Targeted analyte deconvolution and identification by four-way parallel factor analysis using three-dimensional gas...

Area of Science:

• Analytical Chemistry
• Chemometrics
• Mass Spectrometry

Background:

• Comprehensive three-dimensional gas chromatography with time-of-flight mass spectrometry (GC³-TOFMS) offers advanced analytical capabilities.
• Chemometric analysis, particularly Parallel Factor Analysis (PARAFAC), is crucial for interpreting complex chromatographic data.

Purpose of the Study:

• To develop and validate a novel method for utilizing GC³-TOFMS data within a PARAFAC framework.
• To simplify the implementation challenges associated with GC³-TOFMS data analysis.
• To demonstrate the effectiveness of the proposed method in identifying target analytes in complex mixtures.

Main Methods:

• Conceptualizing GC³-TOFMS as a 1D GC with GC×GC-TOFMS detection to enable native PARAFAC target window creation.
• Applying PARAFAC to GC×GC-TOFMS chromatograms generated from each first-dimension modulation.
• Analyzing a 115-compound mixture and a diesel sample using the developed methodology.

Main Results:

• Successful identification of all target analytes in both the simple mixture and the diesel sample.
• High mass spectral matching success rates (over 900 in 40/42 cases) when comparing PARAFAC loadings to library spectra.
• Excellent match values (greater than 950) achieved in 29 of the successful identification cases.

Conclusions:

• The presented method effectively integrates GC³-TOFMS data with PARAFAC for robust chemometric analysis.
• This approach simplifies the analysis of complex samples and enhances target analyte identification.
• The methodology shows significant promise for applications in various fields requiring detailed chemical analysis.