Advanced search
Publication Cover
Materials Research Letters Volume 9, 2021 - Issue 1
Submit an article Journal homepage
5,797
Views
42
CrossRef citations to date
0
Altmetric
Original Reports

Phase prediction of Ni-base superalloys via high-throughput experiments and machine learning

Zijun Qina The State Key Laboratory of Powder Metallurgy, Central South University, Changsha, People’s Republic of ChinaORCID Iconhttps://orcid.org/0000-0003-0665-5924View further author information
ORCID Icon,
Zi Wanga The State Key Laboratory of Powder Metallurgy, Central South University, Changsha, People’s Republic of ChinaView further author information
,
Yunqiang Wangb School of Computer Science and Engineering, Central South University, Changsha, People’s Republic of ChinaView further author information
,
Lina Zhangc National Laboratory of Pattern Recongnition, Institute of Automation, Chinese Academy of Sciences, Beijing, People’s Republic of ChinaView further author information
,
Weifu Lid College of Science, Huazhong Agricultural University, Wuhan, People’s Republic of ChinaView further author information
,
Jin Liub School of Computer Science and Engineering, Central South University, Changsha, People’s Republic of ChinaView further author information
,
Zexin Wanga The State Key Laboratory of Powder Metallurgy, Central South University, Changsha, People’s Republic of ChinaView further author information
,
Zihang Lia The State Key Laboratory of Powder Metallurgy, Central South University, Changsha, People’s Republic of ChinaView further author information
,
Jun Pana The State Key Laboratory of Powder Metallurgy, Central South University, Changsha, People’s Republic of ChinaView further author information
,
Lei Zhaoe Beijing Key Laboratory of Metal Material Characterization, China Iron & Steel Research Institute, Beijing, People’s Republic of ChinaView further author information
,
Feng Liua The State Key Laboratory of Powder Metallurgy, Central South University, Changsha, People’s Republic of ChinaCorrespondence[email protected]
View further author information
,
Liming Tanf School of Metallurgy and Environment, Central South University, Changsha, People’s Republic of ChinaCorrespondence[email protected]
View further author information
,
Jianxin Wangb School of Computer Science and Engineering, Central South University, Changsha, People’s Republic of ChinaView further author information
,
Hua Hanc National Laboratory of Pattern Recongnition, Institute of Automation, Chinese Academy of Sciences, Beijing, People’s Republic of ChinaView further author information
,
Liang Jiangg Institute for Advanced Studies in Precision Materials, Yantai University, Yantai, People’s Republic of ChinaView further author information
&
Yong Liua The State Key Laboratory of Powder Metallurgy, Central South University, Changsha, People’s Republic of ChinaView further author information
 show all
Pages 32-40 | Received 08 Jun 2020, Published online: 27 Sep 2020

Citations (42)

Keep up to date with the latest research on this topic with citation updates for this article.

Subscribe to citation updates

Read on this site (3)

Sae Dieb, Yoshiaki Toda, Keitaro Sodeyama & Masahiko Demura. (2023) Machine learning-assisted determination of material chemical compositions: a study case on Ni-base superalloy. Science and Technology of Advanced Materials: Methods 3:1.
Read now
Zhenghui Zheng, Jian Lv, Ming Lou, Kai Xu, Leilei Chen, Jianbo Zhang, Yujie Du, Weibin Zhang & Keke Chang. (2023) Macro-gradient structures generated in Ti(C, N)-based cermets with supersaturated WC: an experimental and thermodynamic investigation. Materials Research Letters 11:2, pages 152-158.
Read now
Yi Ru, Bin Hu, Wenyue Zhao, Heng Zhang, Yanling Pei, Shusuo Li, Shengkai Gong & Huibin Xu. (2021) Topologically inverse microstructure in single-crystal superalloys: microstructural stability and properties at ultrahigh temperature. Materials Research Letters 9:12, pages 497-506.
Read now

Articles from other publishers (39)

