17th Multidimensional Chromatography Workshop Abstract book

Importance of the Topic

Comprehensive two-dimensional separation techniques such as GC×GC and 2D-LC have revolutionized analytical chemistry by overcoming the limitations of one-dimensional methods. Their enhanced peak capacity, resolution, and sensitivity are critical for unraveling the complexity of petroleum matrices, pharmaceuticals, polymers, environmental contaminants, and biofluids. By delivering richer datasets and more reliable identifications, these methods support quality control, product development, regulatory compliance, and fundamental research across multiple industries.

Objectives and Overview of the Collection

This collection of abstracts presents recent advances in multidimensional chromatography, highlighting key goals:

• Demonstrate novel workflows for GC×GC and 2D-LC in diverse applications.
• Compare modulation strategies (thermal, flow) and carrier gases (helium, hydrogen) to boost performance and sustainability.
• Showcase software tools and AI-based approaches for automated data reduction, alignment, and spectral prediction.
• Illustrate real-world case studies in petroleum analysis, pharmaceutical characterization, plastic recycling, food flavor profiling, forensic science, and metabolomics.

Methodologies and Instrumentation

Key techniques and instruments described include:

• Comprehensive two-dimensional gas chromatography (GC×GC) with dual detectors (FID, TOF-MS) and various modulators (thermal, flow-modulated).
• Two-dimensional liquid chromatography (2D-LC) in heart-cut and comprehensive modes, coupling orthogonal columns (RPLC, HILIC, SEC, chiral) and mass spectrometers.
• Sample preparation methods such as solid-phase microextraction (SPME/arrow), electromembrane-surrounded SPME, direct thermal desorption, pyrolysis, and SPME-TD for VOCs and PFAS analysis.
• High-resolution mass spectrometry modes: electron ionization, chemical ionization (positive/negative), photoionization, and high-resolution accurate mass detection.
• Data processing and chemometric strategies including tile-based Fisher ratio, alteration analysis, 2D correlation, UMAP, PARAFAC/PARAFAC2, retention modeling, AI-driven spectrum prediction, and advanced alignment and subtraction algorithms.

Main Results and Discussion

Several recurring themes emerge:

• GC×GC dramatically increases the number of resolved components—up to fivefold more in complex pyrolysis oils, fermented beverages, PFAS screening, and forensic fire debris—enabling deeper mechanistic insights.
• 2D-LC allows simultaneous achiral and chiral purity assessment, peak-purity evaluation, and fingerprinting of small molecules, biologics, and synthetic polymers.
• Hydrogen carrier gas and cryogen-free modulators enhance sustainability, reduce run times, and maintain or improve resolution.
• Machine learning and AI tools improve spectral library coverage, automate structure prediction for unknown metabolites and polymer fragments, and streamline method development and data analysis.
• Novel sample-prep workflows (EM-SPME, TD methods, SPME arrow) deliver low ppb to sub-ppb limits of detection in complex matrices such as human breath, paint, recycled plastics, and biofluids.

Benefits and Practical Applications

These multidimensional approaches yield tangible benefits:

• Enhanced specificity and sensitivity for QA/QC in petrochemical, pharmaceutical, and food industries.
• Improved characterization of emerging feedstocks and sustainable products (biofuels, recycled materials).
• Advanced forensic analysis of gunshot residue, human remains, and arson debris.
• Comprehensive metabolomic profiling in environmental and biomedical research.
• Accelerated method development through retention modeling and simulation, reducing trial-and-error experiments.

Future Trends and Potential Applications

Emerging directions include:

• Integration of fully software-controlled, alignment-free modulation platforms and cryogen-free cooling to simplify routine GC×GC.
• Expansion of open-source retention databases and web-based simulators to democratize 2D-LC method development.
• Broader adoption of AI-based spectral prediction and machine learning models for untargeted analysis across complex matrices.
• Continued focus on green chemistry: hydrogen carrier gas, low-bleed columns, minimal solvent use, and microfluidic sample-preparation techniques.
• Cross-disciplinary applications in environmental monitoring, clinical diagnostics, material science, and food authentication.

Conclusion

Comprehensive two-dimensional chromatography, combined with advanced detectors, sample-preparation methods, and data-science tools, is transforming analytical workflows. These innovations deliver unprecedented resolution and molecular insight across diverse fields, paving the way for more sustainable, automated, and data-rich analyses. Continued collaboration between instrumentation developers, software engineers, and application scientists will further expand the capabilities and accessibility of multidimensional separations.

References

[1] Lai Z., Tsugawa H., Wohlgemuth G., et al. Identifying metabolites by integrating metabolome databases with mass spectrometry cheminformatics, Nat. Methods, 15(1):53–60.