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RESEARCH PAPER · 中国科学通报：英文版 · 2019

Discovering unusual structures from exception using big data and machine learning techniques

Jianshu Jie, Zongxiang Hu, Guoyu Qian, Mouyi Weng, Shunning Li, Shucheng Li, Mingyu Hu, Dong Chen, Weiji Xiao, Jiaxin Zheng, Lin‐Wang Wang, Feng Pan

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Discovering unusual structures from exception using big data and machine learning techniquesOriginalDiscovery of space aromaticity in transition–metal monoxide crystal Nb3O3 enabled by octahedral Nb6 structural units7Neural Network Force Fields for Metal Growth Based on Energy Decompositions12Topology-Based Machine Learning Strategy for Cluster Structure Prediction46Accelerated design and characterization of non-uniform cellular materials via a machine-learning based framework90Recent progress on discovery and properties prediction of energy materials: Simple machine learning meets complex quantum chemistry62What place does molecular topology have in today’s drug discovery?31Tools, Technologies, and Methodologies to Support Data Science1DART: deep learning enabled topological interaction model for energy prediction of metal clusters and its application in identifying unique low energy isomers13Techno-economic analysis of metal–organic frameworks for adsorption heat pumps/chillers: from directional computational screening, machine learning to experiment48Topological representations of crystalline compounds for the machine-learning prediction of materials properties112Deep learning predicts boiling heat transfer104Construction and Application of Materials Knowledge Graph Based on Author Disambiguation: Revisiting the Evolution of LiFePO432Machine-learning micropattern manufacturing45Encoding the atomic structure for machine learning in materials science85Coupling physics in machine learning to investigate the solution behavior of binary Mg alloys65Research on data fusion method of multi-source complex system4Atomtransmachine: An atomic feature representation model for machine learning4Stacking-Based Multi-Features Fusion Ensemble Learning for Product Quality Prediction1Advances in machine learning for high value-added applications of lignocellulosic biomass46Prediction of intravenous immunoglobulin-resistant Kawasaki disease: a research hotspot10Recent Advance of Machine Learning in Selecting New Materials7Analysis and evaluation of machine learning applications in materials design and discovery33Insight into the Electronic Properties of Semiconductor Heterostructure Based on Machine Learning and First-Principles14Machine learning promotes the development of all-solid-state batteries35Application of Big Data Fusion Model in the Architecture Design of Smart Departure Service Platform0Advancements in High‐Throughput Screening and Machine Learning Design for 2D Ferromagnetism: A Comprehensive Review10Machine learning for beyond Li-ion batteries: Powering the research39Accelerated design and characterization of nonuniformed cellular architected materials with tunable mechanical properties0Highly effective design of high GFA alloys with different metal-based and various components by machine learning14Explorative prediction of novel superhard carbon allotropes with lager cell: Density functional theory-assisted deep learning10Application of machine learning in magnetocaloric materials: A review12Influence of inner-core symmetry on tropical cyclone rapid intensification and its forecasting by a machine learning ensemble model0Unlock the electrochemical performance of g-SiC/Nb2CO2 heterostructure as lithium/sodium ion storage anode with first-principles and machine learning7Unlock the performance mechanism of N/P-doped g-SiC and Nb2CO2 monolayer materials as lithium/sodium-ion batteries2Structure-activity relationship of MXene with different terminal groups for hydrogen evolution reaction based on symbolic regression and interpretable machine learning0

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  1. Discovery of space aromaticity in transition–metal monoxide crystal Nb3O3 enabled by octahedral Nb6 structural units

    中国科学通报：英文版 · 2019-11-03

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  2. Neural Network Force Fields for Metal Growth Based on Energy Decompositions

    The Journal of Physical Chemistry Letters · 2020-01-30

    Qin Hu, Mouyi Weng, Xin Chen, Shucheng Li, Feng Ming Pan, Lin‐Wang Wang

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  3. Topology-Based Machine Learning Strategy for Cluster Structure Prediction

    The Journal of Physical Chemistry Letters · 2020-04-22

    Xin Chen, Dong Chen, Mouyi Weng, Yi Jiang, Guo‐Wei Wei, Feng Ming Pan

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  4. Accelerated design and characterization of non-uniform cellular materials via a machine-learning based framework

    npj Computational Materials · 2020-04-23

    Chunping Ma, Zhiwei Zhang, Benjamin Luce, Simon Pusateri, Binglin Xie, Mohammad Hossein Rafiei, Nan Hu

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  5. Recent progress on discovery and properties prediction of energy materials: Simple machine learning meets complex quantum chemistry

    Journal of Energy Chemistry · 2020-05-27

    Yongqiang Kang, Lejing Li, Baohua Li

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  6. What place does molecular topology have in today’s drug discovery?

