Register for Seminar

Specific seminar times and topics will be communicated to all registered attendees before the conference. There are limited seating spaces for each session. Register early to assure your participation in these seminars.

This three day course in comprehensive two-dimensional gas chromatography covers both the theory and practical applications of GC x GC. Analyses of most complex mixtures are simply not effectively achieved by conventional chromatographic techniques; GC x GC provides the best available technique to resolve, identify and characterize such complex matrices like in petroleum, forensics, environmental, and metabolomics applications. This training course is recommended for both new and experienced GC x GC practitioners.

DAY 1
INTRODUCTION TO GC x GC:
An informative and interesting discussion on the history and progress of both hardware and software - from the original inventor's laboratory at University of Illinois at Carbondale to hundreds of practitioners worldwide. This section will cover GC x GC, thermal modulators, the "Loop Modulator" and Capillary Flow Modulation. Applications discussion will include Petrochemicals, Environmental, Food & Flavors, Metabolomics and Fragrances.

DAY 2
INTERPRETING GC x GC CHROMATOGRAMS:

  • Discussion of key concepts underlying GC x GC technique
  • The retention window concept
  • Wrap around concept and problems
  • GC x GC Tuning rules
  • Np & Pn Column set analysis
  • The chemical logic of sample space - analytical space

GC x GC DATA ANALYSIS:
Hands on workshop on GC Image and GC Project. Attendees will learn how to: Process simple GC x GC chromatograms (images), develop Smart Templates for automated data processing, perform quantitative data analysis, prepare GC Projects for automated data processing and reporting.

DAY 3
GC x GC DATA ANALYSIS CONTINUED

  • Advanced topics in GC Image
  • "CLIC" Applications
  • Image Investigator
  • Practical guide to method development in GC x GC environment
  • Working with GC x GC x HiRes TOFMS data

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