Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Prototyping and Deploying the World’s First Zero-Emission, Fully Electric, Unlimited Range, Commercially Viable Cargo Barge in European Shipping Ports (ZERO-CARGO)

Framework: Horizon Europe — Innovative Europe
Programme: The European Innovation Council (EIC)
Theme: EIC Accelerator
Destination: Other destinations
Action type: EIC actions
Countries involved: United Kingdom
Call: EIC Accelerator 2025 - Short application (HORIZON-EIC-2025-ACCELERATOR-01, 2025)
Duration (months): 12.0
Total project cost (EUR): 2918878.0
EU funding (EUR): 2918878.0
Participants: 1
Project status: CLOSED

Voltic Shipping is a clean maritime deep-tech company spun out of MIT and backed by Y Combinator and the U.S. Department of Energy, is developing a patented, modular towable solar array system. The system includes 5,100–9,000 high-efficiency panels on 50–200 jointed pontoons spanning over 5,000 meters, retractable to the ship’s aft deck for survivability and port compatibility. It supplies 100% of propulsive power to legacy vessels at 11–12 knots while charging onboard batteries, validated by computational fluid dynamics, towing tank campaigns, and on-water trials. We propose the build of a medium-scale barge with this technology as part of this grant proposal, including a retrofit of a marine-certified 560-kWh battery stack, 880-kW electric drive, and vertical storage system, which will help Voltic progress from TRL 6 to 9 with Lloyd’s Register certification. This zero-emission, unlimited-range, commercially viable solution preserves cargo space and leverages existing port infrastructure. With over €100M in contracted revenue, Voltic aims to retrofit 1000-TEU containerships, reducing maritime shipping emissions, which are responsible for 3%, 19%, and 9% of global CO2, NOx, and SOx emissions, respectively. Our innovation offers up to 75% operational cost savings by eliminating fuel expenses, advancing sustainable shipping and fostering Europe’s green economy transition.

Keywords: towable solar array,zero emission shipping,electric vessels,maritime decarbonization,retrofit technology,renewable energy,battery electric propulsion,scalable marine innovation,ship retrofitti
A foundational AI-MRI framework for self-supervised discovery of transformative low-field MRI techniques (NEW-CONTRAST-MRI)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Systems and Communication Engineering
Panel description: Electrical, electronic, communication, optical and systems engineering
Countries involved: Israel
Call: ERC STARTING GRANTS (ERC-2025-STG, 2025)
Start date: 2025-11-01
End date: 2030-10-31
Duration (months): 60.0
Total project cost (EUR): 1812500.0
EU funding (EUR): 1812500.0
Participants: 1
Project status: SIGNED

Magnetic resonance imaging (MRI) is crucial to healthcare for its radiation-free, high-quality scans, but its high cost leaves 70% of the global population without access. Emerging low-field MRI technology offers affordable, portable systems with transformative potential, but faces critical challenges: long scan times, low signal-to-noise ratio (SNR), and poor tissue contrast, which makes some tissues indistinguishable. Although contrast agents help, they add risks. Early studies showed that low-field MRI can detect cancer without contrast agents using unique pulse sequences, but those are manually designed and slow. Recently, AI has been adopted for clinical high-field MRI, but AI pulse-sequence optimization relies on supervised learning, limiting discovery, AI theory is scarce, and simulations do not fully capture MRI’s complex spin dynamics. Moreover, AI use in low-field MRI remains mostly focused on image post-processing, while pulse sequence design, sampling, and reconstruction remain traditional and suboptimal. I propose to develop a foundational AI framework that will transform low-field MRI into a rapid, high-quality modality. To break the barriers posed by supervised AI and simulations, my key innovation is an integrated AI-MRI framework, where on-the-fly MRI measurements guide a self-supervised AI search through the parameter space. Leveraging AI foundations I have recently developed, the framework will jointly optimize pulse sequences, sampling, and reconstruction to revolutionize imaging. Specific aims: (1) speed up MRI by an order of magnitude; (2) establish AI theory; (3) build the framework and develop cutting-edge sequences for optimal tissue contrast; and (4) demonstrate these in human scans with my lab’s low-field MRI. Preliminary results support the feasibility of our design aims. This project will transform low-field MRI into a fast, affordable, contrast-agent-free tool with broad clinical applications, particularly in low-income regions.

