The project aims to contribute to the development of a circular economy by developing i) tools for a chemometrically assisted decontamination (DC) process with advanced quality control and ii) a revolutionary DC technology based on a renewable energy source. The project results are expected to facilitate the reuse and recycling of plastic and glass waste, extend the life of these materials and help comply with strict EU food contact rules. The project team focuses on the removal of plasticizers, herbicides, persistent organic pollutants, lubricating oils and fouling agents.
Current decontamination methods such as hot water washing and gamma irradiation are resource-intensive and harmful to the environment. In contrast, the consortium of this project proposes to use visible light as a renewable energy source and specifically to develop a catalytic system that can be used multiple times for a DC without loss of activity. Since traditional empirical technical development is multi-stage and time/resource-intensive, the project team wants to use the support of AI to reduce the required resource and manpower requirements and achieve maximum effectiveness. Target algorithms and techniques include neural network architectures, trait mapping, reinforcement learning, clustering, genetic algorithms, and Large Language/Multimodal Models (LLM/LMM). This approach is in line with the call for proposals' focus on innovative, resource-efficient processes that support the transition to a sustainable economy. Finally, the developed process will be tested in a photoreactor and in an automated decontamination setup with feedback from AI tools.
The consortium, consisting of leading research institutions (Vienna University of Technology, FOTEC GmbH, SWISDATA gGmbH) and industry partners (Moncon GmbH, Redeem Solar Technologies GmbH), will work together to develop this cutting-edge technology and ensure that it is scalable and suitable for waste management.
The project results will bring significant benefits to the reusable packaging industry, recycling companies, AI developers, photoreactor developers and the wider environmental sector, strengthening Austria's position as a pioneer in circular economy innovation. The chemometric software tool developed for light-driven DC could be further generalized for application to common DC methods. By meeting both the quantitative and qualitative objectives of the tender, the project will contribute to the reduction of greenhouse gas emissions, promote the use of renewable energy sources and support the creation of resilient, resource-efficient production systems. In addition, the integration of advanced chemometric techniques into the decontamination process will set new standards for efficiency and sustainability in waste recycling.