Papers citing Machine learning in materials genome initiative: A review
Bi-objective optimization of thermal conductivity and thermal stress of UO2–Mo–Nb composite through Gaussian process regression and NSGA-II method
Ceramics International · 2022-05-06
Biaojie Yan, Zhiyi Wang, Tao Fa, Liang Cheng, Pengcheng Zhang
Read original paper ↗ ·Polymer informatics for QSPR prediction of tensile mechanical properties. Case study: Strength at break
The Journal of Chemical Physics · 2022-05-09
Fiorella Cravero, Mónica F. Díaz, Ignacio Ponzoni
Read original paper ↗ ·Prediction of Phase Diagrams and Associated Phase Structural Properties
Industrial & Engineering Chemistry Research · 2022-05-23
Federico Zipoli, Victor Viterbo, Oliver Tobias Schilter, Leonid Kahle, Teodoro Laino
Read original paper ↗ ·Recent progress in nanocrystalline Sm–Co based magnets
Materials Today Chemistry · 2022-06-03
Kai Guo, H. Lu, Guojing Xu, D. Liu, H.B. Wang, X.M. Liu, Xiaoyan Song
Read original paper ↗ ·Machine learning approach for ball milling of alumina ceramics
Research Square · 2022-06-06
Jungwon Yu, Raju Kati, So-Hyun Jin, Young-Jae Lee, Hyun Kwuon Lee
Read original paper ↗ ·Exploration of the oxidation and ablation resistance of ultra-high-temperature ceramic coatings using machine learning
Ceramics International · 2022-06-16
Jie Hao, Lihong Gao, Zhuang Ma, Yanbo Liu, Ling Liu, Shizhen Zhu, Weizhi Tian, Xiaoyu Liu, Zhigang Zhou, Alexandr Alexandrovich Rogachev, Hanyang Liu
Read original paper ↗ ·Predicting Material Properties by Deep Graph Networks
Crystal Research and Technology · 2022-06-17
Hantong Jiang, Xuanjie Lin, Liquan Wang, Yongsheng Ren, Shu Zhan, Wenhui Ma
Read original paper ↗ ·Machine learning driven rationally design of amorphous alloy with improved elastic models
Materials & Design · 2022-06-22
Zhuang Li, Zhilin Long, Shan Lei, Yulin Tang
Read original paper ↗ ·Data-Driven Construction Method of Material Mechanical Behavior Model
Metals · 2022-06-25
Qu Meijiao, Mengqi Li, Zhichao Wen, Weifeng He
Read original paper ↗ ·Identifying facile material descriptors for Charpy impact toughness in low-alloy steel via machine learning
Journal of Material Science and Technology · 2022-07-06
Yimian Chen, Shuize Wang, Jie Xiong, Guilin Wu, Junheng Gao, Yuan Wu, Guoqiang Ma, Hong‐Hui Wu, Xinping Mao
Read original paper ↗ ·Machine Learning for Property Prediction and Optimization of Polymeric Nanocomposites: A State-of-the-Art
International Journal of Molecular Sciences · 2022-09-14
Elizabeth Champa-Bujaico, Pilar García-Díaz, Ana Maria Diez-Pascual
Read original paper ↗ ·CRUX: Crowdsourced Materials Science Resource and Workflow Exploration
Proceedings of the ... ACM International Conference on Information & Knowledge Management · 2022-10-16
Mengying Wang, Hanchao Ma, Abhishek Daundkar, Sheng Uei Guan, Yiyang Bian, Alp Sehirlioglu, Yinghui Wu
Read original paper ↗ ·A machine learning approach for ball milling of alumina ceramics
The International Journal of Advanced Manufacturing Technology · 2022-11-18
Jungwon Yu, Kati Raju, So-Hyun Jin, Young-Jae Lee, Hyun-Kwuon Lee
Read original paper ↗ ·Recent developments in the application of machine-learning towards accelerated predictive multiscale design and additive manufacturing
Virtual and Physical Prototyping · 2022-11-20
Sandeep Suresh Babu, Abdel‐Hamid I. Mourad, Khalifa Hamad Harib, Sanjairaj Vijayavenkataraman
Read original paper ↗ ·Predicting Enthalpy of Formation of Energetic Compounds by Machine Learning: Comparison of Featurization Methods and Algorithms
Propellants Explosives Pyrotechnics · 2022-11-21
Xiaolan Tian, Xiujuan Qi, Yi Wang, Junnan Wu, Siwei Song, Qinghua Zhang
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 ↗ ·Recent Advance of Machine Learning in Selecting New Materials
化学学报 · 2023-01-01
Xingyi Qi, Yaofeng Hu, Ruoyu Wang, Yaqing Yang, Yufei Zhao
Read original paper ↗ ·Self-Supervised Representation Learning of Microstructures from Electron Microscopy for Property Prediction
