BetaCitation Atlas

RESEARCH PAPER · JOM · 2020

Predicting Tensile Properties of AZ31 Magnesium Alloys by Machine Learning

Xuenan Xu, Leyun Wang, Gaoming Zhu, Xiaoqin Zeng

Read original paper ↗

See where this research leads.

62 direct citing papers in this saved network. Explore the next layer with second-order citations.

Open in your workspace →Saved 2026-10-14 · complete coverage
Filter Citing Papers
Press Enter or comma to add · × to remove · searches titles and available abstracts
Journals
All journals
Most represented first · select one or more
Explore Terms In These PapersHide SuggestionsShow Suggestions

Original and current center papers stay visible as anchors.
Numbers show citations received
42 direct citing works

Predicting Tensile Properties of AZ31 Magnesium Alloys by Machine LearningOriginalBoosting for concept design of casting aluminum alloys driven by combining computational thermodynamics and machine learning techniques32Accelerated Development of High-Strength Magnesium Alloys by Machine Learning46A combined machine learning and EBSD approach for the prediction of {10-12} twin nucleation in an Mg-RE alloy22Big Data Mining and Classification of Intelligent Material Science Data Using Machine Learning17A reverse design model for high-performance and low-cost magnesium alloys by machine learning48Effect of tempering on bending-induced material strength inhomogeneity in hydrogenation reactor shells6Design of Biodegradable Mg Alloy for Abdominal Aortic Aneurysm Repair (AAAR) Using ANFIS Regression Model24Material Calculation Collaborates with Grain Morphology Knowledge Graph for Material Properties Prediction1Material machine learning for alloys: Applications, challenges and perspectives150Fracture toughness evaluation of silicon nitride from microstructures via convolutional neural network23Experimental study and machine learning model to predict formability of magnesium alloy sheet9Prediction of electronic work function of the second phase in binary magnesium alloy based on machine learning method8Design of new Al-Si-Mg alloys by multi-modal mixed input simulation experiment7Design of Light-Metal Alloys Using Machine Learning Techniques0Intelligent Prediction and Analysis of Mechanical Properties of Magnesium Alloys Using Interpretable Machine Learning1Artificial Intelligence‐based determination of fracture toughness and bending strength of silicon nitride ceramics34Modeling the correlation between texture characteristics and tensile properties of AZ31 magnesium alloy based on the artificial neural networks22Prediction of mechanical strength of magnesium alloy AZ31 with calcium addition using a neural network based model5Microstructure-property mapping modeling for AZ31 alloy rolling deformation using improved PSO-BP neural network19Prediction of Hardness and Fracture Toughness for WC-FeAl from Its Microstructural Images via Convolutional Neural Network1Data-driven machine learning for alloy research: Recent applications and prospects21Predicting the Hall-Petch slope of magnesium alloys by machine learning29Tensile Strength Prediction of Gray Cast Iron for Cylinder Head Based on Microstructure and Machine Learning4Machine Learning Aided Prediction and Design for the Mechanical Properties of Magnesium Alloys60Effect of Bioceramic Reinforcement on Mechanical and Machinability Behaviour of AZ31 Magnesium Alloy Composites5Designing high elastic modulus magnesium-based composite materials via machine learning approach15Research on composition-process-property prediction of die casting Al alloys via combining feature creation and attention mechanisms21Computational Thermodynamics-Assisted Machine Learning Approach to Predict Mechanical Properties of Magnesium Alloys for Bio-Implant Applications0Development of High-Strength Mg–Gd–Y Alloy Based on Machine Learning Method2Enhanced prediction of anisotropic deformation behavior using machine learning with data augmentation29Accelerating Elastic Property Prediction in Fe-C Alloys through Coupling of Molecular Dynamics and Machine Learning9Comprehensive study on the mechanical properties of Ti-doped Si3N4 ceramics: Experimental analysis, DFT calculations, and machine learning6Manufacturing process encoding through natural language processing for prediction of material properties15Alloys innovation through machine learning: a statistical literature review14Design of high performance Cu-Ni-Si alloys via a multiobjective strategy based on machine learning12Data extension-based analysis and application selection of process-composition-properties of die casting aluminum alloy13A brief review of machine learning-assisted Mg alloy design, processing, and property predictions38Predicting grain size-dependent superplastic properties in friction stir processed ZK30 magnesium alloy with machine learning methods17Optimal design of high‐performance rare‐earth‐free wrought magnesium alloys using machine learning17Machine learning-guided accelerated discovery of structure-property correlations in lean magnesium alloys for biomedical applications35An improved extreme learning machine model for predicting the mechanical property of AZ80 magnesium alloy1Accelerated intelligent prediction and analysis of mechanical properties of magnesium alloys based on scaled super learner machine-learning algorithms9An ATPSO-SVM prediction model for flow stress investigation of lightweight materials: a case study of 6181/6016H18 aluminum alloys1Prediction of Mechanical Properties of Hot-Rolled Strip Steel Based on XGBoost and Metallurgical Mechanism10Mechanical property prediction of aluminium alloys with varied silicon content using deep learning33Formability study on welded AZ31B magnesium alloy sheets using machine learning models0Mechanical properties estimation of multi-layer friction stir plug welded aluminium plates using time-series neural network models2Temperature Response Characteristics of Coal Freezing Process Based on Thermal Conductivity Hyperbolic Model2Frontiers in machine learning strategies for dye removal in water treatment20Machine learning accelerated design of magnesium alloys with high strength and high ductility17Deep drawing of magnesium alloys: A review32Machine learning assisted design of reactor steels with high long-term strength and toughness4AAKAN-WGAN: Predicting mechanical properties of magnesium alloys based on generative design and adaptive activation of Kolmogorov-Arnold Networks5Advancing chemical engineering technology with artificial intelligence21A new creep prediction model in Ni‐based superalloys via data‐driven symbolic regression3AI for Materials Development and Degradation Analysis in Automotive, Battery and Nuclear Industries0A two-stage predicting approach of magnesium alloys based on a single target regression strategy1Prediction of mechanical properties of magnesium alloys through machine learning: a review0Interpretable machine learning predictive model for mechanical properties of AZ31 magnesium alloy rolled sheets1A survey of machine learning applications for Mg alloys: A promising prospect for current trends and future directions2Research progress on advanced titanium-molybdenum alloy design driven by machine learning0Synergistic process optimization for strength and ductility in an Mg-Gd-Y-Zn-Zr alloy using an interpretable ensemble learning framework with data augmentation0

