Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
A software tool for the Bayesian estimation of Heterogeneous Agent macroeconomic policy models (BASEforHANK)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Proof of concept grants
Action type: ERC actions
Countries involved: Germany
Call: ERC PROOF OF CONCEPT GRANTS (ERC-2023-POC, 2023)
Start date: 2024-09-01
End date: 2026-02-28
Duration (months): 18.0
Total project cost (EUR): 150000.0
EU funding (EUR): 150000.0
Participants: 1
Project status: SIGNED

My ERC-CoG project has advanced the methodological frontier in solving and estimating macroeconomic equilibrium models, enabling analysis of the interplay between business cycles and inequality. To transform this innovation into a benefit for society, policymakers must be able to work with models with ease. This will allow them to comprehend how the policies they propose impact both the macroeconomy and income/wealth distribution. For this purpose, policymakers require a software tool that allows for swift development and analysis of models. The ERC-CoG-funded research has produced a pilot software that can theoretically achieve this, alongside fundamental methodological research. However, it lacks the versatility and user-friendliness required by policymakers who must develop answers to policy questions under time pressure. The aims of the BASEforHANK project include the further development of the pilot software into a more user-friendly and versatile tool. If successful, this development will enable policymakers worldwide to understand the impacts of their policies better, resulting in more socially cohesive and stable growth. The development follows the model of the Dynare software package, which made it possible to use macroeconomic equilibrium models with representative agents that are now pervasive in policy institutions.
Phase Change Materials for Energy Efficient Edge Computing (PHASTRAC)

Framework: Horizon Europe — Global Challenges and European Industrial Competitiveness
Programme: Digital, Industry and Space
Theme: Industry
Destination: Increased Autonomy in Key Strategic Value Chains for Resilient Industry
Action type: Research and Innovation actions
Countries involved: Netherlands,Hungary,Germany,Switzerland
Call: Innovative materials for advanced (nano)electronic components and systems (RIA) (HORIZON-CL4-2022-RESILIENCE-01, 2022)
Start date: 2023-01-01
End date: 2026-06-30
Duration (months): 42.0
Total project cost (EUR): 2284932.5
EU funding (EUR): 2284932.5
Participants: 4
Project status: SIGNED

In recent years, we have witnessed an explosion of artificial intelligence (AI) applications which will continue to grow over the next decade. An intelligent and digitized society will be ubiquitous, enabled by increased advances in nanoelectronics. Key drivers will be sensors interfacing with the physical world and taking appropriate action in a timely manner while operating with energy efficiency and flexibility to adapt. The vast majority of sensors receive analog inputs from the real world and generate analog signals to be processed. However, digitizing these signals not only creates enormous amount of raw data but also require a lot of memory and high-power consumption. As the number of sensor-based IoTs grows, bandwidth limitations make it difficult to send everything back to a cloud rapidly enough for real-time processing and decision-making, especially for delay-sensitive applications such as driverless vehicles, robotics, or industrial manufacturing. In this context, PHASTRAC proposes to develop a novel analog-to-information neuromorphic computing paradigm based on oscillatory neural networks (ONNs). We propose a first-of-its-kind and novel analog ONN computing architecture to seamlessly interface with sensors and process their analog data without any analog-to-digital conversion. ONNs are biologically inspired neuromorphic computing architecture, where neuron oscillatory behavior will be developed by innovative phase change VO2 material coupled with synapses to be developed by bilayer Mo/HfO2 RRAM devices. PHASTRAC will address key issues 1) novel devices for implementing ONN architecture, 2) novel ONN architecture to allow analog sensor data processing, and 3) processing the data efficiently to take appropriate action. This “sensing-to-action” computing approach based on ONN technology will allow energy efficiency improvement 100x-1000x and establish a novel analog computing paradigm for improved future human-machine interactions.

