This undergraduate experiment teaches headspace GC–MS using forensic toxicology analysis of volatiles, integrating calibration, data evaluation, and real-world analytical workflows.

Researchers present printable, low-cost sensor technologies using smart materials to enable real-time plant health monitoring and advance smart agriculture solutions.

This study combines QuEChERS and low-temperature partitioning with GC–MS to determine multiclass pesticide residues in cocoa beans with good sensitivity and recoveries.

This study presents a sensitive Py-GC–MS/MS method using dynamic reaction monitoring to quantify nano- and microplastics in water, sediment, and biota at nanogram levels.

This study uses in situ Py-GC/MS with complementary analyses to track stage-specific volatile evolution and reaction pathways during lignin slow pyrolysis.

Researchers at IOCB Prague have developed new fluorogenic labels that deliver high-contrast fluorescence microscopy, enabling precise visualization of cellular processes without background noise.

Structure-guided libraries and machine learning enable faster discovery of active nucleic acid sequences beyond random mutagenesis.

This study uses GC×GC–qMS to characterize volatile organic compounds in commercial poi, revealing clear differences between fresh and aged products and distinct brand-specific profiles.

This study combines metabolomics, structural analysis, and public omics data to uncover the extensive diversity and global distribution of kurstakin lipopeptides linked to Bacillus biocontrol activity.

This review examines GC×GC applications in forensic science and evaluates their analytical performance and legal readiness for routine implementation using a technology readiness framework.