However, strong C–C bonds and reactive functional groups in lignin make deconstruction challenging and result in low yields of monomers. High-temperature pyrolysis could further break the C–C bonds and increase the monomer yield. Depolymerization techniques, such as reductive catalytic fractionation (RCF), cleave C-O bonds to produce monomers as building blocks for biofuels, functional polymers, lubricants, etc. Despite its abundance in nature and the vast amount generated in the pulp and paper industry, lignin is either unused or burned for heat. Lignin, an aromatic polymer, constitutes a significant fraction of lignocellulosic biomass (up to 30 wt%) and is crucial to plant life functioning and structural stability. Lignocellulosic biomass is a promising and broadly available feedstock for the production of biofuels and renewable chemicals and materials. Its software implementation in Python, LigninGraphs, is open-source and available on GitHub. The framework could guide researchers towards feasible lignin structures, efficient space exploration, and future kinetics modeling. We obtain structure libraries for various lignin feedstocks based on literature and new experimental NMR data for poplar wood, pinewood, and herbaceous lignin. The framework employs accelerated rejection-free polymerization and hierarchical Metropolis Monte Carlo optimization algorithms. We introduce a graph-based multiscale modeling framework for lignin structure generation and visualization. Computer models could extend the resolution of experiments by representing structures at the molecular and atomistic scales. Experimental characterization techniques, such as 2D-heteronuclear single quantum coherence (HSQC) nuclear magnetic resonance (NMR) spectra, could elucidate the global properties of the polymer molecules. Designing and optimizing lignin valorization processes requires a fundamental understanding of lignin structures. Lignin is an aromatic biopolymer found in ubiquitous sources of woody biomass.

Mestrenova molecule match