Intensified CO₂ absorption process using a green solvent: rate-based modelling, sensitivity analysis, and scale-up

Ionic liquids (ILs) are recognized as environmentally friendly solvents due to their high CO₂ absorption capacity, ease of recovery, and chemical stability, making them a promising alternative to conventional solvents for CO₂ capture. In this study, a rate-based mathematical model was developed for a rotating packed bed (RPB) absorber employing 1-n-butyl-3-methylimidazolium hexafluorophosphate ([bmim][PF₆) as the solvent. The model incorporates mass, energy, and momentum balances, coupled with a thermodynamic model whose parameters were determined using experimental data. The rate-based model was validated against experimental results obtained from the RPB absorber. To enhance predictive accuracy, a sensitivity analysis of various mass transfer correlations was conducted, and simulations were performed based on the outcomes of this analysis. The model provided detailed radial profiles of pressure, gas and liquid flow rates, CO₂ concentration, temperature, volumetric mass transfer coefficients, and both gas- and liquid-phase resistances. The results indicated that the CO₂ capture efficiency and mass transfer coefficients in both phases increased with rotational speed along the bed’s radial direction. Furthermore, the RPB was designed for a flue gas stream from a fired heater in a petrochemical unit containing 10.74 mol % CO₂. The optimal liquid-to-gas ratio at a large scale was found to be 0.3 kg/kg, achieving a CO₂ removal efficiency of 98%. Under these conditions, the required motor power at an outer radius of 1.55 m was approximately 24.6 kW. Furthermore, comparison with a conventional packed bed showed that the liquid-phase volumetric mass transfer coefficient in the RPB was significantly higher, confirming its superior mass transfer performance.

Citation

Afkhamipour, M.; Shamsi, M.; Mousavian, S.; Borhani, T.N. Intensified CO2 Absorption Process Using a Green Solvent: Rate-Based Modelling, Sensitivity Analysis, and Scale-up. Processes 2025, 13, 3774. https://doi.org/10.3390/pr13123774

Type

Journal article

Language

en

Description

© 2025 The authors. Published by MDPI. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.3390/pr13123774

EISSN

2227-9717

Collections

Faculty of Science and Engineering