Papers citing A property-oriented design strategy for high performance copper alloys via machine learning
The influences of Cr and Mn on the strength, electrical conductivity, and stress relaxation properties of Cu-Ni-Si-Co-Mg alloys
Materials Today Communications · 2024
Jiang Feng, Yanmin Zhang, Yanjun Zhou, Shiheng Zhao, Yunqi Shan, Yaopeng Yang, Kexing Song
Read original paper ↗ ·Machine Learning in Solid‐State Hydrogen Storage Materials: Challenges and Perspectives
Advanced Materials · 2024
Panpan Zhou, Qianwen Zhou, Xuezhang Xiao, Xiulin Fan, Yongjin Zou, Lixian Sun, Jinghua Jiang, Dan Song, Lixin Chen
Read original paper ↗ ·Machine Learning for the Design of High Entropy Alloys: A Review
World Scientific Annual Review of Functional Materials · 2025
Si Rong Ng, Verner Soh, Zhongji Sun, Pei Wang, Chee Koon Ng
Read original paper ↗ ·Machine Learning-Based Methods for Materials Inverse Design: A Review
Computers, materials & continua/Computers, materials & continua (Print) · 2025
Yingli Liu, Yuting Cui, Haihe Zhou, Tao Shen, Sheng Lei, Haibin Yuan, Jiancheng Yin
Read original paper ↗ ·Predictor−corrector inverse design scheme for property−composition prediction of amorphous alloys
Transactions of Nonferrous Metals Society of China · 2025
Tao LONG, Zhilin Long, Bo Pang
Read original paper ↗ ·Developing softening-resistant Cu-Cr alloys and understanding their mechanisms via mechanism-informed interpretable machine learning
Journal of Material Science and Technology · 2025
Muzhi Ma, Zhou Li, Yuyuan Zhao, Shen Gong, Qian Lei, Yanlin Jia, Wenting Qiu, Zhu Xiao, Yanbin Jiang, Xiandong Xu, Biaobiao Yang, Chenying Shi
Read original paper ↗ ·Quantifying the effects of cooling rates on Fe-rich intermetallics in recycled Al-Si-Cu alloys by machine learning
Journal of Alloys and Compounds · 2025
Quan Li, Junsheng Wang, Chengpeng Xue, Yisheng Miao, Qinghuai Hou, Yanan Meng, Xinghai Yang, Xingxing Li
Read original paper ↗ ·Green development of molecularly imprinted polymers and the application in CO2 adsorption and separation: A review
Separation and Purification Technology · 2025
Weidong Guo, Junjie Xu, Zhongli Tang, Wenbing Li, Donghui Zhang
Read original paper ↗ ·Machine learning-enabled design of ferroelectrics with multiple properties via a Landau model
Acta Materialia · 2025
Ruihao Yuan, Bo Wang, Jinshan Li, Peng Sun, Zhen Liu, Xiangdong Ding, Dezhen Xue, Turab Lookman
Read original paper ↗ ·A dual-drive design strategy integrating knowledge and data for ternary precipitate-strengthened copper alloys
Materials Science and Engineering A · 2025
Feng Zhao, Xing Wen, Liuyi Huang, Guohuan Bao, Jiabin Liu, Huadong Fu, Yang Yan Lu, Youtong Fang, Wei Yang
Read original paper ↗ ·Design of high strength and ductile recycled Al alloys by machine learning
Materials Today Communications · 2025
Quan Li, Junsheng Wang, Chengpeng Xue, Yisheng Miao, Qinghuai Hou, Yanan Meng, Xinghai Yang, Xingxing Li
Read original paper ↗ ·Advanced deep learning framework for multi-scale prediction of mechanical properties from microstructural features in polycrystalline materials
Computer Methods in Applied Mechanics and Engineering · 2025
Zihao Gao, Changsheng Zhu, Canglong Wang, Yafeng Shu, Shuo Liu, Jintao Miao, Lei Yang
