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RESEARCH PAPER · Science China Chemistry · 2019

Identify crystal structures by a new paradigm based on graph theory for building materials big data

Mouyi Weng, Zhi Wang, Guoyu Qian, Yaokun Ye, Zhefeng Chen, Xin Chen, Shisheng Zheng, Feng Ming Pan

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42 direct citing works

Identify crystal structures by a new paradigm based on graph theory for building materials big dataOriginalCo13O8—metalloxocubes: a new class of perovskite-like neutral clusters with cubic aromaticity36Generative models for inverse design of inorganic solid materials38Research and Development of Civil Engineering Intelligent Structure System4Atomic-scale one-dimensional materials identified from graph theory0Topological representations of crystalline compounds for the machine-learning prediction of materials properties112Construction and Application of Materials Knowledge Graph Based on Author Disambiguation: Revisiting the Evolution of LiFePO432Encoding the atomic structure for machine learning in materials science85Crystal Structure Deduplication Algorithm Based on Interatomic Potential and Its Applications0Graph-based discovery and analysis of atomic-scale one-dimensional materials22Bridging Multiscale Characterization Technologies and Digital Modeling to Evaluate Lithium Battery Full Lifecycle93Graph-component approach to defect identification in large atomistic simulations2Application of machine learning to the structure classification of ternary metal nanoparticles0Algebraic Graph-Based Machine Learning Model for Li-Cluster Prediction11Application of topology-based structure features for machine learning in materials science19Deep alloys: Metal materials empowered by deep learning24EMFDTW: An Automated Crystallographic Identification Tool Supporting Multiple Comparison Criteria2Rapid Mining of Fast Ion Conductors via Subgraph Isomorphism Matching12Autonomous Exploitation of Reaction Pathways for Electrochemical C–N Coupling on Single-Atom Catalysts16AI4Materials: Transforming the landscape of materials science and enigneering25Machine-learning prediction of facet-dependent CO coverage on Cu electrocatalysts8Investigation of water structure and proton transfer within confined graphene by ab initio molecule dynamics and multiscale data analysis4MCTSGT: A graph theory-based Monte Carlo tree strategy for configuration search in disordered structures12Exploring Polymorphism in Metal Carbodiimides from Graph Theory0Integration of materials science and artificial intelligence: From high‐throughput screening to autonomous laboratories15Feature engineering methods for machine learning in heterogeneous catalysis4Topological Data Analysis in Materials Science: Principles, Machine Learning Integration, and Application Landscapes2

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26 direct citing papers saved.

  1. Co13O8—metalloxocubes: a new class of perovskite-like neutral clusters with cubic aromaticity

    National Science Review · 2020-08-26

    Lijun Geng, Mouyi Weng, Cong‐Qiao Xu, Hanyu Zhang, Chaonan Cui, Haiming Wu, Xin Chen, Mingyu Hu, Hai Lin, Zhen-Dong Sun, Xi Wang, Han‐Shi Hu, Jun Li, Jiaxin Zheng, Zhixun Luo, Feng Ming Pan, Jiannian Yao

    Read original paper ↗ ·

  2. Generative models for inverse design of inorganic solid materials

    Journal of Materials Informatics · 2021-01-01

    Litao Chen, Wentao Zhang, Zhiwei Nie, Shunning Li, Feng Ming Pan

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  3. Research and Development of Civil Engineering Intelligent Structure System

    Advances in Civil Engineering · 2021-01-01

    Junkai Xie, Bo Gao, Huamin Cheng

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  4. Atomic-scale one-dimensional materials identified from graph theory

    Research Square · 2021-02-03

    Shunning Li, Zhefeng Chen, Zhi Wang, Mouyi Weng, Jianyuan Li, Mingzheng Zhang, Jing Lu, Kang Xu, Feng Ming Pan

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  5. Topological representations of crystalline compounds for the machine-learning prediction of materials properties

    npj Computational Materials · 2021-02-05

    Yi Jiang, Dong Chen, Xin Chen, Tangyi Li, Guo‐Wei Wei, Feng Ming Pan

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  6. Construction and Application of Materials Knowledge Graph Based on Author Disambiguation: Revisiting the Evolution of LiFePO4

    Advanced Energy Materials · 2021-03-11

    Zhiwei Nie, Yuanji Liu, Luyi Yang, Shunning Li, Feng Pan

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  7. Encoding the atomic structure for machine learning in materials science

    Wiley Interdisciplinary Reviews Computational Molecular Science · 2021-06-18

    Shunning Li, Yuanji Liu, Dong Chen, Yi Jiang, Zhiwei Nie, Feng Pan

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  8. Crystal Structure Deduplication Algorithm Based on Interatomic Potential and Its Applications

    Computer Science and Application · 2022-01-01

    艳婷 孔

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  9. Graph-based discovery and analysis of atomic-scale one-dimensional materials

    National Science Review · 2022-02-24

    Shunning Li, Zhefeng Chen, Zhi Wang, Mouyi Weng, Jianyuan Li, Mingzheng Zhang, Jing Lü, Kang Xu, Feng Ming Pan

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  10. Bridging Multiscale Characterization Technologies and Digital Modeling to Evaluate Lithium Battery Full Lifecycle

