4.7 Article

Experimental and kinetic modeling studies of methanol synthesis from CO2 hydrogenation using In2O3 catalyst

期刊

CHEMICAL ENGINEERING JOURNAL
卷 416, 期 -, 页码 -

出版社

ELSEVIER SCIENCE SA
DOI: 10.1016/j.cej.2021.129120

关键词

Carbon capture and utilization (CCU); Methanol synthesis; CO2 hydrogenation, Indium oxide; Kinetic model

资金

  1. Swedish Energy Agency [474501, 48387-1]

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This study introduces a kinetic model based on LHHW mechanism for the hydrogenation of CO2 to methanol using indium oxide catalyst, and predicts the shift in methanol yield due to the equilibrium limitation and RWGS reaction. The developed model accurately predicts the trends in the experimental data, facilitating the development of reliable reactor and process designs.
Catalytic hydrogenation of CO2 to methanol has gained considerable interest for its significant role in CO2 utilization using heterogeneous catalysts. This study is the first to propose a kinetic model based on Langmuir-Hinshelwood-Hougen-Watson (LHHW) mechanism for CO2 hydrogenation to methanol over a highly effective indium oxide (In2O3) catalyst. The work focuses on different reaction conditions mainly revolving around the variation of operating temperature, total reactor pressure, H-2/CO2 molar feed ratio and weight hourly space velocity (WHSV) of the system. The experimental data were modeled using a competitive single-site kinetic model based on LHHW rate equations. A parameter optimization procedure was undertaken to determine the kinetic parameters of the developed rate equations. The model predicts that when the methanol synthesis reaction becomes equilibrium limited, the progress of the RWGS reaction forces the methanol yield to decrease due to the reversal of the methanol synthesis reaction. A mixture of CO2 and H-2 has been used as the reactor feed in all the cases. Significantly w.r.t. the CO2 partial pressure, the reaction rate for methanol synthesis initially increased and then slightly decreased indicating a varying order. The single-site model accurately predicted the trends in the experimental data which would enable the development of reliable reactor and process designs.

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