| Atom table convolutional neural networks for an accurate prediction of compounds properties S Zeng, Y Zhao, G Li, R Wang, X Wang, J Ni NPJ Computational Materials 5 (1), 84, 2019 | 63 | 2019 |
| Identification of crystalline materials with ultra-low thermal conductivity based on machine learning study X Wang, S Zeng, Z Wang, J Ni The Journal of Physical Chemistry C 124 (16), 8488-8495, 2020 | 41 | 2020 |
| Broadband visual adaption and image recognition in a monolithic neuromorphic machine vision system Y Cai, F Wang, X Wang, S Li, Y Wang, J Yang, T Yan, X Zhan, F Wang, ... Advanced Functional Materials 33 (5), 2212917, 2023 | 34 | 2023 |
| Machine learning for hierarchical prediction of elastic properties in Fe-Cr-Al system R Wang, S Zeng, X Wang, J Ni Computational Materials Science 166, 119-123, 2019 | 24 | 2019 |
| Cubic halide perovskites as potential low thermal conductivity materials: A combined approach of machine learning and first-principles calculations X Wang, Y Zhao, S Zeng, Z Wang, Y Chen, J Ni Physical Review B 105 (1), 014310, 2022 | 18 | 2022 |
| Three-gap superconductivity in two-dimensional films Z Wang, S Zeng, Y Zhao, X Wang, J Ni Physical Review B 104 (17), 174519, 2021 | 13 | 2021 |
| Element-wise representations with ECNet for material property prediction and applications in high-entropy alloys X Wang, ND Tran, S Zeng, C Hou, Y Chen, J Ni npj Computational Materials 8 (1), 253, 2022 | 5 | 2022 |
| Interpretable machine learning to discover perovskites with high spontaneous polarization Y Sun, X Wang, C Hou, J Ni The Journal of Physical Chemistry C 127 (49), 23897-23905, 2023 | 2 | 2023 |
| Magnetic–Electronic Coupling in the Strained Bilayer CrSBr C Hou, X Wang, Y Sun, Y Lu, J Ni The Journal of Physical Chemistry C 127 (46), 22833-22841, 2023 | 2 | 2023 |
