Chromatographic fingerprinting by comprehensive two-dimensional chromatography: Fundamentals and tools

Federico Stilo, Carlo Bicchi, Ana M. Jimenez-Carvelo, Luis Cuadros-Rodriguez, Stephen E. Reichenbach, Chiara Cordero

Research output: Contribution to journalReview articlepeer-review

4 Scopus citations

Abstract

This contribution reviews state-of-the approaches for chromatographic fingerprinting of 2D peak patterns. Concepts of sample's fingerprint and profile, as established in metabolomics, are conceptually translated to comprehensive two-dimensional chromatography (C2DC) separations embracing the principles of biometric fingerprinting. Approaches founded on this principle - referred to as chromatographic fingerprinting - are described and discussed for their information potential and limitations for providing a higher level of information about sample composition. The different type of features (i.e., datapoint, region, peak, and peak-region) are discussed and insights on processing tools and advances in the development of new algorithms are provided. Selected examples cover the most relevant application fields of GC × GC. Challenging scenarios with severe chromatographic misalignment, parallel detection, and translation of methods from thermal to differential-flow modulated GC × GC are also considered for their relevance in specific applications. Machine learning/chemometrics tools are briefly introduced, highlighting their fundamental role in supporting fingerprinting workflows.

Original languageEnglish (US)
Article number116133
JournalTrAC - Trends in Analytical Chemistry
Volume134
DOIs
StatePublished - Jan 2021

Keywords

  • Chemometrics
  • Chromatographic fingerprinting
  • Comprehensive two-dimensional gas chromatography
  • Fingerprinting workflows
  • GC×GC data processing
  • Machine learning
  • Multidimensional analytical platforms
  • Peak features
  • Peak-region features
  • Profiling vs. fingerprinting

ASJC Scopus subject areas

  • Analytical Chemistry
  • Spectroscopy

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