Rosenheim University of Applied Sciences is planning a process technology for the CO2-neutral production of semi-finished fiber products from renewable raw materials. The aim is to optimize the production chain for sustainable lightweight construction, whereby gaps to conventional reinforcing fibres are to be closed.
The project aims to conserve resources and promote the use of renewable raw materials in a circular economy. This is in line with the strategies of the Bavarian state government, the federal government and the UN Sustainable Development Goals. Lightweight construction, especially with renewable raw materials, can replace environmentally harmful petrochemical and glass fibre-reinforced plastics, which cause considerable CO2 emissions.
Rosenheim University of Applied Sciences (THR) has specialized facilities and resources for the development of climate and resource-friendly processes and products, especially in the automotive, construction and timber construction sectors. THR still lacks specific plant technology for the exploration of high-performance areas in mechanical stress. The project aims to close this gap by developing a process and plant technology.
The project focuses on the development and optimization of sustainable, CO2-neutral lightweight construction materials and processes using holistic research methods and modern technology.
The proposed process and plant technology for the impregnation and consolidation of flat fiber-reinforced semi-finished products and thus the complementation of the process chain for sustainable lightweight construction solutions enables the reproducible production of bio-based, long-fiber-reinforced thermoplastic semi-finished products using all common processes in the industry.
The overarching goal is to carry out holistic and knowledge-oriented research in the field of CO2-neutral lightweight construction, involving a wide range of disciplines at THR. This enables Rosenheim Technical University of Applied Sciences to map the entire process chain, present and work out interdependencies across processes and thus provide industry with trend-setting information.
ORCID iD: 0009-0003-9099-1046