Arrows point to the paper being cited. Selecting a paper shows its incoming citations and its known path back to the original paper.

Drag to pan · Use + / − to zoom · Escape to close43 nodes / 53 citation links
Browse Matching Papers

Papers that cite this work

62 direct citing papers saved. Showing the first 50 here; use Browse Matching Papers in the map for all loaded papers.

  1. Boosting for concept design of casting aluminum alloys driven by combining computational thermodynamics and machine learning techniques

    Journal of Materials Informatics · 2021-01-01

    Yi Wang, Guangchen Liu, Jianbao Gao, Lijun Zhang

    Read original paper ↗ ·

  2. Accelerated Development of High-Strength Magnesium Alloys by Machine Learning

    Metallurgical and Materials Transactions A · 2021-01-19

    Yanwei Liu, Leyun Wang, Huan Zhang, Gaoming Zhu, Jie Wang, Yuhui Zhang, Xiaoqin Zeng

    Read original paper ↗ ·

  3. A combined machine learning and EBSD approach for the prediction of {10-12} twin nucleation in an Mg-RE alloy

    Materials Today Communications · 2021-03-27

    Yunwei Gui, Quanan Li, Kaige Zhu, Yibei Xue

    Read original paper ↗ ·

  4. Big Data Mining and Classification of Intelligent Material Science Data Using Machine Learning

    Applied Sciences · 2021-09-16

    Swetha Chittam, Balakrishna Gokaraju, Zhigang Xu, Jagannathan Sankar, Kaushik Roy

    Read original paper ↗ ·

  5. A reverse design model for high-performance and low-cost magnesium alloys by machine learning

    Computational Materials Science · 2021-09-27

    Xiaoxi Mi, Lianjuan Tian, Aitao Tang, Jing X. Kang, Peng Peng, Jia She, Hailian Wang, Xianhua Chen, Fusheng Pan

    Read original paper ↗ ·

  6. Effect of tempering on bending-induced material strength inhomogeneity in hydrogenation reactor shells

    International Journal of Pressure Vessels and Piping · 2021-12-01

    You Li, Zhiping Chen, Hongfei Li, Mengjie Liu, Miao Hao, Song Huang

    Read original paper ↗ ·

  7. Design of Biodegradable Mg Alloy for Abdominal Aortic Aneurysm Repair (AAAR) Using ANFIS Regression Model

    IEEE Access · 2022-01-01

    Rania E. Hammam, Ahmed Solyman, Mohammed H. Alsharif, Peerapong Uthansakul, Mohanad A. Deif

