李旻軒 助理教授
| 專門學門 | 運用智慧科技建置風險評估技術、智慧環境感測技術、基於機器學習之綠色能源元件優化技術、智慧醫療 |
| 研究方向 | 複合型導電聚合物水凝膠應用於智慧生理監測系統之研究、低成本有機半導體元件應用於液/氣態環境感測之研究、運用穿戴式裝置應用於作業勞工危害評估之研究(例如:熱危害暴露及肌肉骨骼傷病) |
PUBLICATIONS
List of selected publications (2017-2023)
| Min-Hsuan Lee, Investigation of the open-circuit voltage of non-fullerene acceptors-based ternary organic solar cells based on interpretable machine-learning approach and chemically inspired descriptors, Journal of Photochemistry and Photobiology A: Chemistry, 450, 2024, 115430 |
| Min-Hsuan Lee, Predicting and Analyzing the Fill Factor of Non-Fullerene Organic Solar Cells Based on Material Properties and Interpretable Machine-Learning Strategies, Solar Energy, Accepted (IF= 7.1) |
| Lee, M. (2023), Frontier Molecular Orbital Offset as an Empirical Descriptor for Predicting Short Circuit Current of Nonfullerene Organic Solar Cells. Sol. RRL, 7: 2300533 (IF=9.178) |
| Lee, M. (2023), Interpretable Machine Learning Model for the Highly Accurate Prediction of Efficiency of Ternary Organic Solar Cells Based on Nonfullerene Acceptor using Effective Molecular Descriptors. Sol. RRL, 7: 2300307 (IF=9.178) |
| Min-Hsuan Lee, Interpretable machine-learning for predicting power conversion efficiency of non-halogenated green solvent-processed organic solar cells based on Hansen solubility parameters and molecular weights of polymers, Solar Energy, 261, 2023, 7-13 (IF= 7.18) |
| Min-Hsuan Lee, Lixiang Chen, Ning Lia and Furong Zhu, MoO3-induced oxidation doping of PEDOT:PSS for high performance full- solution-processed inverted quantum-dot light emitting diodes. J. Mater. Chem. C, 5, 10555-10561(2017) 第一作者 |
| Lixiang Chen,†Min-Hsuan Lee,† Yiwen Wang, Ying Suet Lau, Ali Asgher Syed, and Furong Zhu, Interface Dipole for Remarkable Efficiency Enhancement in All solution processable Transparent Inverted Quantum Dot Light emitting Diodes. J. Mater. Chem. C, 2018,6, 2596-2603. 共同第一作者 |
| Weidong Zhang, Weixia Lan, Min-Hsuan Lee, Jai Singh, Furong Zhu, A versatile solution-processed MoO3/Au nanoparticles/MoO3 hole contact for high performing PEDOT:PSS-free organic solar cells. Organic Electronics, 52,1-6 (2018) |
| Min-Hsuan Lee, Insights from machine learning techniques for predicting the efficiency of fullerene derivatives-based ternary organic solar cells at ternary blend design, Advanced Energy Materials. Adv. Energy Mater. 2019, 1900891第一作者/通訊作者 |
| Min-Hsuan Lee, Machine Learning for Understanding the Relationship between the Charge Transport Mobility and Electronic Energy Levels for n‐Type Organic Field‐Effect Transistors. Adv. Electron. Mater. 2019, 1900573. 第一作者/通訊作者 |
| Min-Hsuan Lee, Robust random forest based non-fullerene organic solar cells efficiency prediction, Organic Electronics, 76, 2020,105465 第一作者/通訊作者 |
| Min-Hsuan Lee, A Machine Learning–Based Design Rule for Improved Open‐Circuit Voltage in Ternary Organic Solar Cells. Adv. Intell. Syst., 2020, 2: 1900108. 第一作者/通訊作者 |
| Min-Hsuan Lee, Performance and Matching Band Structure Analysis of Tandem Organic Solar Cells Using Machine Learning Approaches. Energy Technol., 2020, 8: 1900974 第一作者/通訊作者 |
| Min-Hsuan Lee, Identification of host–guest systems in green TADF-based OLEDs with energy level matching based on a machine-learning study, Phys. Chem. Chem. Phys., 2020,22, 16378-16386第一作者/通訊作者 |
| Lan, Z., Lee, M.* and Zhu, F.* (2021), Recent Advances in Solution-Processable Organic Photodetectors and Applications in Flexible Electronics. Adv. Intell. Syst. 2100167 (Invited Review) 通訊作者 |
| Min-Hsuan Lee, Identifying correlation between the open-circuit voltage and the frontier orbital energies of non-fullerene organic solar cells based on interpretable machine-learning approaches, Solar Energy, 234, 2022, 360-367第一作者/通訊作者 |