Integrated rotating packed bed reactor design for post combustion carbon capture: Parametric analysis, optimization and economic viability

Worldwide deployment of carbon capture (CC) technologies has become inevitable due to vast usage of fossil or carbon-based fuels. To do so, chemical absorption-based CC technology has drawn significant attention due to its potential of capturing higher rates of CO 2 even at lower pressure ranges. Nonetheless, this technique is an energy intensive and requires a huge amount of capital for its deployment. In contrast, rotating packed bed (RPB) reactor technology is relatively new and can provide an ultimate solution to conventional absorption systems due to its lower cost and efficient operation. However, a full-scale CC using RPB technology has been underexplored, with prior studies limited to lab-scale setups or isolated unit designs, often overlooking simultaneous modeling of absorber and regenerator into a continuous loop. Therefore, this study fills the current gap by presenting a comprehensive design and analysis of a full-scale post combustion carbon capture (PCC) process evaluating three different MEA concentrations, i.e., 30, 45, and 60 wt%, and three lean loadings 0.16, 0.24, and 0.3. A cross-platform integration of Aspen Plus and MATLAB was employed to harness computational capabilities and accurately predict thermodynamic and transport properties. Initial parametric analysis demonstrated up to 90 % height reduction in the absorber and 80 % in the regenerator, with packing volumes shrinking by over 95 % compared to conventional packed beds. To capture the complex trade-offs between liquid-to-gas ratio (L/G), lean loading, rotor speeds, and Z/r ratios, a genetic algorithm–driven optimization was applied which resulted in up to 27 % reduction in total annualized cost (84 to 60.99 M$/yr) as compared to initial design, and observed 65 % reduction in total cost when compared to conventional packed bed process. Subsequently, CC cost reduced from $224.6/tCO 2 to $77.88/tCO 2 . These findings provide a robust, scalable framework that paves the way for next-gen energy and cost-efficient carbon capture solutions, offering an alternative to conventional systems. • Full-scale PCC with RPB evaluated at 30, 45 and 60 wt% MEA and three lean loadings. • Cross-platform Aspen Plus–MATLAB integration for accurate property prediction. • Packing volume of absorber cut by up to 95 % and regenerator up to 73 % versus packed bed. • Genetic-algorithm optimization lowered TAC to M$60.99/yr – up to 27 % savings. • Carbon capture cost dropped from $224.6/tCO2 to $77.88/tCO2.