| Accelerated discovery of stable lead-free hybrid organic-inorganic perovskites via machine learning S Lu, Q Zhou, Y Ouyang, Y Guo, Q Li, J Wang Nature communications 9 (1), 3405, 2018 | 577 | 2018 |
| Coupling a crystal graph multilayer descriptor to active learning for rapid discovery of 2D ferromagnetic semiconductors/half‐metals/metals S Lu, Q Zhou, Y Guo, Y Zhang, Y Wu, J Wang Advanced Materials 32 (29), 2002658, 2020 | 102 | 2020 |
| Rapid discovery of ferroelectric photovoltaic perovskites and material descriptors via machine learning S Lu, Q Zhou, L Ma, Y Guo, J Wang Small Methods 3 (11), 1900360, 2019 | 82 | 2019 |
| Property-oriented material design based on a data-driven machine learning technique Q Zhou, S Lu, Y Wu, J Wang The journal of physical chemistry letters 11 (10), 3920-3927, 2020 | 64 | 2020 |
| Perspective on theoretical methods and modeling relating to electro-catalysis processes Q Li, Y Ouyang, S Lu, X Bai, Y Zhang, L Shi, C Ling, J Wang Chemical Communications 56 (69), 9937-9949, 2020 | 58 | 2020 |
| A universal descriptor for complicated interfacial effects on electrochemical reduction reactions C Ren, S Lu, Y Wu, Y Ouyang, Y Zhang, Q Li, C Ling, J Wang Journal of the American Chemical Society 144 (28), 12874-12883, 2022 | 52 | 2022 |
| On-the-fly interpretable machine learning for rapid discovery of two-dimensional ferromagnets with high Curie temperature S Lu, Q Zhou, Y Guo, J Wang Chem 8 (3), 769-783, 2022 | 39 | 2022 |
| Accelerated discovery of single‐atom catalysts for nitrogen fixation via machine learning S Zhang, S Lu, P Zhang, J Tian, L Shi, C Ling, Q Zhou, J Wang Energy & Environmental Materials 6 (1), e12304, 2023 | 28 | 2023 |
| Accelerated design of promising mixed lead-free double halide organic–inorganic perovskites for photovoltaics using machine learning Y Wu, S Lu, MG Ju, Q Zhou, J Wang Nanoscale 13 (28), 12250-12259, 2021 | 24 | 2021 |
| How computations accelerate electrocatalyst discovery C Ling, Y Cui, S Lu, X Bai, J Wang Chem 8 (6), 1575-1610, 2022 | 23 | 2022 |
| Two‐Dimensional Perovskites with Tunable Room‐Temperature Phosphorescence Y Wu, S Lu, Q Zhou, MG Ju, XC Zeng, J Wang Advanced Functional Materials 32 (39), 2204579, 2022 | 17 | 2022 |
| Magnetism and hybrid improper ferroelectricity in LaMO 3/YMO 3 superlattices P Zhou, S Lu, C Li, C Zhong, Z Zhao, L Qu, Y Min, Z Dong, N Zhang, ... Physical Chemistry Chemical Physics 21 (36), 20132-20136, 2019 | 7 | 2019 |
| Inverse design with deep generative models: next step in materials discovery S Lu, Q Zhou, X Chen, Z Song, J Wang National science review 9 (8), nwac111, 2022 | 6 | 2022 |
| Accurate property prediction with interpretable machine learning model for small datasets via transformed atom vector X Chen, S Lu, X Wan, Q Chen, Q Zhou, J Wang Physical Review Materials 6 (12), 123803, 2022 | 5 | 2022 |
| Coexistence of Semiconducting Ferromagnetics and Piezoelectrics down 2D Limit from Non van der Waals Antiferromagnetic LiNbO3-Type FeTiO3 Y Guo, Y Zhang, S Lu, X Zhang, Q Zhou, S Yuan, J Wang The Journal of Physical Chemistry Letters 13 (8), 1991-1999, 2022 | 5 | 2022 |
| Universal machine learning aided synthesis approach of two-dimensional perovskites in a typical laboratory Y Wu, CF Wang, MG Ju, Q Jia, Q Zhou, S Lu, X Gao, Y Zhang, J Wang Nature Communications 15 (1), 138, 2024 | 2 | 2024 |
| Adaptive Design of Alloys for CO2 Activation and Methanation via Reinforcement Learning Monte Carlo Tree Search Algorithm Z Song, Q Zhou, S Lu, S Dieb, C Ling, J Wang The Journal of Physical Chemistry Letters 14 (14), 3594-3601, 2023 | 2 | 2023 |
| Accurate energy prediction of large-scale defective two-dimensional materials via deep learning Y Ma, S Lu, Y Zhang, T Zhang, Q Zhou, J Wang Applied Physics Letters 120 (21), 2022 | 2 | 2022 |
| Machine Learning Accelerated Insights of Perovskite Materials S Lu, Y Wu, MG Ju, J Wang Artificial Intelligence for Materials Science, 197-223, 2021 | 1 | 2021 |
| On the Uncertainty Estimates of Equivariant-Neural-Network-Ensembles Interatomic Potentials S Lu, LM Ghiringhelli, C Carbogno, J Wang, M Scheffler arXiv preprint arXiv:2309.00195, 2023 | | 2023 |
Jinlan WangChief Professor of Physics, Southeast University, ChinaEmail verificata su seu.edu.cn
