Carbon dioxide hydrogenation to methanol: Process simulation and optimization studies

Angel Francis, Ramyashree M.S., S. Shanmuga Priya, S. Harish Kumar, K. Sudhakar, Wei Keen Fan, Muhammad Tahir

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

This work investigates process simulation and optimization as an efficient approach to mitigate global warming using carbon dioxide hydrogenation to methanol. Modeling and simulation of hydrogenation to methanol were studied using Aspen Plus V8. Cu/ZnO/Al2O3 catalyst is used to optimize parameters to enhance the reduction of CO2 to methanol. The effect of temperature, pressure, and the feed flow rate on CO2 conversion and CH3OH yield was reported. Response surface methodology (RSM) is used to analyze the chemical equilibrium of the CH3OH production process to obtain an optimal way of assuring a relatively higher CO2 conversion and CH3OH production rate. It helps to evaluate the optimum temperature, pressure, andH2/CO2 molar ratio to achieve maximum CO2 conversion and CH3OH yield. The impact of conversion and CH3OH yield was evaluated using surface plots. The RSM studies show optimized conditions for conversion and CH3OH yield at a temperature of 210 °C, a pressure of 55 bar, and a H2/CO2 concentration of 1:5. The anticipated CO2 conversion and CH3OH yield were 87.56% and 11.22%, respectively, whereas the simulation gave CO2 conversion of 87.65% and CH3OH yield of 11.39%. The generated quadratic model accurately predicts carbon dioxide conversion to methanol. The applicability of the model to forecast CO2 conversion and CH3OH yield is supported by the agreement between the simulated and expected results. This work can be considered a possible solution to overcome the thermodynamic difficulty by providing a higher CO2 conversion and would be beneficial for further investigation in industrial process.

Original languageEnglish
Pages (from-to)36418-36432
Number of pages15
JournalInternational Journal of Hydrogen Energy
Volume47
Issue number86
DOIs
Publication statusPublished - 22-10-2022

All Science Journal Classification (ASJC) codes

  • Renewable Energy, Sustainability and the Environment
  • Fuel Technology
  • Condensed Matter Physics
  • Energy Engineering and Power Technology

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