Fatty acid alkyl esters (FAAEs) in blends of biodiesel mixed with petrodiesel were chromatographically resolved using gas chromatography with a mass spectrometry (GC-MS) and gas chromatography with a tandem differential mobility spectrometer (GC-DMS). The fuel blends were classified according to feedstock using scaling, principal component analysis (PCA), and hierarchical cluster analysis (HCA). Unsupervised cluster analysis captured over 50% of variance in a single PC while supervised analysis captured over 70% of variance using Fisher ratio feature selection. The PCA and HCA models were able to accurately predict the feedstock of test set samples under constraints of similarity between training set and test samples.

Chromatography and chemometric analysis of biodiesel fuel blends

255th National Meeting (2018)

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