Transport is responsible for around a quarter of EU greenhouse gas (GHG) emissions, and more than two thirds of transport-related GHG emissions are from road transport. Countries around the world are betting on EVs to meet sustainability targets. Battery cells are considered as the heart of EVs, and currently EU OEMs import around 90% of the battery cells from Asian companies. New materials and processes are needed if the EU wants to catch up with Asian battery manufacturers. SAFELiMOVE will gather key European actors in the battery sector, from industrial materials producers, to R&D centers and automotive industry, covering the complete knowledge and value chain. SAFELiMOVE will not only strengthen the R&D in the energy and automotive sectors but especially the European industry in these fields. SAFELiMOVE project aims to support a market-driven disruptive technology change towards high energy density batteries (450 Wh/kg or 1200 Wh/L) and improved safety in a cost-effective manner. SAFELiMOVE delivers innovations in five main technology areas: development of nickel-rich layered oxide cathode materials; high specific capacity, lithium metal anode materials; advanced hybrid ceramic-electrolyte with improved ion conductivity at room temperature; interface adoption for effective Li transport by surface modification and/or over-coatings, and knowhow creation for the development of scale up production of all-solid-state batteries. By higher energy density batteries towards 450 Wh/kg, faster charging and longer cycle life, SAFELiMOVE aims to meet future battery requirements for EVs. Thus, the range of EVs will be extended and the electro-mobility and decarbonization will be further pushed forward with impact in climate change scenarios.

DESTINATE aims to develop tools and methodologies for railway noise simulation and cost-benefit analysis of mitigation actions of interior and exterior noise. For accurate noise prediction it is essential to characterize the structure-borne and airborne sound sources accurately in order to create valid input for sound prediction simulation models. The calculated interior and exterior noise can be auralised and visualised in a studio to evaluate the sound quality and sound comfort of potential mitigation measures in the vehicle design process. Auralisation and visualisation of noise can be used to assess the annoyance reduction of a given measure. Thus human perception is adequately taken into account. For decision-making the cost of different design options is a very important parameter. DESTINATE aims to further develop cost effectiveness prediction and thus create the foundation for powerful tools to support decision-making on noise & vibration mitigation measures.

With the imminent introduction of artificial agents into our digital future, robots will become teammates, companions and counterparts. However, it remains unclear whether people would interact with humanoid robots as social partners or use them as mere tools. NeuroMarkerHRI seeks to identify neural markers of the activation of social cognitive mechanisms with robots based on hemodynamic responses using supervised ML models. This will determine whether the human brain interprets the behavior from a humanoid robot using social (e.g., mirror neuron system, theory of mind) or general domain cognitive mechanisms (e.g., attention, cognitive control). With a hypothesis-driven and stepwise approach, the project will measure hemodynamic responses with functional near-infrared spectroscopy (fNIRS) in brain regions associated with social cognition, theory of mind and perception of mental states during collaborative interactions with humanoid robots. Hemodynamic signal features will be included in the machine learning models to identify predictors of social or general domain cognitive mechanisms. The project's interdisciplinary nature integrates well-documented methods of cognitive neuroscience, advancements in robotics, and state-of-the-art machine learning techniques to thoroughly evaluate the factors that modulate the activation of the social brain exposed to humanoid robots. Outcomes will set standards for future research in human-robot interaction, offer a reliable tool for designers to measure the effect of robot behavior on the users, and boost the development and improvement of efficient human-robot collaboration. The current project contributes to creating a human-centered development of technology and would help towards the digital transition in Europe, allowing to unlock the potential of social, industrial, and commercial human-robot collaboration.