Papers citing Machine learning assisted design of high entropy alloys with desired property
Microstructures and Properties of High‐Entropy Materials: Modeling, Simulation, and Experiments
Advanced Engineering Materials · 2020
Jia Li, Qihong Fang, Peter Kaehuei Liaw
Read original paper ↗ ·Emerging materials intelligence ecosystems propelled by machine learning
Nature Reviews Materials · 2020
Rohit Batra, Le Song, Rampi Ramprasad
Read original paper ↗ ·Improvement of the machine learning-based corrosion rate prediction model through the optimization of input features
Materials & Design · 2020
Yupeng Diao, Luchun Yan, Kewei Gao
Read original paper ↗ ·Yield strength prediction of high-entropy alloys using machine learning
Materials Today Communications · 2020
Uttam Bhandari, Md. Rumman Rafi, Congyan Zhang, Shizhong Yang
Read original paper ↗ ·Prediction of Equilibrium Phase, Stability and Stress-Strain Properties in Co-Cr-Fe-Ni-Al High Entropy Alloys Using Artificial Neural Networks
Metals · 2020
Nicolae Filipoiu, George Alexandru Nemneş
Read original paper ↗ ·Alloy design and properties optimization of multi-component alloy based on solidification characteristics
Materials Science and Engineering A · 2020
Ling Qiao, Aorigele Bao, Zhonghong Lai, Yong Liu, Jingchuan Zhu, Yuan Wang
Read original paper ↗ ·Navigating the Complex Compositional Landscape of High-Entropy Alloys
arXiv (Cornell University) · 2020
Qi, Jie, Andrew M. Cheung, S. J. Poon
Read original paper ↗ ·Generalized small set of ordered structures method for the solid-solution phase of high-entropy alloys
Physical review. B./Physical review. B · 2020
V. Sorkin, Teck Leong Tan, Zhi Gen Yu, Yong‐Wei Zhang
Read original paper ↗ ·The Earth Mover’s Distance as a Metric for the Space of Inorganic Compositions
Chemistry of Materials · 2020
Cameron J. Hargreaves, Matthew Stephen Dyer, Michael W. Gaultois, Vitaliy A. Kurlin, Matthew J. Rosseinsky
Read original paper ↗ ·Expanded dataset of mechanical properties and observed phases of multi-principal element alloys
Scientific Data · 2020
Christopher K. H. Borg, Carolina Frey, Jasper Moh, Tresa M. Pollock, Stéphane Gorsse, Daniel B. Miracle, Oleg N. Senkov, Bryce Meredig, James E. Saal
Read original paper ↗ ·Interpretable machine-learning strategy for soft-magnetic property and thermal stability in Fe-based metallic glasses
npj Computational Materials · 2020
Zhichao Lu, Zhichao Lu, Xin Chen, De-Ye Lin, Deye Lin, Yuan Wu, Yibo Zhang, Hui Wang, Suihe Jiang, Hongxiang Li, Xianzhen Wang, Zhaoping Lü, Zhaoping Lü
Read original paper ↗ ·Composition rules of Ni-base single crystal superalloys and its influence on creep properties via a cluster formula approach
Scientific Reports · 2020
Chen Chen, Qing Wang, Chuang Dong, Yu Zhang, Honggang Dong
Read original paper ↗ ·Contribution à la conception computationnelle d'alliages de titane ou à haute entropie : prédiction de l'occurrence de la transformation martensitique de trempe ou de déformation
Venue not supplied by source · 2020
Madeleine Bignon
Read original paper ↗ ·Machine learning strategies for high-entropy alloys
Journal of Applied Physics · 2020
Jeffrey M. Rickman, Ganesh Balasubramanian, Christopher J. Marvel, Helen M. Chan, M.-T. Burton
Read original paper ↗ ·Développement et étude d'alliages réfractaires complexes, à microstructure cubique centrée et orthorhombique, pour des applications aéronautiques
Venue not supplied by source · 2020
Antoine Lacour-Gogny-Goubert
Read original paper ↗ ·Artificial intelligence and machine learning in design of mechanical materials
Materials Horizons · 2020
Kai Guo, Zhenze Yang, Chi‐Hua Yu, Markus J. Buehler
