Advances in amine-based absorption solvent engineering: Co-solvent strategies toward low-energy post-combustion CO₂ capture

• Co-solvents improve CO₂ capture efficiency in amine-based solvent systems. • Energy demand for CO₂ desorption is reduced with co-solvents being applied. • The absorption rate and degradation of solvents should be investigated. • Nanofluids and rotating packed beds improve CO₂ mass transfer efficiently. • Future research focuses on capture solvent development and process intensification. The continuous rise in anthropogenic CO₂ emissions from fossil fuel combustion underscores the urgency of developing efficient carbon capture technologies. Among various methods, post-combustion CO₂ capture using amine-based solvents remains the most mature and industrially viable. However, conventional aqueous-amine systems suffer from high regeneration energy demands, solvent degradation, and operational challenges. This study systematically reviews recent advances in amine-based solvents and co-solvent formulations designed to enhance absorption efficiency and reduce energy consumption. The discussion covers (i) thermodynamic and kinetic fundamentals of amine–CO₂ interactions, (ii) the effects of co-solvent addition on viscosity, mass transfer, and thermal stability, and (iii) the influence of operating parameters on cyclic capacity and regeneration energy. Emerging classes such as water-lean, biphasic, and nanoparticle-enhanced systems are critically compared based on their absorption kinetics, desorption enthalpy, and stability under cyclic operation. Bibliometric analysis is used to map the evolution of research trends in solvent engineering. The review highlights that co-solvents such as glycols, sulfoxides, and glycol ethers can lower reboiler duty by up to 60% relative to aqueous monoethanolamine while maintaining comparable absorption performance. Remaining challenges include viscosity control, long-term solvent degradation, and scalability. Future research should focus on optimizing solvent composition, integrating process intensification techniques, and developing predictive models linking molecular structure to process performance.