Purency’s Projects

Driving research, innovation and standardization

Benedikt Hufnagl working on the software
Research and Development

Improving and expanding on solutions - for microplastics analysis and beyond

Purency invests into research and development projects - both internally as well as with external partners from industry and science. The goal is to expand the Microplastics Finders capabilities and applicability to become the gold standard for microplastics analysis. Furthermore, we work towards offering automated data analysis solutions for other scalable problems within analytical chemistry.

Start a project

Let us explore the opportunity of working together to leverage the value of your chemical data!

Are you starting a research project on microplastics? Do you need a partner to automate your data analysis workflow? Or have you identified a large data analysis bottleneck within analytical chemistry? We would love to hear from you and explore the options.

Purency is involved in the standardization of microplastics analysis on an international level

There still is a lack of standardized methods for the detection and analysis of microplastics in different samples. Next to developing and establishing methods, it is crucial to define standardized workflows to ensure reliable, reproducible and comparable results across laboratories around the globe. Only then will we be able to make holistic statements about the presence and effects of microplastics.
Working togehter in the Purency headquater

Recent activities
in Research and Development

First prototype of machine learning-based data analysis for Raman

In cooperation with leading researchers, Purency has developed a first prototype to automate the data analysis of microplastics meeasurements using Raman spectroscopy.

Purency joins research project Microplastics@Food

Microplastics at Food: International project strengthens efforts of science and industry in microplastics research.

Publication evaluates machine learning-automated analysis of μFTIR-imaging

New publication evaluates the advantages of computer-assisted microplastics analysis based on μFTIR-images of several environmental samples and machine learning-based data analysis
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