Elucidating Lignin Structure and Its Impact on Fractionation Processes

Lignin, a renewable aromatic polymer abundant in nature, holds significant promise as a replacement for fossil-derived aromatic materials due to its unique chemical structure. However, the very features that make lignin attractive for valorization also present challenges. The high temperatures and harsh pH conditions commonly used for lignin extraction promote condensation reactions, which degrade many of its native ether functional groups and lead to the formation of undesirable interunit carbon-carbon bonds. This loss of structural integrity limits the potential of lignin for the development of new materials.

To address these challenges, many research groups have developed extraction processes designed to protect lignin's reactive structures. However, the absence of standardized methods for characterizing native lignin in biomass hinders the accurate evaluation of these processes. Motivated by this gap, the goal of my research is to apply innovative methodologies to characterize lignin's structure and monitor its reactivity during various extraction processes. This path aims to develop more effective lignin-extraction methods. My work adopts a multidisciplinary approach, combining Nuclear Magnetic Resonance (NMR), kinetic modeling, and Single Molecule Imaging to provide unprecedented insights into lignin structure.

In the first part of my thesis, I present a precise method for characterizing native lignin in biomass using Whole Plant Cell Wall (WPCW) Heteronuclear Single Quantum Correlation time-zero (HSQC0) NMR at elevated temperatures to overcome fast transversal spin relaxation. This methodology offers the first reference for assessing native lignin structural features, thereby assesing the efficiency of lignin extraction processes in preserving lignin's native structure. Additionally, I developed a fast in situ HSQC monitoring method for common delignification processes, providing deeper insights into the structural changes that might occur between extracted lignin and native lignin as characterized by WPCW HSQC.

In the second part, I developed an algorithm that combines LigninGraphs structure generation with a kinetic Monte Carlo (kMC) depolymerization framework. Extensive studies on beta-O-4 model compounds demonstrated that its reactivtiy is highly dependant on its chemical environment. Using accurate LigninGraphs polymer structures and stochastic kMC monitoring, we were able to precisely predict lignin depolymerization. The assumption that lignin might be linear, made through out this doctoral work, was also challenged experimentally, using Electro-Spray-Ionization Scanning Tunneling Microscopy (ESI-STM) to observe single polymers. This technique successfully resolved lignin-like structures, revealing the presence of linear polymers on the surface. Finally, I demonstrate that precise characterization of lignin's structure is crucial for identifying and selecting promising lignin-based materials, such as those suitable for application