BetaCitation Atlas

RESEARCH PAPER · Materials & Design · 2020

Method construction of structure-property relationships from data by machine learning assisted mining for materials design applications

Dongbo Dai, Qing Liu, Rui Hu, Xiao Wei, Guangtai Ding, Baoyu Xu, Tao Xu, Jincang Zhang, Xu Yan, Huiran Zhang

Read original paper ↗

See where this research leads.

49 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

Method construction of structure-property relationships from data by machine learning assisted mining for materials design applicationsOriginalModeling solid solution strengthening in high entropy alloys using machine learning254Exploring structure-composition relationships of cubic perovskite oxides via extreme feature engineering and automated machine learning10Crystal-Site-Based Artificial Neural Networks for Material Classification5The need for a new generation of substructure searching software2Prediction of growth velocity of undercooled multicomponent metallic alloys using a machine learning approach13Automated machine learning structure-composition-property relationships of perovskite materials for energy conversion and storage27Lead-free all-inorganic halide double perovskite materials for optoelectronic applications: progress, performance and design32Machine Learning–Assisted Design of Material Properties80Accelerating the discovery of high-performance donor/acceptor pairs in photovoltaic materials via machine learning and density functional theory23The Development of New Perovskite-Type Oxygen Transport Membranes Using Machine Learning10Feature Fusion Deep Learning Model for Defects Prediction in Crystal Structures4Predicting stress, strain and deformation fields in materials and structures with graph neural networks197A scientific machine learning framework to understand flash graphene synthesis24Gauging the importance of structural parameters for hyperfine coupling constants in organic radicals5Machine learning-assisted materials development and device management in batteries and supercapacitors: performance comparison and challenges66Simulation Construction of Data Mining Model Based on Fuzzy Neural Network0Machine learning analysis on critical structural factors of Al:ZnO (AZO) films2Deriving equation from data via knowledge discovery and machine learning: A study of Young’s modulus of Ti-Nb alloys8Importance of Structural Features and the Influence of Individual Structures of Graphene Oxide Using Shapley Value Analysis17Predicting elastic and plastic properties of small iron polycrystals by machine learning10Machine learning predicts the glass transition of two-dimensional colloids besides medium-range crystalline order5Machine learning aided evaluation and design based on polymer membrane materials3Accelerating search for the polar phase stability of ferroelectric oxide by machine learning4Integrated Convolutional and Graph Neural Networks to Advance Composites Analysis0Expanding the Horizons of Machine Learning in Nanomaterials to Chiral Nanostructures74Structural descriptor and surrogate modeling for design of biodegradable scaffolds6Machine learning for polyphenol-based materials10Application of Machine Learning in Constitutive Relationship Prediction of Porous Titanium Materials for Artificial Bone5Review on Some Important Research Progresses in Biodegradable Plastics/Polymers15Modeling fission gas release at the mesoscale using multiscale DenseNet regression with attention mechanism and inception blocks12A Review on the Application of Superalloys Composition, Microstructure, Processing, and Performance via Machine Learning18A comprehensive review of machine learning applications in perovskite solar cells: Materials discovery, device performance, process optimization and systems integration41An interpretable predictive framework based on rules and machine learning: rule extraction, validation and adaptive integration with machine learning0State-of-the-art review on various applications of machine learning techniques in materials science and engineering26Recent Progress in 3D Printing Polymer‐Based Bone Scaffolds5Artificial Neural Network Modeling of Mechanical Properties of 3D-Printed Polyamide 12 and Its Fiber-Reinforced Composites30Machine learning guided design of RE-Fe-B(RE=PrNd,La,Ce) with comprehensive high performance17Machine learning-driven optimization of physical properties in Al-Ga Co-doped ZnO films for hydrogen production applications6Artificial intelligence in materials science and engineering: Current landscape, key challenges, and future trajectories33AI-guided biomaterials and biofabrication strategies for enhanced tumor extracellular matrix mimicry23Data‐Driven Design of Bimodal Networked Dielectric Elastomers for High‐Performance Artificial Muscles3Machine Learning Descriptors for Mapping Structure‐Property‐Performance Relationships of Perovskite Solar Cells7A function-oriented design approach for mapping Structure-Property-Function relations in the case of a composite blade0Data-driven approaches for functional ceramics3A graph neural network surrogate for 3D finite element modeling: accelerated full-field parameter identification in aluminum alloy 6DR10Clustering in mixed broiler chicken batches for improvement of daily average weight0AI-guided design of optoelectronic molecularly modified CH 3 NH 3 PbI 3 perovskite thin films with improved aqueous stability1The next-generation polymer composite revolution: AI-driven multi-functional polymer composite for intelligent additive manufacturing2Machine learning-assisted materials design, mechanistic insights, and predictive modeling for high performance lithium-sulfur batteries2

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

49 direct citing papers saved.

