Ultra-sensitive detection and identification of chemical unknowns is critical for sectors including clinical diagnostics, pharmaceutical research, and environmental monitoring. Current state-of-the-art methodologies rely on often unavailable chemical standards creating challenges, delays, and increased costs. This project integrates IR-spectroscopy, liquid chromatography mass spectrometry and machine learning to accelerate molecular identification, enhancing industrial and scientific analyses.

Advanced Analytical Platform

This collaborative project between HFML-FELIX and Synvenio B.V. develops an innovative analytical platform combining liquid chromatography-mass spectrometry (LC-MS) with Free Electron Laser-based infrared ion spectroscopy (FEL-IRIS). The FEL-IRIS method uniquely identifies unknown molecules without chemical standards, overcoming major bottlenecks. Synvenio synthesizes these new standards, enabling routine identification in a much broader range of routine analytical laboratories. Enhanced hardware coupling and advanced machine learning algorithms further accelerate identification processes.

Impact and Applications

The project targets critical sectors like clinical diagnostics, pharmaceutical research, and environmental monitoring, significantly improving sensitivity, speed, and accuracy in molecular analysis. The developed platform will strengthen Dutch analytical sciences, establish national and international research collaborations, and support sustainable research practices through optimized analytical efficiency. The technologies developed here will be deployed in an experimental user-station at the institute HFML-FELIX for broad industry and academic usage.