17th Multidimensional Chromatography Workshop Guidebook
Others | 2026 | MDCWInstrumentation
GC/MS/MS, SPME, Thermal desorption, Pyrolysis, Microscopy, X-ray, GC/MSD, Software, LC/HRMS, LC/MS, 2D-LC, GC/HRMS, SFC, GC/TOF, GCxGC
IndustriesEnvironmental, Food & Agriculture, Energy & Chemicals , Pharma & Biopharma
ManufacturerLECO, Markes, Restek, Trajan Scientific, GL Sciences
Summary
Importance of the Topic
Multidimensional chromatography techniques such as comprehensive two-dimensional gas chromatography (GC×GC) and two-dimensional liquid chromatography (2D-LC) have become essential tools in analytical chemistry. They offer unparalleled separation power for complex mixtures across pharmaceutical, environmental, food, and forensic applications. The 16th Multidimensional Chromatography Workshop brought together researchers to share advances in methodology, instrumentation, and data analysis, fostering innovation and collaboration.Objectives and Overview of the Workshop
The workshop aimed to:- Present the latest developments in GC×GC, 2D-LC, and hyphenated techniques.
- Demonstrate applications ranging from small molecules and polymers to biologics and volatile organic compounds.
- Provide hands-on learning through short courses, lab tours, and guided discussions.
- Create a platform for students and professionals to network and exchange knowledge.
Methodologies and Instrumentation
Participants discussed various methodological innovations, including:- Flow-modulated GC×GC with split-flow minimization
- PARAFAC and PARAFAC2 algorithms for automated GC×GC-MS data analysis
- Tile-based Fisher-ratio and machine-learning approaches for peak detection in GC×GC-TOFMS datasets
- Capillary 2D-LC employing polymer fiber columns for biomolecule isolation
- Green extraction techniques such as on-chip electromembrane extraction and thermal desorption for high-water content samples
Key Themes and Highlights
- Environmental monitoring of PFAS and plastic pyrolysis oils
- Aroma profiling of fermented beverages and mead using GC-O and GC×GC
- Machine learning for unknown metabolite structure elucidation in HeLa cells
- Data standardization tools for group-type template matching in multidimensional datasets
- Forensic applications including gunshot residue analysis and cadaver odor profiling
Practical Benefits and Applications
The workshop demonstrated how multidimensional separations enhance resolution, reduce coelution, and improve quantitation in complex matrices. Attendees gained insights into accelerating method development, ensuring peak purity, and applying hyphenated techniques to real-world challenges in quality control, environmental forensics, and biopharmaceutical characterization.Used Instrumentation
- Comprehensive two-dimensional gas chromatography coupled to time-of-flight mass spectrometry (GC×GC-TOFMS)
- GC×GC with quadrupole mass spectrometry and flame ionization detection (FID)
- Two-dimensional liquid chromatography–mass spectrometry (2D-LC-MS)
- Thermal desorption units for VOC and PAH analysis
- On-chip electromembrane surrounded solid-phase extraction devices
Future Trends and Opportunities
- Integration of artificial intelligence and deep-learning for automated data processing and peak annotation
- Development of green chromatographic workflows using hydrogen carrier gas and solvent-free extraction
- Miniaturized and on-chip multidimensional separation platforms for point-of-need analysis
- High-resolution mass spectrometry coupling to capture ever more complex sample profiles
- Enhanced software solutions for real-time data visualization and standardized reporting
Conclusion
The 16th Multidimensional Chromatography Workshop underscored the critical role of advanced separation science in addressing contemporary analytical challenges. By showcasing innovative instrumentation, data-driven methodologies, and cross-disciplinary applications, the event paved the way for future breakthroughs in both research and industry settings.References
No literature references were provided in the original guidebook.Content was automatically generated from an orignal PDF document using AI and may contain inaccuracies.
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