Keywords: vo2 oscillator devices,hfo2 rram memristors,analog sensing to action computing neuromorphic computing,ai on chip,edge ai computing,energy efficient computing
Efficient zero-emissions gas turbine POWER system for MARitime transport (MARPOWER)

Framework: Horizon Europe — Global Challenges and European Industrial Competitiveness
Programme: Climate, Energy and Mobility
Theme: Mobility
Destination: Clean and competitive solutions for all transport modes
Action type: Research and Innovation actions
Partnership: ZEWT (co-programmed)
Countries involved: Finland,Italy,Germany,Denmark,Spain,France
Call: Developing the next generation of power conversion technologies for sustainable alternative carbon neutral fuels in waterborne applications (ZEWT Partnership) (HORIZON-CL5-2023-D5-01, 2023)
Start date: 2024-09-01
End date: 2028-08-31
Duration (months): 48.0
Total project cost (EUR): 7999805.0
EU funding (EUR): 7999805.0
Participants: 11
Project status: SIGNED

The transition of the waterborne fleet to a zero-emission mode of transport critically depends on the development of power conversion systems that effectively can use sustainable alternative fuels. Going beyond the state-of-the-art in gas turbine technology, MARPOWER will deliver a highly efficient system endowed with an intercooled recuperative two-shaft gas turbine with a bottoming cycle. The modularity and versatility of the system is a unique function and provides its own competitive benefit, it is designed for flexible use of neutral (green methane, green methanol) and zero-emissions (hydrogen, ammonia) fuels, and it can reach up to 50-55% electrical efficiency and 73-76% overall electrical+thermal efficiency. In this sense, it can be operated to optimise the electrical power generation on-board a ship, but also to be operated in Combined Heat and Power (CHP) mode, both modes will be assessed through two case studies. MARPOWER will optimise the design of the turbomachinery components which are essential and specifically conceived for using zero-emission fuels. Accordingly, it will develop a new fuel-flexible combustion concept, in which the combustor will be able to run on 100% hydrogen or other neutral or zero-emission fuels without any additional changes to the combustion system. High efficiencies will be additionally fostered by the integration of an Active Magnetic Bearings (AMB) technology for control of long high-speed shafts. The impacts generated from MARPOWER will allow the creation of a value chain for the construction and deployment of the energy conversion system in different types of ships worldwide, achieving significant economic, social, and environmental impacts, and therefore boosting European leadership in the maritime sector: The project can contribute significantly to the decarbonisation of the maritime sector avoiding the emission of more than 2.3 million of tonnes of CO2 into the atmosphere.

Keywords: gas turbines,efficiency,combined heat and power
COnfident DEcisions (CODE)

Framework: Horizon Europe — Excellent Science
Programme: Marie Skłodowska-Curie Actions (MSCA)
Theme: Marie Skłodowska-Curie
Destination: Doctoral Networks
Action type: Marie Skłodowska-Curie actions
Panel: Social Sciences and Humanities
Countries involved: Netherlands,France,Belgium,Germany,United Kingdom,Spain
Call: MSCA Doctoral Networks 2022 (HORIZON-MSCA-2022-DN-01, 2022)
Start date: 2024-01-01
End date: 2027-12-31
Duration (months): 48.0
Total project cost (EUR): 2446322.4
EU funding (EUR): 2446322.4
Participants: 19
Project status: SIGNED

