After almost five years in the Digitalization Research Group, Timo Grunemann took over as head of the Spectroscopy Group on January 1, 2026. Until now, his work in the Digitalization Group has focused on projects to develop AI models for process optimization in the plastics industry. There were already some overlaps with spectroscopy: “During my time in digitalization, I was able to implement two successful applications for research projects together with the Spectroscopy Group,” says Grunemann.
One of these projects is the ongoing SME-innovative joint project SpectralAIge. It combines state-of-the-art spectroscopic methods, including hyperspectral imaging combined with multispectral LED-induced fluorescence excitation, with AI-based evaluation methods. The aim of the project is to detect process-related aging of plastics in the recycling cycle at an early stage. This allows recycled plastics to be efficiently directed to different recycling routes depending on their degree of aging – for example, mechanical or chemical recycling, but also downcycling.
With a degree in physics from Julius Maximilian University of Würzburg and a master's degree in optoelectronics and lasers from Heriot-Watt University in Edinburgh, the 40-year-old is ideally qualified for his new role. “We are delighted that we have been able to recruit Timo Grunemann, who has a wealth of interdisciplinary experience and expertise, for the position of group leader,” says Dr. Linda Mittelberg, Head of Quality and Life Cycle and former group leader of Spectroscopy.
Future development of the Spectroscopy Group
The Spectroscopy Group will continue to focus on the application and further development of modern spectroscopic methods. A particular focus will be on the initial evaluation of recyclates using hyperspectral imaging. Since recyclates often exhibit fluctuating material parameters from batch to batch, their processing remains a major challenge for many companies.
Hyperspectral imaging offers great opportunities here, as this technology enables the rapid analysis of large quantities of material. Other current areas of focus include inline Raman spectroscopy, for example for the detection of foreign material in the melt during the extrusion process, and the use of machine learning methods to create chemometric analysis models.
In addition, the group is also working on hydrogen permeation in plastics. One focus here is on the development of hydrogen-free testing methods that offer industry efficient and safe alternatives to conventional hydrogen tests.
Further information on spectoscropy