Papers citing Cluster-formula-embedded machine learning for design of multicomponent β-Ti alloys with low Young’s modulus
A review on alloy design, biological response, and strengthening of β-titanium alloys as biomaterials
Materials Science and Engineering C · 2020
Sarabjeet Singh Sidhu, Harpreet Singh, Mohamed Abdel-Hady Gepreel
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 ↗ ·Application of Gradient Boosting Machine Learning Algorithms to Predict Uniaxial Compressive Strength of Soft Sedimentary Rocks at Thar Coalfield
Advances in Civil Engineering · 2021
Niaz Muhammad Shahani, Muhammad Kamran, Xigui Zheng, Cancan Liu, Xiaowei Guo
Read original paper ↗ ·Machine Learning for High-Entropy Alloys
Springer series in materials science · 2021
Shuai Chen, Yuan Cheng, Huajian Gao
Read original paper ↗ ·A CALPHAD-type Young's modulus database of Ti-rich Ti–Nb–Zr–Mo system
Calphad · 2021
Jinfeng Ling, Zhuhao Wen, Guiming Yang, Yao Wang, Weimin Chen
Read original paper ↗ ·High-throughput determination of the composition-dependent mechanical and diffusion properties in β Ti–Nb–Zr–Hf refractory alloys
Journal of Alloys and Compounds · 2021
Zhuhao Wen, Yongzhe Wang, Jinfeng Ling, Weimin Chen, Lijun Zhang, Yong Du
Read original paper ↗ ·A machine-learning-based alloy design platform that enables both forward and inverse predictions for thermo-mechanically controlled processed (TMCP) steel alloys
Scientific Reports · 2021
Jin-Woong Lee, Chaewon Park, Byung Do Lee, Joonseo Park, Nam Hoon Goo, Kee‐Sun Sohn
Read original paper ↗ ·Applications of artificial intelligence and machine learning in metal additive manufacturing
Journal of Physics Materials · 2021
Leila Jannesari Ladani
Read original paper ↗ ·Developing an XGBoost Regression Model for Predicting Young’s Modulus of Intact Sedimentary Rocks for the Stability of Surface and Subsurface Structures
Frontiers in Earth Science · 2021
Niaz Muhammad Shahani, Xigui Zheng, Cancan Liu, Fawad Ul Hassan, Peng Li
Read original paper ↗ ·Well-dispersed Li2CoTi3O8 nanoparticles as a multifunctional material for lithium-ion batteries and lithium-sulfur batteries
Journal of Alloys and Compounds · 2021
Mao Qian, Yakun Tang, Lang Liu, Yang Gao, Xiaohui Fiona Li
Read original paper ↗ ·XGBoost automates the characterisation of reversibly actuating planar-flow-casted NiTi shape memory alloy foil
Research Square · 2021
Ritaban Dutta, Cherry Chen, David Renshaw, Daniel Liang
Read original paper ↗ ·Computational intelligence based design of biomaterials
Computer Methods in Materials Science. · 2022
A. Vinoth, Shubhabrata Datta
Read original paper ↗ ·Construction of the Integrated “Material Design Theory and Application” Course Based on Academic Innovation
Advances in Education · 2022
清 王
Read original paper ↗ ·Machine-learning and high-throughput studies for high-entropy materials
Materials Science and Engineering R Reports · 2022
E‐Wen Huang, Wen‐Jay Lee, Sudhanshu Shekhar Singh, Poresh Kumar, Chih‐Yu Lee, Tu‐Ngoc Lam, Hsu-Hsuan Chin, Bi‐Hsuan Lin, Peter Kaehuei Liaw
Read original paper ↗ ·Machine Learning-Based Intelligent Prediction of Elastic Modulus of Rocks at Thar Coalfield
Sustainability · 2022
Niaz Muhammad Shahani, Xigui Zheng, Xiaowei Guo, Xin Wei
Read original paper ↗ ·New β-type Ti-Zr-V-Nb alloys used for laser-based direct energy deposition: Design, microstructure, and properties
Materials Characterization · 2022
Zisong Zhao, Cunshan Wang, Qun Yu, Lijun Song, Guang Yang, Jingtao Zhang
Read original paper ↗ ·Machine Learning Assisted Prediction of Microstructures and Young’s Modulus of Biomedical Multi-Component β-Ti Alloys
Metals · 2022
Xingjun Liu, Qinghua Peng, Shaobin Pan, Jingtao Du, Shuiyuan Yang, Jiajia Han, Yong Lu, Jinxin Yu, Cuiping Wang
Read original paper ↗ ·Neural Network Modeling of NiTiHf Shape Memory Alloy Transformation Temperatures
Journal of Materials Engineering and Performance · 2022
Hamid Reza Abedi, Keyvan Safaei Baghbaderani, Ala’aldin Alafaghani, Mohammadreza Nematollahi, Fatemeh Kordizadeh, Moataz M. Attallah, Ala Qattawi, Mohammad Elahinia
