Mnova 16 delivers powerful updates for NMR, LC/GC-MS, and spectroscopy. Streamline analysis with Python automation, Allotrope support, and an intuitive Command Palette. Try it free for 45 days!

Using GC×GC and statistical tools, researchers highlight differences between alternative and petroleum-based jet fuels, focusing on minor aromatics and heteroatom-containing compounds.

Peak detection is crucial in GC×GC & LC×LC workflows. We study how signal features impact detection performance, helping select tools for both manual and automated method development.

A team at IOCB Prague revealed a novel phase where liquids flip rapidly between metal and nonmetal states. The theory, based on advanced modeling, was featured in Nature Communications.

The integration of chromatographic and statistical approaches in GC×GC-MS enhances compound separation, data interpretation, and reliability—crucial for complex sample analysis across many fields.

We developed an AI-based EI mass spectral database with 120 million predicted spectra to improve unknown compound identification in GC×GC-MS beyond commercial library limits.

We’re pleased to release the first update for KnowItAll 2025, improving performance and fixing issues introduced since the major release featuring new tools and enhancements.

LC-GC×GC-FID/TOFMS enhances MOSH/MOAH analysis in food ingredients and additives, helping to resolve coelutions and reduce interpretation errors beyond current ISO 20122:2024 limitations.

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.

Can the design of a gas chromatograph (GC) impact the productivity of your laboratory? The answer is yes, especially when it allows you to work more efficiently.