Virtually every decision people make comes with a sense of confidence – a subjective estimate of decision quality. The human capacity for confidence has tremendous social, clinical, and industrial impact. For example, children who can correctly judge their own level of confidence perform better academically. In the elderly, confidence declines faster than other cognitive functions. Clinically, confidence plays a key role in our understanding of various brain-related disorders, including dementia, anxiety, addiction, and depression. In industry, confidence helps people trust algorithms and automated systems, and creates more natural interactions with smartphones and self-driving cars. While the past decade has seen major advances in our scientific understanding of decision confidence, its mechanisms remain poorly understood. This lack of understanding significantly hampers the translation to real-world applications, such as educational programmes and clinical interventions. A major challenge for the immediate future is to fill this gap, by expanding fundamental knowledge on decision confidence and explicitly bridging to technologies, interventions, and clinical practice. CODE aims to address this need. We are an international, interdisciplinary and intersectoral training network that spans fundamental and applied confidence-based research, and bridges between academia, industry, education, and the clinic. By reaching across domains that usually work in silos, CODE will provide critical new insights into decision confidence, and pave the way for important future confidence-based applications. We will train doctoral students to become the interdisciplinary decision confidence experts of the future, who can flexibly apply their knowledge and skills in a wide variety of domains and sectors, and are exceptionally well prepared for successful careers in either academia or industry.

Keywords: metacognition,perception,psychophysics,neuroimaging,computational modelling
Engage2innovate – Enhancing security solution design, adoption and impact through effective engagement and social innovation (E2i)

Framework: Horizon Europe — Global Challenges and European Industrial Competitiveness
Programme: Civil Security for Society
Theme: Civil Security for Society
Destination: Strengthened Security Research and Innovation
Action type: Research and Innovation actions
Countries involved: Israel,Germany,Portugal,United Kingdom
Call: Social innovations as enablers of security solutions and increased security perception (HORIZON-CL3-2022-SSRI-01, 2022)
Start date: 2023-08-01
End date: 2027-03-31
Duration (months): 44.0
Total project cost (EUR): 1286125.0
EU funding (EUR): 1286125.0
Participants: 6
Project status: SIGNED

Engage2innovate (E2i) will investigate and address barriers to implementing EU security research and innovation outputs, including: poor engagement with end-users, stakeholders and citizens; lack of front-end research and problem framing; and ineffective innovation processes. E2i adopts a human-centred, transdisciplinary approach (as demonstrated in CCI – GA: 787100), recognising innovation as requiring both key elements: novelty and implementation. Social Innovation is a human-centred approach to developing meaningful solutions rooted in a rich understanding of end-user contexts, such that novel ideas (inventions) are actually implemented. Through effective engagement with security policymakers, researchers, and practitioners across the quadruple helix, E2i will champion good practice in Social Innovation and human-centred design. Researchers will demonstrate and deliver the E2i Security R&I Toolbox: (i) enabling adoption of Social Innovation and human-centred design approaches to engage citizens and end users in security R&I; (ii) supporting security R&I actions in framing and designing security solutions and outputs and optimising their acceptance and adoption; (iii) providing benchmarks, standards and quality criteria for security solutions through Responsible Research and Innovation; and thereby (iv) strengthening EU security research and innovation. To promote the engagement of citizens and end users, E2i will develop a Societal Development Plan describing the current landscape of Social Innovation. This will provide guidance on how the approach can strengthen EU security research and innovation, and include an explanatory conceptual model and practical exemplars to inspire and motivate. Finally, E2i will build on the enthusiasm and inspiration of the next generation of researchers and design thinkers through two international Social Innovation Design Challenges, showcasing new innovative thinking and solution concepts while fostering adoption of E2i outputs.

Keywords: human centred design
Multiscale-Multiphysics Modelling of Ti alloy medical implants based on Additive Manufacturing technology (M3TiAM)

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: Spain,Ireland
Call: MSCA Postdoctoral Fellowships 2021 (HORIZON-MSCA-2021-PF-01, 2021)
Start date: 2023-02-01
End date: 2025-01-31
Duration (months): 24.0
Total project cost (EUR): 165312.96
EU funding (EUR): 165312.96
Participants: 2
Project status: CLOSED