Read original paper ↗ ·Machine-learning-assisted discovery of empirical rule for inherent brittleness of full Heusler alloys
Journal of Material Science and Technology · 2022
Haoxuan Liu, Haile Yan, Nan Jia, Shuai Tang, Daoyong Cong, Bo Yang, Zongbin Li, Yudong Zhang, Claude Esling, Xiang Zhao, Liang Zuo
Read original paper ↗ ·Material machine learning for alloys: Applications, challenges and perspectives
Journal of Alloys and Compounds · 2022
Xiujuan Liu, Pengcheng Xu, Juanjuan Zhao, Wencong Lu, Minjie Li, Gang Wang
Read original paper ↗ ·Artificial intelligence automates the characterization of reversibly actuating planar-flow-casted NiTi shape memory alloy foil
PLoS ONE · 2022
Ritaban Dutta, Ling Chen, David Renshaw, Daniel Liang
Read original paper ↗ ·Machine learning assisted design of aluminum-lithium alloy with high specific modulus and specific strength
Materials & Design · 2022
Huiyu Li, Xiwu Li, Yanan Li, Wei Xiao, Kai Wen, Zhihui Li, Yongan Zhang, Baiqing Xiong
Read original paper ↗ ·Gaussian process regressions on hot deformation behaviors of FGH98 nickel-based powder superalloy
Journal of Material Science and Technology · 2022
Jie Xiong, Jianchao He, Xuesong Leng, Tong‐Yi Zhang
Read original paper ↗ ·Multi-objective optimization for high-performance Fe-based metallic glasses via machine learning approach
Journal of Alloys and Compounds · 2023
Yuxing Zhang, She-Juan Xie, Wei Peng Guo, Jun Cai Ding, Leong Hien Poh, Zhen-Dong Sha
Read original paper ↗ ·Novel Biomedical Ti-Based Alloys with Low Young’s Modulus: A First-Principles Study
Journal of Materials Engineering and Performance · 2023
Xinxin Yan, Wei Cao, Haohuan Li
Read original paper ↗ ·Deriving equation from data via knowledge discovery and machine learning: A study of Young’s modulus of Ti-Nb alloys
Computational Materials Science · 2023
Huiran Zhang, Xi Liu, Guangjie Zhang, Yuquan Zhu, Shengzhou Li, Quan Qian, Dongbo Dai, Renchao Che, Tao Xu
Read original paper ↗ ·NiTiHfX Shape Memory Alloy Actuation Strain Prediction
Research Square · 2023
Hossein Abedi, Ala Qattawi
Read original paper ↗ ·High-throughput exploration of composition-dependent elasto-plastic and diffusion properties of refractory multi-element Ti-Nb-Zr-W alloys
Transactions of Nonferrous Metals Society of China · 2023
Zhuhao Wen, Hao-qin LIN, Weimin Chen, Kewu Bai, Lijun Zhang
Read original paper ↗ ·Recent progress in gradient-structured metals and alloys
Progress in Materials Science · 2023
Weiming Ji, Runhua Zhou, Priyanka Vivegananthan, Mao See Wu, Huajian Gao, Kun Zhou
Read original paper ↗ ·Integrating machine learning and CALPHAD method for exploring low‐modulus near‐β‐Ti alloys
Rare Metals · 2023
Hao Lin Zou, Yueyan Tian, Ligang Zhang, Ren‐Hao Xue, Zixuan Deng, Mingming Lu, Jianxin Wang, Libin Liu
Read original paper ↗ ·An embedded machine learning strategy for analyzing interfacial characteristics in impact welding of dissimilar alloys
Composite Interfaces · 2023
Arif Sarı, Candra Zonyfar, Shavan K. Askar, Sherzod Shukhratovich Abdullaev, Raaid Alubady, Mukesh Kumar Sharma
Read original paper ↗ ·A Review of Deformation Mechanisms, Compositional Design, and Development of Titanium Alloys with Transformation-Induced Plasticity and Twinning-Induced Plasticity Effects
Metals · 2024
Yu Fu, Yue Gao, Wentao Jiang, Wenlong Xiao, Xinqing Zhao, Chaoli Ma
Read original paper ↗ ·Hybrid PSO with tree-based models for predicting uniaxial compressive strength and elastic modulus of rock samples
Frontiers in Earth Science · 2024
Niaz Muhammad Shahani, Qin Xiaowei, Xin Wei, Jun Li, Tuerhong Aizitiliwumaier, Xiaohu Ma, Qiu Shigui, Cao Weikang, Liu Longhe
Read original paper ↗ ·Machine learning-assisted design of low elastic modulus β-type medical titanium alloys and experimental validation
Computational Materials Science · 2024
Chengran Chai, Yang Wang, Shuai Zhao, Yuanxiang Zhang, Yuan-xiang Zhang, Feng Fang, Lin Peng, Xiaoming Zhang
Read original paper ↗ ·Machine learning-assisted efficient design of Cu-based shape memory alloy with specific phase transition temperature
