Machine Learning is a game-changing technology that has a track record of disrupting and challenging the status quo. With respect to microplastics analysis it can enable a scalable data analysis pipeline: labs can analyse more samples at a lower cost.

Cutting-edge methods for the detection of microplastics in food are the focus of this international project that consists of strong research partners and more than 55 companies from F&B and packaging industries.

Purency Co-Founder Benedikt Hufnagl has been nominated for the CEN and CENELEC Standards + Innovation award in the category Young Researcher!

What began as laborious manual processing in 2016 has now become one of the fastest and most accurate analysis pipelines for microplastics analysis. Learn more!

Purency contributes at Society of Environmental Toxicology and Chemistry (SETAC) annual meeting with a presentation on the 'Automated Ultra-Fast Analysis of Microplastics in large µFTIR Imaging Datasets From Environmental Samples Via RDF Classifiers'.