Nowadays the overall energy demand in downstream steel production is mainly based on fossil fuel, so it is fundamental to find and set new ways to overcome the environmental impact of steel production Currently, the state-of-art of reheating furnaces is based on CH4 burners, with an evident environmental impact on CO2 emissions The main objective is to decarbonize this process, based on the introduction of hybrid heating technology, based on electrification and gas-burning properly combined. This solution provides an opportunity to explore the synergic effect of different technologies, by “hybrid heating”. Moreover, the whole efficiency of the heating process can be furtherly improved by the recovery of enthalpy content of off-gases from the furnace. The furnace partial electrification will be realized by the installation of an induction system. The electricity to feed the inductor will be provided by a renewable source (RES) and by the heat recovery system.

The proposed project aims to increase recycling ratio of steel and metals through improved sorting of scrap, better separation of non-wanted tramp elements as well as the valuable alloying elements. Steel can be recycled over and over again while retaining its technical properties. However, contaminations of tramp elements and losses of alloying elements do occur in the solid state and liquid state recovery processes currently employed in the industrial value chain. The project aims to enhance the integrated value chain of scrap based steel production through; investigate and develop scrap preparation methods, research new ways of sorting and separation of material, investigate and develop specific methods to remove copper and tin in the liquid phase and to recover copper form steelmaking residues through pyrometallurgical processes, create new steel products that can handle a higher copper content while maintaining required application properties, and finally lab-scale experiments to develop thermodynamic and kinetic modelling focusing on tramp elements. The target is to achieve 90% EOL recovery rates and a reduction of tramp elements by 60-70%, improved separation and sorting of scrap with a targeted increase in separation specificity of 50% and a target of copper element recovery from steelmaking residues about 60%. Ultimately the developed models will, when relevant, be verified with data from full-scale tests in industrially relevant environments. The consortium includes 8 partners from 5 different EU-countries a scrap recycler (STEIL) / a steelmaker (SIDENOR) – and different R&D entities (KTH, KOBOLDE, TECNALIA, University of Limerick and Politecnico de Bari) as well as a supplier (LSA) of sensors for scrap identification covering all the competences needed for the development of the MEDALS project

The overall objective of s-X-AIPI is to research, develop, test and experiment an innovative toolset of custom trustworthy self-X AI technologies (autonomous AI that minimizes human involvement in the loop an exhibit self-improving abilities). AI applications will help workers to deal with external and internal influences and enable agile and resilient reaction of European process industry processes and products? lifecycle for a true integration into the circular manufacturing economy ecosystem. The aim is to provide existing process industries and its workers with agility of operation, improvement of performance across different indicators and state of the art AI-based sustainability tools for the design, development, engineering, operation and monitoring of their plants, products and value chains. Demonstration at four representative industrial use cases (asphalt, steel, aluminium and pharmaceutics) will generate a showcase portfolio of trustworthy AI technologies (data sets, AI model and applications) integrated into an innovative open source toolset available for industry and research as an example of self-X AI technologies integrated in actual process industries? value chains. s-X-AIPI toolset of AI technologies will include an innovative AI data pipeline with autonomic computing capabilities (self-X AI and autonomic manager), architecture, realistic datasets together with their respective algorithms derived from the demonstration in four realistic use cases of process industry. s-X-AIPI technologies will consider workers? heterogeneous skill levels and self-adaptation capabilities to the actual profile of the worker respecting their human-in-the-loop role. s-X-AIPI will be performed by an interdisciplinary consortium (AI integration and Big Data analytics, use case process understanding, modelling and digital platforms, research, industry, SME [4 companies, 1 industrial], communication, exploitation, standardisation).

Effectively combating global warming requires a significant reduction in CO2 emissions. This poses enormous challenges, especially for the energy-intensive process and production industry, as this industry accounts for one third of total energy consumption. What is needed is intelligent electrification across all operational processes. Electrification has such a large potential impact on decarbonisation because it allows clean, renewable electricity to power processes that previously used emissions-intensive technologies (such as gas burners). This means that a process that previously produced high emissions can become absolutely emission-free when powered by renewable energy. The aim of the CITADEL project is to substitute fossil combustion processes with innovative electric technologies, such as electric resistance heating, microwave heating and plasma heating. Five use cases are considered, targeting the production of refractory bricks, glass and copper wires, preheating processes in steel production and the recycling of concrete. For these specific applications, appropriate demonstration plants have to be designed, built, tested close to the process and validated. This is supported by corresponding activities to provide suitable high-temperature materials and tools for instrumentation and effective process control. Challenges regarding a stable energy supply, electrical and thermal load management or intelligent energy management are simulated by means of numerical models. This includes corresponding risk assessments, e.g. with regard to possible time constraints in terms of a continuous power supply and the consequences of supply fluctuations for process safety. All demonstration cases will be evaluated by a life cycle analysis and with regard to the effectiveness in the reduction of greenhouse gases. The impact of the technical solutions developed here for the process industry will be assessed and strategies for scale-up and deployment will be elaborated.

HyWay aims to develop adaptive multiscale material modelling and characterisation suites for assessing interactions between hydrogen and advanced metallic materials and demonstrate their capabilities on hydrogen storage and transport components. Advanced materials application like hydrogen technologies is essential for achieving the EU carbon neutrality goal. However, deploying hydrogen technologies needs a tremendous effort to complete the infrastructure, requiring efficient material assessment suites, enabling industries to be more effective in developing and working with materials. Furthermore, since hydrogen is stored and transported in several forms, the material assessment suites must be flexible and capable of revealing hydrogen-material interactions in various conditions. The HyWay suites contain 3 key modules: Physical realm, Virtual world, and Data and knowledge management platform (DKMP). The Physical realm will advance experimental capabilities to reveal hydrogen-material interactions by compiling characterisation methodologies across length scales. The Virtual world will develop a multiscale and multiphysics materials modelling framework for disclosing how hydrogen alters changes in advanced materials under various service conditions. The Physical realm and the Virtual world are interdependent and complement each other through the data exchange between modules. We will establish the DKMP to facilitate the data exchange and merge material research disciplines. HyWay will ensure the productive allocation of investments required in constructing the hydrogen infrastructure. We will strengthen European capability in steering green transition with digital technologies and future emerging enabling technologies and ensure an open strategic autonomy by supporting the transformation of the EU energy mix to be dominated by hydrogen. The consortium comprises renowned experts from academia and industries across the EU and will support Ukraine on its European path.