Read original paper ↗ ·Investigating the efficacy of machine learning tools in modeling the continuous stabilization and carbonization process and predicting carbon fiber properties
Carbon · 2020
Narayan Shirolkar, Prachi Patwardhan, Aowabin Rahman, Ashley D. Spear, Satish Kumar
Read original paper ↗ ·Machine learning-based prediction of phases in high-entropy alloys
Computational Materials Science · 2020
Ronald Machaka
Read original paper ↗ ·Investigating Active Learning and Meta-Learning for Iterative Peptide Design
Journal of Chemical Information and Modeling · 2020
Rainier Barrett, Andrew Dickson White
Read original paper ↗ ·A data-driven approach to predicting band gap, excitation, and emission energies for Eu 2+ -activated phosphors
Inorganic Chemistry Frontiers · 2021
Chaewon Park, Jin-Woong Lee, Minseuk Kim, Byung Do Lee, Satendra Pal Singh, Woon Bae Park, Kee‐Sun Sohn
Read original paper ↗ ·A High Stability B2-Containing Refractory Multi-Principal Element Alloy
Acta Materialia · 2021
Carolina Frey, Ravit Silverstein, Tresa M. Pollock
Read original paper ↗ ·A Personal Perspective on the Discovery and Significance of Multicomponent High-Entropy Alloys
Springer eBooks · 2021
Brian Cantor
Read original paper ↗ ·A property-oriented adaptive design framework for rapid discovery of energetic molecules based on small-scale labeled datasets
RSC Advances · 2021
Yunhao Xie, Yijing Liu, Renling Hu, Xu Lin, Jing Hu, Xuemei Pu
Read original paper ↗ ·Boosting for concept design of casting aluminum alloys driven by combining computational thermodynamics and machine learning techniques
Journal of Materials Informatics · 2021
Yi Wang, Guangchen Liu, Jianbao Gao, Lijun Zhang
Read original paper ↗ ·Generative deep learning as a tool for inverse design of high entropy refractory alloys
Journal of Materials Informatics · 2021
Arindam Debnath, Adam M. Krajewski, Hui Sun, Shuang Lin, Marcia Ahn, Wenjie Li, Shanshank Priya, Jogender Singh, Shun‐Li Shang, Allison M. Beese, Zi‐Kui Liu, Wesley F. Reinhart
Read original paper ↗ ·Harnessing the Complex Compositional Space of High-Entropy Alloys
Springer eBooks · 2021
S. J. Poon, Jie Qi, Andrew M. Cheung
Read original paper ↗ ·High-entropy energy materials: challenges and new opportunities
Energy & Environmental Science · 2021
Yanjiao Ma, Yanjiao Ma, Yuan Ma, Yuan Ma, Qingsong Wang, Simon Schweidler, Miriam Botros, Tongtong Fu, Horst Hahn, Torsten Brezesinski, Ben Breitung
Read original paper ↗ ·Machine Learning and Data Analytics for Design and Manufacturing of High-Entropy Materials Exhibiting Mechanical or Fatigue Properties of Interest
Springer eBooks · 2021
Baldur Steingrimsson, Xuesong Fan, Anand P. Kulkarni, Michael C. Gao, Peter Kaehuei Liaw
Read original paper ↗ ·Machine Learning Assisted Composition Effective Design for Precipitation Strengthened Copper Alloys
Acta Materialia · 2021
Hongtao Zhang, Huadong Fu, Shuaicheng Zhu, Wei Yong, Jianxin Xie
Read original paper ↗ ·Machine Learning for High-Entropy Alloys
Springer series in materials science · 2021
Shuai Chen, Yuan Cheng, Huajian Gao
Read original paper ↗ ·Mechanical Behavior of High-Entropy Alloys: A Review
Springer eBooks · 2021
Yuanyuan Shang, Jamieson M. Brechtl, Claudio Pistidda, Peter Kaehuei Liaw
Read original paper ↗ ·Phase Prediction of Multi-principal Element Alloys Using Support Vector Machine and Bayesian Optimization
Lecture notes in computer science · 2021
Nguyen Hai Chau, Masatoshi Kubo, Le Viet Hai, Tomoyuki Yamamoto
Read original paper ↗ ·Deep Learning-Based Hardness Prediction of Novel Refractory High-Entropy Alloys with Experimental Validation
Crystals · 2021
Uttam Bhandari, Congyan Zhang, Congyuan Zeng, Shengmin Guo, Aashish Adhikari, Shizhong Yang
Read original paper ↗ ·Machine Learning Approach to Design High Entropy Alloys with Heterogeneous Grain Structures
