Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Isolation, observation and quantification of mechanisms responsible for hydrogen embrittlement by TRITIum based microMEchanics (TRITIME)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: Materials Engineering
Panel description: Advanced materials development: performance enhancement, modelling, large -scale preparation, modification, tailoring, optimisation, novel  and combined use of materials, etc.
Countries involved: Germany
Call: ERC CONSOLIDATOR GRANTS (ERC-2021-COG, 2021)
Start date: 2022-11-01
End date: 2027-10-31
Duration (months): 60.0
Total project cost (EUR): 1994136.0
EU funding (EUR): 1994136.0
Participants: 1
Project status: SIGNED

Hydrogen is an indispensable element in the energy transition and expected to be key for decarburization of the European society. Hydrogen embrittlement – recognized and in focus of materials science since almost 150 years – still causes catastrophic failure until today. It is well-understood that all mechanisms of hydrogen embrittlement materialize at the scale of individual defects, such as dislocations, grain- and phase-boundaries. But we are still missing a correlative measurement of the mechanical behaviour of individual defects and the local hydrogen content, which is urgently needed to assess the occurrence, importance and magnitude of mechanisms playing a role during hydrogen embrittlement. In aid of this, TRITIME for the first time facilitates the isolation, observation and quantification of hydrogen embrittlement mechanisms by TRITIum based microMEchanics. The mechanisms of hydrogen embrittlement will be isolated by small scale mechanical testing on samples containing only a few crystal defects. The defect properties are observed and measured by in situ micromechanical experiments in the scanning electron microscope and at synchrotron beamlines. Simultaneously, TRITIME will monitor the local hydrogen content by observing the decay of tritium with high spatial resolution, for which a unique tool will be developed. In addition, post mortem analysis using atom probe tomography and secondary ion mass spectroscopy take advantage of the reduced mobility of tritium. TRITIME will provide unprecedented insights into the local hydrogen content of newly formed slip bands, mobile and immobile dislocations and fracture surfaces. Consequently, if successful, TRITIME will obtain a mechanism-based, quantitative understanding of HEDE, HELP and their interplay. In doing so, TRITIME sets the base for a mechanism-based optimization of microstructures used in distribution and storage of hydrogen and, therefore, is an indispensable tool towards Europe`s hydrogen society.

Keywords: hydrogen embrittlement
Flying companion for floating litter collection (Flyflic)

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: Netherlands
Call: MSCA Postdoctoral Fellowships 2021 (HORIZON-MSCA-2021-PF-01, 2021)
Start date: 2022-09-01
End date: 2024-10-31
Duration (months): 26.0
Total project cost (EUR): 187624.32
EU funding (EUR): 187624.32
Participants: 1
Project status: CLOSED

Plastic pollution is considered one of the most challenging environmental risks globally, and rivers have been identified as a dominant pathway for the accumulation of plastic in the oceans. The Flyflic (FLYing companion for Floating LItter Collection) project addresses this global challenge by deploying a first-of-its-kind robotic platform composed of multiple unmanned aerial robots to effectively collect litter from rivers and canals, thus preventing such litter from reaching our oceans. Chiara Gabellieri will carry out the Flyflic project under the supervision of Prof. Antonio Franchi at the University of Twente (UT), The Netherlands. The project contributes to European strategic priorities (Horizon Europe Mission on healthy oceans, seas, coastal and inland waters) and global strategic priorities (United Nations Sustainable Development Goals). Compared to state-of-the-art solutions, which are boat-like robots or fixed trapping mechanisms, a flying platform can target desired spots, can easily discharge the collected litter, is low cost, and is not hindered by non-navigable spots such as dams and low bridges. The general vision of the Flyflic project will be accomplished through four specific objectives: a novel prototype composed of two physically connected aerial robots and a net to be dragged in the water to collect the litter will be assembled; the dynamic model of the complex manipulation aerial system embedding the water-related disturbances will be computed and a model-based control law designed accordingly; all the components for autonomous functioning will be integrated, especially the control law and state-of-the-art algorithms for object recognition and trajectory generation; finally, a user interface will be created to let a human monitor the task execution and possibly select actions, and the cooperative human-robot discharge of the litter will be made possible through the design of an advanced physical interaction control algorithm.