Read original paper ↗ ·Metaheuristics Algorithm-Based Optimization for High Conductivity and Hardness CuNi2Si1 Alloy
Materials · 2025
J. Konieczny, K. Labisz, Satılmış Ürgün, Halil Yiğit, Sinan Fi̇dan, Mustafa Özgür Bora, Ş. Hakan Atapek
Read original paper ↗ ·Machine learning-assisted prediction of mechanical properties in WC-based composites with multicomponent alloy binders
Composites Part B Engineering · 2025
Hui Ren, Kaiyue Wang, Kai Xu, Ming Lou, Gaohui Kan, Qingtao Jia, Changheng Li, Xuelian Xiao, Keke Chang
Read original paper ↗ ·Molecular dynamics and machine learning study of tensile behavior in single-crystal tungsten containing He bubbles
Materials & Design · 2025
Pan-dong Lin, Yan Lin, Hongguang Li, Shu-gang Cui, Jun-feng Nie, Bai-wen Zhong, Yu‐peng Lu
Read original paper ↗ ·Accelerated discovery of near-zero ablation ultra-high temperature ceramics via GAN-enhanced directionally constrained active learning
Advanced Powder Materials · 2025
Wenjian Guo, Fayuan Li, Lingyu Wang, Li’an Zhu, Yicong Ye, Zhen Wang, Bin Yang, Shifeng Zhang, Shuxin Bai
Read original paper ↗ ·Machine learning-driven design of rare metal doped niobium alloys with enhanced strength and ductility
Journal of Materials Research and Technology · 2025
Zhenqiang Xiong, ZhaoKun Song, Jianwei Li, Heran Wang, Xiaoxin Zhang, Bin Liang, Dong Wang
Read original paper ↗ ·Accelerated development of high-strength and high-conductivity Cu-Cr-Ti alloys based on data-driven design and experimental validation
Materials & Design · 2025
Feng Li, Jiangnan Li, Qiong Lu, Yuanqi You, Zunyan Xu, Liyuan Liu, Li Fu, Gao Peng, Jianhong Yi, Caiju Li
Read original paper ↗ ·Bayesian optimization and explainable machine learning for High-dimensional multi-objective optimization of biodegradable magnesium alloys
Journal of Material Science and Technology · 2025
Peng Peng, Chunyi Peng, Fuguo Liu, Shuai Long, Cheng Zhang, Ai Tao Tang, Jia She, Jianyue Zhang, Fusheng Pan
Read original paper ↗ ·Design of high‐performance Cu–Be alloy based on machine learning with integrated phase diagram information
Rare Metals · 2025
Wei Chen, Yanbin Jiang, Fei Tan, Zi‐Xuan Zhao, Muzhi Ma, Meng Wang, Xiaoyu Jiang, Yi‐Wei Qin, Qian Lei, Zhou Li
Read original paper ↗ ·AI‐Driven TENGs for Self‐Powered Smart Sensors and Intelligent Devices
Advanced Science · 2025
Aiswarya Baburaj, Syamini Jayadevan, Akshaya Kumar Aliyana, S. K. Naveen Kumar, George K. Stylios
Read original paper ↗ ·Innovative design of Ag-based braze alloy and composites for dissimilar joints: Strategies and prospects
Journal of Material Science and Technology · 2025
Zongye Ding, Junchao Yang, Guan Huang, Yongtao Jiu, Weimin Long, Sujuan Zhong, Jian Ping Qin, Quanbin Lu, Hao Guo, Jianguo Li, Qiaodan Hu
Read original paper ↗ ·Explainable AI and Feature Engineering for Machine-Learning-Driven Predictions of the Properties of Cu-Cr-Zr Alloys: A Hyperparameter Tuning and Model Stacking Approach
Processes · 2025
Mohammed A. Atiea, Reham Reda, Sabbah Ataya, Mervat Mohamed Ibrahim
Read original paper ↗ ·Data–Driven Stress Prediction and Microstructure Characterization During Hot Deformation of Al–Zn–Mg–Cu Alloys
Metals and Materials International · 2025