    Read original paper ↗ ·

  8. Material Calculation Collaborates with Grain Morphology Knowledge Graph for Material Properties Prediction

    IEEE International Conference on Computer Supported Cooperative Work in Design (CSCWD) · 2022-05-04

    Ziwen Pan, Chao Shu, Zhuoran Xin, Cheng Xie, Qi Shen, Yun Yang

    Read original paper ↗ ·

  9. Material machine learning for alloys: Applications, challenges and perspectives

    Journal of Alloys and Compounds · 2022-06-21

    Xiujuan Liu, Pengcheng Xu, Juanjuan Zhao, Wencong Lu, Minjie Li, Gang Wang

    Read original paper ↗ ·

  10. Fracture toughness evaluation of silicon nitride from microstructures via convolutional neural network

    Journal of the American Ceramic Society · 2022-09-26

    Ryoichi Furushima, Yutaka Maruyama, Yuki Nakashima, Minh Chu Ngo, Tatsuki Ohji, Manabu Fukushima

    Read original paper ↗ ·

  11. Experimental study and machine learning model to predict formability of magnesium alloy sheet

    F1000Research · 2022-09-29

    Balaji Viswanadhapalli, V.K. Bupesh Raja, Krishna Chythanya Nagaraju

    Read original paper ↗ ·

  12. Prediction of electronic work function of the second phase in binary magnesium alloy based on machine learning method

    Journal of materials research/Pratt's guide to venture capital sources · 2022-09-29

    Xiaoxiu Wei, Jianfeng Wang, Chao Wang, Shijie Zhu, Liguo Wang, Shaokang Guan

    Read original paper ↗ ·

  13. Design of new Al-Si-Mg alloys by multi-modal mixed input simulation experiment

    Acta Physica Sinica · 2022-10-19

    Zhiqiang Duan, Xiao-long Pei, Qingwei Guo, Hua Hou, Yuhong Zhao

    Read original paper ↗ ·

  14. Design of Light-Metal Alloys Using Machine Learning Techniques

    Materials horizons · 2022-11-18

    P. G. Kubendran Amos

    Read original paper ↗ ·

  15. Intelligent Prediction and Analysis of Mechanical Properties of Magnesium Alloys Using Interpretable Machine Learning

    SSRN Electronic Journal · 2023-01-01

    Atwakyire Moses, Ying Gui, Marembo Micheal, Buzhuo Chen, Ding Chen

    Read original paper ↗ ·

  16. Artificial Intelligence‐based determination of fracture toughness and bending strength of silicon nitride ceramics

    Journal of the American Ceramic Society · 2023-04-14

    Ryoichi Furushima, Yuki Nakashima, Yutaka Maruyama, Kiyoshi Hirao, Tatsuki Ohji, Manabu Fukushima

    Read original paper ↗ ·

  17. Modeling the correlation between texture characteristics and tensile properties of AZ31 magnesium alloy based on the artificial neural networks

    Journal of Materials Research and Technology · 2023-04-22

    Yibing Zhang, Shengwen Bai, Bin Jiang, Kun Li, Zhihua Dong, Fusheng Pan

    Read original paper ↗ ·

  18. Prediction of mechanical strength of magnesium alloy AZ31 with calcium addition using a neural network based model

    Journal of Physics Conference Series · 2023-05-01

    A. Thamarai Selvan, S. Palani

    Read original paper ↗ ·

  19. Microstructure-property mapping modeling for AZ31 alloy rolling deformation using improved PSO-BP neural network

    Journal of Materials Research and Technology · 2023-06-12

    Shuang Xu, Xiaodi Xu, Weitao Jia, Wenbin Liu, Jialong Li, Dengao Li

    Read original paper ↗ ·

  20. Prediction of Hardness and Fracture Toughness for WC-FeAl from Its Microstructural Images via Convolutional Neural Network