    Advanced Energy Materials · 2022-06-15

    Xinhua Liu, Lisheng Zhang, Hanqing Yu, Jianan Wang, Junfu Li, Kai Yang, Yunlong Zhao, Huizhi Wang, Billy Wu, Nigel Peter Brandon, Shichun Yang

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  11. Graph-component approach to defect identification in large atomistic simulations

    Computational Materials Science · 2022-08-26

    Jenna A. Bilbrey, Nanjun Chen, Shenyang Hu, Peter V. Sushko

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  12. Application of machine learning to the structure classification of ternary metal nanoparticles

    AIP conference proceedings · 2023-01-01

    Владимир Сергеевич Мясниченко, Павел Викторович Матренин, Nickolay Yu. Sdobnyakov, Денис Николаевич Соколов

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  13. Algebraic Graph-Based Machine Learning Model for Li-Cluster Prediction

    The Journal of Physical Chemistry A · 2023-02-21

    Shengming Ma, Shisheng Zheng, Wentao Zhang, Dong Chen, Feng Ming Pan

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  14. Application of topology-based structure features for machine learning in materials science

    Chinese Journal of Structural Chemistry · 2023-06-07

    Shisheng Zheng, Haowen Ding, Shunning Li, Dong Chen, Feng Ming Pan

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  15. Deep alloys: Metal materials empowered by deep learning

    Materials Science in Semiconductor Processing · 2024-05-18

    Kaiyuan Zheng, Zhongping He, Lun Che, Hong Cheng, Meiling Ge, Tianyu Si, Xiaotian Xu

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  16. EMFDTW: An Automated Crystallographic Identification Tool Supporting Multiple Comparison Criteria

    Crystal Growth & Design · 2024-06-13

    Bing He, Yao Meng, Zhuming Gong, Kaixuan Wang, Jiang Zhou, Maxim Avdeev, Siqi Shi

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  17. Rapid Mining of Fast Ion Conductors via Subgraph Isomorphism Matching

    Journal of the American Chemical Society · 2024-06-28

    Wentao Zhang, Mouyi Weng, Mingzheng Zhang, Zhefeng Chen, Bingxu Wang, Shunning Li, Feng Ming Pan

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  18. Autonomous Exploitation of Reaction Pathways for Electrochemical C–N Coupling on Single-Atom Catalysts

    ACS Catalysis · 2024-12-19

    Junjie Pan, Haowen Ding, Xinzhe Yang, Xianhui Liang, Shanglin Wu, Mingzheng Zhang, Shunning Li, Shisheng Zheng, Feng Ming Pan

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  19. AI4Materials: Transforming the landscape of materials science and enigneering

    Review of Materials Research · 2025-01-01

    Xue Feng Jiang, Dezhen Xue, Yang Bai, William Yi Wang, Jianjun Liu, Mingli Yang, Yanjing Su

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  20. Machine-learning prediction of facet-dependent CO coverage on Cu electrocatalysts

    Journal of Materials Informatics · 2025-02-26

    Shanglin Wu, Shisheng Zheng, Wentao Zhang, Mingzheng Zhang, Shunning Li, Feng Pan

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  21. Investigation of water structure and proton transfer within confined graphene by ab initio molecule dynamics and multiscale data analysis

    Chinese Journal of Structural Chemistry · 2025-04-07

    Heng-Su Liu, Xi-Ming Zhang, Ge-Hao Liang, Shisheng Zheng, Jianfeng Li

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  22. MCTSGT: A graph theory-based Monte Carlo tree strategy for configuration search in disordered structures

    Acta Materialia · 2025-10-12

    Bing He, Zhicong Lai, Da Wang, Xiaotong Liu, Yue Liu, Miao Xu, Bowei Pu, Qisen Wang, Ruofang Wang, Maxim Avdeev, Siqi Shi

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  23. Exploring Polymorphism in Metal Carbodiimides from Graph Theory

    Inorganic Chemistry · 2025-10-31

    Juan Medina‐Jurado, Moritz Köller, Hicham Bourakhouadar, Lothar Schrey, Alex J. Corkett, Richard Dronskowski

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  24. Integration of materials science and artificial intelligence: From high‐throughput screening to autonomous laboratories

    Materials Genome Engineering Advances · 2025-11-30

    Pengfei Huang, Wei‐Di Liu, Chenhua Sun, Zekun Li, Yu Wang, Yanan Chen

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  25. Feature engineering methods for machine learning in heterogeneous catalysis

    Physical Chemistry Chemical Physics · 2026-01-01

    Yu Jin, Hang-Biao Lv, Shisheng Zheng, Jian-Feng Li

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  26. Topological Data Analysis in Materials Science: Principles, Machine Learning Integration, and Application Landscapes

    Chemical Reviews · 2026-06-09

    Shisheng Zheng, Bingxu Wang, Mengmeng Zhang, Jiawei Tan, Hang-Biao Lv, Ran Liu, Zhong-Zhang Shi, Xin Li, Ruoxuan Wang, S Q Zhang, Jingyan Li, Jingyan Li, Y Q Zhao, Jie Wu, Jian‐Feng Li, Jian‐Feng Li, Shing–Tung Yau, Feng Ming Pan

    Read original paper ↗ ·
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