  1. Modeling solid solution strengthening in high entropy alloys using machine learning

    Acta Materialia · 2021-05-01

    Cheng Wen, Changxin Wang, Yan Zhang, Stoichko Antonov, Dezhen Xue, Turab Lookman, Yanjing Su

    Read original paper ↗ ·

  2. Exploring structure-composition relationships of cubic perovskite oxides via extreme feature engineering and automated machine learning

    Materials Today Communications · 2021-06-26

    Qin Deng, Bin Lin

    Read original paper ↗ ·

  3. Crystal-Site-Based Artificial Neural Networks for Material Classification

    Crystals · 2021-08-29

    Juan Iván Gómez-Peralta, Nidia Guadalupe García-Peña, Xim Bokhimi

    Read original paper ↗ ·

  4. The need for a new generation of substructure searching software

    Acta Crystallographica Section B Structural Science Crystal Engineering and Materials · 2021-09-10

    Paul R. Raithby, Robin Taylor

    Read original paper ↗ ·

  5. Prediction of growth velocity of undercooled multicomponent metallic alloys using a machine learning approach

    Scripta Materialia · 2021-10-01

    Vanga Sreekar Goud, M.R. Rahul, Gandham Phanikumar

    Read original paper ↗ ·

  6. Automated machine learning structure-composition-property relationships of perovskite materials for energy conversion and storage

    Energy Materials · 2021-10-09

    Deng Qin, Bin Lin

    Read original paper ↗ ·

  7. Lead-free all-inorganic halide double perovskite materials for optoelectronic applications: progress, performance and design

    Physical Chemistry Chemical Physics · 2022-01-01

    Tao Zuo, Fangfang Qi, ChiYung Yam, Lingyi Meng

    Read original paper ↗ ·

  8. Machine Learning–Assisted Design of Material Properties

    Annual Review of Chemical and Biomolecular Engineering · 2022-03-17

    Sanket Kadulkar, Zachary M. Sherman, Venkat Ganesan, Thomas M. Truskett

    Read original paper ↗ ·

  9. Accelerating the discovery of high-performance donor/acceptor pairs in photovoltaic materials via machine learning and density functional theory

    Materials & Design · 2022-03-18

    Xiujuan Liu, Yueyue Shao, Tian Lu, Dongping Chang, Minjie Li, Wencong Lu

    Read original paper ↗ ·

  10. The Development of New Perovskite-Type Oxygen Transport Membranes Using Machine Learning

    Crystals · 2022-07-05

    Hartmut Schlenz, Stefan Baumann, Wilhelm Albert Meulenberg, Olivier Guillon

    Read original paper ↗ ·

  11. Feature Fusion Deep Learning Model for Defects Prediction in Crystal Structures

    Crystals · 2022-09-19

    Abeer Abdulaziz AlArfaj, Hanan A. Hosni Mahmoud

    Read original paper ↗ ·

  12. Predicting stress, strain and deformation fields in materials and structures with graph neural networks

    Scientific Reports · 2022-12-17

    M Maurizi, Chao Gao, Filippo Berto

    Read original paper ↗ ·

  13. A scientific machine learning framework to understand flash graphene synthesis

    Digital Discovery · 2023-01-01

    Kianoosh Sattari, Lucas Eddy, Jacob L. Beckham, Kevin M. Wyss, Richard Byfield, Long Qian, James M. Tour, Jian Lin

    Read original paper ↗ ·

  14. Gauging the importance of structural parameters for hyperfine coupling constants in organic radicals

    RSC Advances · 2023-01-01

    Conrad Szczuka, Rüdiger‐A. Eichel, Josef Granwehr

    Read original paper ↗ ·

  15. Machine learning-assisted materials development and device management in batteries and supercapacitors: performance comparison and challenges

    Journal of Materials Chemistry A · 2023-01-01

    Swarn Jha, Matthew Yen, Yazmin Soto Salinas, Evan Palmer, John Anzel Villafuerte, Hong Yu Liang

    Read original paper ↗ ·

  16. Simulation Construction of Data Mining Model Based on Fuzzy Neural Network

    SSRN Electronic Journal · 2023-01-01

    ji li, Juan Li, Fengmin ma

    Read original paper ↗ ·

  17. Machine learning analysis on critical structural factors of Al:ZnO (AZO) films

    Materials Letters · 2023-01-21

    Cumhur Yıldırım, Nilgün Baydoğan

    Read original paper ↗ ·

  18. Deriving equation from data via knowledge discovery and machine learning: A study of Young’s modulus of Ti-Nb alloys

    Computational Materials Science · 2023-06-27

    Huiran Zhang, Xi Liu, Guangjie Zhang, Yuquan Zhu, Shengzhou Li, Quan Qian, Dongbo Dai, Renchao Che, Tao Xu