Metallurgical and Materials Transactions A · 2021
Li Li, Baobin Xie, Qihong Fang, Jia Li
Read original paper ↗ ·Mechanical behavior of high-entropy alloys
Progress in Materials Science · 2021
Weidong Li, Di Xie, Dongyue Li, Yong Zhang, Yanfei Gao, Peter Kaehuei Liaw
Read original paper ↗ ·Efficient estimation of material property curves and surfaces via active learning
Physical Review Materials · 2021
Yuan Tian, Dezhen Xue, Ruihao Yuan, Yumei Zhou, Xiangdong Ding, Jun Sun, Turab Lookman
Read original paper ↗ ·Accelerated Development of High-Strength Magnesium Alloys by Machine Learning
Metallurgical and Materials Transactions A · 2021
Yanwei Liu, Leyun Wang, Huan Zhang, Gaoming Zhu, Jie Wang, Yuhui Zhang, Xiaoqin Zeng
Read original paper ↗ ·A general and transferable deep learning framework for predicting phase formation in materials
npj Computational Materials · 2021
Shuo Feng, Huadong Fu, Huiyu Zhou, Yuan Wu, Zhaoping Lü, Hongbiao Dong
Read original paper ↗ ·Machine learning guided automatic recognition of crystal boundaries in bainitic/martensitic alloy and relationship between boundary types and ductile-to-brittle transition behavior
Journal of Material Science and Technology · 2021
Xiaorui Li, Jingxiao Zhao, J.H. Cong, R.D.K. Misra, Xiaoya Wang, X.L Wang, Chengjia Shang
Read original paper ↗ ·Revealing high-fidelity phase selection rules for high entropy alloys: A combined CALPHAD and machine learning study
Materials & Design · 2021
Yingzhi Zeng, Mengren Man, Kewu Bai, Yongwei Zhang
Read original paper ↗ ·Mechanical and thermodynamic data-driven design of Al-Co-Cr-Fe-Ni multi-principal element alloys
Materials Today Communications · 2021
Yuchen Liu, Shao-yu Yen, Shun-hsiang Chu, Shih‐kang Lin, Ming‐Hung Tsai
Read original paper ↗ ·Accelerated crystal structure prediction of multi-elements random alloy using expandable features
Scientific Reports · 2021
Taewon Jin, Ina Park, Taesu Park, Jaesik Park, Ji Hoon Shim
Read original paper ↗ ·Machine learning prediction of magnetic properties of Fe-based metallic glasses considering local structures
arXiv (Cornell University) · 2021
Xin Li, Guangcun Shan, C.H. Shek
Read original paper ↗ ·Machine learning of phases and mechanical properties in complex concentrated alloys
Journal of Material Science and Technology · 2021
Jie Xiong, San‐Qiang Shi, Tong‐Yi Zhang
Read original paper ↗ ·Discovery of marageing steels: machine learning vs. physical metallurgical modelling
Journal of Material Science and Technology · 2021
Chunguang Shen, Chenchong Wang, Pedro E.J. Rivera-Díaz-del-Castillo, Dake Xu, Qian Zhang, Chi Zhang, Wei Xu
Read original paper ↗ ·Modelling and optimization of microhardness of electroless Ni–P–TiO2 composite coating based on machine learning approaches and RSM
Journal of Materials Research and Technology · 2021
Imtiaz Ahmed Shozib, Azlan Ahmad, Md Shokor A. Rahaman, Ahmad Majdi Abdul-Rani, Mohammad Azad Alam, Mohammadali Beheshti, Iqbal Taufiqurrahman
Read original paper ↗ ·Efficient sampling for decision making in materials discovery*
Chinese Physics B · 2021
Yuan Tian, Turab Lookman, Dezhen Xue
Read original paper ↗ ·Predictive descriptors in machine learning and data-enabled explorations of high-entropy alloys
Computational Materials Science · 2021
Ankit Roy, Ganesh Balasubramanian
Read original paper ↗ ·Machine learning for design, phase transformation and mechanical properties of alloys
Progress in Materials Science · 2021
J.F. Durodola
Read original paper ↗ ·A perspective on corrosion of multi-principal element alloys
npj Materials Degradation · 2021
N. Birbilis, Sanjay Choudhary, John R. Scully, Mitra L. Taheri
Read original paper ↗ ·