Keywords: mri,machine learning,contrast,pulse sequence,contrast agent free,contrast mechanisms,mri in the loop
Exploration of Back-End-Of-Line Compatible Te-Based P-Type Transistors With 2D Material Van Der Waals Contacts for Monolithic 3D Integration (BEOLTPT)

Framework: Horizon Europe — Excellent Science
Programme: Marie Skłodowska-Curie Actions (MSCA)
Theme: Marie Skłodowska-Curie
Destination: Postdoctoral Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Information Science and Engineering
Countries involved: Germany
Call: MSCA Postdoctoral Fellowships 2023 (HORIZON-MSCA-2023-PF-01, 2023)
Start date: 2025-09-01
End date: 2027-08-31
Duration (months): 24.0
Total project cost (EUR): 173847.36
EU funding (EUR): 173847.36
Participants: 2
Project status: SIGNED

The performance enhancement of integrated circuits relying on the downscaling of transistor dimensions following Moore’s law is becoming more and more challenging as silicon is reaching its physical limit. Thus, monolithic 3D integration has been considered as a powerful method to improve system performance further. This requires that transistors be stacked on top of each other at back-end-of-line (BEOL) compatible temperatures to avoid degradation of underlying devices. Two-dimensional (2D) semiconductors are promising candidates for such BEOL transistors but most advancements in terms of device performance and reliable BEOL integration concern n-type devices, while p-type is still lagging behind. Hence, better p-type BEOL transistors are highly sought after to enable complementary metal oxide semiconductor (CMOS) technology. One of several challenges for p-type devices is contact resistance because wide band gap 2D semiconductors typically have large Schottky barriers between the metal contact and their valence band. Tellurium (Te) and its compounds have recently been identified as promising candidates for BEOL p-type 2D transistors, which offer decent access to their valence bands, integration at BEOL-compatible temperatures, and good material prospects for device performance. However, research on such devices is still in its infancy, and drive current, stability (passivation), and contact resistance still need improvements. Thus, in this work, we propose to advance the research in Te-based p-type devices. In particular, we will experimentally explore the potential of 2D material van der Waals contacts. Furthermore, we will evaluate the CMOS logic circuit performance coupling with its n-type counterpart and the prospects of our devices for monolithic 3D integration through simulation.

Keywords: 2d material,transistor,p type semiconductor,device fabrication,tellurium,2d van der walls contact,cmos circuit,simulation,material growth,thin film deposition,monolithic 3d integration
Investigation of mechanical properties, reversing energy absorption, ultrasound monitoring and identification of progressive failure behavior of 4D printed meta structures (SRMS)

Framework: Horizon Europe — Excellent Science
Programme: Marie Skłodowska-Curie Actions (MSCA)
Theme: Marie Skłodowska-Curie
Destination: Postdoctoral Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Information Science and Engineering
Countries involved: Belgium,Greece
Call: MSCA Postdoctoral Fellowships 2021 (HORIZON-MSCA-2021-PF-01, 2021)
Start date: 2022-09-01
End date: 2025-01-31
Duration (months): 29.0
Total project cost (EUR): 191760.0
EU funding (EUR): 191760.0
Participants: 2
Project status: CLOSED

Using additive manufacturing methods and the capability of introducing meta structures by four dimensional (4D) printing technology, the study of smart reinforced meta structures (SRMS) is one of the most attractive areas of research. Literature survey reveals that there is the lack of comprehensive research in this area. Therefore, there is a good potential to improve the design of meta structures using fiber-reinforced composite materials and to optimize and improve the quality of engineering structures. The proposed research program will deliver a novel, robust, efficient and accurate methodology for designing the 4D printed reinforced meta structures with nonlinear damaged structural segments. In addition, for identifying the existence of a certain damage type the ultrasonic wave actuation will be employed which has never been applied on composite meta structures before. To proceed the project, the 4D printer set up will be developed for fabricating the SRMS lattice structures for the first time. To examine the capacity of absorbed energy, the fabricated SMRS will be undergone the virtual and real experimental tests. Realization of the results of this research will make it possible to design structures with high energy absorption capacity that have suitable mechanical properties including higher special absorb energy to ideal weight. To characterize and monitor the potential damage mechanisms formed in the structures, ultrasound measurements will be employed for the first time in tessellated composite structures. For this aim, after calibrating ultrasound sensors, at different level of applied compressive load, the piezoelectric transducer excites propagating waves within the composite meta structures. The outgoing reflected and transmitted waves will be used for on quantifying and identifying damage.

Keywords: smart meta structure,composite 4d printed structures,absorb energy,ultrasound measurement
Nonequilibrium Many Body Control of Quantum Simulators (QuSimCtrl)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Fundamental Constituents of Matter
Panel description: Particle, nuclear, plasma, atomic, molecular, gas, and optical physics
Countries involved: Germany
Call: ERC STARTING GRANTS (ERC-2023-STG, 2023)
Start date: 2023-12-01
End date: 2028-11-30
Duration (months): 60.0
Total project cost (EUR): 1500000.0
EU funding (EUR): 1500000.0
Participants: 1
Project status: SIGNED

The ability to control quantum matter in a state of equilibrium is a milestone of 20th-century physics. A major goal of modern physics is to extend this knowledge to out-of-equilibrium systems. Located at the boundary between equilibrium and nonequilibrum, quantum simulation appears particularly suitable for this purpose. Using periodic drives, quantum simulators can experimentally emulate phenomena hitherto inaccessible in conventional materials, such as artificial gauge fields or topological and dynamically localized matter. However, our understanding of how to manipulate systems exposed to intense nonequilibrium drives is in its infancy, especially regarding strongly interacting models. We propose to overcome the current limitations by combining ideas from quantum control and artificial intelligence (AI) algorithms. We will develop a new theoretical framework for nonadiabatic many-body state control on top of strong periodic drives underlying the optimal manipulation of ordered prethermal states of matter without equilibrium counterparts. Understanding this many-body dynamics will improve cutting-edge manipulation techniques in cold atoms, trapped ions, superconducting circuits, and quantum solids. We will add reinforcement learning (RL), one of the most promising techniques in AI, to the quantum entanglement control toolbox. Deep RL has the potential to push the state-of-the-art of (dis-)entangling quantum states since it is capable of identifying effective degrees of freedom even when no underlying physical structure is immediately obvious. Discovering guiding principles of physics for many-body control away from equilibrium has the potential to reveal new connections across quantum dynamics, statistical mechanics, optimal control, and machine learning. The proposed research establishes a missing link on the roadmap for designing future materials and technologies based on nonequilibrium processes in condensed matter, quantum optics, and quantum computing.

Keywords: periodically driven systems,floquet systems,nonequilibrium quantum many body dynamics,prethermal steady states,reinforcement learning for quantum control,shortcuts to adiabaticity
ATOMIC-scale foundation of a Physics-based Interface Engineering in crystalline materials (AtomicPIE)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Countries involved: France
Call: ERC CONSOLIDATOR GRANTS (ERC-2025-COG, 2025)
Start date: 2026-04-01
End date: 2031-03-31
Duration (months): 60.0
Total project cost (EUR): 1999357.0
EU funding (EUR): 1999357.0
Participants: 2
Project status: SIGNED

