Papers citing A general and transferable deep learning framework for predicting phase formation in materials
Transfer Learning Across Materials Classes: Conceptual Boundaries of Reusability
Journal of Computational and Data-Driven Materials Engineering · 2024-01-01
Lucas Meyer, Stefan Braun, Anna Schmid
Read original paper ↗ ·Structure-aware graph neural network based deep transfer learning framework for enhanced predictive analytics on diverse materials datasets
npj Computational Materials · 2024-01-02
Vishu Gupta, Kamal Kumar Choudhary, Brian DeCost, Francesca Tavazza, Carelyn E. Campbell, Wei‐keng Liao, Alok Choudhary, Ankit Agrawal
Read original paper ↗ ·Deep learning-based prediction of saturation magnetic flux density in Fe-based metallic glasses via transfer learning
Materials Chemistry and Physics · 2024-02-15
Chunghee Nam
Read original paper ↗ ·Deep learning based on small sample dataset: prediction of dielectric properties of SrTiO 3 -type perovskite with doping modification
Royal Society Open Science · 2024-05-01
Quan Luo, Hua Hao, Hanxing Liu
Read original paper ↗ ·Machine learning-enabled prediction of high-temperature oxidation resistance for Ni-based alloys
Corrosion Science · 2024-05-18
Changheng Li, Kai Xu, Ming Lou, Linjing Wang, Keke Chang
Read original paper ↗ ·Addressing the Accuracy-Cost Trade-off in Material Property Prediction Using a Teacher-Student Strategy
Journal of Chemical Theory and Computation · 2024-06-14
D D Zhu, Zhikuang Xin, Siming Zheng, Yangang Wang, Xiaoyu Yang
Read original paper ↗ ·Comparative Study on Different CNN Architectures Developed on Microstructural Classification in Al-Si Alloys
Archives of Metallurgy and Materials · 2024-06-21
Mahmut Furkan Kalkan, Mehmet Aladağ, Krzysztof Jan Kurzydłowski, Necip Fazıl Yilmaz, Abdulcabbar Yavuz
Read original paper ↗ ·Machine learning studies for magnetic compositionally complex alloys: A critical review
Progress in Materials Science · 2024-06-26
Xin Li, C.H. Shek, Peter Kaehuei Liaw, Guangcun Shan
Read original paper ↗ ·Machine-learning-assisted analysis of highly transient X-ray imaging sequences of weld pools
Philosophical Magazine Letters · 2024-08-13
Fan Wu, Juzheng Zhang, Ken Vidar Falch, Wajira U. Mirihanage
Read original paper ↗ ·A Review on the Application of Superalloys Composition, Microstructure, Processing, and Performance via Machine Learning
JOM · 2024-10-10
Junhui Zhang, Haiyan Gao, Yahui Liu, Jun Wang
Read original paper ↗ ·LSTM-based framework for predicting point defect percentage in semiconductor materials using simulated XRD patterns
Scientific Reports · 2024-10-17
Mehran Motamedi, Reza Shidpour, Mehdi Ezoji
Read original paper ↗ ·Influence of Al and Ti Alloying and Annealing on the Microstructure and Compressive Properties of Cr-Fe-Ni Multi-Principal Element Alloy
Metals · 2024-10-26
Keyan An, Tailin Yang, Junjie Feng, Honglian Deng, Xiang Zhang, Zeyu Zhao, Qingkun Meng, Jiqiu Qi, Fuxiang Wei, Yanwei Sui
Read original paper ↗ ·Data-driven inverse design of MoNbTiVWZr refractory multicomponent alloys: Microstructure and mechanical properties
Materials Science and Engineering A · 2024-10-30
Lavanya Raman, Arindam Debnath, Erik T. Furton, Shuang Lin, Adam M. Krajewski, Subrata Ghosh, Na Liu, Marcia Ahn, Bed Poudel, Shun‐Li Shang, Shashank Priya, Zi‐Kui Liu, Allison M. Beese, Wesley F. Reinhart, Wenjie Li
Read original paper ↗ ·Intelligent Nanomaterial Image Characterizations – A Comprehensive Review on AI Techniques that Power the Present and Drive the Future of Nanoscience
Advanced Theory and Simulations · 2024-10-30
Umapathi Krishnamoorthy, Sukanya Balasubramani
Read original paper ↗ ·Advances in smart cities with system integration and energy digitalization technologies: A state-of-the-art review