International Journal of Minerals Metallurgy and Materials · 2024
Mengwei Wu, Wei Yong, Cunqin Fu, Chun-Mei Ma, Ruiping Liu
Read original paper ↗ ·Design of high performance Cu-Ni-Si alloys via a multiobjective strategy based on machine learning
Materials Today Communications · 2024
Zhiyang Qin, Hongliang Zhao, Shuya Zhang, Yuheng Fan, Xianglei Dong, Zishuo Lan, Xiaobing Hu, Yang Song, Chunwen Guo
Read original paper ↗ ·Experimentally validated inverse design of multi-property Fe-Co-Ni alloys
iScience · 2024
Shakti P. Padhy, Varun Chaudhary, Yee-Fun Lim, Ruiming Zhu, Muang Thway, Kedar Hippalgaonkar, Raju V. Ramanujan
Read original paper ↗ ·Machine learning-enabled prediction of high-temperature oxidation resistance for Ni-based alloys
Corrosion Science · 2024
Changheng Li, Kai Xu, Ming Lou, Linjing Wang, Keke Chang
Read original paper ↗ ·Automated, economical, and environmentally-friendly asphalt mix design based on machine learning and multi-objective grey wolf optimization
Journal of Traffic and Transportation Engineering (English Edition) · 2024
Jian Liu, Fangyu Liu, Linbing Wang
Read original paper ↗ ·Predictive modeling for design of low elastic modulus and biocompatible β-Ti alloys: A comprehensive machine learning-data driven approach with XGBoost as the key predictor
Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science · 2024
Gouthamaraj Kanapaakala, Venkatesan Subramani
Read original paper ↗ ·Predicting actuation strain in quaternary shape memory alloy NiTiHfX using machine learning
Computational Materials Science · 2024
Hossein Abedi, Mohammad Abdollahzadeh, T. Bush, Othmane Benafan, Ala Qattawi, Mohammad Elahinia
Read original paper ↗ ·Applications of machine learning method in high-performance materials design: a review
Journal of Materials Informatics · 2024
Junhao Yuan, Zhen Li, Yujia Yang, Anyi Yin, Wenjie Li, Dan Sun, Qing Wang
Read original paper ↗ ·High-throughput studies and machine learning for design of β titanium alloys with optimum properties
Transactions of Nonferrous Metals Society of China · 2024
Weimin Chen, Jinfeng Ling, Kewu Bai, Kaihong Zheng, Fuxing Yin, Lijun Zhang, Yong Du
Read original paper ↗ ·Comprehensive review of biological response, alloy design, strengthening mechanisms, performance evaluation, and surface modifications of titanium alloys for biomedical applications
Multiscale and Multidisciplinary Modeling Experiments and Design · 2024
Ranjan Kumar Mishra, Sarthak S. Singh
Read original paper ↗ ·Modeling and Prediction Method for Young’s Moduli of Ti Alloys Based on Residual Muti-layer Perceptron
JOM · 2024
Hua Yan, Qiang Li, Bin Yang, Yang Yang, Ying Wang, Hao Zhang
Read original paper ↗ ·Predicting and Enhancing Ductility in X2YZ-type Heusler Alloys Using Machine Learning and Abinitio Calculations
International Conference on Image Processing, Computer Vision and Machine Learning (ICICML) · 2024
Haoxuan Liu, Xiang Zhao, Haile Yan
Read original paper ↗ ·Physics-coupled data-driven design of high-temperature alloys
Acta Materialia · 2024
Sun Yong Kwon, Yukinori Yamamoto, Jian Peng, Michael P. Brady, Thomas R. Watkins, J. Allen Haynes, Dongwon Shin
Read original paper ↗ ·Robustness of machine learning predictions for Fe-Co-Ni alloys prepared by various synthesis methods
iScience · 2024
Shakti P. Padhy, Soumya R. Mishra, Li Ping Tan, Karl Peter Davidson, Xuesong Xu, Varun Chaudhary, Raju V. Ramanujan
Read original paper ↗ ·Developing novel low-density high-entropy superalloys with high strength and superior creep resistance guided by automated machine learning
Acta Materialia · 2024
Yancheng Li, Jingyu Pang, Zhen Li, Qing Wang, Zhen-Hua Wang, Jinlin Li, Hongwei Zhang, Zengbao Jiao, Chuang Dong, Peter Kaehuei Liaw
Read original paper ↗ ·Machine learning-based prediction of the mechanical properties of β titanium shape memory alloys
Journal of Materials Research and Technology · 2024
Naoki Nohira, Taichi Ichisawa, Masaki Tahara, Itsuo Kumazawa, Hideki HOSODA
Read original paper ↗ ·