This week we bring you application notes by Agilent Technologies, Thermo Fisher Scientific, brochure by Shimadzu and presentation by MDCW / LECO!

Tile-based analysis of GC×GC–MS data reveals volatile metabolites and metabolic interactions between pathogens, enabling advanced interpretation of complex microbiological datasets.

This week we bring you application notes by Agilent Technologies, Shimadzu, and Thermo Fisher Scientific and presentation by MDCW / Mount Royal University!

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.

This week we bring you application notes by Agilent Technologies, BaySpec and Shimadzu and presentation by MDCW / JEOL.

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.

This week we bring you application notes by Agilent Technologies, Shimadzu and Waters Corporation and presentation by MDCW / William & Mary!

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.