This review explores the role of AI in enhancing CO2 adsorption efficiency using biomass-derived materials.
The pressing need to reduce carbon dioxide emissions has driven recent advances in carbon capture technologies. Among these, adsorption has emerged as one of the most efficient and promising methods for CO2 sequestration. This review provides a comprehensive analysis of recent progress in biomass-derived activated carbon (AC) as a sustainable solution for carbon capture. It explores the influence of various biomass precursors, their composition, and the effects of chemical and thermal treatments on the textural properties and CO2 adsorption capacity of AC. The role of functional groups and pore structures in enhancing adsorption performance, particularly under humid conditions, is also examined. Additionally, the integration of artificial intelligence (AI)-driven technologies in process modeling and the discovery of optimized bio-based AC materials is highlighted. Classic adsorption kinetic models are reviewed to provide deeper insights into CO2 adsorption mechanisms and the efficiency of bio-based AC. The discussion underscores the necessity of continued research to enhance the properties, scalability, and cost-effectiveness of bio-based AC while leveraging AI-driven innovations to advance carbon capture and storage (CCS) solutions.
No takes yet. Share an insight, caveat, or question.
Hajiali et al. (2025) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: