Highly efficient energy conversion of solar power and storage will play a vital role in a future sustainable energy system. Thus, this project focuses on the development of a novel high-efficiency solar thermal power plant concept with an integrated electricity storage solution. The project combines air-based central receiver Concentrated Solar Power (CSP) and Compressed Air Energy Storage (CAES) to maximize conversion efficiency and power grid energy management, enabling a new operation strategy and business models. The hybrid concept initiates a futuristic era with adaptive renewable power plants, producing both electrical and thermal energy, including process heat supply and reverse osmosis desalination. Because cheap off-peak electricity is used to provide the air compression work of the topping Brayton cycle, the overall peak solar-to-electric energy conversion efficiency of the proposed power plant may reach up to 40% efficiency, which roughly doubles the peak efficiency with respect to state-of-the-art CSP technology. The project’s activity will cover the techno-economic-environmental optimisation of the innovative CSP-CAES plant using representative boundary conditions, provided by grid operators and specialised partners, as well as the development and extensive testing of key components needed for its implementation. The main development will cover: (i) an advanced high-efficiency solar receiver, (ii) optical sensors and AI-based control, (iii) optimized CAES with heat exchangers and compressor/expander detailed designs and (iv) innovative integration of desalination. The proposed technology is set forth by an interdisciplinary partnership spanning the entire CSP value chain. Targeting a TRL of 6-7, the ASTERIx-CAESar concept will be validated with a demonstration scale of 480 kWth prototype in a relevant environment.

The growing energy demand aggravated by the high dependency on non-renewable fossil fuels has severely impacted on climate change, as evidenced by Earth’s global average temperature increase in the last century. Road transport is responsible for around three quarters of transport-related greenhouse gas (GHG) emissions, thus decarbonization of this sector is necessary to achieve a climate neutrality. Battery Electric Vehicles (BEVs) are a crucial enabler for accomplishing this target. In this frame, SOLIDBAT proposes a disruptive solid-state battery (SSB) technology to meet the challenging demands of the automotive sector. The focus is on high energy density SSB (400 Wh/kg, 1000 Wh/L) enabling fast charging, long life, and safety. To achieve these goals, SOLIDBAT entails innovation in five main areas: i) Digital tools and models for materials development and cell parameters design; ii) High capacity and water processable surface protected nickel-rich NMC cathode active material; iii) 3D-texturized high energy lithium metal anode coated with a protective artificial solid-electrolyte interphase (SEI); iv) Highly conductive and electrochemically stable hybrid gel polymer electrolyte (HGPE), crosslinked in-situ; and v) Scalable solutions for SSB technology manufacturing that are easily adaptable to current lithium-ion technology, thus hastening the introduction into the EV market. Moreover, cost, sustainability and recycling are prioritized along the whole project development, in e.g., reducing raw material use and avoiding organic solvents for greener processing. SOLIDBAT's collaborative consortium spans the whole battery value chain, fostering European innovation and industry growth. By establishing SSB manufacturing in Europe, SOLIDBAT contributes to climate-neutral energy and transport transitions, as well as avoids the dependence of battery production on Asian countries such as the current situation for Li-ion technology.

The Skyrmionic Artificial Neural Network (SkyANN) presents a groundbreaking paradigm for neuromorphic computing, closely emulating brain neurophysiology by combining skyrmionic quasiparticles, which mimic neurotransmitters and facilitate complex computations at the synapse level, with electrical CMOS connections that simulate the propagation of action potentials among neurons for rapid and dense inter-layer connectivity. Our innovative magneto-electric devices aim to achieve energy consumption four orders of magnitude lower than CMOS technology and double the bandwidth for the same device footprint, enhancing edge inference and learning capabilities. This approach challenges contemporary neural networks implemented with CMOS digital, mixed-signal, and emerging in-memory computing technologies, which are limited by lower energy efficiency and reliability. Building on preliminary results from SkyANN partners, we plan an ambitious endeavor to develop a first-of-its-kind magneto-electric neural network, showcasing the promising potential of this novel technology. Along the way, we will refine materials, processes, design methodologies, and architectures to prepare the European micro- and nano-electronics ecosystem for the future, while supporting the EU's Green Deal vision. Our well-balanced consortium brings together complementary expertise and extensive knowledge, spanning from device physics to circuits and architectures across multiple layers of design abstraction. As a result, the SkyANN consortium is poised to facilitate the rapid transfer of fundamental discoveries to relevant industrial stakeholders, accelerating impact and reinforcing European strengths in the economically, geopolitically, and socially vital semiconductor sector.

MacroFuels aims to produce advanced biofuels from seaweed or macro-algae. The targeted biofuels are ethanol, butanol, furanics and biogas. The project will achieve a breakthrough in biofuel production from macroalgae by: • Increasing the biomass supply by developing a rotating crop scheme for cultivation of seaweed, using native, highly productive brown, red and green seaweeds. Combined with the use of advanced textile substrates these breakthroughs will result in a year round biomass yield of 25 kg seaweeds (wet weight) per m2 per year harvested at 1000m2/hr; • Improving the pre-treatment and storage of seaweed and to yield fermentable and convertible sugars at economically relevant concentrations (10-30%); • Increasing the bio-ethanol production to economically viable concentrations of > 4%/l and; • Increasing the bio-butanol yield to 15 g./l by developing novel fermenting organisms which metabolize all sugars at 90% efficiency for ethanol and butanol; • Increasing the biogas yield to convert 90% of the available carbon in the residues by adapting the organisms to seaweed; • Developing the thermochemical conversion of sugars to fuels from the mg. scale to the kg. scale; • Performing an integral techno-economic, sustainability and risk assessment of the entire seaweed to biofuel chain. MacroFuels will develop technology for the production of fuels which are suitable as liquid fuels or precursor thereof for the heavy transport sector as well as potentially for the aviation sector. The technology will be taken from TRL3 to TRL 4/5. MacroFuels will expand the biomass available for the production of advanced biofuels. Seaweed does not need fresh water, arable land or fertilizers to grow, which provides environmental benefits, and in addition has a high carbon dioxide reduction potential as well as reduces the demand for natural resources on land. The technology offers many novel opportunities for employment along the entire value chain.

The goal of RadioSpin is to build a hardware neural network that computes using neural dynamics as in the brain, has a deep layered architecture as in the neocortex, but runs and learns faster, by seven orders of magnitude. For this purpose, we will use ultrafast radio-frequency (RF) oscillators to imitate the rich, reconfigurable dynamics of biological neurons. Within the RadioSpin project, we will develop a new breed of nanosynapses, based on spintronics technology, that directly process the RF signals sent by neurons and interconnects them layer-wise. We will demonstrate and benchmark our concept by building a lab-scale prototype that co-integrates for the first time CMOS RF neurons with spintronic RF synapses. We will develop brain-inspired algorithms harnessing oscillations, synchrony and edge-of-chaos for computing and show that they can run on RadioSpin deep network RF technology. Finally, we will benchmark RadioSpin technology for biomedical and RF fingerprinting applications where fast and low energy consumption classification of RF signals are key. To achieve its ambitious goals RadioSpin brings together frontier researchers along the entire chain of neuromorphic engineering, from material science (spintronic nanodevices), physics (non-linear dynamics), electronics (RF CMOS design), computer science (artificial intelligence algorithms), and microwave signal processing. Two innovative companies bring real-life use-cases (microwave mammography and IoT RF fingerprinting). The scientific experts are further complemented by experts in the field of innovation, commercial deployment and IP monetisation, as well as communication and public engagement.