| Insights from machine learning techniques for predicting the efficiency of fullerene derivatives‐based ternary organic solar cells at ternary blend design MH Lee Advanced Energy Materials 9 (26), 1900891, 2019 | 89 | 2019 |
| Robust random forest based non-fullerene organic solar cells efficiency prediction MH Lee Organic Electronics 76, 105465, 2020 | 62 | 2020 |
| MoO 3-induced oxidation doping of PEDOT: PSS for high performance full-solution-processed inverted quantum-dot light emitting diodes MH Lee, L Chen, N Li, F Zhu Journal of Materials Chemistry C 5 (40), 10555-10561, 2017 | 56 | 2017 |
| Recent advances in solution‐processable organic photodetectors and applications in flexible electronics Z Lan, MH Lee, F Zhu Advanced Intelligent Systems 4 (3), 2100167, 2022 | 44 | 2022 |
| Interface dipole for remarkable efficiency enhancement in all-solution-processable transparent inverted quantum dot light-emitting diodes L Chen, MH Lee, Y Wang, YS Lau, AA Syed, F Zhu Journal of Materials Chemistry C 6 (10), 2596-2603, 2018 | 34 | 2018 |
| Identifying correlation between the open-circuit voltage and the frontier orbital energies of non-fullerene organic solar cells based on interpretable machine-learning approaches MH Lee Solar Energy 234, 360-367, 2022 | 26 | 2022 |
| A Machine Learning–Based Design Rule for Improved Open‐Circuit Voltage in Ternary Organic Solar Cells MH Lee Advanced Intelligent Systems 2 (1), 1900108, 2020 | 26 | 2020 |
| Machine learning for understanding the relationship between the charge transport mobility and electronic energy levels for n‐type organic field‐effect transistors MH Lee Advanced Electronic Materials 5 (12), 1900573, 2019 | 25 | 2019 |
| Performance and matching band structure analysis of tandem organic solar cells using machine learning approaches MH Lee Energy Technology 8 (3), 1900974, 2020 | 24 | 2020 |
| A versatile solution-processed MoO3/Au nanoparticles/MoO3 hole contact for high performing PEDOT: PSS-free organic solar cells W Zhang, W Lan, MH Lee, J Singh, F Zhu Organic Electronics 52, 1-6, 2018 | 22 | 2018 |
| Identification of host–guest systems in green TADF-based OLEDs with energy level matching based on a machine-learning study MH Lee Physical Chemistry Chemical Physics 22 (28), 16378-16386, 2020 | 19 | 2020 |
| Solution-processable organic-inorganic hybrid hole injection layer for high efficiency phosphorescent organic light-emitting diodes MH Lee, WH Choi, F Zhu Optics Express 24 (6), A592-A603, 2016 | 19 | 2016 |
| Predicting and analyzing the fill factor of non-fullerene organic solar cells based on material properties and interpretable machine-learning strategies MH Lee Solar Energy 267, 112191, 2024 | 4 | 2024 |
| Interpretable machine learning model for the highly accurate prediction of efficiency of ternary organic solar cells based on nonfullerene acceptor using effective molecular … MH Lee Solar RRL 7 (14), 2300307, 2023 | 4 | 2023 |
| Interpretable machine-learning for predicting power conversion efficiency of non-halogenated green solvent-processed organic solar cells based on Hansen solubility parameters … MH Lee Solar Energy 261, 7-13, 2023 | 3 | 2023 |
| Frontier Molecular Orbital Offset as an Empirical Descriptor for Predicting Short Circuit Current of Nonfullerene Organic Solar Cells MH Lee Solar RRL, 2300533, 2023 | 3 | 2023 |
| Investigation of the open-circuit voltage of non-fullerene acceptors-based ternary organic solar cells based on interpretable machine-learning approach and chemically inspired … MH Lee Journal of Photochemistry and Photobiology A: Chemistry 450, 115430, 2024 | 1 | 2024 |
Furong ZhuProfessor of Physics, Hong Kong Baptist University在 hkbu.edu.hk 的电子邮件经过验证
