Unquestionable, Raman micro spectroscopy has become one of the major approaches for microplastics detection. However, a key issue with this approach is the difficulty of automating the measurement process and data processing. In a joint project researchers from Purency and Leibniz-Institut für Polymerforschung Dresden e.V. investigated, whether machine learning can be used effectively for the identification of Raman microplastics spectra. Based on Purency's software technology and the years of experience of IPF Dresden, the partners developed an initial prototype which can detect 7 different types of microplastics and is robust against fluorescence, low signal to noise ratio as well as matrix residuals common in environmental samples.
This initial prototype, however, is just the beginning, as we at Purency want to extend the applicability and robustness and bring it to market readiness. This is why we are looking for testers and early adopters which are willing to give us feedback and participate in the ongoing development. If you are interested or know research groups which use Raman spectroscopy for microplastics detection, then please connect with us.