Elucidating Biomass-Derived Pyrolytic Lignin Structures from Demethylation Reactions through Density Functional Theory Calculations

Abstract

Pyrolytic lignin is a fraction of pyrolysis oil that contains a wide range of phenolic compounds that can be used as intermediates to produce fuels and chemicals. However, the characteristics of the raw lignin structure make it difficult to establish a pyrolysis mechanism and determine pyrolytic lignin structures. This study proposes dimer, trimer, and tetramer structures based on their relative thermodynamic stability for a hardwood lignin model in pyrolysis. Different configurations of oligomers were evaluated by varying the positions of the guaiacyl (G) and syringyl (S) units and the bonds βO4 and β5 in the hardwood model lignin through electronic structure calculations. The homolytic cleavage of βO4 bonds is assumed to occur and generate two free radical fragments. These can stabilize by taking hydrogen radicals that may be in solution during the intermediate liquid (pathway 1) formation before the thermal ejection. An alternative pathway (pathway 2) could occur when the radicals use intramolecular hydrogen, turning themselves into stable products. Subsequently, a demethylation reaction can take place, thus generating a methane molecule and new oligomeric lignin-derived molecules. The most probable resulting structures were studied. We used FTIR and NMR spectra of selected model compounds to evaluate our calculation approach. Thermophysical properties were calculated using group contribution methods. The results give insights into the lignin oligomer structures and how these molecules are formed. They also provide helpful information for the design of pyrolysis oil separation and upgrading equipment.

Estimation of Fuel Properties for the Heavy Fraction of Biomass Pyrolysis Oil Consisting of Proposed Structures for Pyrolytic Lignin and Humins

“…Estimates for fuel properties provided herein are based on empirical correlations from structural features of molecules and/or subsequent indirect correlations estimating the value of one property based on the value of others. In general, results from regularized regression presented here correspond well with computational structure analyses and property estimation work recently published by Garcia-Perez and associates [18,[81][82][83]. However, as in prior work on solubility parameters [43], the advantage of regularized regression for property estimation is the ability to use unified, simpler models rather than relying on several (potentially disparate) group contribution methods.…”

“…Many published group contribution methods may also rely on first-, second-, and third-order groups with a large absolute number of parameters, which can be cumbersome in practice for property estimation. Three recent works that used group contribution for thermochemical/physical property estimation for bio-oils can be found from Garcia-Perez and associates [18,82,83]. In these studies, property estimation relied on published correlations for the computation of critical properties, boiling point, and heat of vaporization.…”

Elucidation of Structure and Physical Properties of Pyrolytic Sugar Oligomers Derived from Cellulose Depolymerization/Dehydration Reactions: A Density Functional Theory Study

“…Therefore, the second-order group contributions were built on the first-order groups to at least capture more information on the molecular structure of compounds like the fine differences among isomers and conjugate forms. , In this work, the first-group contributions were employed for reasons of model simplification and user friendliness. Fonts et al and Manrique et al used these same methods to estimate the physical and thermodynamic properties of bio-oil compounds derived from the fast pyrolysis of lignocellulosic compounds.…”

“…27,43 In this work, the first-group contributions were employed for reasons of model simplification and user friendliness. Fonts et al 42 and Manrique et al 44 used these same methods to estimate the physical and thermodynamic properties of bio-oil compounds derived from the fast pyrolysis of lignocellulosic compounds.…”

Modeling Fast Pyrolysis of Waste Biomass: Improving Predictive Capability

“…Ranzi et al 29,30 and Gorensek et al 60 propose a single molecule with a molecular weight of 380.5 g•mol −1 (C 24 H 28 O 4 ), on a lower range, while Ille et al 61 propose a surrogate with a molecular weight of 202.2 g•mol −1 (C 12 H 10 O 3 ), suitable for liquid−vapor modeling. Manrique et al 62 proposed diverse structures of dimers, trimers, and tetramers with a molecular weight range of 326.7−758.3 g• mol −1 . Fonseca 63 developed a surrogate based on the results presented by Scholze et al 25 with a molecular weight of 680.2 g•mol −1 .…”