Sustainable Energy Technologies and Assessments · 2024-11-16
Jiashu Kong, Yitong Dong, Z F Zhang, Pow‐Seng Yap, Yuekuan Zhou
Read original paper ↗ ·A Multi-Fidelity Learning Framework for High-Entropy Alloy Design with Sparse DFT and Abundant CALPHAD Data
Journal of Computational and Data-Driven Materials Engineering · 2025-01-01
Elena Petrova, Ivan Georgiev, Nikolay Stoyanov, Petar Kolev
Read original paper ↗ ·Applications of machine learning in high-entropy alloys: a review of recent advances in design, discovery, and characterization
Nanoscale · 2025-01-01
Mohammad Hossein Golbabaei, Mohammad Zohrevand, Ning Zhang
Read original paper ↗ ·Cluster expansion augmented transfer learning for property prediction of high-entropy alloys
Journal of Materials Chemistry C · 2025-01-01
Zimo Li, Nguyen-Dung Tran, Yibo Sun, Yuhang Lu, Cong Hou, Ying Chen, Jun Ni
Read original paper ↗ ·Harnessing the leading edge: machine learning ventures in chemistry and materials science
Physical Chemistry Chemical Physics · 2025-01-01
Yuheng Li, Fengming Guo, Shui‐Yang Lien, Abd. Rashid bin Mohd Yusoff, Zhihong Zheng, Jingyun Zhang, Peng Fei Gao
Read original paper ↗ ·Machine Learning Algorithms for Applications in Materials Science I
Challenges and advances in computational chemistry and physics · 2025-01-01
Azizeh Abdolmaleki, Fereshteh Shiri, Shahin Ahmadi
Read original paper ↗ ·Toward super-clean bearing steel by a novel physical-data integrated design strategy
Materials & Design · 2025-01-15
Jian Guan, Guolei Liu, Wenguang Hu, Hongwei Liu, Paixian Fu, Yanfei Cao, Dong-Rong Liu, Dianzhong Li
Read original paper ↗ ·Enhancing material property prediction via a dual stream model fusing spatial and topological information
Computational Materials Science · 2025-01-30
Jiangnan Xie, Xiaolong Zheng, Zhihua Ying, Hui Zheng, Liang Zheng
Read original paper ↗ ·A catalogue of metallic glass-forming alloy systems
Materialia · 2025-02-15
Weijie Xie, Mingxing Li, Yitao Sun, Chao Wang, Liwei Hu, Yanhui Liu
Read original paper ↗ ·Machine Learning-Based Computational Design Methods for High-Entropy Alloys
High Entropy Alloys & Materials · 2025-03-01
Yan Ming Zhao, J. Y. Zhang, Peter Kaehuei Liaw, Tao Yang
Read original paper ↗ ·Application of Machine Learning in Amorphous Alloys
Materials · 2025-04-13
Like Zhang, Huangyou Zhang, Boyan Ji, Leqing Liu, Xianlan Liu, Ding Chen
Read original paper ↗ ·Design of BCC/FCC dual-solid solution refractory high-entropy alloys through CALPHAD, machine learning and experimental methods
npj Computational Materials · 2025-04-20
Longjun He, Chaoyue Wang, Mina Zhang, Jinghao Li, T. L. Chen, Xianglin Zhou
Read original paper ↗ ·Metallic glass roadmap
Materials Futures · 2025-04-23
Weihua Wang, Rui Zhao, Rong Han, Ying-Hui Shang, Yong Gang Yang, Songling Liu, Shiyun Zhang, Yuan‐Chao Hu, Yitao Sun, Ming-Xing Li, Lingxiang Shi, Ke-Fu Yao, Jiang Ma, Haibo Ke, Yong Zhao, Bo Zhang, Xin Tong, H. Y. Bai, Sinan Liu, Hai‐Bin Yu, Si Lan, Qi Cheng, Jihan Zhou, Heng Kang, Pengfei Guan, Zhenwei Wu, Huaping Zhang, Peng Luo, Laiquan Shen, Hai‐Bin Yu, Si Meng, Zheng Wang, Hailong Peng, Shuai Ren, Yu Tong, Lijian Song, Juntao Huo, Junqiang Wang, Jing-Li Ren, Peng Wang, Maozhi Li, Bei-Bei Fan, Bo Huang, Jun Yi, Xilei Bian, Qing Wang, Gang Wang, Minqiang Jiang, Yin-Xiao Wang, Zhengwang Zhu, Haifeng Zhang, Chuan-Kun Zhou, Ming Liu, Shaofan Zhao, Jing Zhou, Xuesong Li, Baoan Sun, Zhen Lu, Shu-Jie Pang, Hu-Yang Li, Huaijun Lin, Ji Wang, X S Wang, Yuhan Shen, Cheng-Rong Cao, B.Z. Tang, Peng Yu
Read original paper ↗ ·Multi-attribute-physical-law-informed transfer learning to design high-entropy Elinvar alloys
Materials Science and Engineering A · 2025-04-29