Patient-customized bone replacement implants with (micro)structural and mechanical properties tuned by design would constitute a major advance in the biomedical field. Classical metallurgical post-processing (e.g. annealing or hot-isostatic-pressing) offer an efficient way to modify metallic alloys microstructure and resulting properties. Hence, the combination of titanium alloys, scaffold structures, and additive manufacturing open promising avenues to produce custom implants that mimic natural bones and thus reduce the need for revision surgery. Moreover, modelling tools across scales are mature enough to simulate microstructural evolution and its effect on material properties, which could accelerate the design of high-quality, high-fidelity, affordable implants. The aim of M3TiAM project is to develop robust computational tools to predict the effect of post-processing treatments on microstructure and mechanical properties of additively manufactured scaffolds structures, in order to guide the design of novel Ti-based implants. To do so, multidisciplinary and multiscale theories will be combined into i) a process-sensitive structural module using phase-field modelling to predict phase evolution of biocompatible Ti alloys and ii) a structure-scaffold geometry-sensitive mechanical performance module using crystal-plasticity (microscale) and finite element (macroscale) models to predict the mechanical behaviour of bulk material and scaffold structures. The resulting computational framework will guide the design and optimisation of novel metallic implants, from the level of their microstructure to that of entire scaffold-based implants. The expected impact include: new insight into process-microstructure-properties in metallic alloys, new multi-scale and multi-physics coupling and upscaling strategies, accelerated adoption and deployment of additive manufacturing of scaffold implants for personalized medicine.

Keywords: titanium alloys additive manufacturing microstructure mechanical properties modelling and simulations phase field crystal plasticity
Machine-Assisted Teaching for Open-Ended Problem Solving: Foundations and Applications (TOPS)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Computer Science and Informatics
Panel description: Informatics and information systems, computer science, scientific computing, intelligent systems
Countries involved: Germany
Call: ERC STARTING GRANTS (ERC-2021-STG, 2021)
Start date: 2022-04-01
End date: 2027-03-31
Duration (months): 60.0
Total project cost (EUR): 1495000.0
EU funding (EUR): 1495000.0
Participants: 1
Project status: SIGNED

Computational thinking and problem solving skills are essential for everyone in the 21st century, both for students to excel in STEM+Computing fields and for adults to thrive in the digital economy. Consequently, educators are putting increasing emphasis on pedagogical tasks in open-ended domains such as programming, conceptual puzzles, and virtual reality environments. When learning to solve such open-ended tasks by themselves, people often struggle. The difficulties are embodied in the very nature of tasks being open-ended: (a) underspecified (multiple solutions of variable quality), (b) conceptual (no well-defined procedure), (c) sequential (series of interdependent steps needed), and (d) exploratory (multiple pathways to reach a solution). These struggling learners can benefit from individualized assistance, for instance, by receiving personalized curriculum across tasks or feedback within a task. Unfortunately, human tutoring resources are scarce, and receiving individualized human-assistance is rather a privilege. Technology empowered by artificial intelligence has the potential to tackle this scarcity challenge by providing scalable and automated machine-assisted teaching. However, the state-of-the-art technology is limited: it is designed for well-defined procedural learning, but not for open-ended conceptual problem solving. The TOPS project will develop next-generation technology for machine-assisted teaching in open-ended domains. We will design novel algorithms for assisting the learner by bridging reinforcement learning, imitation learning, cognitive science, and symbolic reasoning. Our theoretical foundations will be based on a computational framework that models the learner as a reinforcement learning agent who gains mastery with the assistance of an automated teacher. In addition to providing solid foundations, we will demonstrate the performance of our techniques in a wide range of pedagogical applications.

Keywords: educational technology,artificial intelligence,reinforcement learning,computational thinking,problem solving skills,open ended learning domains
Discover molecular pathways for marine glyco-Carbon sequestration (C-Quest)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: Earth System Science
Panel description: Physical geography, geo logy, geophysics, atmospheric sciences, oceanography, climatology, cryology, ecology, global environmental change, biogeochemical cycles, natural resources management
Countries involved: Germany
Call: ERC CONSOLIDATOR GRANTS (ERC-2021-COG, 2021)
Start date: 2022-10-01
End date: 2027-09-30
Duration (months): 60.0
Total project cost (EUR): 2277248.0
EU funding (EUR): 2277248.0
Participants: 1
Project status: SIGNED

