| High temperature shockwave stabilized single atoms Y Yao, Z Huang, P Xie, L Wu, L Ma, T Li, Z Pang, M Jiao, Z Liang, J Gao, ... Nature nanotechnology 14 (9), 851-857, 2019 | 328 | 2019 |
| Damage detection in a novel deep-learning framework: a robust method for feature extraction T Guo, L Wu, C Wang, Z Xu Structural Health Monitoring 19 (2), 424-442, 2020 | 92 | 2020 |
| Carbonized wood decorated with cobalt‐nickel binary nanoparticles as a low‐cost and efficient electrode for water splitting W Gan, L Wu, Y Wang, H Gao, L Gao, S Xiao, J Liu, Y Xie, T Li, J Li Advanced Functional Materials 31 (29), 2010951, 2021 | 67 | 2021 |
| Data‐driven high‐throughput rational design of double‐atom catalysts for oxygen evolution and reduction L Wu, T Guo, T Li Advanced Functional Materials 32 (31), 2203439, 2022 | 59 | 2022 |
| Rational design of transition metal single-atom electrocatalysts: a simulation-based, machine learning-accelerated study L Wu, T Guo, T Li Journal of Materials Chemistry A 8 (37), 19290-19299, 2020 | 59 | 2020 |
| Surface‐decorated high‐entropy alloy catalysts with significantly boosted activity and stability K Zeng, J Zhang, W Gao, L Wu, H Liu, J Gao, Z Li, J Zhou, T Li, Z Liang, ... Advanced Functional Materials 32 (33), 2204643, 2022 | 51 | 2022 |
| Machine learning-accelerated prediction of overpotential of oxygen evolution reaction of single-atom catalysts L Wu, T Guo, T Li IScience 24 (5), 2021 | 51 | 2021 |
| Hierarchical polyelemental nanoparticles as bifunctional catalysts for oxygen evolution and reduction reactions M Wu, M Cui, L Wu, S Hwang, C Yang, Q Xia, G Zhong, H Qiao, W Gan, ... Advanced Energy Materials 10 (25), 2001119, 2020 | 46 | 2020 |
| Stabilizing mechanism of single-atom catalysts on a defective carbon surface L Wu, S Hu, W Yu, S Shen, T Li npj Computational Materials 6 (1), 23, 2020 | 44 | 2020 |
| Interface engineering between multi‐elemental alloy nanoparticles and a carbon support toward stable catalysts T Li, Q Dong, Z Huang, L Wu, Y Yao, J Gao, X Wang, H Zhang, D Wang, ... Advanced Materials 34 (9), 2106436, 2022 | 42 | 2022 |
| Machine learning accelerated, high throughput, multi‐objective optimization of multiprincipal element alloys T Guo, L Wu, T Li Small 17 (42), 2102972, 2021 | 24 | 2021 |
| Stability of stacking fault tetrahedron in twin boundary bicrystal copper under shear L Wu, W Yu, S Hu, S Shen International Journal of Plasticity 97, 246-258, 2017 | 24 | 2017 |
| The critical roles of water in the processing, structure, and properties of nanocellulose S Jing, L Wu, AP Siciliano, C Chen, T Li, L Hu ACS nano 17 (22), 22196-22226, 2023 | 23 | 2023 |
| Adhesion properties of Cu (111)/α-quartz (0001) interfaces: A molecular dynamics study W Yu, L Wu, S Shen Materials Science and Engineering: A 695, 239-248, 2017 | 15 | 2017 |
| Size-dependent stability of stacking fault tetrahedron in coherent twin boundary bicrystal: Comparisons among Al, Ni, Cu and Ag L Wu, W Yu, S Hu, S Shen Computational Materials Science 155, 256-265, 2018 | 10 | 2018 |
| Radiation response of nanotwinned Cu under multiple-collision cascades L Wu, W Yu, S Hu, S Shen Journal of Nuclear Materials 505, 183-192, 2018 | 9 | 2018 |
| Shear response of grain boundary bicrystals with a stacking fault tetrahedron L Wu, W Yu, S Hu, S Shen Computational Materials Science 147, 137-144, 2018 | 8 | 2018 |
| Machine learning enabled rational design of atomic catalysts for electrochemical reactions L Wu, T Li Materials Chemistry Frontiers 7 (19), 4445-4459, 2023 | 4 | 2023 |
| Optimization of extrusion die of spherical plain bearings based on BP neural network and GA algorithm L Wu, X Yang China Mechanical Engineering 26 (10), 1351, 2015 | 4 | 2015 |
| A machine learning interatomic potential for high entropy alloys L Wu, T Li Journal of the Mechanics and Physics of Solids 187, 105639, 2024 | 3 | 2024 |
