Comprehensive Two-Dimensional Chromatography with Chemometric Data Analysis

Abstract

The use of comprehensive two-dimensional (2D) chromatography is growing, as analysts require higher peak capacities to resolve increasingly complex samples. However, these separations produce large and information-rich data sets, which can be cumbersome to manually analyze. Therefore, chemometric methods are essential to analyze these large data sets quickly and effectively. Chemometrics relies on the use of both linear algebra and statistical calculations to extract meaningful chemical information from chromatographic data. A variety of chemometric methods can be used to mathematically resolve overlapped peaks, discover significant analytes, classify samples, or predict independently measured properties. Herein, this chapter aims to describe the fundamentals and analysis goals for each chemometric method that is commonly paired with comprehensive 2D separations. Since chemometric performance is highly dependent on data quality, key instrumental and preprocessing considerations will also be provided. Furthermore, current applications and prospects will be highlighted to demonstrate the benefit of incorporating chemometric into data analysis workflows.