(562e) A Multi-Scale Kinetic Modeling and Optimal Control Strategy for an Effective Lignin Fractionation Process

The utilization of biomass, rather than petroleum-based resources, which are associated with environmental challenges and future uncertainties, has become a pressing concern in recent times [1]. Due to its abundance, biomass has garnered substantial research interests, as the scientific community aims to maximize the profitability of biorefineries. In this regard, the successful utilization of biomass components is essential for the commercialization of renewable and sustainable resources. Lignin, a primary constituent of woody biomasses, is currently underutilized despite its potential as a significant source of natural aromatic chemicals [2]. The complex structure of biomass hinders the efficient utilization of lignin, which is often removed as it restricts cellulose accessibility to fractionation reagents.

The utilization of lignin has been emphasized to improve the overall profitability of the biorefinery industry [3, 4]. Although numerous experimental developments have been made [5], a knowledge gap remains in the comprehensive understanding of lignin dynamics in reaction systems. Existing mathematical models [6], which focus solely on de/repolymerization processes with dissolved lignin chains, cannot fully explain the overall biorefinery dynamics. Moreover, real-time measurements of key parameters such as lignin content and molecular weight distribution are still in their infancy [7] and cannot be performed in full-scale pulp digesters. Therefore, a high-fidelity mathematical model and process control strategy are necessary for feasible biomass processing.

Motivated by this need, we introduce a multiscale model that elaborates on both macroscopic (delignification) and microscopic (de/repolymerization) reactions, based on fractionation experiment using a novel solvent, phenol-4-sulfonic acid (PSA) [8]. We employed a bilayer framework, consisting of ordinary differential equations for delignification and a kinetic Monte Carlo (kMC) algorithm for de/repolymerization. Following the successful development of a data-driven kinetic model, we applied a model predictive control to optimize the reaction, using a soft sensor (i.e., Kalman filter) to estimate the primary variables (lignin content and average molecular weight) from the available data (solution temperature).

We verified our model against experimental data and validated our control framework using a real pulp digester, showcasing the seamless integration of theoretical studies with experiments in our work. Our process control demonstrated low offsets from set points for key variables, including lignin content and the average molecular weight of lignin chains. This study highlights the successful combination of experimental work and simulation, leading to a deeper understanding of lignin dynamics in reaction systems and ultimately enabling a lignin fractionation approach in biorefineries.

Literature cited:

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[2] Gao C., Li M., Zhu C., Hu Y., Shen T., Li M., Ji X., Lyu G., & Zhuang W. (2021). One-pot depolymerization, demethylation and phenolation of lignin catalyzed by HBr under microwave irradiation for phenolic foam preparation. Compos. B. Eng., 205, 108530.

[3] Shuai L., Amiri M.T., Questell-Santiago Y.M., Heroguel F., Li Y., Kim H., Meilan R., Chapple C., Ralph J., & Luterbacher J.S. (2016). Formaldehyde stabilization facilitates lignin monomer production during biomass depolymerization. Science, 2016, 354, 329-333.

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[5] Abu-Omar, M.M., Barta, K., Beckham G.H., Luterbacher J.S., Ralph J., Rinaldi R., Roman-Leshkov Y., Samec J.S.M., Sels B.F., & Wang F. (2021). Guidelines for performing lignin-first biorefinering. Energy Environ. Sci., 14, 262-292.

[6] Bawareth B, Marino D.D., Nijhuis T.A., & Wessling M. (2018). Unravelling electrochemical lignin depolymerization. ACS Sustainable Chem. Eng., 6, 7565-7573.

[7] Khalili K.N., de Peinder P., Donkers J., Gosselink R.J., Bruijininex P.C., & Weckhuysen B.M. (2021). Monitoring molecular weight changes during technical lignin depolymerization by operando attenuated total reflectance infrared spectroscopy and chemometries. ChemSusChem, 14, 5517-5524.

[8] He D., Wang Y., Yoo C.G., Chen Q.-J., & Yang Q. (2020). The fractionation of woody biomass under mild conditions using bifunctional phenol-4-sulfonic acid as a catalyst and lignin solvent. Green Chem., 22, 5414-5422.