Inorganic materials are integral to numerous fields, including transportation, electronics, and medical applications. Understanding their mechanical properties, particularly permanent inelastic deformation, has been a central pursuit in material science. My project, AtomicPIE, focuses on uncovering the key mechanisms driving plasticity in metallic alloys, emphasizing dislocation-interface interactions. These interactions occur at grain boundaries and phase boundaries, which significantly influence material strength, reliability, and lightweight properties. Despite extensive studies, a comprehensive understanding of slip transfer—how dislocations propagate across interfaces—remains elusive. AtomicPIE integrates atomistic simulations, generative machine learning models, and enhanced discrete dislocation dynamics to address this gap. By simulating crystalline defects and their interactions, the project employs Nye dislocation densities to bridge atomic- to micro-scale modeling. A key innovation is the use of machine learning to predict complex Nye dislocation fields for mesoscale simulations. The framework developed within AtomicPIE will be validated through experiments and cross-scale molecular dynamics, focusing on ultra-fine-grain aluminum alloys. AtomicPIE aims to establish a physics-based understanding of slip transfer at interfaces, paving the way for advanced materials design and interface engineering.
Accelerating renewable energy adoption by increasing grid capacity by 30% (Grid Raven)

Framework: Horizon Europe — Innovative Europe
Programme: The European Innovation Council (EIC)
Theme: EIC Accelerator
Destination: Other destinations
Action type: EIC actions
Countries involved: Estonia
Call: EIC Accelerator 2024 - Short application (HORIZON-EIC-2024-ACCELERATOR-01, 2024)
Duration (months): 48.0
Total project cost (EUR): 2500000.0
EU funding (EUR): 2500000.0
Participants: 1
Project status: SIGNED

One of the biggest obstacles to transitioning to renewable energy is the limitation of the electricity transmission grid, as existing grids are built to connect non-renewable energy production sites. The example of Estonia is illustrative: historical electricity generation is in the east, but favorable locations for offshore wind turbines are in the west. IEA estimates that globally, 3,000 GW of renewable energy is awaiting grid connection, which is equivalent to the entire installed capacity of solar and wind power in 2022. BNEF has estimated that nearly a trillion dollars per year is needed to invest in electricity grids for the transition to renewable energy worldwide. The electric grid is highly dependent on weather, especially wind. For example, a 2m/s crosswind doubles electricity throughput on the grid. 1m/s wind can increase the grid capacity at least by 35%. To account for weather conditions, highly accurate day-ahead predictions are required. However, all solutions available today rely on the installation of physical measuring devices. These sensor-based solutions are not helpful for increasing the share of renewable energy. Due to the lack of sufficiently accurate wind forecasts, today's electricity grid operators do not consider the cooling effect of the wind when determining the throughput of power lines. Grid Raven has developed a Dynamic Line Rating solution that allows for accurate and hyper-local day-ahead predictions to manage electricity volumes in the grid, maximizing the use of its capacity on any given day. Our technology consists of two parts: machine learning-based weather forecasting and digital twin of the electrical grid. Dynamic Line Ratings that account with all weather conditions including wind enable utilization of existing grid with maximum potential. With hyper-local weather predictions, our solution enables grids to be utilized at their maximum capacity without the fear of overheating.
NUTRI-KNOW - BROADENING THE IMPACT OF EIP-AGRI OPERATIONAL GROUPS IN THE FIELD OF NUTRIENT MANAGEMENT: KNOWLEDGE EXPLOITATION AND EASY-TO-UNDERSTAND MATERIAL FOR FARMERS AND PRACTITIONERS (NUTRI-KNOW)

Framework: Horizon Europe — Global Challenges and European Industrial Competitiveness
Programme: Food, Bioeconomy Natural Resources, Agriculture and Environment
Theme: Bio-Environment
Destination: Innovative governance, environmental observations and digital solutions in support of the Green Deal
Action type: Coordination and support actions
Countries involved: Spain,Belgium,Ireland,Denmark,Italy,Germany
Call: Broaden EIP Operational Group outcomes across borders by means of thematic networks, compiling and sharing knowledge ready for practice (HORIZON-CL6-2022-GOVERNANCE-01, 2022)
Start date: 2023-01-01
End date: 2026-04-30
Duration (months): 40.0
Total project cost (EUR): 1999962.5
EU funding (EUR): 1999962.5
Participants: 11
Project status: SIGNED