The scientific frontier project C-Quest will study algal sugar polymers - glycans - in the ocean to resolve their contribution to global carbon cycling and sequestration. C-Quest will explore the hypothesis that marine diatoms, which fix similar amounts of carbon as tropical forests on a global scale, secrete glycan types that are stable, meaning harder to degrade for bacteria than other substrates. This stability results in glyco-carbon sequestration removing the greenhouse gas carbon dioxide from the atmosphere. C-Quest will identify and quantify glycan structural types in seawater, where salt, low glycan concentration and their high molecular diversity challenge classic analytical techniques. With two articles in PNAS (2020) and Nature Communications (2021), implementing bioanalytical strategies to measure glycans in the ocean, we broke through the glyco-carbon challenge setting the stage for testing the glyco-carbon sequestration hypothesis. In the test tube, my team will reveal marine bacterial enzymatic degradation pathways that degrade diatom glycans. Our characterized enzymes will become analytical tools to identify and quantify these glycans across the ocean. In different oceanic regions, we will quantify glycan production during algal blooms, glycan export in sinking particles and glycan burial in sediments to pinpoint the types that have a high potential to sequester carbon. The outcome will be knowledge of glycan contribution to carbon sequestration shedding light into what remains a black box of the global carbon cycle to this day. C-Quest will discover enzymes new to science, explore the potential of glycans for carbon sequestration and reveal molecular principles that govern carbon sequestration in and beyond the ocean.
Collecting Plasmonic Near-Infrared Photons through a Schottky junction (INFRALIGHT)

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: Italy
Call: MSCA Postdoctoral Fellowships 2023 (HORIZON-MSCA-2023-PF-01, 2023)
Start date: 2024-09-01
End date: 2026-08-31
Duration (months): 24.0
Total project cost (EUR): 172750.08
EU funding (EUR): 172750.08
Participants: 1
Project status: TERMINATED

Harvesting infrared light, specifically wavelengths above 1000 nm, is of paramount importance for enhancing photovoltaic and photoelectric efficiencies, as well as for applications in imaging and communication. In recent years, significant strides have been made in the realm of infrared optoelectronics, leveraging colloidal quantum dots (0D materials) as a cost-effective alternative to conventional semiconductor technologies like InGaAs, InSb, HgCdTe, and others. Nevertheless, prevailing infrared technologies often rely on toxic compounds such as lead, cadmium, and mercury chalcogenide, giving rise to significant environmental concerns. Recently, heavy metal-free doped metal oxide nanocrystals (NCs), exemplified by Sn-doped In2O3 (ITO), have garnered recognition in the fields of nanoelectronics and energy storage owing to their alluring optical and electronic properties. The integration of plasmonic nanomaterials into semiconductor matrices holds great promise in diverse areas, including solar energy harvesting, photocatalysis, and photodetection. However, their application in the infrared spectrum alongside semiconductors remains relatively underexplored. To address this gap, we introduce the INFRALIGHT project, which introduces a pioneering approach: the establishment of a dedicated Schottky junction between semiconducting fluorographene and heavy metal-free doped metal oxide nanocrystals (e.g., Sn@In2O3) to efficiently capture infrared light. This junction will facilitate efficient charge transfer when exposed to infrared excitation. Our subsequent objective is to demonstrate a proof-of-concept photodetector device operating at a self-bias voltage (0 V). This device will exhibit an enhanced near-infrared (NIR) photoresponse achieved through the photoinduced extraction of plasmon hot electrons from IR hotspot plasmons. Within the framework of INFRALIGHT, we will delve into device development and investigate the interaction of IR plasmons with 2D semiconductors.

Keywords: infared plasmonics,heavy metal free nanocrystals,2d materials,fluorographene,charge transfer,plasmon hotspot,ir photodetector