    Expert Opinion on Drug Discovery · 2020-06-04

    Riccardo Zanni, María Gálvez-Llompart, Ramón García‐Domenech, Jorge Gálvez

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  7. Tools, Technologies, and Methodologies to Support Data Science

    Advances in data mining and database management book series · 2020-10-08

    Ricardo A. Barrera-Cámara, Ana Canepa Saénz, Jorge A. Ruíz-Vanoye, Alejandro Fuentes-Penna, Miguel Ángel Ruiz-Jaimes, María Beatríz Bernábe Loranca

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  8. DART: deep learning enabled topological interaction model for energy prediction of metal clusters and its application in identifying unique low energy isomers

    Physical Chemistry Chemical Physics · 2021-01-01

    Rohit Modee, Sheena Agarwal, Ashwini Verma, Kavita Joshi, U. Deva Priyakumar

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  9. Techno-economic analysis of metal–organic frameworks for adsorption heat pumps/chillers: from directional computational screening, machine learning to experiment

    Journal of Materials Chemistry A · 2021-01-01

    Zenan Shi, Xueying Yuan, Yaling Yan, Yuanlin Tang, Junjie Li, Hong Liang, Lianpeng Tong, Zhiwei Qiao

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  10. 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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  11. Deep learning predicts boiling heat transfer

    Scientific Reports · 2021-03-10

    Youngjoon Suh, Ramin Bostanabad, Yoonjin Won

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  12. 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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  13. Machine-learning micropattern manufacturing

    Nano Today · 2021-04-19

    Si Wang, Ziao Shen, Zhenyu Shen, Yuanjun Dong, Yanran Li, Yuxin Cao, Yanmei Zhang, Shengshi Guo, Jianwei Shuai, Yun Mo Yang, Changjian Lin, Xun Chen, Xingcai Zhang, Qiaoling Huang

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  14. 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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  15. Coupling physics in machine learning to investigate the solution behavior of binary Mg alloys

    Journal of Magnesium and Alloys · 2021-07-23

    Tao Chen, Qian Gao, Yuan Yuan, Tingyu Li, Qian Xi, Tingting Liu, Aitao Tang, Andy Watson, Fusheng Pan

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  16. Research on data fusion method of multi-source complex system

    Journal of Web Engineering · 2021-08-26

    Yuxiang Cai

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  17. Atomtransmachine: An atomic feature representation model for machine learning

    Computational Materials Science · 2021-09-08

    Mengxian Hu, Jianmei Yuan, Tao Sun, Meng Tian Huang, Qingyun Liang

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  18. Stacking-Based Multi-Features Fusion Ensemble Learning for Product Quality Prediction

    IEEE International Conference on e-Business Engineering (ICEBE) · 2022-10-01

    Wenbiao Tao, Luyao Xu, Yuran Dong, Cheng Xie

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  19. Advances in machine learning for high value-added applications of lignocellulosic biomass

    Bioresource Technology · 2022-12-10

    Hanwen Ge, Jun Zheng, Huanfei Xu

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  20. Prediction of intravenous immunoglobulin-resistant Kawasaki disease: a research hotspot

    中国科学通报：英文版 · 2023-01-01

    Bowen Xu, Qingyou Zhang, Junbao Du, Isao Shiraishi, Hongfang Jin

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  21. 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

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  22. Analysis and evaluation of machine learning applications in materials design and discovery

    Materials Today Communications · 2023-01-25

    Mahsa Golmohammadi, Masoud Aryanpour

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  23. Insight into the Electronic Properties of Semiconductor Heterostructure Based on Machine Learning and First-Principles

    ACS Applied Materials & Interfaces · 2023-02-24

    Yuanyuan Yuan, Junqiang Ren, Hongtao Xue, Junchen Li, Fuling Tang, Peiqing La, Xuefeng Lu

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  24. Machine learning promotes the development of all-solid-state batteries

    Chinese Journal of Structural Chemistry · 2023-06-07

    Yong Long Qiu, Xu Zhang, Yun Tian, Zhen Ping Zhou

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  25. Application of Big Data Fusion Model in the Architecture Design of Smart Departure Service Platform

    International Conference on Artificial Intelligence and Autonomous Robot Systems (AIARS) · 2023-07-01

    Dong Li, Xiao Yang Huang, Yi Zhuang, Gang Yu, Guowei Cai

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  26. Advancements in High‐Throughput Screening and Machine Learning Design for 2D Ferromagnetism: A Comprehensive Review

    Advanced Theory and Simulations · 2023-08-31

    Chao Xin, Bingqian Song, Guangyong Jin, Yongli Song, Feng Ming Pan

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  27. Machine learning for beyond Li-ion batteries: Powering the research

    Journal of Energy Storage · 2023-09-27

    Aysegul Kilic, Burcu Oral, Damla Eroğlu, Ramazan Yıldırım

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  28. Accelerated design and characterization of nonuniformed cellular architected materials with tunable mechanical properties

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  29. Highly effective design of high GFA alloys with different metal-based and various components by machine learning

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  30. Explorative prediction of novel superhard carbon allotropes with lager cell: Density functional theory-assisted deep learning

    Diamond and Related Materials · 2024-06-25

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  31. Application of machine learning in magnetocaloric materials: A review

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  32. Influence of inner-core symmetry on tropical cyclone rapid intensification and its forecasting by a machine learning ensemble model

    Weather and Climate Extremes · 2025-04-17

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  33. Unlock the electrochemical performance of g-SiC/Nb2CO2 heterostructure as lithium/sodium ion storage anode with first-principles and machine learning

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  34. Unlock the performance mechanism of N/P-doped g-SiC and Nb2CO2 monolayer materials as lithium/sodium-ion batteries

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  35. Structure-activity relationship of MXene with different terminal groups for hydrogen evolution reaction based on symbolic regression and interpretable machine learning

    Journal of Energy Chemistry · 2026-07-03

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