Keywords: aerial robotics,aerial manipulation,multi robot systems
Corporate Political Power: How Business Actors Define the Rules that Govern their Responsible Behaviour (COPP)

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: Social Sciences and Humanities
Countries involved: Denmark
Call: MSCA Postdoctoral Fellowships 2021 (HORIZON-MSCA-2021-PF-01, 2021)
Start date: 2023-09-01
End date: 2026-08-31
Duration (months): 36.0
Total project cost (EUR): 230774.4
EU funding (EUR): 230774.4
Participants: 1
Project status: SIGNED

In this cutting-edge project, I ask the research question: “How do business actors define the transnational rules that govern corporations’ responsible behaviour?”. Extending insights from political science and management studies, the central objective of this research project is to enlarge the scope of actors, activities, and processes being studied, and reveal more nuanced ways through which corporations exert power in and over political rules. This main objective is operationalized into four working packages. WP1 aims to synthesize the existing literature on corporate power in and over rules. The other WPs elucidate three indirect and often overlooked types of corporate political power i.e., power in and through: global production networks (GPNs) [WP2]; big four consultancies [WP3]; and trade associations [WP4]. To this end, I create a novel dataset of national and international governmental CSR policies from different countries, international organizations, and regional organizations in all major world regions spanning a 65-year period by drawing together data from different online platforms. In WP2, I measure the similarities between different governmental CSR policies (based on Cosine similarity) as a result of backward and forward GPN participation. In WP3, I code the authorshipof these CSR policies and the degree of similarities with publications by the big four consultancies. In WP4, I send out a large-scale survey to trade association representatives to ask about their lobbying on the CSR policies within my dataset. To further unpack the causal relations of WP3 and WP4, I also conduct in-depth interviews. By drawing on management theories on how companies govern global markets and political theories on the functioning of governments, I ambitiously move this research agenda forward in an interdisciplinary manner. This helps to overcome the treatment of either business or politics as black-boxes while also bridging the analytical macro-micro divide.

Keywords: corporate social responsibility corporate political activities environmental and social regulation mixed methods
Larpocracy: Developing Spaces for Deliberation and Democratic Skills through Role-Playing (Larpocracy)

Framework: Horizon Europe — Global Challenges and European Industrial Competitiveness
Programme: Culture, creativity and inclusive society
Theme: Culture, creativity and inclusive society
Destination: Innovative Research on Democracy and Governance
Action type: Research and Innovation actions
Countries involved: Sweden,United Kingdom,Finland,Greece,Poland,Italy
Call: Culture, the arts and cultural spaces for democratic participation and political expression, online and offline (HORIZON-CL2-2024-DEMOCRACY-01, 2024)
Start date: 2025-01-01
End date: 2027-12-31
Duration (months): 36.0
Total project cost (EUR): 3066450.0
EU funding (EUR): 3066306.0
Participants: 7
Project status: SIGNED

Online social media is not living up to its promise to offer alternative arenas promoting civic deliberation among people with diverse opinions. In the wake of this perceived failure of the online environment, activists, educators and scholars alike have begun to turn to alternative forms of civic engagement, both online, offline and mixed. Larp, live role playing, is one such form. Larps create cultural, artistic spaces offering great potential for alternative engagement with politics. Furthermore, Larps are not restricted to physical space. Rather, larp exemplify how social spaces can be deliberately and collaboratively designed to be conductive of inclusivity and democratic engagement. Studying larp, enhancing their capacity of supporting democratic engagement and political expression, and learning from them to inspire the deliberate design of social media and other spaces for political expression, thus directly answers to the call topic and opens unique opportunities for the design of future spaces for democratic deliberation, including future social media. The project will produce: - Studies and experiments chartering capacities of larp in supporting democratic engagement and fostering democratic skill-building - Public events in collaboration with designers and organisers from marginalised and vulnerable communities - Design exemplars of larp and larp spaces capable of supporting inclusivity and democratic engagement. - Evidence-based Democracy by Design Toolkit - A widespread community of Experts understanding the capacities of larp and larp-like spaces in fostering democratic engagement. - Evidence-based Policy Recommendations supporting policy-makers in multiple domains

Keywords: larp,deliberation,democracy,role play,marginalized communities,social space design
Fast and versatile real-time balancing of electricity demand flexibility: shaping a clean and levelled power grid in Europe (Flex4Scale)

Framework: Horizon Europe — Innovative Europe
Programme: The European Innovation Council (EIC)
Theme: EIC Accelerator
Destination: Challenges
Action type: EIC actions
Countries involved: Netherlands,Sweden,Finland
Call: Green Deal innovations for the Economic Recovery (HORIZON-EIC-2021-ACCELERATORCHALLENGES-01, 2021)
Start date: 2022-05-01
End date: 2024-04-30
Duration (months): 24.0
Total project cost (EUR): 3295105.0
EU funding (EUR): 2306573.5
Participants: 4
Project status: CLOSED

