Papers citing A property-oriented design strategy for high performance copper alloys via machine learning
Predicting the corrosion properties of cast and hot isostatic pressed CoCrMo/W alloys in seawater by machine learning
Anti-Corrosion Methods and Materials · 2022-03-11
Xue Feng Jiang, Yu Jing Yan, Yanjing Su
Read original paper ↗ ·Recent progress in the machine learning-assisted rational design of alloys
International Journal of Minerals Metallurgy and Materials · 2022-04-01
Huadong Fu, Hong‐Tao Zhang, Changsheng Wang, Wei Yong, Jianxin Xie
Read original paper ↗ ·Materials genome engineering: a promising approach for the development of high-performance metal–organic frameworks
中国科学通报：英文版 · 2022-05-11
Xiangdong Xue, Xiubing Huang, Ge Wang
Read original paper ↗ ·Rapid design of secondary deformation-aging parameters for ultra-low Co content Cu-Ni-Co-Si-X alloy via Bayesian optimization machine learning
International Journal of Minerals Metallurgy and Materials · 2022-05-23
Hongtao Zhang, Huadong Fu, Yuheng Shen, Jianxin Xie
Read original paper ↗ ·Creep rupture life prediction of nickel-based superalloys based on data fusion
Computational Materials Science · 2022-06-06
Yaliang Zhu, Fangmiao Duan, Wei Yong, Huadong Fu, Hongtao Zhang, Jianxin Xie
Read original paper ↗ ·On the use of transfer modeling to design new steels with excellent rotating bending fatigue resistance even in the case of very small calibration datasets
Acta Materialia · 2022-06-17
Xiaolu Wei, Sybrand van der Zwaag, Zixi Jia, Chenchong Wang, Wei Xu
Read original paper ↗ ·Material machine learning for alloys: Applications, challenges and perspectives
Journal of Alloys and Compounds · 2022-06-21
Xiujuan Liu, Pengcheng Xu, Juanjuan Zhao, Wencong Lu, Minjie Li, Gang Wang
Read original paper ↗ ·Design of super-hard high-entropy ceramics coatings via machine learning
Ceramics International · 2022-07-30
Xiaoqian Xu, Xiaobo Wang, Shaoyu Wu, Luchun Yan, Tao Guo, Kewei Gao, Xiaolu Pang, Alex A. Volinsky
Read original paper ↗ ·Machine learning of the mechanical properties and data-driven design of lead-free solder alloys
Scientia Sinica Technologica · 2022-08-15
Hao Yuan, Bin Cao, Kangdong You, Ziqiang Dong, Tong‐Yi Zhang, Jubo Peng, Shanshan Cai, Xiaobin Luo, Chen LIU, JiaJun WANG
Read original paper ↗ ·A feasibility study of machine learning-assisted alloy design using wrought aluminum alloys as an example
Computational Materials Science · 2022-09-14
Yasaman J. Soofi, Md Asad Rahman, Yijia Gu, Jinling Liu
Read original paper ↗ ·Stacking-Based Multi-Features Fusion Ensemble Learning for Product Quality Prediction
IEEE International Conference on e-Business Engineering (ICEBE) · 2022-10-01
Wenbiao Tao, Luyao Xu, Yuran Dong, Cheng Xie
Read original paper ↗ ·Random forest incorporating ab-initio calculations for corrosion rate prediction with small sample Al alloys data
npj Materials Degradation · 2022-10-07
Yucheng Ji, Ni Li, Zhanming Cheng, Xiaoqian Fu, Min Ao, Menglin Li, Xiaoguang Sun, Thee Chowwanonthapunya, Dawei Zhang, Kui Xiao, Jingli Ren, Poulumi Dey, Xiaogang Li, Chaofang Dong
Read original paper ↗ ·A novel neural network-based alloy design strategy: Gated recurrent unit machine learning modeling integrated with orthogonal experiment design and data augmentation
Acta Materialia · 2022-10-13
Jie Yin, Qian Lei, Xiang Li, Xiaoyan Zhang, Xiangpeng Meng, Yanbin Jiang, Liang Tian, Shuang Zhou, Zhou Li
Read original paper ↗ ·Design of new Al-Si-Mg alloys by multi-modal mixed input simulation experiment
Acta Physica Sinica · 2022-10-19
Zhiqiang Duan, Xiao-long Pei, Qingwei Guo, Hua Hou, Yuhong Zhao
Read original paper ↗ ·Dynamic Modeling of Intrinsic Self-Healing Polymers Using Deep Learning
ACS Applied Materials & Interfaces · 2022-11-08
Hashina Parveen Anwar Ali, Zichen Zhao, Yu Jun Tan, Wei Yao, Qianxiao Li, Benjamin C. K. Tee
Read original paper ↗ ·Exploration of V–Cr–Fe–Co–Ni high-entropy alloys with high yield strength: A combination of machine learning and molecular dynamics simulation
Computational Materials Science · 2022-11-08
Lu Chen, Asker Jarlöv, Hang Li Seet, Mui Ling Sharon Nai, Yefei Li, Kun Zhou
