Biomass waste-derived porous carbons (BWDPCs) are a class of complex materials that are widely used in sustainable waste management and carbon capture. However, their diverse textural properties, the presence of various functional groups, and the varied temperatures and pressures to which they are subjected during CO₂ adsorption make it challenging to understand the underlying mechanism of CO₂ adsorption. Here, we compiled a data set including 527 data points collected from peer-reviewed publications and applied machine learning to systematically map CO₂ adsorption as a function of the textural and compositional properties of BWDPCs and adsorption parameters. Various tree-based models were devised, where the gradient boosting decision trees (GBDTs) had the best predictive performance with R² of 0.98 and 0.84 on the training and test data, respectively. Further, the BWDPCs in the compiled data set were classified into regular porous carbons (RPCs) and heteroatom-doped porous carbons (HDPCs), where again the GBDT model had R² of 0.99 and 0.98 on the training and 0.86 and 0.79 on the test data for the RPCs and HDPCs, respectively. Feature importance revealed the significance of adsorption parameters, textural properties, and compositional properties in the order of precedence for BWDPC-based CO₂ adsorption, effectively guiding the synthesis of porous carbons for CO₂ adsorption applications.

Microporous carbon compartments (MCCs) were developed via controlled carbonization of wheat flour producing large cavities that allow CO₂ gas molecules to access micropores and adsorb effectively. KOH activation of MCCs was conducted at 700 °C with varying mass ratios of KOH/C ranging from 1 to 5, and the effects of activation conditions on the prepared carbon materials in terms of the characteristics and behavior of CO₂ adsorption were investigated. Textural properties, such as specific surface area and total pore volume, linearly increased with the KOH/C ratio, attributed to the development of pores and enlargement of pores within carbon. The highest CO₂ adsorption capacities of 5.70 mol kg⁻¹ at 0 °C and 3.48 mol kg⁻¹ at 25 °C were obtained for MCC activated with a KOH/C ratio of 3 (MCC-K3). In addition, CO₂ adsorption uptake was significantly dependent on the volume of narrow micropores with a pore size of less than 0.8 nm rather than the volume of larger pores or surface area. MCC-K3 also exhibited excellent cyclic stability, facile regeneration, and rapid adsorption kinetics. As compared to the pseudo-first-order model, the pseudo-second-order kinetic model described the experimental adsorption data methodically.