The Material Analytics Department focuses on the molecular characterization of plastics and their compounds. To this end, it develops methods of liquid chromatography, spectroscopy, and spectrometry. The aim is to create molecular fingerprints of plastic compounds and investigate structure-property relationships. In addition, measurement methods for recording macroscopic properties are being developed in order to create material models. The focus is on morphology and application-relevant properties in order to investigate aging and failure mechanisms, the effects of media, and dielectric properties. AI-supported analytics and data-based models enable more precise prediction of material properties, which increases the efficiency of material development and enables tailor-made solutions for specific applications. In addition, the department is expanding its analytical methods to include metallic and polymeric materials along the entire value chain up to the component level. A particular focus is on trace analysis of plastic formulations, especially with regard to critical components in a regulatory context. Machine learning approaches are used to systematically link analytical data with application properties in order to support requirements for accelerated material development, taking into account costs, regulations, and sustainability.