Journal of Artificial Intelligence for Materials Science · 2023-01-01
Maria Hernandez, Carlos Vega
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 ↗ ·Application of machine learning to reveal relationship between processing-structure-property for polypropylene injection molding
Polymer · 2023-02-01
Feng-Yang Wu, Jin Yin, Shao-Chen Chen, Xueqin Gao, Li Zhou, Ying Lü, Jun Lei, Gan‐Ji Zhong, Zhong‐Ming Li
Read original paper ↗ ·Machine Learning Applications for 3D-Printed Polymers and Their Composites
Advances in chemical and materials engineering book series · 2023-02-17
Mamta B Savadatti, Kiran Kumar N., K. G. Jaya Christiyan, Amithkumar Gajakosh, Mukesh Thakur, R. Suresh Kumar, Richard Lincoln Paulraj, H. K. Madhusudhana
Read original paper ↗ ·Computational insight into stability-enhanced systems of anthocyanin with protein/peptide
Food Chemistry Molecular Sciences · 2023-02-21
Xing Cheng, Pei Chen, Lei Zhang
Read original paper ↗ ·Discovery of novel low modulus Nb–Ti–Zr biomedical alloys via combined machine learning and first principles approach
Materials Chemistry and Physics · 2023-02-25
Zhihao Huang, Hanxige Chen, Hanxige Chen, Songbo Ye, Guotan Liu, Han Chen, Han Chen, Yudong Fu, Yibo Sun, Mufu Yan
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 ↗ ·“Lubrication Brain” ― A machine learning framework of lubrication oil molecule design
Tribology International · 2023-03-02
Rui Zhou, Rui Zhou, Rui Ma, Luyao Bao, Meirong Cai, Feng Zhou, Weimin Li, Xiaobo Wang
Read original paper ↗ ·Knowledge-aware design of high-strength aviation aluminum alloys via machine learning
Journal of Materials Research and Technology · 2023-03-09
Juan Yong-fei, Guoshuai Niu, Yang Yang, Dai Yong-Bing, Zhang Jiao, Han Yan-feng, Sun Bao-de
Read original paper ↗ ·Creating 3D Objects with Integrated Electronics via Multiphoton Fabrication In Vitro and In Vivo
Advanced Materials Technologies · 2023-03-12
Sara J. Baldock, Punarja Kevin, Garry R. Harper, Rebecca Griffin, Hussein H. Genedy, James Fong, Zhiyi Zhao, Zijian Zhang, Yaochun Shen, Hungyen Lin, Catherine E. Au, Jack Martin, Mark Ashton, Mathew J. Haskew, Beverly Stewart, Olga Efremova, Reza N. Esfahani, Hedley C A Emsley, John Appleby, David Cheneler, Damian M. Cummings, Alexandre Benedetto, John George Hardy
Read original paper ↗ ·A Connected World: System-Level Support Through Biosensors
Annual Review of Analytical Chemistry · 2023-04-05
Eric Scott McLamore, Shoumen Datta
Read original paper ↗ ·Advances in machine learning- and artificial intelligence-assisted material design of steels
International Journal of Minerals Metallurgy and Materials · 2023-04-18
Guangfei Pan, Feiyang Wang, Chunlei Shang, Hong‐Hui Wu, Guilin Wu, Junheng Gao, Shuize Wang, Zhijun Gao, Xiaoye Zhou, Xinping Mao
Read original paper ↗ ·Improved material descriptors for bulk modulus in intermetallic compounds via machine learning
Rare Metals · 2023-05-12
Dexin Zhu, Kunming Pan, Yuan Wu, Xiaoye Zhou, Xiang‐Yue Li, Yongpeng Ren, Sairu Shi, Hua Yu, Shizhong Wei, Hong‐Hui Wu, Xusheng Yang
Read original paper ↗ ·Auto-MatRegressor: liberating machine learning alchemists
中国科学通报：英文版 · 2023-05-22
Yue Liu, Shuangyan Wang, Zhengwei Yang, Maxim Avdeev, Siqi Shi
Read original paper ↗ ·Deep ensembles vs committees for uncertainty estimation in neural-network force fields: Comparison and application to active learning
The Journal of Chemical Physics · 2023-05-22
Jesús Carrete, Hadrián Montes‐Campos, Ralf Wanzenböck, Esther Heid, Georg K. H. Madsen
Read original paper ↗ ·Improved data-driven performance of Charpy impact toughness via literature-assisted production data in pipeline steel
Science China Technological Sciences · 2023-05-25
Chunlei Shang, Chuanjun Wang, Hong‐Hui Wu, Wenyue Liu, Yimian Chen, Guangfei Pan, Shuize Wang, Guilin Wu, Junheng Gao, Haitao Zhao, Chaolei Zhang, Xinping Mao
