A CO2 utilization framework for liquid fuels and chemical production: techno-economic and environmental analysis TN Do, C You, J Kim Energy & Environmental Science 15 (1), 169-184, 2022 | 71 | 2022 |
Process development and techno-economic evaluation of methanol production by direct CO2 hydrogenation using solar-thermal energy TN Do, J Kim Journal of CO2 Utilization 33, 461-472, 2019 | 70 | 2019 |
Green C2-C4 hydrocarbon production through direct CO2 hydrogenation with renewable hydrogen: Process development and techno-economic analysis TN Do, J Kim Energy conversion and Management 214, 112866, 2020 | 68 | 2020 |
Carbon-neutral hydrogen production from natural gas via electrified steam reforming: Techno-economic-environmental perspective TN Do, H Kwon, M Park, C Kim, YT Kim, J Kim Energy Conversion and Management 279, 116758, 2023 | 15 | 2023 |
Film formation in Y (4NO2Cin) 3 compound on 6061 aluminum alloy to protect against corrosion in chloride ion media ND Nam, TV Hung, DT Ngan, NLT Hung, TKN Hoi Journal of the Taiwan Institute of Chemical Engineers 67, 495-504, 2016 | 13 | 2016 |
Rethinking of conventional Gas-to-Liquid via dimethyl ether intermediate incorporating renewable energy against Power-to-Liquid TN Do, YG Hur, HE Jeong, JW Chung, W Won, J Kim Energy Conversion and Management 261, 115643, 2022 | 12 | 2022 |
Energy-efficient liquid hydrogen production using cold energy in liquefied natural gas: Process intensification and techno-economic analysis H Kwon, TN Do, J Kim Journal of Cleaner Production 380, 135034, 2022 | 11 | 2022 |
Comprehensive decision framework combining price prediction and production-planning models for strategic operation of a petrochemical industry H Kwon, TN Do, J Kim Industrial & Engineering Chemistry Research 59 (25), 11610-11620, 2020 | 10 | 2020 |
Optimization-based integrated decision model for smart resource management in the petrochemical industry H Kwon, TN Do, J Kim Journal of Industrial and Engineering Chemistry 113, 232-246, 2022 | 5 | 2022 |
Optimization-based framework for technical, economic, and environmental performance assessment of CO2 utilization strategies TN Do, H Chung, Y Lee, C Kim, B Kim, J Kim IFAC-PapersOnLine 55 (7), 412-417, 2022 | 3 | 2022 |
Potentials and benefit assessment of green fuels from residue gas via gas-to-liquid TN Do, YG Hur, H Chung, J Kim Renewable and Sustainable Energy Reviews 182, 113388, 2023 | 2 | 2023 |
Superstructure optimization model for design and analysis of CO2-to-fuels strategies TN Do, C You, H Chung, J Kim Computers & Chemical Engineering 170, 108136, 2023 | 2 | 2023 |
An optimization model for the market-responsive operation of naphtha cracking process with price prediction H Kwon, TN Do, W Won, J Kim Chemical Engineering Research and Design 188, 681-693, 2022 | 2 | 2022 |
Machine learning-based approach to identify the optimal design and operation condition of organic solvent nanofiltration (OSN) C Kim, C You, M Park, D Jang, S Lee, J Kim Computer Aided Chemical Engineering 50, 933-938, 2021 | 2 | 2021 |
Technical and Economic Feasibility of Direct Methane Conversion for Hydrocarbon Production: Process Design and Techno-economic Analysis TN Do, YT Kim, J Kim Computer Aided Chemical Engineering 48, 1015-1020, 2020 | 2 | 2020 |
Advanced Design and Comparative Analysis of Methanol Production Routes from CO2 and Renewable H2: via Syngas vs. Direct Hydrogenation Processes S Cho, TN Do, J Kim International Journal of Energy Research 2023, 2023 | 1 | 2023 |
Gas-to-liquid strategy for liquid fuel production from industrial residue gases: Process development and technoeconomic analysis TN Do, C You, J Kim Computer Aided Chemical Engineering 50, 1605-1610, 2021 | 1 | 2021 |
A Hybrid Catalytic Route to Ethanol from Residue Gases Via the Dimethyl Ether and Methyl Acetate Synthesis: Process Design and Techno-Economic Analysis M Park, C You, C Kim, H Yang, TN Do, J Kim 2023 AIChE Annual Meeting, 2023 | | 2023 |
Upcycling Steelwork Residue Gas to High-Value Products TN Do, H Chung, C You, M Park, J Kim 2023 AIChE Annual Meeting, 2023 | | 2023 |
Machine learning-based analysis of the physio-chemical properties for the predictive thickness control of atomic layer deposition C Kim, TN Do, J Kim IFAC-PapersOnLine 55 (7), 626-631, 2022 | | 2022 |