Discover how AI-driven GC-MS workflows and predictive spectral libraries enable confident identification of unknown metabolites, integrating molecular-formula estimation and high-resolution GC×GC-TOFMS.

Discover how custom MS libraries and retention index filtering improve GC×GC–MS peak identification, alignment, and data quality in complex samples.

Integrating GC-O with GC×GC enables a direct link between chemical data and sensory perception. Sample enrichment, two-dimensional separation, and chemometrics improve aroma analysis.

ICP-OES and GC×GC-TOFMS compare new vs. used aircraft oils. Results show >20% phosphorus loss in jet oils and strong lead accumulation in piston oils—highlighting potential cabin-air and handling risks.

GC×GC-HRTOFMS enables fast and reliable screening of PFAS and emerging contaminants in complex consumer goods, combining EI/PCI/NCI and mass defect workflows for confident identification.

GC×GC-TOFMS reveals how yeast strain and honey concentration shape mead aroma. Learn the workflow from headspace sampling to PCA/PCoA/HCA, plus key VOC trends across fermentations.

Advanced chemometric methods reveal subtle, statistically significant changes in complex GC×GC-MS and LC-MS data. Learn how Alteration Analysis and 2D correlation turn massive datasets into actionable insights.

Day 3 of MDCW 2026 focused on advanced GC×GC and 2D-LC innovations, from flow-modulated GC×GC-QMS and tensor decomposition to plastic pyrolysis, forensics, bioanalysis, and polymer separations.

Day 2 of MDCW 2026 highlighted the power of multidimensional chromatography, from plastic recycling and pyrolysis to GC×GC-MS automation, 2D-LC in biopharma, PFAS analysis, and thermal desorption.

Day one of MDCW 2026 showcased GC×GC and 2D-LC advances across energy, pharma, PFAS, aroma, and metabolomics, combining keynote insights, oral sessions, posters, and expert discussion.