Read original paper ↗ ·Multi-objective optimization for high-performance Fe-based metallic glasses via machine learning approach
Journal of Alloys and Compounds · 2023-05-30
Yuxing Zhang, She-Juan Xie, Wei Peng Guo, Jun Cai Ding, Leong Hien Poh, Zhen-Dong Sha
Read original paper ↗ ·Artificial Intelligence in Material Genomics
Materials research foundations · 2023-06-05
Joy H. Hoskeri
Read original paper ↗ ·Materials genome strategy for metallic glasses
Journal of Material Science and Technology · 2023-06-20
Zhichao Lu, Yibo Zhang, Wenyue Li, Jinyue Wang, Xiongjun Liu, Yuan Wu, Hui Wang, Dong Ma, Zhaoping Lü
Read original paper ↗ ·Center-environment deep transfer machine learning across crystal structures: from spinel oxides to perovskite oxides
npj Computational Materials · 2023-06-22
Yihang Li, Ruijie Zhu, Yuanqing Wang, Lingyan Feng, Yi Liu
Read original paper ↗ ·Application of Machine Learning in Material Synthesis and Property Prediction
Materials · 2023-08-31
Guannan Huang, Yani Guo, Ye Chen, Zhengwei Nie
Read original paper ↗ ·Prospective on methods of design of experiments for limited data scenarios in materials design and engineering
MRS Communications · 2023-09-13
Emily Margaret Ryan, Athar Roshandelpoor, Zoe A. Pollard, Jillian L. Goldfarb, Pirooz Vakili
Read original paper ↗ ·Machine learning-based multi-objective parameter optimization for indium electrorefining
Separation and Purification Technology · 2023-09-15
Hong-Qiang Fan, Xuan Zhu, Hong-Xing Zheng, Peng Lu, Mei‐Zhen Wu, Jubo Peng, He-Sheng Zhang, Quan Qian
Read original paper ↗ ·Accelerated Design for High-Entropy Alloys Based on Machine Learning and Multiobjective Optimization
Journal of Chemical Information and Modeling · 2023-09-26
Yingying Ma, Minjie Li, Yongkun Mu, Gang Wang, Wencong Lu
Read original paper ↗ ·Layered double hydroxides: next promising materials for energy storage and conversion
Next Materials · 2023-09-27
Kui Fan, Pengcheng Xu, Zhenhua Li, Mingfei Shao, Xue Duan
Read original paper ↗ ·Machine Learning-Aided High-Throughput First-Principles Calculations to Predict the Formation Energy of μ Phase
ACS Omega · 2023-09-27
Yue Su, Jiong Wang, You Feng Zou
Read original paper ↗ ·From prediction to design: Recent advances in machine learning for the study of 2D materials
Nano Energy · 2023-10-04
Hua He, Yuhua Wang, Yajuan Qi, Zichao Xu, Yue Li, Yumei Wang
Read original paper ↗ ·Irradiated mechanical properties predicted by a machine learning method with the Fourier-transform-based feature extension
Journal of Nuclear Science and Technology · 2023-10-10
Yingxuan Dong, Junnan Lv, Hong Zuo, Qun Li
Read original paper ↗ ·Review on applications of artificial neural networks to develop high entropy alloys: A state-of-the-art technique
Materials Today Communications · 2023-10-11
Sheetal Kumar Dewangan, Cheenepalli Nagarjuna, Reliance Jain, Rameshwar L. Kumawat, Vinod Kumar, Ashutosh Sharma, Byungmin Ahn
Read original paper ↗ ·A Comprehensive Review on Combinatorial Film via High-Throughput Techniques
Materials · 2023-10-15
Dongxin Wang, Wei Jiang, Shurong Li, Xuehui Yan, Shuaishuai Wu, Haochen Qiu, Shengli Guo, Baohong Zhu
Read original paper ↗ ·Application of Digital Methods in Polymer Science and Engineering
Advanced Functional Materials · 2023-10-27
Timo Schuett, Patrick Endres, Tobias Standau, Stefan Zechel, Rodrigo Queiroz Albuquerque, Christian Brütting, Holger Ruckdäschel, Ulrich S. Schubert
Read original paper ↗ ·Facilitating polymer property prediction with machine learning and group interaction modelling methods
International Journal of Solids and Structures · 2023-10-31
Elaheh Kazemi-Khasragh, Juan P. Fernandéz‐Blázquez, David Garoz Gómez, Carlos González, Maciej Harańczyk
Read original paper ↗ ·Bayesian inference of composition-dependent phase diagrams
Physical review. B./Physical review. B · 2023-11-14
Timofei Miryashkin, Olga Klimanova, Vladimir V. Ladygin, Alexander V. Shapeev
Read original paper ↗ ·