    Journal of the Japan Society of Powder and Powder Metallurgy · 2023-07-14

    Ryoichi Furushima, Yutaka Maruyama

    Read original paper ↗ ·

  21. Data-driven machine learning for alloy research: Recent applications and prospects

    Materials Today Communications · 2023-07-19

    Xueyun Gao, Haiyan Wang, Huijie Tan, Lei Xing, Zhiyu Hu

    Read original paper ↗ ·

  22. Predicting the Hall-Petch slope of magnesium alloys by machine learning

    Journal of Magnesium and Alloys · 2023-08-03

    Bo Guan, Chao Chen, Yunchang Xin, Jing Rui Xu, Bo Feng, Xiaoxu Huang, Qing Liu

    Read original paper ↗ ·

  23. Tensile Strength Prediction of Gray Cast Iron for Cylinder Head Based on Microstructure and Machine Learning

    steel research international · 2023-08-31

    Xiaoyuan Teng, J.C. Pang, Feng Liu, Chenglu Zou, Shouxin Li, Zhefeng Zhang

    Read original paper ↗ ·

  24. Machine Learning Aided Prediction and Design for the Mechanical Properties of Magnesium Alloys

    Metals and Materials International · 2023-09-13

    Shuya Dong, Yingying Wang, Jinya Li, Yuanyuan Li, Li Wang, Jinglai Zhang

    Read original paper ↗ ·

  25. Effect of Bioceramic Reinforcement on Mechanical and Machinability Behaviour of AZ31 Magnesium Alloy Composites

    JOM · 2023-10-03

    Arunachalam Saravanakumar, P. Sreenivas, Sivasundar Vijayakumar, L. Rajeshkumar, Nachimuthu Radhika, M. Ramesh

    Read original paper ↗ ·

  26. Designing high elastic modulus magnesium-based composite materials via machine learning approach

    Materials Today Communications · 2023-10-06

    Zhihong Zhu, Wenhang Ning, Xuanyang Niu, Qiaoling Wang, Renhai Shi, Yuhong Zhao

    Read original paper ↗ ·

  27. Research on composition-process-property prediction of die casting Al alloys via combining feature creation and attention mechanisms

    Journal of Materials Research and Technology · 2023-11-30

    Jian Lin Yang, Bo Liu, Haiyou Huang

    Read original paper ↗ ·

  28. Computational Thermodynamics-Assisted Machine Learning Approach to Predict Mechanical Properties of Magnesium Alloys for Bio-Implant Applications

    SSRN Electronic Journal · 2024-01-01

    Parham Valipoorsalimi, Mihriban Pekguleryuz, Yuksel Asli Sari

    Read original paper ↗ ·

  29. Development of High-Strength Mg–Gd–Y Alloy Based on Machine Learning Method

    ˜The œminerals, metals & materials series · 2024-01-01

    Yunchuan Cheng, Zhihua Dong, Yuan Peng, Zhi-Ying Zheng, Xiaoying Qian, Cuihong Wang, Bin Jiang, Fusheng Pan

    Read original paper ↗ ·

  30. Enhanced prediction of anisotropic deformation behavior using machine learning with data augmentation

    Journal of Magnesium and Alloys · 2024-01-01

    Sujeong Byun, Jinyeong Yu, Seho Cheon, Seong Ho Lee, Sung Hyuk Park, Taekyung Lee

    Read original paper ↗ ·

  31. Accelerating Elastic Property Prediction in Fe-C Alloys through Coupling of Molecular Dynamics and Machine Learning

    Materials · 2024-01-26

    Sandesh Risal, Navdeep Singh, Yan Li Yao, Li Sun, Samprash Risal, Weihang Zhu

    Read original paper ↗ ·

  32. Comprehensive study on the mechanical properties of Ti-doped Si3N4 ceramics: Experimental analysis, DFT calculations, and machine learning

    Ceramics International · 2024-02-09

    Jing Wu, Zhenru Xu, Xunyong Liu, Huaguo Tang, Tongyang Li, Zhuhui Qiao

    Read original paper ↗ ·

  33. Manufacturing process encoding through natural language processing for prediction of material properties

    Computational Materials Science · 2024-02-26

    Ana P. O. Costa, Mariana R. R. Seabra, José M.A. César de Sá, Abel Dias dos Santos

    Read original paper ↗ ·

  34. Alloys innovation through machine learning: a statistical literature review

    Science and Technology of Advanced Materials Methods · 2024-03-04

    Alireza Valizadeh, Ryoji Sahara, Maaouia Souissi

    Read original paper ↗ ·

  35. Design of high performance Cu-Ni-Si alloys via a multiobjective strategy based on machine learning

    Materials Today Communications · 2024-04-05

    Zhiyang Qin, Hongliang Zhao, Shuya Zhang, Yuheng Fan, Xianglei Dong, Zishuo Lan, Xiaobing Hu, Yang Song, Chunwen Guo

    Read original paper ↗ ·

  36. Data extension-based analysis and application selection of process-composition-properties of die casting aluminum alloy