Our solution prepares the electricity grid for a 100% renewable future. It manages the power consumption of connected electric devices in real-time to ensure that electricity supply and demand remain closely matched. This is achieved by temporarily curtailing, advancing, or postponing the electricity usage of these devices depending on the availability of electricity in the grid. Importantly, by using relatively simple and low-cost hardware to integrate the devices into a large network that is driven by our powerful cloud-based intelligent software platform, our technology can (cost)effectively control large and diverse networks of electric devices, even those with relatively low power consumption (down to 10kW). The owners of these electrical devices in turn get paid for contributing to grid stability. As our solution will exist of a modular framework it allows rapid expansion to different flexibility products and adjustment to national technical and regulatory requirements in Europe.
Demonstrating circular value chains for complex plastics via collection, reuse, repair, remanufacture, recycling and ecodesign of PVC tarpaulins (RETAIN)

Framework: Horizon Europe — Global Challenges and European Industrial Competitiveness
Programme: Food, Bioeconomy Natural Resources, Agriculture and Environment
Theme: Bio-Environment
Destination: Other Bio-environnement destinations
Action type: Innovation actions
Countries involved: Belgium,Austria,Czechia,France,Spain,Netherlands,Germany,Italy
Call: Increasing the circularity in plastics value chains (HORIZON-CL6-2024-CIRCBIO-02, 2024)
Start date: 2025-05-01
End date: 2028-10-31
Duration (months): 42.0
Total project cost (EUR): 6538156.25
EU funding (EUR): 4999379.38
Participants: 16
Project status: SIGNED

Tarpaulins are complex composite-like materials, typically composed of polyethylene terephthalate (PET) as reinforcement material and plasticized/soft polyvinyl chloride (PVC) as coating material. These durable plastics have a wide range of applications going from trailer covers to professional tents and from advertisement banners to biogas membranes. Each year 200 kton of tarpaulins enter the EU market, 65% of this volume , corresponding to ca. 200 Mio m2, being produced in the EU. After their functional lifetime, which ranges from a few months up to 30 years, over 99% of tarpaulins currently end up as landfill or are being incinerated as today’s recycling technologies are insufficient. The target of RETAIN is to contribute to the final ambition of having by 2036 at least 90% of circular tarpaulins use (re-used, remanufactured or recycled). To reach our ambition, we will further develop various recycling technologies (i.e. mechanical, physical, and selective dissolution) and demonstrate circular business practices (advanced collection, monitoring, sorting, repair/reuse/recycling and conversion of post-production and end-of-life tarpaulins) at TRL8 scale at three DEMO locations in the EU. Additionally, we will develop and implement an efficient decision-making mechanism for process and lifecycle optimization such as the RETAIN gate control procedure for post-industrial and end-of-life tarpaulins. Finally, we will implement a digital product passport (DPP) for tarpaulins to ensure traceability, support certification and quality validation, quantify environmental, social, and economic impacts, incorporate learning and training activities, contribute to relevant standards, and connect with other recycling initiatives in the EU and abroad.

Keywords: complex plastics tarpaulin reuse recycling circular business models adanced digital solutions ecodesign assessment studies traceability digital product passport
A Helicopter View on Electrocatalysis (HeliECat)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Physical and Analytical Chemical Sciences
Panel description: Analytical chemistry, chemical theory, physical chemistry/chemical physics
Countries involved: Germany
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): 1486906.0
EU funding (EUR): 1486906.0
Participants: 1
Project status: SIGNED

Converting carbon dioxide, an unwanted by-product of industrial processes and combustion engines, into valuable chemical compounds is key for a cyclic carbon economy and can be achieved by the electrochemical CO2 reduction reaction (CO2RR). Despite the immense importance of this reaction in the fight against climate change, no catalyst to date meets the industrial requirements for product selectivity and catalyst stability. Theoretical models and simulations have played a fundamental role in the understanding of these and similar catalytic processes and aided the development of more efficient catalysts for this reaction. These models, however, assume few often idealized surface structures, ignoring the fact that a variety of structures is present under working conditions that define the catalyst properties in terms of efficiency, selectivity, and stability. With HeliECat, I will for the first time establish an approach that offers a holistic view of the catalytic processes, including side reactions and degradation mechanisms. To achieve this ambitious goal, I will combine an efficient semiempirical model for structural exploration with accurate embedded cluster models for kinetic studies. This combination shifts the focus from idealized structures to the diversity of the catalyst surface under realistic conditions. I will then model the interconversion of accessible surface structures with deep reinforcement learning techniques. The analysis of the emerging connected kinetic reaction networks will ultimately allow me to simultaneously study the catalytic activity, stability, and selectivity in silico. I will study the CO2RR on a Cu/Au catalyst surface and demonstrate that automated kinetic modeling, considering structural diversity and realistic thermodynamic boundary conditions, is the key to a predictive simulation of catalyst behavior under actual working conditions. HeliECat will hence pave the way for realistic in silico catalyst screening.

