(192c) Comprehensive Generation of Libraries of Lignin Structures As an Exploration of Lignin Space

The structure of lignin has yet to be entirely understood owing to its polydispersity, complexity, and hyperbranched topology. In previous work, the Broadbelt group has developed an algorithm capable of generating libraries of structural representations of wheatstraw lignin whose average properties – monomer distribution, bond distribution, molecular weight distribution, and branching coefficient – statistically agree with the experimental values. In this work, we have extended this stochastic method to accommodate more complexity, in addition to any type of biomass – softwood, hardwood, or herbaceous. The individual lignin molecules were constructed by random walks along decision trees, where the structure of the trees and the values of the edge weights were informed by unique structural and mechanistic details. With the additional complexity, two methods were investigated and ultimately utilized to reduce the degrees of freedom of the optimization of the edge weights. The first method was pruning the decision trees so as to have fewer parameters, and the second method was biasing the edge weights to within a certain range of their experimental values so as to decrease the size of the parameter space. Utilizing these two methods, we were able to obtain edge weights that produced libraries for miscanthus (herbaceous), spruce (softwood), and birch (hardwood). Notably, wheatstraw and beech proved problematic, revealing that drawing experimental values from disparate sources may lead to a combination of properties that cannot be physically realized. Building on these results, we put forth the concept of feasible “lignin space”, i.e., ranges of experimental characteristics quantified by the four main properties above that can be realized simultaneously. Thus, the advantages of the approach are twofold: generation of lignin libraries for any biomass source to be used in kinetic modeling studies, and guidance for experimentalists as they seek to design and characterize lignin.