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

This proof-of-principle study applies static headspace enantioselective GC×GC–TOFMS for solvent-free volatile profiling and chiral analysis in citrus essential oils.

This week we bring you posters by Agilent Technologies / ASMS and MDCW / William & Mary, application note by Shimadzu and other document by Thermo Fisher Scientific!

Pixel-based GC×GC-TOFMS preprocessing enables rapid chemometric comparison of Brazilian pre-salt oils, revealing subtle light-hydrocarbon patterns and distinguishing Barra Velha from Itapema.

Peter’s lab combines GC×GC innovation, real forensic workflows, and strong industry partnerships to train students and advance research from fingerprint aging to complex chemical mixture analysis.

A nontargeted GC×GC-TOFMS workflow for fingermark residue analysis identified 70 compounds and differentiated donors by exogenous materials, enhancing forensic trace evidence studies.

Discover a fully automated GC×GC method for sex classification and identity verification of human scent samples with machine learning, achieving 85% accuracy in validation tests.

Pilot study shows human scent can survive firing on cartridge cases. Using olfactronics and olfactorics, traces were matched to volunteers to reveal who loaded the weapon.

Non-target screening of indoor dust revealed 2500+ contaminants, including phthalates and COVID-19-related chemicals. Samples from 4 cities show distinct pollutant profiles. Workflow under development.

Using the FDA's Century Mix, we developed a robust QA/QC system for untargeted GC×GC-TOFMS metabolomics, tracking 100 compounds to improve standardization, reproducibility, and long-term performance.