Lee, Hee W. Kim, Kyeongsu An, JinJoo Na, Jonggeol Kim, Honggon Lee, Hyunjoo Lee, Ung 2024-01-19T16:34:22Z 2024-01-19T16:34:22Z 2021-09-05 2020-09 0363-907X https://pubs.kist.re.kr/handle/201004/118172 Methanol production via direct CO2 hydrogenation is one of the most promising means of utilizing greenhouse gases owing to the significant market for methanol and the potential to simultaneously reduce CO2 emissions. However, the practical applications of this process still suffer from high production costs owing to the expensive raw materials required and the severe operating conditions. Herein, we propose an economically attractive methanol production process that also works to sequester CO2, developed through technoeconomic optimization. This economically optimized process design and the associated operating conditions were simultaneously obtained from among thousands of possible configurations using a superstructure optimization. A modified machine learning-based optimization algorithm was also employed to efficiently achieve this complex superstructure optimization. The optimum process design involves a multistage reactor together with an interstage product recovery system and substantially improves the CO2 conversion to greater than 52%. Consequently, the revenue obtained from methanol production changes from a $4.3 deficit to a $2.5 profit per ton. In addition, the proposed process is capable of generating the same amount of methanol with only half the CO2 emissions associated with conventional methanol production methods. A comprehensive sensitivity analysis is also provided along with the optimum process design to identify the influence of various technoeconomic parameters. English WILEY CARBON-DIOXIDE HYDROGENATION MULTIOBJECTIVE OPTIMIZATION SENSITIVITY-ANALYSIS CAPTURED CO2 CATALYST REACTOR CONVERSION SIMULATION SOLVENT SYSTEMS Toward the practical application of direct CO2 hydrogenation technology for methanol production Article 10.1002/er.5573 1 INTERNATIONAL JOURNAL OF ENERGY RESEARCH, v.44, no.11, pp.8781 - 8798 INTERNATIONAL JOURNAL OF ENERGY RESEARCH 44 11 8781 8798 scie scopus 000539013800001 2-s2.0-85086087053 Energy & Fuels Nuclear Science & Technology Energy & Fuels Nuclear Science & Technology Article CARBON-DIOXIDE HYDROGENATION MULTIOBJECTIVE OPTIMIZATION SENSITIVITY-ANALYSIS CAPTURED CO2 CATALYST REACTOR CONVERSION SIMULATION SOLVENT SYSTEMS Bayesian optimization CO2 hydrogenation Methanol superstructure technoeconomic optimization