Classification of high-speed gas chromatography-mass spectrometry data by principal component analysis coupled with piecewise alignment and feature selection

A useful methodology is introduced for the analysis of data obtained via gas chromatography with mass spectrometry (GC-MS) utilizing a complete mass spectrum at each retention time interval in which a mass spectrum was collected. Principal component analysis (PCA) with preprocessing by both piecewise retention time alignment and analysis of variance (ANOVA) feature selection is applied to all mass channels collected. The methodology involves concatenating all concurrently measured individual m/z chromatograms from m/z 20 to 120 for each GC-MS separation into a row vector. All of the sample row vectors are incorporated into a matrix where each row is a sample vector. This matrix is piecewise aligned and reduced by ANOVA feature selection. Application of the preprocessing steps (retention time alignment and feature selection) to all mass channels collected during the chromatographic separation allows considerably more selective chemical information to be incorporated in the PCA classification, and is the primary novelty of the report. This methodology is objective and requires no knowledge of the specific analytes of interest, as in selective ion monitoring (SIM), and does not restrict the mass spectral data used, as in both SIM and total ion current (TIC) methods. Significantly, the methodology allows for the classification of data with low resolution in the chromatographic dimension because of the added selectivity from the complete mass spectral dimension. This allows for the successful classification of data over significantly decreased chromatographic separation times, since high-speed separations can be employed. The methodology is demonstrated through the analysis of a set of four differing gasoline samples that serve as model complex samples. For comparison, the gasoline samples are analyzed by GC-MS over both 10-min and 10-s separation times. The successfully classified 10-min GC-MS TIC data served as the benchmark analysis to compare to the 10-s data. When only alignment and feature selection was applied to the 10-s gasoline separations using GC-MS TIC data, PCA failed. PCA was successful for 10-s gasoline separations when the methodology was applied with all the m/z information. With ANOVA feature selection, chromatographic regions with Fisher ratios greater than 1500 were retained in a new matrix and subjected to PCA yielding successful classification for the 10-s separations.     

Enhanced surfactant determination by ion-pair formation using flow-injection analysis and dynamic surface tension detection

Chemical analysis of surface active species (surfactants) is of interest for many applications, such as in process monitoring, biomedical applications, environmental monitoring and surface science investigations. Recently, we reported a dynamic surface tension detector (DSTD) based upon optically probing the size of a repeating drop resulting from constant flow of an aqueous solvent out of the end of a capillary. Presence of a surfactant in a growing drop reduces the surface tension at the air-solvent interface, causing the drop to detach at a smaller volume, which is detected. The DSTD has a kinetic dependence, and with increasing flow rate the sensitivity decreases due to diffusional and adsorption effects. We report that for the sodium salt of dodecylsulfate (DS), the DSTD performs significantly better with a stainless steel (S.S.) capillary dropper than with a fused silica dropper because the S.S. dropper exhibits a smaller adsorption effect as a function of time. Flow-injection analysis with the DSTD of DS was found to enhance sensitivity 50-fold by in-situ reaction with the ion-pair reagent tetrabutylammonium hydroxide (TBA) in water, even though the TBA alone was not very surface active. The TBA-DS system serves as a model for a selective detection method in which surface activity is exploited and enhanced. The detection limit for DS, as TBA-DS, was 400 ppb. Additionally, weakly surface active species such as TBA could be analyzed "indirectly" by ion-pair formation with DS. The enhanced sensitivity is due to increased packing of the ion-pairs at the air-aqueous solvent interface. The flow rate dependence on the sensitivity of detecting the TBA-DS ion-pair was examined. Two limiting conditions were observed as a function of ion-pair concentration: sensitivity decreases linearly with inverse flow rate at high flow rates and approaches a steady state at slower flow rates.