A universal biomass screening model for skeleton activated carbon based on TG data using CR method and peak-splitting technique

Skeleton activated carbon retains the natural cellulose skeleton structure of biomass, resulting in a large surface area and green preparation. However, various biomass types make it difficult to obtain which biomass under what conditions the skeleton can be preserved through experiments. Seeking the temperature range where oxidants react preferentially with carbonized lignin over carbonized cellulose is the key to the successful preparation of skeleton activated carbon. Herein, based on the assumption that combining kinetic modeling with peak-splitting technique and generalizing the model enables prediction of whether the biomass can be prepared into skeleton activated carbon and the preparation conditions based solely on its composition. The combination of the CR method and peak-splitting technique can be used to fit biomass’s pyrolysis process and obtain the reaction temperature window between oxidants and carbonized cellulose/lignin. To enhance universal applicability, modified parameters E’ and n were incorporated into the predictive model. Finally, a universal biomass screening model was established by correlating modified parameters with biomass composition, eliminating the need for extensive experimentation in traditional screening processes.