Both comprehensive two-dimensional gas chromatography (GCxGC) and comprehensive two-dimensional liquid chromatography (LCxLC) have emerged as powerful tools capable of increasing the peak capacity of a single chromatographic analysis. Utilizing orthogonal chromatographic systems, analytes can be separated by two different, sequential retention mechanisms; this process allows for analytes to be separated from other compounds that would normally co-elute in a single dimensional separation. Efforts at NIST are being directed toward the study of issues related to quantitation by both GCxGC and LCxLC, value assignment of complex matrix Standard Reference Materials (SRMs), and non-targeted analysis.
The development of robust analytical methods remains one of the most important (and costly) parts of chemical metrology. The separation of targeted constituents from other components in a sample matrix is necessary for accurate and precise measurements. Multidimensional chromatography is an important analytical tool since it provides high chromatographic resolution. The Chemical Sciences Division has used SRMs to thoroughly evaluate the quantitative capabilities of both GCxGC and LCxLC and examine the parameters that impact quantitation such as peak description, integration, data processing and experimental parameters. In addition to the investigation on the quantitative capabilities of two-dimensional chromatography, researchers at NIST have studied the qualitative strengths of the instrumentation, including non-targeted analysis. Non-targeted screening is an emerging analytical technique where previously unknown compounds can be identified through a combination of chromatographic and mass spectra data. Currently, GCxGC and LCxLC methods are being developed for the non-targeted screening of environmental, food, and nutritional supplement samples.
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Large amounts of data is generated using GCxGC and LCxLC, especially when coupled to mass spectrometry. Hence data management and data analysis is crucial when using these techniques. Data analysis tools such as peak finding, spectral deconvolution, blank subtraction, and use of computational scripts to search for characteristic mass spectra fragmentations (both commercial and in-house written programs) are used.