Abstract
The development of rapid and accurate techniques to predict the composition of crude bio-oils obtained via the pyrolysis of lignocellulosic biomass is a prerequisite for their industrial implementation. Here, we demonstrate the potential of Fourier transform infrared spectroscopy to replace gas chromatography–mass spectrometry (GC-MS) in determining the compositional groups of bio-oils. Using the mid-infrared spectroscopic technique as a predictor, chemometric tools based on partial least-squares regression models were contrasted with GC-MS results to foresee the various families of organic compounds. A broad data set consisting of more than 100 samples obtained from the thermal and catalytic pyrolysis of woody biomass and from the upgrading of bio-oil vapors by catalytic cracking over zeolites and metal oxides was used. The applicability of the developed model was assessed by external validation using the Kennard–Stone algorithm, showing that more than 90 wt % of the bio-oil composition was accurately de...
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