Analysis of gas chromatography/mass spectrometry data for catalytic lignin depolymerization using positive matrix factorization?

Green Chemistry Pub Date: 2018-08-13 DOI: 10.1039/C8GC01474D

Abstract

Various catalytic technologies are being developed to efficiently convert lignin into renewable chemicals. However, due to its complexity, catalytic lignin depolymerization often generates a wide and complex distribution of product compounds. Gas chromatography/mass spectrometry (GC-MS) is a common analytical technique to profile the compounds that comprise lignin depolymerization products. GC-MS is applied not only to determine the product composition, but also to develop an understanding of the catalytic reaction pathways and of the relationships among catalyst structure, reaction conditions, and the resulting compounds generated. Although a very useful tool, the analysis of lignin depolymerization products with GC-MS is limited by the quality and scope of the available mass spectral libraries and the ability to correlate changes in GC-MS chromatograms to changes in lignin structure, catalyst structure, and other reaction conditions. In this study, the GC-MS data of the depolymerization products generated from organosolv hybrid poplar lignin using a copper-doped porous metal oxide catalyst and a methanol/dimethyl carbonate co-solvent was analyzed by applying a factor analysis technique, positive matrix factorization (PMF). Several different solutions for the PMF model were explored. A 13-factor solution sufficiently explains the chemical changes occurring to lignin depolymerization products as a function of lignin, reaction time, catalyst, and solvent. Overall, seven factors were found to represent aromatic compounds, while one factor was defined by aliphatic compounds.

Graphical abstract: Analysis of gas chromatography/mass spectrometry data for catalytic lignin depolymerization using positive matrix factorization
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