19F NMR APPLICATION
FLUOVIAL 19F NMR & Machine Learning Platform
CASC4DE has developped FLUOVIAL, efficient 19F NMR and Machine Learning techniques for analysis, detection, characterisation, quantification and even identification of fluorinated compounds from NMR spectra. In particular, this platform is suitable for PFAS pollutants (Per- and/or PolyFluoroAlkyl substances classified as “emerging contaminants”).
Thus our FLUOVIAL platform combines:
- a Fluorine NMR spectral database including spectra from various known fluorinated species families,
- a Machine Learning software to automate analysis of 19F NMR datasets.
Interested in detecting fluorinated compounds, characterising, quantifying and identifying them on your samples ?
FLUOVIAL platform allows to differentiate species !
Fast and automatized analysis by Machine Learning treatment.
Indeed Casc4de has developed a non-specific and non destructive analytical method without previous separation or purification on samples. It even allows to differentiate fluorinated molecules in complex mixtures (even water effluents, soils,…) from their NMR spectra.
Typically, for fluorinated molecules, 19F NMR allows to distinguish:
- aromatic Φ-F,
- -CF3, -O-CF3
- aliphatic -CF2-, -CHF-…
For PFAS compounds, additional information may be available through NMR experiments such as estimation of :
- average length of chain,
- functionalization of per- and polyfluoroalkyl chains.
Fluorinated NMR datasets are preprocessed implementing an automatic pipeline: Plasmodesma web service.
The work was partly supported by innovation funding programs from ANR, the French National Research Agency and Alsace Innovation agency.