    Engineering Applications of Artificial Intelligence · 2024-04-27

    Jian Lin Yang, Bo Liu, Yunbo Zeng, Yiben Zhang, Haiyou Huang, Jichao Hong

    Read original paper ↗ ·

  37. A brief review of machine learning-assisted Mg alloy design, processing, and property predictions

    Journal of Materials Research and Technology · 2024-05-01

    Yanhui Cheng, Lifei Wang, Chaoyang Yang, Yunli Bai, Hongxia Wang, Weili Cheng, Hanuma Reddy Tiyyagura, Alexander A. Komissarov, Kwang Seon Shin

    Read original paper ↗ ·

  38. Predicting grain size-dependent superplastic properties in friction stir processed ZK30 magnesium alloy with machine learning methods

    Journal of Magnesium and Alloys · 2024-05-01

    Farid Bahari-Sambran, F. Carreño, Carmen María Cepeda-Jiménez, Alberto Orozco‐Caballero

    Read original paper ↗ ·

  39. Optimal design of high‐performance rare‐earth‐free wrought magnesium alloys using machine learning

    Materials Genome Engineering Advances · 2024-05-31

    Shaojie Li, Zaixing Dong, Jianfeng Jin, Hucheng Pan, Zongqing Hu, Rui Hou, Gaowu W. Qin

    Read original paper ↗ ·

  40. Machine learning-guided accelerated discovery of structure-property correlations in lean magnesium alloys for biomedical applications

    Journal of Magnesium and Alloys · 2024-06-01

    Sreenivas Raguraman, Maitreyee Sharma Priyadarshini, Tram T. T. Nguyen, Ryan McGovern, Andrew Kim, Adam J. Griebel, Paulette Clancy, Timothy P. Weihs

    Read original paper ↗ ·

  41. An improved extreme learning machine model for predicting the mechanical property of AZ80 magnesium alloy

    Applied Physics A · 2024-07-25

    Jiahan Gu, Song Jiang, Wenbo Guo, Leilei Wang, Jianping Zhang

    Read original paper ↗ ·

  42. Accelerated intelligent prediction and analysis of mechanical properties of magnesium alloys based on scaled super learner machine-learning algorithms

    Mechanics of Materials · 2024-09-19

    Atwakyire Moses, Ying Gui, Buzhuo Chen, B.H. Chen, Marembo Micheal, Ding Chen

    Read original paper ↗ ·

  43. An ATPSO-SVM prediction model for flow stress investigation of lightweight materials: a case study of 6181/6016H18 aluminum alloys

    Applied Physics A · 2024-09-26

    Tianwei Shi, Jiahan Gu, Bin Li, Jianping Zhang

    Read original paper ↗ ·

  44. Prediction of Mechanical Properties of Hot-Rolled Strip Steel Based on XGBoost and Metallurgical Mechanism

    The Physics of Metals and Metallography · 2024-10-20

    Ming Li, Guiqin Li, Li Xihang, Lu Lixin, Peter Mitrouchev

    Read original paper ↗ ·

  45. Mechanical property prediction of aluminium alloys with varied silicon content using deep learning

    Acta Materialia · 2024-12-25

    Yūichiro Murakami, Ryoichi Furushima, Keiji Shiga, Tatsuya Miyajima, Naoki Omura

    Read original paper ↗ ·

  46. Formability study on welded AZ31B magnesium alloy sheets using machine learning models

    AIP conference proceedings · 2025-01-01

    Krishna Chythanya Nagaraju, Balaji Viswanadhapalli, Karanam Madhvai, Gajula Ramesh, Ramakrishna Reddy, Mohammed Ihassan, Amita Bisht, Vaibhav Kaushik

    Read original paper ↗ ·

  47. Mechanical properties estimation of multi-layer friction stir plug welded aluminium plates using time-series neural network models

    Soft Computing · 2025-01-01

    Mohammad Reza Chalak Qazani, Moosa Sajed, Siamak Pedrammehr, Seyed Mohammad Hossein Seyedkashi

    Read original paper ↗ ·

  48. Temperature Response Characteristics of Coal Freezing Process Based on Thermal Conductivity Hyperbolic Model

    JOM · 2025-01-07

    Gaowei Yue, Zihao Li, Minmin Li, Wenwu Tan, Haixiao Lin

    Read original paper ↗ ·

  49. Frontiers in machine learning strategies for dye removal in water treatment

    Journal of Water Process Engineering · 2025-02-15

    Guanfeng Zheng, Peng Fu, Xinglin Li

    Read original paper ↗ ·

  50. Machine learning accelerated design of magnesium alloys with high strength and high ductility

    Materials Today Communications · 2025-02-17

    Guosong Zhu, Xiaoming Du, Dandan Sun

    Read original paper ↗ ·
More citing papers →
Citation Atlas · A map of research, not a ranking.