Enormous amounts of data are produced during the measurement processes based on imaging spectroscopy: millions of spectra and datasets of several GB require a reliable analysis. To identify materials, each spectrum needs to be classified by using reference spectra. Measured spectra from microplastics samples come with a high variability (e.g. total absorption, weathering effects etc.) which need to be taken into account during the analysis.
During years of research and development, we were able to build up a unique, expert-curated dataset of several thousands of spectra from real-life samples that include this variability. With conventional approaches, such as spectral libraries, more reference spectra lead to longer processing times. Therefore, the Microplastics Finder is based on machine learning and overcomes this challenge. By leveraging the power of this technology, you do not have to make a compromise between speed and analytical quality anymore. One solution, one button empowers you to analyze a wide variety of samples and polymers - within minutes.
Interested in learning more about how the Microplastics Finder works?