Microplastic analysis presents significant challenges for laboratories worldwide: complex datasets, inconsistent methodologies, and the lack of standardized workflows make it difficult to compare results across studies and laboratories.

With AI4PlastiTrax, we are developing a web-based software solution that combines advanced optical particle detection with AI-driven, spectrum-based data analysis. The system is trained on tens of thousands of polymer spectra, enabling robust and reliable identification through machine learning.

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Our goal is to contribute to the harmonization and standardization of microplastic analysis, independent of laboratory, instrument, or analytical method.

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In combination with our particle-based reference materials, this approach creates a unique integrated concept designed to improve precision, reproducibility, and efficiency in microplastic analysis.