Min Bai, Xiaodong Wu, Lingfei Cao, Songbai Tang, Youcai Qiu, Ying Zhou, Xiaomin Lin, Zhenghao Zhang
Read original paper ↗ ·Interpretable Machine Learning Applications: A Promising Prospect of AI for Materials
Advanced Functional Materials · 2025
Xue Feng Jiang, Huadong Fu, Yang Bai, Lei Jiang, Hongtao Zhang, Weiren Wang, Peiwen Yun, Jingjin He, Dezhen Xue, Turab Lookman, Yanjing Su, Jianxin Xie
Read original paper ↗ ·PCS: Property-composition-structure chain in Mg-Nd alloys through integrating sigmoid fitting and conditional generative adversarial network modeling
Scripta Materialia · 2025
Xu Qin, Qinghang Wang, Xinqian Zhao, Shouxin Xia, Li Wang, Yuhui Zhang, Chao He, Daolun L. Chen, Bin Jiang
Read original paper ↗ ·Design of superalloys with multiple properties via multi-task learning
Acta Materialia · 2025
Weiren Wang, Xue Feng Jiang, Wenyao Li, Chi Zhang, Pei Liu, Shaohan Tian, Turab Lookman, Yanjing Su
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
Shuang Zhou, Qian Lei, Jie Yin, Xiang Yan, Xiukuang Zhang, Wenwen Liu
Read original paper ↗ ·Machine learning-driven optimization of wear-resistant high-manganese steel properties: achieving multi-property matching under specified composition
Journal of Materials Science · 2025
Ruizhi Han, Shuai Zhao, Rong Mu, Renbo Song
Read original paper ↗ ·A phase prediction strategy of high entropy alloys manufactured by selective laser melting based on feature selection and machine learning
Journal of Materials Research and Technology · 2025
Donghui Chen, Jia-Xing Guo, Liang Guo, Xiaojun Tan, Yi Ba, Lei Zhang, Qingmao Zhang
Read original paper ↗ ·Novel machine learning driven design strategy for high strength Zn Alloys optimization with multiple constraints
npj Computational Materials · 2025
Chun-zhi Pan, Wenwen Lin, Jianxing Zhou, Wei Jian, Ka Chun Chan, Yuk Lun Chan, Lu Ren
Read original paper ↗ ·A Review of Intelligent Design and Optimization of Metal Casting Processes
Acta Metallurgica Sinica (English Letters) · 2025
Xiaolong Pei, Hua Hou, Yuhong Zhao
Read original paper ↗ ·AI assisted design of high thermal conductivity Al-Fe-Ni-Mg alloys
Journal of Alloys and Compounds · 2025
Quan Li, Junsheng Wang, Mohamed Suleiman Ziadi, Yisheng Miao, Xuelong Wu, Qinghuai Hou, Xinghai Yang, Zhongyao Li, Yanxiang Li
Read original paper ↗ ·Machine learning for obtaining values of thermomechanical processing parameters of high-entropy alloys with desirable strength and ductility
Intermetallics · 2025
Zolfaghar Ali Akhlaghi, Hamed Shahmir, Ahmad R. Sharafat
Read original paper ↗ ·Intelligent Design and Simulation of High-Entropy Alloys via Machine Learning and Multiobjective Optimization Algorithms
Journal of Chemical Theory and Computation · 2025
Jian Zhong Cao, Zian Chen, Haichao Li, Chang Liu, Yutong He, Hongbin Zhang, Lina Xu, Hong‐Ping Xiao, Xiao Dong He, Guoyong Fang
Read original paper ↗ ·Absorbent material composition prediction based on multi-objective regression with value stacking and selection
Frontiers in Materials · 2025
Shi He, Jiaying Chen, Kai Huang, Jian Mao, Kexun Li, Taikang Liu
Read original paper ↗ ·Reverse design of Mg-Zn-Mn-Sr-Ca alloys for biodegradable implants by interpretable machine learning and genetic algorithm