Ronghai Wu, Lei Zeng, Jiangkun Fan, Zichao Peng & Yunsong Zhao. (2023) Composition, heat treatment, microstructure and loading condition based machine learning prediction of creep life of superalloys. Mechanics of Materials 187, pages 104819.
Crossref
Shuai Li, Shu Li, Dongrong Liu, Jia Yang & Mingyu Zhang. (2023) Hardness prediction of high entropy alloys with periodic table representation of composition, processing, structure and physical parameters. Journal of Alloys and Compounds 967, pages 171735.
Crossref
Mingwei Hu, Qiyang Tan, Ruth Knibbe, Miao Xu, Bin Jiang, Sen Wang, Xue Li & Ming-Xing Zhang. (2023) Recent applications of machine learning in alloy design: A review. Materials Science and Engineering: R: Reports 155, pages 100746.
Crossref
Yonggang Yan, Yalin Liao & Kun Wang. (2023) Accelerated discovery of oxidation-resistant ultra-high temperature ceramics via data driven methodology. Corrosion Science 223, pages 111457.
Crossref
Zexin Wang, Chuanxin Liang, Dong Wang, Xiaodai Yue, Jiarong Li & Xiangdong Ding. (2023) Unveiling the Co effect on the temporal evolution kinetics of γ′ phase in Ni–Al–Co model superalloys via CALPHAD–informed phase field simulations. Acta Materialia 258, pages 119247.
Crossref
Chengcheng Liu, Xuandong Wang, Weidong Cai, Jiahui Yang & Hang Su. (2023) Optimal Design of the Austenitic Stainless-Steel Composition Based on Machine Learning and Genetic Algorithm. Materials 16:16, pages 5633.
Crossref
Vickey Nandal, Sae Dieb, Dmitry S. Bulgarevich, Toshio Osada, Toshiyuki Koyama, Satoshi Minamoto & Masahiko Demura. (2023) Artificial intelligence inspired design of non-isothermal aging for γ–γ′ two-phase, Ni–Al alloys. Scientific Reports 13:1.
Crossref
Yuyu Huang, Jide Liu, Chongwei Zhu, Xinguang Wang, Yizhou Zhou, Xiaofeng Sun & Jinguo Li. (2023) An explainable machine learning model for superalloys creep life prediction coupling with physical metallurgy models and CALPHAD. Computational Materials Science 227, pages 112283.
Crossref
Patrick L. Taylor & Gareth Conduit. (2023) Machine learning superalloy microchemistry and creep strength from physical descriptors. Computational Materials Science 227, pages 112265.
Crossref
Yonggang Yan, Zongrui Pei, Michael C. Gao, Scott Misture & Kun Wang. (2023) Data-driven discovery of a formation prediction rule on high-entropy ceramics. Acta Materialia 253, pages 118955.
Crossref
Longlong Yang, Kun Sun & Huaying Wu. (2023) Effect of Void Defects on the Indentation Behavior of Ni/Ni3Al Crystal. Nanomaterials 13:13, pages 1969.
Crossref
Benjamin Wahlmann, Jakob Bandorf, Nicklas Volz, Andreas Förner, Johannes Pröbstle, Kerstin Multerer, Mathias Göken, Matthias Markl, Steffen Neumeier & Carolin Körner. (2022) Numerical Design of CoNi-Base Superalloys With Improved Casting Structure. Metallurgical and Materials Transactions A 54:5, pages 1683-1698.
Crossref
Lin Ye, Feng Liu, Heng Dong, Xiaoqiong Ouyang, Xiangyou Xiao, Liming Tan & Lan Huang. (2023) Investigation on the Microstructure and Mechanical Properties of Ni-Based Superalloy with Scandium. Metals 13:3, pages 611.
Crossref
Martin Bäker. (2023) Understanding element solution energies in nickelbase alloys using machine learning. Materials Research Express 10:3, pages 036503.
Crossref
Yong-Gang Yan, Dan Lu & Kun Wang. (2022) Overview: recent studies of machine learning in phase prediction of high entropy alloys. Tungsten 5:1, pages 32-49.
Crossref
Xiaolin Zhu, Wenhai Wan, Ling Qian, Yu Cai, Xiang Chen, Pingze Zhang, Guanxi Huang, Bo Liu, Qiang Yao, Shaoyuan Li & Zhengjun Yao. (2023) Research on Intelligent Identification and Grading of Nonmetallic Inclusions in Steels Based on Deep Learning. Micromachines 14:2, pages 482.
Crossref
Zihang Li, Zexin Wang, Zi Wang, Zijun Qin, Feng Liu, Liming Tan, Xiaochao Jin, Xueling Fan & Lan Huang. (2023) Quantifying Solid Solution Strengthening in Nickel-Based Superalloys via High-Throughput Experiment and Machine Learning. Computer Modeling in Engineering & Sciences 135:2, pages 1521-1538.
Crossref
Xiaoli Zhuang, Stoichko Antonov, Wendao Li, Song Lu, Longfei Li & Qiang Feng. (2023) Alloying effects and effective alloy design of high-Cr CoNi-based superalloys via a high-throughput experiments and machine learning framework. Acta Materialia 243, pages 118525.
Crossref
Jiheng Fang, Ming Xie, Xingqun He, Jiming Zhang, Jieqiong Hu, Yongtai Chen, Youcai Yang & Qinglin Jin. (2022) Machine learning accelerates the materials discovery. Materials Today Communications 33, pages 104900.
Crossref
Dong-wei Li, Jin-xiang Liu, Wei-qing Huang, Zheng-xing Zuo, Yi Shi & Wen-jun Bai. (2022) Machine learning-based prediction for time series damage evolution of Ni-based superalloy microstructures. Materials Today Communications 33, pages 104533.