Read original paper ↗ ·Machine learning accelerates the materials discovery
Materials Today Communications · 2022-11-09
Jiheng Fang, Ming Xie, Xingqun He, Jiming Zhang, Jieqiong Hu, Yongtai Chen, Youcai Yang, Qinglin Jin
Read original paper ↗ ·Customized development of promising Cu-Cr-Ni-Co-Si alloys enabled by integrated machine learning and characterization
Acta Materialia · 2022-11-11
Shaobin Pan, Jinxin Yu, Jiajia Han, Yanqing Zhang, Qinghua Peng, Mujin Yang, Youheng Chen, Xiang Yi Huang, Rongpei Shi, Cuiping Wang, Xingjun Liu
Read original paper ↗ ·Alloying effects and effective alloy design of high-Cr CoNi-based superalloys via a high-throughput experiments and machine learning framework
Acta Materialia · 2022-11-12
Xiaoli Zhuang, Stoichko Antonov, Wendao Li, Song Lu, Longfei Li, Qiang Charles Feng
Read original paper ↗ ·Fatigue life evaluation model for various austenitic stainless steels at elevated temperatures via alloy features‐based machine learning approach
Fatigue & Fracture of Engineering Materials & Structures · 2022-11-21
Lei He, Wei Yong, Huadong Fu, Takamoto Itoh
Read original paper ↗ ·Data-driven investigation of microstructure and surface integrity in additively manufactured multi-principal-element alloys
Journal of Alloys and Compounds · 2022-12-09
Jing Peng, Jia Li, Weipeng Li, Peter Kaehuei Liaw, Jia Li, Qihong Fang
Read original paper ↗ ·Machine learning assisted design of aluminum-lithium alloy with high specific modulus and specific strength
Materials & Design · 2022-12-09
Huiyu Li, Xiwu Li, Yanan Li, Wei Xiao, Kai Wen, Zhihui Li, Yongan Zhang, Baiqing Xiong
Read original paper ↗ ·Artificial intelligence in multiscale scaffolds for cancer organoids testbed
Elsevier eBooks · 2023-01-01
Dinesh R. Katti, Kalpana S. Katti, Hanmant K. Gaikwad, Sharad V. Jaswandkar
Read original paper ↗ ·Development of Key Technologies for Intelligent Research and Development of New Materials
Strategic Study of CAE · 2023-01-01
Yanjing Su, Mingli Yang, Weili Zhu, Kechao Zhou, Dezhen Xue, Hong Wang, Jianxin Xie
Read original paper ↗ ·Discovery of thermosetting polymers with low hygroscopicity, low thermal expansivity, and high modulus by machine learning
Journal of Materials Chemistry A · 2023-01-01
Xinyao Xu, Wenlin Zhao, Yaxi Hu, Liquan Wang, Jiaping Lin, Huimin Qi, Lei Du
Read original paper ↗ ·Exploring the absolute yield curve of secondary electrons using machine learning methods
Physical Chemistry Chemical Physics · 2023-01-01
Mehnaz, Bo Da, Zejun Ding
Read original paper ↗ ·Machine-learning assisted compositional optimization of 2xxx series aluminum alloys towards tensile strength
Materials Research Express · 2023-01-01
Yingbo Zhang, Pu Zhang, Jiaheng Li, Qi Zeng, Mojia Li, Yunfeng Hu, Yuanhui Peng
Read original paper ↗ ·Data Augmentation of Micrographs and Prediction of Impact Toughness for Cast Austenitic Steel by Machine Learning
Metals · 2023-01-04
Gang Xu, Xiaotong Zhang, Jinwu Xu
Read original paper ↗ ·An improved composition design method for high-performance copper alloys based on various machine learning models
AIP Advances · 2023-02-01
Zhao Siyue, Na Li, Guangtong Hai, Zhigang Zhang
Read original paper ↗ ·Exploring the relationship between lattice distortion and phase stability in a multi-principal element alloy system based on machine learning method
Computational Materials Science · 2023-02-26
Jiaxin Huang, Wei Fang, Congcong Xue, Tiexu Peng, Haoyang Yu, Jia Li, Liying Sun, Xinbo He, Baoxi Liu, Yong Gang Yang, Fuxing Yin
Read original paper ↗ ·Phase Equilibria, Thermodynamics and Solidified Microstructure in the Copper–Zirconium–Yttrium System
Materials · 2023-03-02
Fengting Jing, Yuling Liu, Yong Du, Chenying Shi, Biao Hu, Xiancong He
Read original paper ↗ ·Design Strategy for Art Copper Alloys’ Colors Through Machine Learning and Oxidation Treatment
JOM · 2023-03-14
Shuang Zhou, Qian Lei, Jie Yin, Yuxin Liang, Qianye Ren, Can Dai, Zhou Li
Read original paper ↗ ·Accelerating the design of compositionally complex materials via physics-informed artificial intelligence
Nature Computational Science · 2023-03-31
Dierk Raabe, Jaber Rezaei Mianroodi, Jörg Neugebauer
