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RESEARCH PAPER · The Journal of Physical Chemistry Letters · 2022

Predicting Experimental Formability of Hybrid Organic–Inorganic Perovskites via Imbalanced Learning

Tian Lu, Hongyu Li, Minjie Li, Shenghao Wang, Wencong Lu

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42 direct citing works

Predicting Experimental Formability of Hybrid Organic–Inorganic Perovskites via Imbalanced LearningOriginalMachine Learning-Assisted Design of Yttria-Stabilized Zirconia Thermal Barrier Coatings with High Bonding Strength36Charge Recombination Dynamics in a Metal Halide Perovskite Simulated by Nonadiabatic Molecular Dynamics Combined with Machine Learning30Small data machine learning in materials science866Feature Selection in Machine Learning for Perovskite Materials Design and Discovery59Machine learning for perovskite solar cell design58Accurate, interpretable predictions of materials properties within transformer language models39MIC-SHAP: An ensemble feature selection method for materials machine learning35Discovery and verification of two-dimensional organic–inorganic hybrid perovskites via diagrammatic machine learning model3Inverse design of Bulk metallic glasses with reduced glass transform temperatures via Target-Optimal inverse projection3CSIML: a cost-sensitive and iterative machine-learning method for small and imbalanced materials data sets5Machine learning guided efficiency improvement for Sn‐based perovskite solar cells with efficiency exceeding 20%43The mastery of details in the workflow of materials machine learning64Exploring the physical characteristics of chalcogenide SrZrS3 perovskite: Insights for photovoltaic use2Discovering novel lead-free mixed cation hybrid halide perovskites via machine learning6Theoretical advances and future perspectives of all-inorganic germanium-based perovskites9机器学习辅助钙钛矿太阳能电池制备工艺参数优化2Farthest point sampling in property designated chemical feature space as an effective strategy for enhancing the machine learning model performance for small scale chemical dataset9Artificial intelligence for post-moore field-effect transistors: a review and perspective1Interpretable machine learning on a curated dataset identifies chemical descriptors governing 2D perovskite solar cell performance1Taguchi–machine learning hybrid framework for optimization of particulate drug delivery systems2Machine Learning Unlocks New Directions in Halide Perovskite Research6Machine Learning for Stability Enhancement in Perovskite Solar Cells: A Pathway to Commercial Viability0Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO 2 Conversion3Integrating NSGA-II and TOPSIS for Stacking Model Optimization in Pursuit of Halide Double Perovskite Screening0A review of transition metal-based double perovskite oxides for photovoltaic applications0

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  1. Machine Learning-Assisted Design of Yttria-Stabilized Zirconia Thermal Barrier Coatings with High Bonding Strength

    ACS Omega · 2022-06-09

    Pengcheng Xu, Can Chen, Shuizhou Chen, Wencong Lu, Quan Qian, Yi Han Zeng

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  2. Charge Recombination Dynamics in a Metal Halide Perovskite Simulated by Nonadiabatic Molecular Dynamics Combined with Machine Learning

    The Journal of Physical Chemistry Letters · 2022-11-11

    Zhaosheng Zhang, Jiazheng Wang, Yingjie Zhang, Jianzhong Xu, Run Long

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  3. Small data machine learning in materials science

    npj Computational Materials · 2023-03-25

    Pengcheng Xu, Xiaobo Ji, Minjie Li, Wencong Lu

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  4. Feature Selection in Machine Learning for Perovskite Materials Design and Discovery

    Materials · 2023-04-16

    Junya Wang, Pengcheng Xu, Xiaobo Ji, Minjie Li, Wencong Lu

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  5. Machine learning for perovskite solar cell design

    Computational Materials Science · 2023-04-30

    Zhan Hui, Min Wang, Xiang Qian Yin, Yanan Wang, Yunliang Yue

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  6. Accurate, interpretable predictions of materials properties within transformer language models

    Patterns · 2023-08-02

    Vadim Korolev, Pavel V. Protsenko

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  7. MIC-SHAP: An ensemble feature selection method for materials machine learning

    Materials Today Communications · 2023-08-16

    Junya Wang, Pengcheng Xu, Xiaobo Ji, Minjie Li, Wencong Lu

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  8. Discovery and verification of two-dimensional organic–inorganic hybrid perovskites via diagrammatic machine learning model

    Materials & Design · 2024-01-18

    Qiyuan Zhu, Pengcheng Xu, Tian Lu, Xiaobo Ji, Min Shao, Zhiming Duan, Wencong Lu

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  9. Inverse design of Bulk metallic glasses with reduced glass transform temperatures via Target-Optimal inverse projection

