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PFAS pollution and NMR: a rapid and non-destructive diagnostic

In the context of ongoing PFAS crisis, CASC4DE proposes a quick NMR diagnosis to detect significant PFAS pollution by recognizing their distinctive NMR fingerprint.

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PFAS: The 'Forever Pollution' Project

This week multiple colorful maps have been published gathering and analysing available data on PFAS contamination. This has been initiated by a group of journalists interested in a cross-boarder project about:

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It's raining PFAS

Researchers from Stockholm University, ETH Zürich and RECETOX - Masaryk University Brno under supervision of Pr Ian Cousins and Pr.

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ANSES focus on PFAS

Focus of the National Health Safety Agency - Anses on PFAS, synthetic perfluoroalkyl and polyfluoroalkyl compounds used for their non-stick, heat-resistant and waterproof properties.

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'ENVOYE SPECIAL' focus on PFAS pollution

This Thursday evening on France 2 with ENVOYE SPECIAL, Elise Lucet’s team denounces a pollution of soils with perfluorinated substances, also called PFAS.

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Extreme resolution and sensitivity in FT-ICR MS

Phase sensitive 2D in absorption mode allows extreme resolution and sensitivity in FT-ICR MS. A collaboration between Maria van Agthoven , Katrin Breuker, Marc André Delsuc from CASC4DE, IGBMC, University of Strasbourg & Leopold-Franzens Universität Innsbruck.

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Higher Levels of 'Forever Chemicals' Found in Volunteer Firefighters

Research efforts on PFAS are needed to fully understand their impact and reduces PFAS risks to the public Exposure to per- and polyfluorialkyl substances (PFAS) has been evaluated for volunteer firefighters in New Jersey by Graber and coworkers.

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Application of Optimal Control Theory to Fourier Transform Ion Cyclotron Resonance

When quantum computing meets chemistry issue. Prof Dominique Sugny and Dr Steffen Glaser, Optimal Control Theory specialists from the ICB Laboratoire, collaborated with CASC4DE scientists for a deeper understanding of experimental techniques in analytical sciences.

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Extraction of organic chemistry grammar from unsupervised learning of chemical reactions

A significant step forward to automate atom mapping without human supervision using Transformer Neural Network and training set of reaction SMILES.

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