Real circular economy of natural fiber-based material systems

© DFG

Natural fiber-based materials offer sustainable applications, but are usually incinerated. The project investigates recycling barriers and develops AI-supported models for circular value creation.

Project background

The project is investigating how natural fiber-based material systems (NWS) can be better integrated into a circular economy. To this end, barriers and drivers for the recycling of NWS are analyzed, recycling processes are investigated and optimal recycling paths and process parameters are identified using a digital model and AI methods.

Currently, NWS are mostly recycled for energy at the end of their life cycle, resulting in the loss of valuable resources. With increasing quantities of end-of-life products, the need for efficient recycling solutions is growing. The project creates knowledge about materials, processes and market conditions to enable robust recycling systems and circular value creation.

Project objective

The project aims to create a comprehensive understanding of the technical and socio-economic barriers and drivers for the recycling of natural fiber-based material systems and to analyze recycling processes and secondary materials from the automotive and construction sectors.

The aim is to identify optimal recycling paths and process parameters with the help of measurement series, a modular digital model and AI methods, thus enabling robust recycling systems and circular value creation.

Project procedure

The project combines qualitative and quantitative methods to analyze technical and socio-economic barriers to the circular economy for NWS. Secondary materials from the automotive and construction sectors are examined, in particular with regard to preparation, sorting and further processing in material and chemical recycling paths. Measurement series are used to quantitatively describe dependencies between materials and processes as well as the performance of various processes.

Based on this data, a modular, digital model is being developed to identify and optimize optimal recycling paths and process parameters. Artificial intelligence methods such as Explainable AI (XAI) are applied and evaluated. In addition, a system dynamics approach is used to analyze material volumes, market mechanisms and environmental impacts for the development of robust recycling systems.


Project coordinator


Sub-project lead









Project staff


Alisa Kehr
T +49 (0) 8031 / 805 - 2864
alisa.kehr[at]th-rosenheim


Nina Leiter
T +49 (0) 8031 / 805 - 2857
nina.leiter[at]th-rosenheim.de

ORCID iD: 0009-0009-6472-4255


M.Sc. Jan Luka Maurischat
T +49 (0) 8031 / 805 - 2985
jan-luka.maurischat[at]th-rosenheim.de

Frederik Obermeier
T +49 (0) 8031 / 805 - 2266
Frederik.Obermeier[at]th-rosenheim.de

ORCID iD: 0009-0007-6049-9017






External project collaboration

Dr. Ursula von Gliscynski
Deutsche Forschungsgemeinschaft

Project duration

2026-01-01 - 2030-12-31

Project funding

Deutsche Forschungsgemeinschaft

Funding programme

DFG - Forschungsimpulse

Sustainable Development Goals