An advanced analytical chemistry experiment using gas chromatography-mass spectrometry, MATLAB, and chemometrics to predict biodiesel blend percent composition

摘要

We present a laboratory experiment for an advanced analytical chemistry course where we first focus on the chemometric technique partial least-squares (PLS) analysis applied to one-dimensional (1D) total-ion-current gas chromatography-mass spectrometry (GCTIC) separations of biodiesel blends. Then, we focus on n-way PLS (n-PLS) applied to two-dimensional (2D) gas chromatography-mass spectrometry (GC-MS) separations of biodiesel blends. The purpose of the experiment is to determine the percent composition, by volume, of biodiesel in an unknown blend of biodiesel and conventional diesel. A secondary goal is to compare the prediction results of the PLS model to the n-PLS model to see if there is an advantage to analyzing multiple dimensions. The instructor initially creates a PLS model and an n-PLS model using separations of standard biodiesel blends where the percent compositions are known and vary from 0% to 20%. Then, the student collects the GC-TIC and GC-MS chromatograms of an unknown biodiesel blend to regress onto PLS and n-PLS models and discover the percent composition of the unknown sample.