| All-optical mass sensing with coupled mechanical resonator systems JJ Li, KD Zhu Physics Reports 525 (3), 223-254, 2013 | 144 | 2013 |
| Surface-Electronic-State-Modulated, Single-Crystalline (001) TiO2 Nanosheets for Sensitive Electrochemical Sensing of Heavy-Metal Ions WY Zhou, JY Liu, JY Song, JJ Li, JH Liu, XJ Huang Analytical chemistry 89 (6), 3386-3394, 2017 | 104 | 2017 |
| A design aid for crystal growth engineering J Li, CJ Tilbury, SH Kim, MF Doherty Progress in Materials Science 82, 1-38, 2016 | 95 | 2016 |
| Ab initio molecular crystal structures, spectra, and phase diagrams S Hirata, K Gilliard, X He, J Li, O Sode Accounts of chemical research 47 (9), 2721-2730, 2014 | 94 | 2014 |
| Three-dimensional graphene-based nanocomposites for high energy density Li-ion batteries JY Liu, XX Li, JR Huang, JJ Li, P Zhou, JH Liu, XJ Huang Journal of Materials Chemistry A 5 (13), 5977-5994, 2017 | 81 | 2017 |
| A solid–solid phase transition in carbon dioxide at high pressures and intermediate temperatures J Li, O Sode, GA Voth, S Hirata Nature communications 4 (1), 2647, 2013 | 71 | 2013 |
| Nonlinear optical mass sensor with an optomechanical microresonator JJ Li, KD Zhu Applied Physics Letters 101 (14), 2012 | 59 | 2012 |
| A machine learning based morphological classification of 14,245 radio agns selected from the best–heckman sample Z Ma, H Xu, J Zhu, D Hu, W Li, C Shan, Z Zhu, L Gu, J Li, C Liu, X Wu The Astrophysical Journal Supplement Series 240 (2), 34, 2019 | 58 | 2019 |
| Ultra-fast and accurate binding energy prediction of shuttle effect-suppressive sulfur hosts for lithium-sulfur batteries using machine learning H Zhang, Z Wang, J Ren, J Liu, J Li Energy Storage Materials 35, 88-98, 2021 | 48 | 2021 |
| Rate expressions for kink attachment and detachment during crystal growth J Li, CJ Tilbury, MN Joswiak, B Peters, MF Doherty Crystal Growth & Design 16 (6), 3313-3322, 2016 | 46 | 2016 |
| Steady state morphologies of paracetamol crystal from different solvents J Li, MF Doherty Crystal Growth & Design 17 (2), 659-670, 2017 | 43 | 2017 |
| Accelerated discovery of stable spinels in energy systems via machine learning Z Wang, H Zhang, J Li Nano Energy 81, 105665, 2021 | 42 | 2021 |
| Engineering early prediction of supercapacitors’ cycle life using neural networks J Ren, X Lin, J Liu, T Han, Z Wang, H Zhang, J Li Materials Today Energy 18, 100537, 2020 | 41 | 2020 |
| Coupling-rate determination based on radiation-pressure-induced normal mode splitting in cavity optomechanical systems W He, JJ Li, KD Zhu Optics letters 35 (3), 339-341, 2010 | 38 | 2010 |
| Modeling olanzapine solution growth morphologies Y Sun, CJ Tilbury, SM Reutzel-Edens, RM Bhardwaj, J Li, MF Doherty Crystal Growth & Design 18 (2), 905-911, 2018 | 37 | 2018 |
| Potential inhibitors for the novel coronavirus (SARS-CoV-2) Y Han, Z Wang, J Ren, Z Wei, J Li Briefings in Bioinformatics 22 (2), 1225-1231, 2021 | 36 | 2021 |
| Deep learning for ultra-fast and high precision screening of energy materials Z Wang, Q Wang, Y Han, Y Ma, H Zhao, A Nowak, J Li Energy Storage Materials 39, 45-53, 2021 | 35 | 2021 |
| Predicting the phase diagram of solid carbon dioxide at high pressure from first principles Y Han, J Liu, L Huang, X He, J Li npj Quantum Materials 4 (1), 10, 2019 | 35 | 2019 |
| A machine learning shortcut for screening the spinel structures of Mg/Zn ion battery cathodes with a high conductivity and rapid ion kinetics J Cai, Z Wang, S Wu, Y Han, J Li Energy Storage Materials 42, 277-285, 2021 | 33 | 2021 |
| Combining the fragmentation approach and neural network potential energy surfaces of fragments for accurate calculation of protein energy Z Wang, Y Han, J Li, X He The Journal of Physical Chemistry B 124 (15), 3027-3035, 2020 | 33 | 2020 |
