Revisiting biomass compositions determination using thermogravimetric analysis and independent parallel reaction model

• Published in: Thermochimica acta Vol. 739; p. 179814
• Main Authors: Sophonrat, Nanta, Wooldridge, Margaret
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.09.2024
• Subjects: bark; Betula; biomass; cellulose; Composition analysis workflow; Extractive analysis; hemicellulose; Kinetic model; lignin; Panicum virgatum; starch; statistical analysis; thermal degradation; thermogravimetry; wood; Extractive analysis; Kinetic model; Composition analysis workflow
• ISSN: 0040-6031; 1872-762X
• DOI: 10.1016/j.tca.2024.179814

•Revised workflow to determine biomass compositions via thermogravimetric analysis.•Improved independent parallel reaction model by constraining parameter boundaries.•The biomass tested was pine, birch, and oak woods, switchgrass, and pine bark.•The compositions using the new method were within 8 wt% of the literature values. The determination of biomass composition via thermogravimetric analysis (TGA) has been a subject of considerable interest for many years. The current work proposes a revised workflow for determining the amounts of cellulose, hemicellulose, and lignin in biomass by combining TGA under an inert atmosphere with analyses of extractives and ash. An independent parallel reaction (IPR) model used for the deconvolution of the derivative thermogravimetry data was improved by constraining model parameters, i.e., thermal decomposition kinetic parameters and char fractions of cellulose, hemicellulose, and lignin, with values compiled from the literature using statistical analysis. The workflow is developed and demonstrated using cellulose and starch mixtures and then applied to biomass with varying levels of ash, including pine, birch, and oak wood, switchgrass, and pine bark. Using extractive-free biomass in the new TGA-IPR workflow improved the composition results compared with untreated biomass. The compositions determined by this method agreed well with values reported in the literature (within approx. 8 wt%) for the tested samples. The results demonstrate improved biomass composition accuracy using an accessible and rapid TGA-based approach. [Display omitted]