Over the past years, a great amount of knowledge on managing practices, technologies, products and recommendations in the primary sector has been developed by several EU funded projects. Despite the continuous flow of information, new or improved managing choices have not been appropriated by practitioners as expected. The main objective of NUTRI-KNOW is to broaden EIP-AGRI Operational Group (OG) outcomes on the thematic of nutrient management across borders to modernise and dynamise the agricultural sector by collecting, translating and sharing easy-to-understand and practice-oriented knowledge. NUTRI-KNOW will assure the appropriate adoption of the OGs results and experience by farmers, practitioners and other relevant end-users. To reach this ambitious goal, NUTRI-KNOW is built considering 12 EIP-AGRI OGs from 4 Member States (Spain, Italy, Belgium and Ireland), ensuring that at least one partner of the consortium has been involved in each OG. The engaged projects cover the whole value chain of nutrient management (livestock farming, storage systems, processing technologies, fertiliser production, transport and application). NUTRI-KNOW methodology is divided in 5 different steps: (1) Data collection and analysis of all the outcomes of the engaged OGs, (2) Multi-approach analysis to establish a solid baseline of the current situation (policies, farming practices, needs and challenges), (3) Consolidation and translation of the knowledge in a language that can be easy to understand for farmers and practitioners, (4) Delivery and transfer of the practice-oriented material created in the communication channels most consulted by farmers and (5) Interconnection of actors and territories with the creation of a Community of Practice. Finally, with all the knowledge gained during NUTRI-KNOW execution, the project will develop a Results Amplification Methodology that will serve as a guideline to upscale and broaden project outcomes effectively in any thematic of interest.

Keywords: nutrient management nutrient recycling soil management and fertilisation farming equipment value chain practice oriented material practice abstracts training operational group eip agri
Printing Infrastructure Technology for European Water (PITEW)

Framework: Horizon Europe — Innovative Europe
Programme: The European Innovation Council (EIC)
Theme: EIC Accelerator
Destination: Other destinations
Action type: EIC actions
Countries involved: United Kingdom
Call: EIC Accelerator 2025 - Short application (HORIZON-EIC-2025-ACCELERATOR-01, 2025)
Duration (months): 24.0
Total project cost (EUR): 1745625.0
EU funding (EUR): 1745625.0
Participants: 1
Project status: SIGNED

Traditional buildings and construction sector is the largest emitter of greenhouse gases emissions, accounting for 37% of global emissions according to the UN. The challenge to achieve net-zero requires compromise between Productivity, or Sustainability or Profitability. Due to recent densification of European cities and climate change related events such as flooding, the need to improve infrastructure is urgently increasing. Transforming the infrastructure landscape is a critical factor in reaching the EU’s and UK’s Net Zero commitments and supporting the SDGs. ChangeMaker 3D, an award-wining female-led company was founded with the mission of supporting construction by leaving a lighter footprint on our planet, reducing carbon emissions, and increasing social value. Thus, ChangeMaker 3D developed PrintfrastructureTM ecosystem, an integration solution that brings together a wide range of 3D construction technology. Cutting-edge robotics and innovative low-carbon materials, to optimise the flexible design and build of infrastructure assets. The proposed solution will enable companies to provide water infrastructure without having to sacrifice productivity or profit to do so. Being technology agnostic, ChangeMaker 3D will be able to leverage the European supply chain and partners to deliver its patented designs. Hence, the Company, through Printfrastructure, will be able to support the development of the EU 3D Concrete Printing companies by aligning them into its supply chain, consequently, supporting inward investment to EU countries. Currently, no other company in Europe can do so. Sustainability must be our urgent priority. This project will develop innovative technology that will significantly contribute to accelerate the transition to cleaner, more sustainable and circular operations associated with infrastructure development across different sectors, focussing on the water industry.

Keywords: printfrastructure,3d concrete printing,water infrastructure,water chamber,flood defence,wastewater distribution,groundwater flood defence,robotics,sustainable,low carbon 3d material