    Read original paper ↗ ·

  19. Importance of Structural Features and the Influence of Individual Structures of Graphene Oxide Using Shapley Value Analysis

    Chemistry of Materials · 2023-08-25

    Amanda Susan Barnard, Bronwyn Louise Fox

    Read original paper ↗ ·

  20. Predicting elastic and plastic properties of small iron polycrystals by machine learning

    Scientific Reports · 2023-08-26

    Marcin Mińkowski, Lasse Laurson

    Read original paper ↗ ·

  21. Machine learning predicts the glass transition of two-dimensional colloids besides medium-range crystalline order

    Physical review. E · 2023-10-09

    Eun Cheol Kim, Dong Jae Chun, Chung Bin Park, Bong June Sung

    Read original paper ↗ ·

  22. Machine learning aided evaluation and design based on polymer membrane materials

    Journal of Experimental Nanoscience · 2023-10-17

    Jianfeng Liao

    Read original paper ↗ ·

  23. Accelerating search for the polar phase stability of ferroelectric oxide by machine learning

    Materials & Design · 2023-11-25

    Md Mokhlesur Rahman, Shazia Janwari, Minsu Choi, Umesh Vasudeo Waghmare, Jaichan Lee

    Read original paper ↗ ·

  24. Integrated Convolutional and Graph Neural Networks to Advance Composites Analysis

    SSRN Electronic Journal · 2024-01-01

    Marwa Yacouti, Maryam Shakiba

    Read original paper ↗ ·

  25. Expanding the Horizons of Machine Learning in Nanomaterials to Chiral Nanostructures

    Advanced Materials · 2024-01-19

    Vera A. Kuznetsova, Áine Coogan, Dmitry Botov, Yulia A. Gromova, Elena V. Ushakova, Yurii K. Gun’ko

    Read original paper ↗ ·

  26. Structural descriptor and surrogate modeling for design of biodegradable scaffolds

    Journal of the mechanical behavior of biomedical materials/Journal of mechanical behavior of biomedical materials · 2024-01-22

    Jesse M. Sestito, Tequila A. L. Harris, Yan Wang

    Read original paper ↗ ·

  27. Machine learning for polyphenol-based materials

    Smart Materials in Medicine · 2024-02-11

    Shengxi Jiang, Peiji Yang, Yujia Zheng, Xiong Gang Lu, Chaoming Xie

    Read original paper ↗ ·

  28. Application of Machine Learning in Constitutive Relationship Prediction of Porous Titanium Materials for Artificial Bone

    Metals · 2024-05-27

    Chengzhi Tan, Chunjin Li, Zhiqiang Liu

    Read original paper ↗ ·

  29. Review on Some Important Research Progresses in Biodegradable Plastics/Polymers

    Recent Progress in Materials · 2024-06-27

    Zhong Hu, Ruanbao Zhou

    Read original paper ↗ ·

  30. Modeling fission gas release at the mesoscale using multiscale DenseNet regression with attention mechanism and inception blocks

    Journal of Nuclear Materials · 2024-08-05

    Peter P. Toma, Md Ali Muntaha, Joel B. Harley, Michael Tonks

    Read original paper ↗ ·

  31. 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 ↗ ·

  32. A comprehensive review of machine learning applications in perovskite solar cells: Materials discovery, device performance, process optimization and systems integration

    Materials Today Energy · 2024-11-15

    Ling Mao, Changying Xiang

    Read original paper ↗ ·

  33. An interpretable predictive framework based on rules and machine learning: rule extraction, validation and adaptive integration with machine learning

    Research Square · 2024-11-25

    Huiran Zhang, Mengmeng Dai, Yudian Lin, Pin Wu, Lei Huang, Huanyu Xu, Shengzhou Li, Xu Yan, Zheng Tang, Jinchang Zhang, Renchao Che, Tao Xu, Dongbo Dai

    Read original paper ↗ ·

  34. State-of-the-art review on various applications of machine learning techniques in materials science and engineering

    Chemical Engineering Science · 2024-12-24

    Bing Yu, LiQin Zhang, Xiaoxia Ye, JunQi Wu, JunQi Wu, HuaYong Ying, Wei Zhu, Xiaoming Wu, Xiaoming Wu

    Read original paper ↗ ·

  35. Recent Progress in 3D Printing Polymer‐Based Bone Scaffolds

    Advanced Engineering Materials · 2025-02-13

    Ruiqi Feng, Ang Chu, Yunlong Guo, Guang Wei Hu, Biao Zhang

    Read original paper ↗ ·

  36. Artificial Neural Network Modeling of Mechanical Properties of 3D-Printed Polyamide 12 and Its Fiber-Reinforced Composites

