| Combined approach using mathematical modelling and artificial neural network for chemical industries: Steam methane reformer ND Vo, DH Oh, SH Hong, M Oh, CH Lee Applied energy 255, 113809, 2019 | 68 | 2019 |
| Dynamic-model-based artificial neural network for H2 recovery and CO2 capture from hydrogen tail gas ND Vo, DH Oh, JH Kang, M Oh, CH Lee Applied energy 273, 115263, 2020 | 51 | 2020 |
| Dynamic model and performance of an integrated sorption-enhanced steam methane reforming process with separators for the simultaneous blue H2 production and CO2 capture ND Vo, JH Kang, M Oh, CH Lee Chemical Engineering Journal 423, 130044, 2021 | 27 | 2021 |
| Pre-combustion CO2 capture using amine-based absorption process for blue H2 production from steam methane reformer HT Oh, J Kum, J Park, ND Vo, JH Kang, CH Lee Energy Conversion and Management 262, 115632, 2022 | 26 | 2022 |
| Moving boundary modeling for solid propellant combustion ND Vo, MY Jung, DH Oh, JS Park, I Moon, M Oh Combustion and Flame 189, 12-23, 2018 | 26 | 2018 |
| Actor-critic reinforcement learning to estimate the optimal operating conditions of the hydrocracking process DH Oh, D Adams, ND Vo, DQ Gbadago, CH Lee, M Oh Computers & Chemical Engineering 149, 107280, 2021 | 25 | 2021 |
| Proposal and surrogate-based cost-optimal design of an innovative green ammonia and electricity co-production system via liquid air energy storage M Qi, M Kim, ND Vo, L Yin, Y Liu, J Park, I Moon Applied Energy 314, 118965, 2022 | 24 | 2022 |
| Revisiting magnesium oxide to boost hydrogen production via water-gas shift reaction: Mechanistic study to economic evaluation S Jin, Y Park, G Bang, ND Vo, CH Lee Applied Catalysis B: Environmental 284, 119701, 2021 | 22 | 2021 |
| Sensitivity analysis and artificial neural network-based optimization for low-carbon H2 production via a sorption-enhanced steam methane reforming (SESMR) process integrated … ND Vo, JH Kang, DH Oh, MY Jung, K Chung, CH Lee International Journal of Hydrogen Energy 47 (2), 820-847, 2022 | 21 | 2022 |
| Prediction of CO2 capture capability of 0.5 MW MEA demo plant using three different deep learning pipelines DH Oh, ND Vo, JC Lee, JK You, D Lee, CH Lee Fuel 315, 123229, 2022 | 12 | 2022 |
| Strategies for flexible operation of power-to-X processes coupled with renewables M Qi, DN Vo, H Yu, CM Shu, C Cui, Y Liu, J Park, I Moon Renewable and Sustainable Energy Reviews 179, 113282, 2023 | 9 | 2023 |
| Design guideline for CO2 to methanol conversion process supported by generic model of various bed reactors ND Vo, M Oh, CH Lee Energy Conversion and Management 269, 116079, 2022 | 9 | 2022 |
| Modeling and simulation for acrylamide polymerization of super absorbent polymer GH Lee, ND Vo, RY Jeon, SW Han, SU Hong, M Oh Korean Journal of Chemical Engineering 35, 1791-1799, 2018 | 9 | 2018 |
| Techno-Economic Assessment of Natural Gas Combined Cycle Power Plants with Carbon Capture and Utilization Z Zhang, DH Oh, V Dat Nguyen, CH Lee, JC Lee Energy & Fuels 37 (8), 5961-5975, 2023 | 7 | 2023 |
| Performance and ANN-based optimization of an advanced process for wet CO2-to-Methanol using a catalytic fluidized bed reactor integrated with separators VD Nguyen, JH Chang, SH Hong, CH Lee Fuel 343, 128045, 2023 | 5 | 2023 |
| Enhancing energy efficiency of chemical absorption-based CO2 capture process with advanced waste-heat recovery modules at a high capture rate Z Zhang, DN Vo, J Kum, SH Hong, CH Lee Chemical Engineering Journal 472, 144918, 2023 | 4 | 2023 |
| Advanced process integration and machine learning-based optimization to enhance techno-economic-environmental performance of CO2 capture and conversion to methanol Z Zhang, DN Vo, TBH Nguyen, J Sun, CH Lee Energy, 130758, 2024 | 1 | 2024 |
| Comparative performance and machine learning-based optimization of TSA configurations for NH3 removal from NH3 cracking gas DN Vo, JH Chang, SH Hong, CH Lee Chemical Engineering Journal 475, 146195, 2023 | 1 | 2023 |
| Rigorous Development and Comparison of Multi-Dimensional Reactor Models Encompassing the Catalyst Domains for Steam Methane Reforming C Cui, DN Vo, Y Zhao, M Qi, M Xia, D Ramkrishna, CM Masuku Available at SSRN 4756527, 0 | | |
Chang-Ha LeeYonsei University Department of Chemical and Biomolecular Engineeringכתובת אימייל מאומתת בדומיין yonsei.ac.kr