Read original paper ↗ ·Insight into the Influence of Alloying Elements on the Elastic Properties and Strengthening of Copper: A High-Throughput First-Principles Calculations
Metals · 2023-05-01
Jinhao Zhang, Youcheng Zhang, Aiqin Wang, Tingting Liang, Zhiping Mao, Bo Su, Haisheng Li, Jingpei Xie
Read original paper ↗ ·Searching for medium entropy alloys with desired mechanical property by adaptive design combined with experiments
International Journal of Refractory Metals and Hard Materials · 2023-05-01
Xuefei Wang, Hong Luo, Qiancheng Zhao, Hongxu Cheng, Zhimin Pan, Xiaogang Li
Read original paper ↗ ·Modeling the Double-Pass Flow Curve of Nb Micro-Alloyed Steel by Machine Learning and its Extrapolation to Static Softening Kinetics
Journal of Materials Engineering and Performance · 2023-05-04
Xin Li, Qiming Jiang, Xiaoguang Zhou, Siwei Wu, Guangming Cao, Zhenyu Liu
Read original paper ↗ ·An Improved Random Forest Magnesium Alloy Prediction Method Based on Particle Swarm Optimization
Materials science forum · 2023-05-18
Yu Zhang, Shi Cheng Wei, Bo Wang, Lin Wei Li
Read original paper ↗ ·Stability of binary precipitates in Cu-Ni-Si-Cr alloys investigated through active learning
Materials Chemistry and Physics · 2023-06-15
Ángel Díaz Carral, Xiang Xu, Simon Gravelle, Azade YazdanYar, Siegfried Schmauder, Maria Fyta
Read original paper ↗ ·Physics‐Informed Multistage Machine Learning Strategy for the Nanomachining‐Induced Plastic Deformation Behavior
Advanced Engineering Materials · 2023-06-28
Baobin Xie, Shenyou Peng, Jia Li, Qihong Fang, Peter Kaehuei Liaw
Read original paper ↗ ·Machine learning guided optimal composition selection of niobium alloys for high temperature applications
APL Machine Learning · 2023-07-05
Trupti Mohanty, K.S. Ravi Chandran, Taylor D. Sparks
Read original paper ↗ ·Alloying element distributions of precipitates in Cu–Cr alloys aided by machine learning
Materials Today Communications · 2023-07-06
Haipeng Jin, Hang Wang, Xin Wang, Jiasong Zhang, Chenyang Zhou
Read original paper ↗ ·An Intelligent Manufacturing Platform of Polymers: Polymeric Material Genome Engineering
Engineering · 2023-08-01
Liang Gao, Liquan Wang, Jiaping Lin, Lei Du
Read original paper ↗ ·Mechanical properties: Fatigue
Elsevier eBooks · 2023-08-04
Desmond Edem Primus Klenam, Fred McBagonluri, Winston Oluwole Soboyejo
Read original paper ↗ ·The γ/γ′ microstructure in CoNiAlCr-based superalloys using triple-objective optimization
npj Computational Materials · 2023-08-10
Pei Liu, Haiyou Huang, Cheng Wen, Turab Lookman, Yanjing Su
Read original paper ↗ ·In pursuit of a suitable machine learning algorithm for hardness prediction of aluminium alloy
Engineering Computations · 2023-08-16
Suman Chabri, Krishnendu Hazra, Amitava Choudhury, Arijit Sinha, Manojit Ghosh
Read original paper ↗ ·Composition design of high-performance copper alloy by coupling artificial neural network and genetic algorithm
Computational Materials Science · 2023-08-21
Kang Liu, Ruijie Zhang, Si Zhang, Yongqin Chang, Mingyang Li, Yijie Wang, Qingqing Liu, Daohan Yu
Read original paper ↗ ·Classification of T6 Tempered 6XXX Series Aluminum Alloys Based on Machine Learning Principles
JOM · 2023-08-22
Tanu Tiwari, Sadegh Jalalian, Chamini Lakshi Mendis, Dmitry G. Eskin
Read original paper ↗ ·Data science and material informatics in physical metallurgy and material science: An overview of milestones and limitations
Results in Materials · 2023-09-01
Desmond Edem Primus Klenam, Tabiri Kwayie Asumadu, Mobin Vandadi, Nima Rahbar, Fred McBagonluri, Winston Oluwole Soboyejo
Read original paper ↗ ·Comprehensive elemental screening of solid-solution copper alloys
Science and Technology of Advanced Materials Methods · 2023-09-04
Kenji Yamaguchi, Takuya Ishigaki, Yuki Inoue, Shuhei Arisawa, Hirotaka Matsunoshita, Yuki Ito, Hiroyuki Mori, Kenichiro Suehiro, Kazunari Maki, Kenji Nagata, Masahiko Demura
Read original paper ↗ ·Machine learning-based quantitative analysis of metal ductile fracture surface
Materialia · 2023-09-17
Neng Zhang, Hao Fu, Pei Liu, Cynthia Wang, Yan Zhang, Turab Lookman, Haiyou Huang, Yanjing Su
Read original paper ↗ ·