Prediction of structural properties of activated carbons derived from lignocellulosic biomass components using mixture design of experiments

There is significant interest in using biomass to produce activated carbons for applications such as environmental remediation, energy storage, and construction. To date, the research has primarily focused on exploring the potential of individual biomass sources. There is little research on how interactions between the fundamental components of lignocellulosic biomass affect activated carbons' structural properties, and, therefore, their suitability for various applications. This investigation sought to address this knowledge gap by exploring how the relative compositions of cellulose nanofibers, cellulose nanocrystals, and lignin affected the final properties of activated carbons produced through a two-step KOH activation process. A simplex-lattice mixture design was used to understand how the composition affected activated carbon yield, specific surface area, and micropore fraction. Mixture regression models showed that the specific surface area was highest when the activated carbon was composed of 16.7% cellulose nanofibers, 16.7% cellulose nanocrystals, and 66.7% lignin by mass. In addition, the micropore fraction was largest at 76.3% while also maintaining a high surface area, with a precursor mixture of 50% cellulose nanocrystals and 50% lignin by mass. The results of this investigation provide a foundation for future efforts to be able to predict, and tune, activated carbon properties based on biomass composition.