Lei Nie, Baobin Xie, Haiyu Wan, Bin Liu, Qihong Fang, Peter Kaehuei Liaw, Jia Li
Read original paper ↗ ·Machine Learning Inverse Prediction of Cu-Zn-Al Alloy’s Composition and Target Properties Using a Two-Way Feedback Structure on a Small Data Set
JOM · 2025-05-29
Shuang Zhou, Qian Lei, Jie Yin, Xiang Yan, Xiukuang Zhang, Wenwen Liu
Read original paper ↗ ·Phase classification of high entropy alloys with composition, common physical, elemental-property descriptors and periodic table representation
Transactions of Nonferrous Metals Society of China · 2025-06-01
Shuai LI, Shuai LI, Jia Yang, Shu LI, Shu LI, Dong-Rong Liu, Mingyu Zhang
Read original paper ↗ ·Composition Design and Property Prediction for AlCoCrCuFeNi High-Entropy Alloy Based on Machine Learning
Metals · 2025-06-30
Cuixia Liu, Meng Meng, Xian Luo
Read original paper ↗ ·Enhancing Machine Learning Potentials through Transfer Learning across Chemical Elements
Journal of Chemical Information and Modeling · 2025-07-07
Sebastien Röcken, Julija Zavadlav
Read original paper ↗ ·Computation- and process-based design for advanced structural high-entropy alloy development and analyses: A critical review
Progress in Materials Science · 2025-07-15
Zaigham Saeed Toor, Renhao Wu, Muhammad Raihan Hashmi, Jeong Ah Lee, Xiaoqing Li, Harada Yuji, Haiming Zhang, Hyoung Seop Kim
Read original paper ↗ ·Probing dendrite growth under microgravity via machine learning-aided multi-scale characterisation
Acta Materialia · 2025-10-22
Fan Wu, J. S. Mullen, Yangchao Deng, Shashidhara Marathe, Saranarayanan Ramachandran, Mert Çelikin, Andrew G. Murphy, Wim H. Sillekens, Wajira U. Mirihanage, David J. Browne
Read original paper ↗ ·A deep recurrent learning framework for predicting saturation magnetic flux density in Fe-based metallic glasses
Journal of Non-Crystalline Solids · 2025-11-27
Yi-Cheng Wu, Lei Yan, Chen-Bo Ma, Peng-Shuai Gao, Dong-Peng Wang
Read original paper ↗ ·Theoretical investigations on the activation of Silanes by rare-earth complexes: Mechanisms, bonding, and catalytic implications
Coordination Chemistry Reviews · 2026-02-03
Jiafeng Zhang, Xiaoxia Wu, Meirong Song, Laurent Maron
Read original paper ↗ ·Towards intelligent design of metallic glasses: a data-driven pathway for closing the theory-experiment loop
AI for Science · 2026-02-05
Huanrong Liu, Shan Zhang, Qingan Li, Bin Xu, Jian Li, Pengfei Guan
Read original paper ↗ ·A Comprehensive Review of the Computational Approaches for Structure–Property Prediction of High Entropy Materials
High Entropy Alloys & Materials · 2026-03-01
Suman Chabri, G. Anand
Read original paper ↗ ·Integrated machine-learning modelling for mechanical property prediction – A case study on laser-welded TC4 titanium alloy
Optics & Laser Technology · 2026-03-04
Shangpan Zhang, Rui Cao, Maryam Khaksar Ghalati, Hongbiao Dong, Yilin Wei
Read original paper ↗ ·From empirical rules to data-driven design of Al-based amorphous alloys
Journal of Alloys and Compounds · 2026-03-22
Xili liu, Jiahao Luo, Enhao Zhang, Enhao Zhang, Zhiyuan Jing, Wengang Bu, Jiamao Hao, Zhibin Zhang, Qiuzhi Gao, Xiubing Liang
Read original paper ↗ ·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
Read original paper ↗ ·A novel feature engineering method for high-performance and interpretable machine learning prediction of fatigue life in high-strength steel weld metal
Engineering Applications of Artificial Intelligence · 2026-07-04
Yilin Wei, Rui Cao, Shangpan Zhang, Jinge Lv, Hongbiao Dong
Read original paper ↗ ·Leveraging large language models to address data scarcity in machine learning for graphene synthesis
Diamond and Related Materials · 2026-07-17
Devi Dutta Biswajeet, Sara Kadkhodaei
Read original paper ↗ ·