Keywords: electrolyte solvation,machine learning
REliable eXplAinable Swarm Intelligence for People with Reduced mObility-Hop On (REXASI-PRO-HOP-ON)

Framework: Horizon Europe — Widening Participation and Strengthening the European Research Area
Programme: Widening participation and spreading excellence
Theme: Improved access to Excellence
Destination: Improved access to Excellence
Action type: Research and Innovation actions
Countries involved: Italy,Romania
Call: Hop on Facility (HORIZON-WIDERA-2023-ACCESS-06, 2023)
Duration (months): 18.0
Total project cost (EUR): 219400.0
EU funding (EUR): 219400.0
Participants: 2
Project status: SIGNED

Artificial intelligence (AI) is adopted at a fast pace and is being applied widely in many domains. The aim of the REXASI-PRO project is to design a novel framework in which safety, security, ethics, and explainability are entangled to develop a Trustworthy Artificial Swarm Intelligence solution. The framework will make a trustworthy collaboration among a swarm formed by autonomous wheelchairs and flying robots to allow a seamless door-to-door experience for people with reduced mobility. Within REXASI-PRO-Hop-On, the widening partner (SIE) will address the following challenges, which were already identified in the REXASI-PRO proposal: - Foundational challenge 3: How to develop green AI systems without affecting the system’s performance? - Domain-specific challenge 4: How to preserve machine learning accuracy while reducing the power consumption of embedded computers? These two challenges are currently being addressed in the REXASI-PRO project by employing optimization and efficiency computational topology methods for energy saving, notably by limiting the amount of training data while maintaining the highest standards of completeness and accuracy. The REXASI-PRO-Hop-On proposal will address a different dimension of a green AI solution: algorithms for AI model compression, with the goal of optimizing the energy efficiency during AI model inference on the wheelchair;

Keywords: greener ai
Assumption-Lean (Causal) Modelling and Estimation: A Paradigm Shift from Traditional Statistical Modelling (ACME)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Advanced grants
Action type: ERC actions
Panel: Mathematics
Panel description: All areas of mathematics, pure and applied, plus mathematical foundations of computer science, mathematical physics and statistics
Countries involved: Belgium
Call: ERC ADVANCED GRANTS (ERC-2023-ADG, 2023)
Start date: 2024-10-01
End date: 2029-09-30
Duration (months): 60.0
Total project cost (EUR): 2445063.0
EU funding (EUR): 2445063.0
Participants: 1
Project status: SIGNED

I propose a cutting-edge and transformative paradigm for statistical modelling that is crucial to enhance the quality of data analyses. Leveraging my expertise in causal inference and semiparametric statistics, I will establish the fundamental principles of a comprehensive estimation theory, which maps model parameters onto generic, interpretable, model-free estimands (e.g., association or effect measures) with favourable efficiency bound, and harnesses the power of debiased (statistical/machine) learning techniques to estimate these. My core objective is to develop a flexible and accessible data modelling framework, called ‘assumption-lean modelling’. This framework will deliver minimal bias and maximal interpretability, even in the presence of model misspecification, along with honest confidence bounds that account for model uncertainty. Debiased learning is at the core of this research. While gaining popularity, a rigorous scientific optimality theory is lacking. I shall draw on my expertise in (bias-reduced) double robust estimation to develop optimal debiased learning estimators. These utilize learners that optimize strategically chosen loss functions to achieve low variance and high stability, along with confidence intervals that are valid under weak conditions on the learners. I will connect to timely, exciting developments in statistics, such as debiased learning of function-valued parameters and the construction of confidence bounds for such parameters. I will offer novel avenues into these problems by incorporating the assumption-lean modelling principles and connecting to real-world needs. I will develop assumption-lean modelling strategies to tackle significant challenges in causal modelling, including target trial emulation, causal mediation analysis, and statistical modelling of dependent outcomes. I will deliver methods with potential impact on all empirical sciences, as well as on the foundations of the discipline of statistical modelling.

Keywords: debiased statistical learning causal inference statistical modelling nonparametric inference