martensitic phase transformation23Machine learning-driven design of refractory high-entropy alloys with high performance of hardness and corrosion resistance7A machine learning method to predict grain refinement and hardness of severely deformed materials6Denoising diffusion probabilistic model-based tabular data augmentation for improved phase classification of high-entropy alloys2Kinetic control of deformation-induced martensitic transformation as a toughening mechanism in advanced metastable austenitic alloys7A comparative study on modeling the hot deformation behavior of titanium-containing CoCrFeNi high entropy alloy using constitutive equation and machine learning algorithms4High-throughput computational and machine-learning design of high-entropy alloys based on thermodynamic and empirical parameters: Al-Si-Cr-Fe-(Ni,Mn) systems3Machine learning-assisted high-throughput exploration of single-phase high-entropy alloys2High performance yet cost effective structural high-entropy alloys: a review0Physics-informed machine learning framework integrating solid solution strengthening theory for accelerated hardness prediction in high-entropy alloys0Using machine learning to predict superplasticity in high-entropy alloys0Machine learning for high-performance alloy design: A review0

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  1. Multi-objective grey wolf optimization of selective laser melting process parameters for the fabrication of Al0.2CuFeMnNi high entropy alloy and evaluation of mechanical, tribological and corrosion behaviour

    Intermetallics · 2025-08-27

    K Hareharen, T. Panneerselvam

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  2. Superior strength-ductility synergy in metastable high-entropy alloys: The crucial role of FCC to BCC martensitic phase transformation

    Journal of Alloys and Compounds · 2025-10-17

    Alireza Jalali, Mohammad Sajad Mehranpour, Alireza Kalhor, Mohammad Javad Sohrabi, Ali Heydarinia, Farhad Hasanabadi, Hamed Mirzadeh, Mehdi Malekan, Mahmoud Sarkari Khorrami, Vahid Fallah, Kinga Rodak, Hyoung Seop Kim

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  3. Machine learning-driven design of refractory high-entropy alloys with high performance of hardness and corrosion resistance

    Materials & Design · 2026-01-23

    Tao Wu, Ruiquan Wang, Guang Chen, Yajun Yin, Yanbin Shen, Changxin Lei, Huayong Zhao

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  4. A machine learning method to predict grain refinement and hardness of severely deformed materials

    Materials Science and Engineering A · 2026-01-30

    Hamed Shahmir, Sina Kooshamanesh, Terence G. Langdon

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  5. Denoising diffusion probabilistic model-based tabular data augmentation for improved phase classification of high-entropy alloys

    Acta Materialia · 2026-03-14

    Libin Zhang, Yoon Suk Choi

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  6. Kinetic control of deformation-induced martensitic transformation as a toughening mechanism in advanced metastable austenitic alloys

    Materials & Design · 2026-03-20

    Mohammad Sajad Mehranpour, Mohammad Javad Sohrabi, Alireza Jalali, Mahmoud Sarkari Khorrami, Hamed Mirzadeh, Saeed Sadeghpour, Hyoung Seop Kim, Terence G. Langdon, Hamed Shahmir

    Read original paper ↗ ·

  7. A comparative study on modeling the hot deformation behavior of titanium-containing CoCrFeNi high entropy alloy using constitutive equation and machine learning algorithms

    Intermetallics · 2026-04-16

    Mehrdad Karimzadeh, Mehdi Malekan, Hamed Mirzadeh, M. Malekpour Shahraki, Leijun Li, M. V. Farahani

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  8. High-throughput computational and machine-learning design of high-entropy alloys based on thermodynamic and empirical parameters: Al-Si-Cr-Fe-(Ni,Mn) systems

    Intermetallics · 2026-05-14

    Hamed Shahmir, Farsad Forghani

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  9. Machine learning-assisted high-throughput exploration of single-phase high-entropy alloys

    Journal of Materials Science · 2026-06-15

    Hamed Shahmir, Farsad Forghani

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  10. High performance yet cost effective structural high-entropy alloys: a review

    Journal of Materials Science · 2026-08-27

    Mohammad Sajad Mehranpour, Mohammad Javad Sohrabi, Hamed Mirzadeh, Mahmoud Sarkari Khorrami, Hyoung Seop Kim

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  11. Physics-informed machine learning framework integrating solid solution strengthening theory for accelerated hardness prediction in high-entropy alloys

    Journal of Materials Informatics · 2026-09-08

    Ao Gao, Yixiang Yan, Qiuling Tao, Jinxin Yu, Shengkun Xi, Geng Li, Xiaoyu Chong, Xingjun Liu

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  12. Using machine learning to predict superplasticity in high-entropy alloys

    Journal of Materials Science · 2026-09-29

    Hamed Shahmir, Sina Kooshamanesh, Mohammad Sajad Mehranpour, Terence G. Langdon

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  13. Machine learning for high-performance alloy design: A review

    Metals Advances · 2026-10-01

    Zinuo Wang, Qi Xu, Peng Zhou, Tao Zhang, Fuhui Wang

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