During the first 18 months of the project, significant advancements were made across multiple domains, including materials, processes, measurement systems, and modelling techniques, all aimed at enhancing the efficiency of microwave-assisted processes in energy-intensive industries.
A new class of circular refractories was developed and tested for use as insulating linings, susceptors, or to enhance microwave attenuation. These materials, tailored with active compounds like copper slag and graphene-based additives, were characterised for their thermal and electrical properties. Predictive models of permittivity were created, enabling the production of castable and formed products via geopolymerization. This marks a major leap forward, addressing the previous lack of materials and data specific to microwave heating applications.
Advanced multi-physics modelling and new post-processing algorithms were implemented to assess temperature and heat distribution uniformity. These tools go beyond standard commercial software by providing quantitative indicators of heating effectiveness. Simplified modelling approaches, such as one-way coupling and 2D approximations, were introduced to accelerate the optimisation of microwave applicator designs, supporting a “design for processing” strategy focused on performance and efficiency.
Modular microwave-plasma furnace sections were proposed, enabling smaller prototypes that replicate larger systems for reliable scale-up data. A new plasma torch design minimised microwave emission, simplifying the ceramic firing prototype and improving material handling and shielding. For asphalt processing, a redesigned system reduced operating temperatures by over 1000°C and enabled recycled asphalt processing on a conveyor belt instead of a trommel. In anode baking, the integration of microwave and induction heating, with frequency-controlled solid-state sources, allowed for precise heat pattern control.
Advanced sensor systems are under development, including distributed FOS and multispectral SWIR cameras, to monitor high temperatures in real-time and to function without metal components, ensuring accurate readings in strong electromagnetic fields.
Sensor data will feed into a five-step methodology for real-time process monitoring and control via an IEC61499-compliant automation platform, which supports flexible sensor integration and cloud connectivity, enabling digital twin comparisons. Finally, a layered data architecture has been developed, enabling seamless data flow from the shop floor to the cloud, supporting secure data hosting and sharing.
