Multiscale modeling, experimental validation, and optimal operation for a batch pulp digester with a novel solvent

Abstract

The rising need for reducing the usage and wastage of paper has mandated the production of mechanically superior papers, and it is known that maintaining a high degree of polymerization (DP) for cellulose microfibers ensures the high tensile strength of the pulp. To mitigate the cellulose degradation and establish the optimum operating strategies of the pulping processes, it is necessary to understand the effect of the operation conditions on cellulose DP. In this sense, we proposed a novel multiscale model which can predict the mesoscopic properties (e.g., Kappa number, and fiber morphology) alongside the microscopic properties (e.g., cellulose DP). The model incorporates a multi-layered kinetic Monte Carlo (kMC) framework that allows us to capture the temporal evolution of Kappa number, fiber morphology, and cellulose DP in a computationally tractable fashion. Furthermore, the model predictions are validated with the experimental results, which are then used to find an optimal operation profile to achieve desired Kappa number and cellulose DP.