    Polymers · 2025-03-03

    Cătălin Fetecău, Felicia Stan, Doina Boazu

    Read original paper ↗ ·

  37. Machine learning guided design of RE-Fe-B(RE=PrNd,La,Ce) with comprehensive high performance

    Acta Materialia · 2025-04-10

    Zheng Wang, Shiyi Zhang, Jing Wang, Ming Zhang, Yunzhong Chen, Baohe Li, Tongyun Zhao, Minggang Zhu, Minggang Zhu, Shen Baogen, Wei Li

    Read original paper ↗ ·

  38. Machine learning-driven optimization of physical properties in Al-Ga Co-doped ZnO films for hydrogen production applications

    Materials Science and Engineering B · 2025-05-27

    Gaith Rjoub, Qais M. Al‐Bataineh, Ihsan A. Aljarrah, Ahmad A. Ahmad

    Read original paper ↗ ·

  39. Artificial intelligence in materials science and engineering: Current landscape, key challenges, and future trajectories

    Composite Structures · 2025-07-05

    Iman Peivaste, Salim Belouettar, Francesco Mercuri, Nicholas Fantuzzi, Hamidreza Dehghani, Razie Izadi, Halliru Ibrahim, Jakub Lengiewicz, Mael Belouettar-Mathis, Kouider Bendine, Ahmed Makradi, Martin Horsch, Peter Klein, M. Hachemi, Heinz A. Preisig, Yacine Rezgui, Natalia Konchakova, Ali Daouadji

    Read original paper ↗ ·

  40. AI-guided biomaterials and biofabrication strategies for enhanced tumor extracellular matrix mimicry

    Cell Biomaterials · 2025-09-01

    Jin Yan, Min Hu, Peiyuan Zhao, Chunling Zhang, Jiayi Lin, Yiwen Shen, Hongzhuan Chen, Weidong Zhang, Min Tang, Xin Luan

    Read original paper ↗ ·

  41. Data‐Driven Design of Bimodal Networked Dielectric Elastomers for High‐Performance Artificial Muscles

    Advanced Intelligent Systems · 2025-10-05

    Ofoq Normahmedov, Hanzhi Ma, Junbo Peng, Huifeng Dong, Jiangshan Zhuo, Mengke Shi, Lvting Wang, Shengchao Jiang, Ye Shi

    Read original paper ↗ ·

  42. Machine Learning Descriptors for Mapping Structure‐Property‐Performance Relationships of Perovskite Solar Cells

    Advanced Energy Materials · 2025-12-12

    Yu Su, Kongxiang Wang, Xiang Guan, Yumao Wu, Hong Zhang, Fengxian Xie, Junhao Chu

    Read original paper ↗ ·

  43. A function-oriented design approach for mapping Structure-Property-Function relations in the case of a composite blade

    Materials Today Communications · 2026-03-01

    Evgenia Madia, Georgios Tzortzinis, N. Sharma, K. Kumar Yadav, Μaik Gude, Angelos Filippatos

    Read original paper ↗ ·

  44. Data-driven approaches for functional ceramics

    Materials Science and Engineering R Reports · 2026-04-01

    Jincheng Qin, Faqiang Zhang, Mingsheng Ma, Yongxiang Li, Zhifu Liu

    Read original paper ↗ ·

  45. A graph neural network surrogate for 3D finite element modeling: accelerated full-field parameter identification in aluminum alloy 6DR1

    Journal of Materials Science Materials Theory · 2026-04-17

    Ossama Abou Ali Modad, Mustapha Makki, Abdallah Chehade, Georges Y. Ayoub

    Read original paper ↗ ·

  46. Clustering in mixed broiler chicken batches for improvement of daily average weight

    Computers and Electronics in Agriculture · 2026-04-30

    Josenalde B. Oliveira, Laura Emmanuella A. dos S. Santana, Alessandro Augusto Simões, Roni Gasparetto, Genoino Sonda Junior

    Read original paper ↗ ·

  47. AI-guided design of optoelectronic molecularly modified CH 3 NH 3 PbI 3 perovskite thin films with improved aqueous stability

    AI for Science · 2026-05-09

    Lei Zhang, Youle Wang, Yinguo Zhou, Cunyu Li

    Read original paper ↗ ·

  48. The next-generation polymer composite revolution: AI-driven multi-functional polymer composite for intelligent additive manufacturing

    Review of Materials Research · 2026-05-28

    Quanjin Ma, R. A. Ilyas, Mohd Shahneel Saharudin, Rejab M.R, Fawad Inam, Nadlene Razali, Yiheng Song, Bo Sun, Muhammad Asyraf Muhammad Rizal

    Read original paper ↗ ·

  49. Machine learning-assisted materials design, mechanistic insights, and predictive modeling for high performance lithium-sulfur batteries

    Energy storage materials · 2026-06-21

    Kaijie Miao, Chengwei Ma, Jiangqi Zhou

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