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RESEARCH PAPER · Journal of Materials Science · 2022

Design of Ni-based turbine disc superalloys with improved yield strength using machine learning

Bin Xu, Haiqing Yin, Xue Feng Jiang, Cong Zhang, Ruijie Zhang, Yongwei Wang, Zhenghua Deng, Xuanhui Qu

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18 direct citing papers in this saved network. Explore the next layer with second-order citations.

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42 direct citing works

Design of Ni-based turbine disc superalloys with improved yield strength using machine learningOriginalProgress in Nb-Si ultra-high temperature structural materials: A review141Nickel-based polycrystalline superalloy composition design framework based on non-dominated sorting genetic algorithm II5Data-driven design of Ni-based turbine disc superalloys to improve yield strength56Design of novel Ni-based superalloys with better oxidation resistance with the aid of machine learning29Advances in materials informatics: a review42Effect of Ti, Ta, Nb on structural transformation of Ni3Al in terms of stacking faults7ASaRE-Net: automatic information extraction from Al-Si alloy materials science literature for corpus construction3Investigation on the component prediction and supercritical water oxidation of Ni-Cr-Mo alloy based on machine learning9Effect of additive elements on plastic deformation: a three-dimensional discrete dislocation dynamics study1Design of Novel High-Strength Ni-Based Superalloys Using a Data-Driven Approach1Inverse Design of Alloys via Generative Algorithms: Optimization and Diffusion within Learned Latent Space4Application of a multivariate feature-driven ACO-BPNN integrated model in predicting ultimate tensile strength and composition optimization of Ni-based alloys7A unified physical model for precipitation strengthening in Nickel-Based superalloys2Confidence-driven adaptive evolutionary learning for reliability-based design optimization of nickel-based alloys0Compositional design of Ni-based superalloys for additive manufacturing: Progress and perspectives9Mechanical property prediction of superalloys with microporosity defects using a multi-source deep learning framework0Ti coordinated element partitioning of γ′ strengthened CoNi-based superalloys: An integrated design and experimental study0Machine learning for high-performance alloy design: A review0

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18 direct citing papers saved.

  1. Progress in Nb-Si ultra-high temperature structural materials: A review

    Journal of Material Science and Technology · 2023-01-07

    Wei Liu, Shuai Huang, Chengtong Ye, Lina Jia, Yongwang Kang, Jiangbo Sha, Bingqing Chen, Yu Wu, Huaping Xiong

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  2. Nickel-based polycrystalline superalloy composition design framework based on non-dominated sorting genetic algorithm II

    Computational Materials Science · 2023-02-08

    Yaxi Liu, Bin Xu, Wei Huangfu, Haiqing Yin

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  3. Data-driven design of Ni-based turbine disc superalloys to improve yield strength

    Journal of Material Science and Technology · 2023-03-17

    Bin Xu, Haiqing Yin, Xue Feng Jiang, Cong Zhang, Ruijie Zhang, Yongwei Wang, Xuanhui Qu, Zhenghua Deng, Guoqiang Yang, Dil Faraz Khan

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  4. Design of novel Ni-based superalloys with better oxidation resistance with the aid of machine learning

    Journal of Materials Science · 2023-06-30

    Xingjun Duan, Hui Xu, Enhui Wang, Chunyu Guo, Zhi Fang, Tao Yang, Yunsong Zhao, Xinmei Hou

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  5. Advances in materials informatics: a review

    Journal of Materials Science · 2024-02-01

    Dawn Sivan, K. Satheesh Kumar, Aziman Abdullah, Veena Raj, Izan Izwan Misnon, Seeram Ramakrishna, Rajan Jose

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  6. Effect of Ti, Ta, Nb on structural transformation of Ni3Al in terms of stacking faults

    Journal of Materials Science · 2024-04-29

    Chao Lü, Xiaohua Min, Weiqiang Wang, Tieshan Cao

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  7. ASaRE-Net: automatic information extraction from Al-Si alloy materials science literature for corpus construction

    Journal of Materials Science · 2024-08-01

    Yingli Liu, Shaojie Wen, Jiancheng Yin, Haihe Zhou

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  8. Investigation on the component prediction and supercritical water oxidation of Ni-Cr-Mo alloy based on machine learning

    Journal of Nuclear Materials · 2024-12-10

    Jianxing Zhou, Lu Ren, Yue Lv, Wenwen Lin, Wei Jian, Dongyang Zhang, Xinkun Suo, Dianbo Ruan, Qinhao Zhang

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  9. Effect of additive elements on plastic deformation: a three-dimensional discrete dislocation dynamics study

    Modelling and Simulation in Materials Science and Engineering · 2025-01-30

    Ronghai Wu, Zheng xin Wang, Xiaoxiang Wu, Heng Li

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  10. Design of Novel High-Strength Ni-Based Superalloys Using a Data-Driven Approach

    Transactions of the Indian Institute of Metals · 2025-06-24

    Jinli Xie, Hailong Qin, Pei Liu, Songyi Shi, Yixin Cheng, Zhimin Sun, Bin Xu

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  11. Inverse Design of Alloys via Generative Algorithms: Optimization and Diffusion within Learned Latent Space

    Advanced Intelligent Discovery · 2025-07-11

    Mohammad Abu‐Mualla, Ellis Crabtree, fredrick michael, Yayue Pan, Jida Huang

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  12. Application of a multivariate feature-driven ACO-BPNN integrated model in predicting ultimate tensile strength and composition optimization of Ni-based alloys

    Materials Science and Engineering A · 2025-07-15

    Jianxing Zhou, Wei Jian, Lei Shen, Xi Yi, Hainan Wang, Ka Chun Chan, Yuk Lun Chan, Haozheng Wang, Qin-Hao Zhang, Xinkun Suo, Lu Ren

    Read original paper ↗ ·

  13. A unified physical model for precipitation strengthening in Nickel-Based superalloys

    Materials Science and Engineering A · 2025-11-26

    Dingge Fan, Xiongxi Zhao, Jian Zhang, Hao Jiang, Hao Jiang, Zhaoyang Lu, Yong Yuan, Jiantang Jiang, Liang Zhen

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  14. Confidence-driven adaptive evolutionary learning for reliability-based design optimization of nickel-based alloys

    Engineering Optimization · 2025-12-10

    Qian Tang, Tianlong Xu, Jun Xu, Xinru Zhang, Zequn Wang

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  15. Compositional design of Ni-based superalloys for additive manufacturing: Progress and perspectives

    Materials Science and Engineering R Reports · 2026-01-14

    Bingbing Yin, Yong Wei, Jiarui Zhu, Haoyu Ge, Shuaicheng Zhu, Yunwei Gui, Wenjing Zhang, Huadong Fu, Jinghe Xie

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  16. Mechanical property prediction of superalloys with microporosity defects using a multi-source deep learning framework

    npj Computational Materials · 2026-03-26

    Huipeng Yu, Chenyang Ding, Maodong Kang, Yunting Li, Yahui Liu, Jun Wang, Wei Xiong, Baode Sun

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  17. Ti coordinated element partitioning of γ′ strengthened CoNi-based superalloys: An integrated design and experimental study

    Materials Science and Engineering A · 2026-09-01

    Kunning Niu, Pei Liu, Zan Zhang, ShiBo Wei, Ye Shan, Shenglong Wang, Haiyou Huang, Yongsheng Li

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  18. 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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