Materials & Design · 2025
Joung Sik Suh, Jae Hoon Jang, Byeong‐Chan Suh, Jae‐Yeon Kim
Read original paper ↗ ·Rapid design of processing parameters for Zero-Sample alloys via multi-acquisition-function Bayesian optimization
Materials Science and Engineering A · 2025
Jingtai Sun, Huadong Fu, Hongtao Zhang, Menghe Zhao, Peiwen Yun, Jianxin Xie
Read original paper ↗ ·Machine learning assisted design of CrTaTiV-based refractory high entropy alloys with enhanced hardness
International Journal of Refractory Metals and Hard Materials · 2025
Liang Li, Shu Wang, Su Chen, Shengfeng Guo
Read original paper ↗ ·Composition design and process optimization of refractory boride coatings based on high-throughput preparation and machine learning
Journal of Materials Science · 2025
Binyuan Jia, Wenhui Ma, Qiang Wan, Cai Lu, Qiwen Wei, Bing Yang, Yangyi Xiao
Read original paper ↗ ·Enhanced stress relaxation resistance of Cu–Ni–Si alloy strips through Sn addition and pre-aging treatment
Journal of Materials Research and Technology · 2025
Jiahao Wang, Jinming Hu, Qiang Hu, Mingxue Shen, Bo Guan, Dan Wu, Jing Kun Xu, Jin Liu, Guojie Huang, Xueqing Zheng
Read original paper ↗ ·The Atomic Structure of Copper: Understanding Its Properties
IntechOpen eBooks · 2025
Irfan Toqeer, Muhammad Afzaal, Muhammad Faisal Iqbal, Abdul Ghuffar
Read original paper ↗ ·Review: Recent progress in titanium alloys development via machine learning and high-throughput preparation
Journal of Materials Science · 2025
Feiyang Gao, Weiwen Zhang, Xiaotao Liu, Xuan Luo, Zhi Wang, Ning Li, L.H. Liu
Read original paper ↗ ·A machine learning based inverse design method for high-performance copper alloys
Materials Today Communications · 2025
Yingli Liu, Yuting Cui, Jiancheng Yin, Haihe Zhou
Read original paper ↗ ·A new multi-objective optimization design framework for high-temperature alloy steel via machine learning
Materials Today Communications · 2025
Cun Chen, Dandan Zang, Jingli Ren
Read original paper ↗ ·Reverse design of copper alloy composition based on ensemble learning and genetic algorithm
Journal of materials research/Pratt's guide to venture capital sources · 2025
Li Wang, Fuxin Lu, Shunhu Zhang, Lei Zhang, Yecheng Ruan
Read original paper ↗ ·Data-driven multi-process modeling and integrated design strategy for complex high-performance alloys
Acta Materialia · 2025
Hongtao Zhang, Huadong Fu, Jingtai Sun, Lei Jiang, Shuaicheng Zhu, Jianxin Xie
Read original paper ↗ ·Development of a Machine Learning-Based Incremental Model for Achieving Property-Variation-Driven Composition Design of Cu-Ni-Si Alloys
Journal of Materials Engineering and Performance · 2025
Li Wang, Fuxin Lu, Shun Hu Zhang, Zhiqiang Qiu, Lei Zhang
Read original paper ↗ ·Data-driven optimization strategy for the mechanical properties of ZM5 alloy
Journal of Alloys and Compounds · 2025
Ming Ji, Yongmei Zhang, Xiaolong Pei, Yuhong Zhao, Gaolong Zhang, Hua Hou
Read original paper ↗ ·Machine-learning-driven synergistic optimization of multi-objective mechanical properties in steel materials
Journal of Intelligent Manufacturing · 2025
F. Lan, Jian-hua Liu, Yang He, Jian Shao, Min Xiao, Lin Zhang, Shuai Zhang, Feng Xu, Xiao-tian Duan
Read original paper ↗ ·