Crossref
Raymundo Arróyave. (2022) Phase Stability Through Machine Learning. Journal of Phase Equilibria and Diffusion 43:6, pages 606-628.
Crossref
Zijun Qin, Weifu Li, Zi Wang, Junlong Pan, Zexin Wang, Zihang Li, Guowei Wang, Jun Pan, Feng Liu, Lan Huang, Liming Tan, Lina Zhang, Hua Han, Hong Chen & Liang Jiang. (2022) High-throughput characterization methods for Ni-based superalloys and phase prediction via deep learning. Journal of Materials Research and Technology 21, pages 1984-1997.
Crossref
Yong-Gang Yan & Kun Wang. (2022) The intrinsic strength prediction by machine learning for refractory high entropy alloys. Tungsten.
Crossref
Jian Jia, Yiwen Zhang, Yu Tao, Ting Yan & Hongyan Ji. (2022) Effects of Solution Temperature on Tensile Properties of a High γ′ Volume Fraction P/M Superalloy. Materials 15:16, pages 5528.
Crossref
Feng Liu, Zexin Wang, Zi Wang, Jing Zhong, Lei Zhao, Liang Jiang, Runhua Zhou, Yong Liu, Lan Huang, Liming Tan, Yujia Tian, Han Zheng, Qihong Fang, Lijun Zhang, Lina Zhang, Hong Wu, Lichun Bai & Kun Zhou. (2022) High‐Throughput Method–Accelerated Design of Ni‐Based Superalloys. Advanced Functional Materials 32:28.
Crossref
Wenyi Li, Weifu Li, Zijun Qin, Liming Tan, Lan Huang, Feng Liu & Chi Xiao. (2022) Deep Transfer Learning for Ni-Based Superalloys Microstructure Recognition on γ′ Phase. Materials 15:12, pages 4251.
Crossref
Shiya Yu, Xin Zhan, Feng Liu, Yu Guo, Qiangbing Wang, Yunping Li, Zi Wang, Zexin Wang, Liming Tan, Xueling Fan, Yan Wei & Lan Huang. (2022) 900 °C oxidation resistance of Ni-base superalloys alloyed with different refractory elements. Journal of Alloys and Compounds 904, pages 164071.
Crossref
Shijie Sun, Naicheng Sheng, Shigang Fan, Yuejiao Ma, Xi Cao, Zhiru Sang, Guichen Hou, Jinguo Li, Yizhou Zhou & Xiaofeng Sun. (2022) Abnormal feather-like grains induced by the thin-wall effect in a polycrystalline nickel-based superalloy. Journal of Alloys and Compounds 901, pages 163581.
Crossref
Zhuochen Yu & Weimin Huang. (2021) Accelerating Optimizing the Design of Carbon‐based Electrocatalyst via Machine Learning. Electroanalysis 34:4, pages 599-607.
Crossref
Rafael Casas, Rafael Sancho, Mónica Campos & Francisco Gálvez. (2022) The effect of temperature on the high-strain-rate response of Co-Al-W- base alloys: Experiments and modeling. Journal of Alloys and Compounds 897, pages 163154.
Crossref
Qihong Fang, Zhen Huang, Li Li, Zaiwang Huang, Bin Liu, Yong Liu, Jia Li & Peter K. Liaw. (2022) Modeling the competition between solid solution and precipitate strengthening of alloys in a 3D space. International Journal of Plasticity 149, pages 103152.
Crossref
Chenchong Wang, Xiaolu Wei, Da Ren, Xu Wang & Wei Xu. (2022) High-throughput map design of creep life in low-alloy steels by integrating machine learning with a genetic algorithm. Materials & Design 213, pages 110326.
Crossref
Shuning Gu, Hangshan Gao, Haiqing Pei, Chengjiang Zhang, Zhixun Wen, Zhenwei Li & Zhufeng Yue. (2021) Degradation of microstructural and mechanical properties with serviced turbine blades. Materials Characterization 182, pages 111582.
Crossref
Yan Sun, Zhichao Lu, Xiongjun Liu, Qing Du, Huamin Xie, Jiecheng Lv, Ruoxuan Song, Yuan Wu, Hui Wang, Suihe Jiang & Zhaoping Lu. (2021) Prediction of Ti-Zr-Nb-Ta high-entropy alloys with desirable hardness by combining machine learning and experimental data. Applied Physics Letters 119:20.
Crossref
Yonggang Yan, Dan Lu & Kun Wang. (2021) Accelerated discovery of single-phase refractory high entropy alloys assisted by machine learning. Computational Materials Science 199, pages 110723.
Crossref
Bruce Craig. (2020) Clarifying the Applicability of PREN Equations: A Short Focused Review. Corrosion 77:4, pages 382-385.
Crossref
Zi Wang, Lina Zhang, Weifu Li, Zijun Qin, Zexin Wang, Zihang Li, Liming Tan, Lilong Zhu, Feng Liu, Hua Han & Liang Jiang. (2021) A high-throughput approach to explore the multi-component alloy space: A case study of nickel-based superalloys. Journal of Alloys and Compounds 858, pages 158100.
Crossref
Dongwei Li, Weiqing Huang, Jinxiang Liu, Zhengxing Zuo, Yi Shi & Wenjun Bai. (2022) Machine Learning-Based Prediction for Time Series Damage Evolution of Ni-Based Superalloy Microstructures. SSRN Electronic Journal.
Crossref
Dongwei Li, Weiqing Huang, Jinxiang Liu, Zhengxing Zuo, Yi Shi & Wenjun Bai. (2022) Machine Learning-Based Prediction for Time Series Damage Evolution of Ni-Based Superalloy Microstructures. SSRN Electronic Journal.
Crossref

Related research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.