(400d) Understanding the Transport and Reaction Kinetics in Plant Biomass Pretreatment Processes Using Raman Spectroscopy Images and Modeling

The renewable nature of plant biomass makes it an ideal raw material for the production of a wide variety of bio-based products that include pulp and paper, bioplastics, biofuels, wood plastic composites etc. The first step in the conversion process is the pretreatment step, which achieves the disruption of the recalcitrant structure of lignocellulose and increases the efficiency of the subsequent hydrolysis. During this process, one or more of the cell wall components are dissolved. The structure and topochemistry of the plant cell wall significantly affect the transport and reaction during the pretreatment process. Hence, it is extremely important to develop a fundamental understanding of the underlying process in order to develop effective pretreatment methods.

In the current work, a stochastic dynamic model using 3D structure of plant biomass is presented to evaluate the transport and reaction behavior of lignin dissolution during pretreatment processes. The structure and topochemical changes in lignin during pretreatment are obtained using Raman spectroscopy. The transport-reaction model is based on a hybrid random walk process for diffusion of the pretreatment reagent followed by reaction with the cell wall components. The reagent walkers diffuse through the lumen and pore spaces of the cell wall and follow a random walk path until they encounter the cell wall interface. At the interface, based on the probability of reaction and the ratio of diffusivities between the pore space and cell wall, they either react with the lignin in the cell wall or diffuse further into the cell wall and react inside the cell wall. The probability of reaction is based on the Thiele modulus which accounts for both diffusion and reaction. Lignin dissolution is modeled as a pseudo first order reaction where lignin is the limiting reactant. This process is continued with number of reagent walkers to simulate the entire course of the reaction and the results are compared with experimental data. This stochastic dynamic approach keeps track of the bulk concentration and spatial distribution of both lignin and the reagent used for pretreatment in real time. Additionally, an overall transport rate coefficient K_T and a time dependent effective rate constant K_eff, which accounts for both transport and reaction, are determined. This model enables us to determine the effect of 3D structure as well as the effective diffusivity and local reaction kinetics on the overall pretreatment process and structural evolution. This will provide additional fundamental insights on biomass pretreatment and conversion process and develop effective biomass conversion strategies. Even more broadly, this can provide additional opportunities for better understanding the role of structure and reaction kinetics in porous materials such as catalyst pellets and their wide-ranging applications.