    Computational Materials Science · 2024-01-21

    Dongping Chang, Tian Lu, Wencong Lu, Wenyan Zhou, Minjie Li, Gang Wang

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  10. CSIML: a cost-sensitive and iterative machine-learning method for small and imbalanced materials data sets

    Chemistry Letters · 2024-05-01

    Shengzhou Li, Ayako Nakata

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  11. Machine learning guided efficiency improvement for Sn‐based perovskite solar cells with efficiency exceeding 20%

    Rare Metals · 2024-06-17

    Weiyin Gao, Chenxin Ran, Liang Zhao, He Dong, Wang‐Yue Li, Zhao-Qi Gao, Yingdong Xia, Hai Huang, Yonghua Chen

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  12. The mastery of details in the workflow of materials machine learning

    npj Computational Materials · 2024-07-02

    Yingying Ma, Pengcheng Xu, Minjie Li, Xiaobo Ji, Wenyue Zhao, Wencong Lu

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  13. Exploring the physical characteristics of chalcogenide SrZrS3 perovskite: Insights for photovoltaic use

    MRS Advances · 2024-12-09

    Md Zillur Rahman, Sayed Sahriar Hasan, Mist Shamima Akter, M. A. Rayhan, Md. Zahid Hasan, Md Ariful Islam

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  14. Discovering novel lead-free mixed cation hybrid halide perovskites via machine learning

    Physical Chemistry Chemical Physics · 2025-01-01

    Fatemeh Jamalinabijan, Somayyeh Alidoust, Gözde İniş Demir, Adem Tekin

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  15. Theoretical advances and future perspectives of all-inorganic germanium-based perovskites

    Journal of Materials Chemistry C · 2025-01-01

    Ziming Kuang, Baoyun Liang, Tengcheng Huang, Tingting Shi, Weiguang Xie

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  16. 机器学习辅助钙钛矿太阳能电池制备工艺参数优化

    Laser & Optoelectronics Progress · 2025-01-01

    高音 Gao Yin, 李阳 Li Yang, 夏创林 Xia Chuanglin, 陈谦 Chen Qian

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  17. Farthest point sampling in property designated chemical feature space as an effective strategy for enhancing the machine learning model performance for small scale chemical dataset

    Journal of Materials Informatics · 2025-06-19

    Yuze Liu, Lejia Wang, Weigang Zhu, Xi Yu

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  18. Artificial intelligence for post-moore field-effect transistors: a review and perspective

    Materials Today Electronics · 2025-09-05

    Xiang Li, Nan Jiang, Wenhan Zhou, Xiaoyi Zhang, Yang Hu, Shuo Wang, Huipu Wang, Hengze Qu, Haibo Zeng, Shengli Zhang

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  19. Interpretable machine learning on a curated dataset identifies chemical descriptors governing 2D perovskite solar cell performance

    Solar Energy · 2025-10-31

    Migon Choi, Aiden Sable, Nicolas Ramos, Richard J. Sheridan, Olivier A. Delaire, Hai Li, David B. Mitzi, L. Catherine Brinson

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  20. Taguchi–machine learning hybrid framework for optimization of particulate drug delivery systems

    Journal of Drug Delivery Science and Technology · 2025-11-27

    Doğukan Duymaz, Seda Kızılel

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  21. Machine Learning Unlocks New Directions in Halide Perovskite Research

    ChemElectroChem · 2025-12-10

    Hyejin Choe, Heesung Yoon, Inhyang Kim, Soo Young Kim

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  22. Machine Learning for Stability Enhancement in Perovskite Solar Cells: A Pathway to Commercial Viability

    Progress in Photovoltaics Research and Applications · 2025-12-24

    Shen Wang, Weiren Zhao, Minjia Zhou, Tanghao Liu, Yian Wang, Yian Wang, Run Shi, Yunfan Wang, Yunfan Wang, Zhuoqiong Zhang

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  23. Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO 2 Conversion

    Advanced Intelligent Discovery · 2026-02-22

    Paul Rossener Regonia, Christian Mark Pelicano

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  24. Integrating NSGA-II and TOPSIS for Stacking Model Optimization in Pursuit of Halide Double Perovskite Screening

    Materials · 2026-05-12

    Guiqin Liang, Jian Zhang

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  25. A review of transition metal-based double perovskite oxides for photovoltaic applications

    Next Materials · 2026-08-06

    Nangamso Nathaniel Nyangiwe, Ndzondelelo Bingwa

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