Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
REvolutionising the use of coherent x-ray diffraction for structural crystallography Applied to CaTalysis (REACT)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Advanced grants
Action type: ERC actions
Panel: Physical and Analytical Chemical Sciences
Panel description: Analytical chemistry, chemical theory, physical chemistry/chemical physics
Countries involved: France
Call: ERC ADVANCED GRANTS (ERC-2024-ADG, 2024)
Start date: 2026-02-01
End date: 2031-01-31
Duration (months): 60.0
Total project cost (EUR): 2500000.0
EU funding (EUR): 2500000.0
Participants: 2
Project status: SIGNED

Heterogeneous (electro-, photo-) catalysis is at the heart of our modern chemical industry, driving 90% of chemical manufacturing processes. Key challenges include measuring reaction kinetics, identifying intermediates and bridging the “pressure” and “materials” gaps. To study the behaviour of individual nanocatalysts involved in chemical reactions, I will develop new, faster structural and chemical characterisation systems and state-of-the-art in situ monitoring techniques to address catalytic problems. The REACT project will revolutionise our understanding of near-industrial catalysis by overcoming current limitations in pressure and materials science by integrating fast in situ non-invasive three-dimensional imaging of single catalysts with spectroscopy to achieve 3D nanospectroscopic imaging during catalysis. This innovative method will operate at high temperature, pressure and in complex environments, providing atomic resolution and high temporal precision. Taking advantage of 4th generation synchrotron sources, new revolutionary charge-integrating detectors and my recognised expertise in synchrotron coherent X-ray diffraction microscopy, the project will enable 3D study of both the chemistry and structure of nanocatalysts under realistic reaction conditions with unprecedented spatial, temporal and energy resolution, to identify reaction intermediates during catalysis for a deeper understanding of the phenomena critical to nanocatalysis: activity, selectivity, reusability and sustainability. Experiment is nothing without simulation. We will use state-of-the-art atomistic capabilities developed by AI to reveal the full dynamics of catalytic mechanisms, setting a new standard in the integration of computational and experimental sciences. My project will shed light on the most relevant unsolved issues (durability, activity, ...) that limit the efficiency of today's processes and will open new horizons with outstanding impact in catalytic research.

Keywords: synchrotron,bragg coherent diffraction imaging,spectroscopy,strain,defects,in situ,operando,co2 reduction,hydrogenation,ammonia oxidation,photocatalysis,
Sensors and Eco-fRiendly food-grade matErials for a sustaiNable and smArt fooD storagE and quality monitoring (SERENADE)

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: Information Science and Engineering
Countries involved: Spain,Germany,Italy,Belgium
Call: MSCA Doctoral Networks 2021 (HORIZON-MSCA-2021-DN-01, 2021)
Start date: 2023-01-01
End date: 2026-12-31
Duration (months): 48.0
Total project cost (EUR): 2152638.04
EU funding (EUR): 1761128.1
Participants: 11
Project status: SIGNED

Promoting circular economy approaches is critical to decrease the environmental footprint of food production activities. However, there are still inefficiencies at all stages of the food supply chain hindering sustainable food production. In this line, to contribute to sustainability in the last part of the food supply chain, SERENADE proposes a multidisciplinary approach combining three pillars: food, sensors, and materials technologies with the objective of building smart sustainable solutions targeting the reduction of food waste at the end of the food supply chain (households, supermarkets, and food retailers). Thus, SERENADE’s main goal is to develop sustainable innovations for food quality tracking, while training at the same time a new generation of 7 multidisciplinary Doctoral Candidates (DCs) in the fields of food technology, sensor technology, artificial intelligence (AI), and eco-friendly materials (circular economy) and allowing them to work in team with experts in other disciplines. These innovations will result in the development of i) a smart and sustainable food container for monitoring food freshness at households and markets, using sensor technology and made of novel food-grade materials (biobased or recycled) and ii) a handheld food spoilage analyzer combining sensor technology, and artificial intelligence (AI) software to determine food freshness in unpackaged food at markets. To achieve the development of said monitoring solutions, the close collaboration of experts in the three research pillars of the SERENADE project and the training of multidisciplinary researchers in the three fields at the same time, will be needed and will be possible thanks to the international and intersectoral cooperation of the SERENADE partners distributed among 4 EU countries (Spain, Germany, Belgium, and Italy), and to the strong involvement of the industry, with the participation and leadership of industrial partners (SMEs and large industries).

Keywords: smart and sustainable food container,handheld food spoilage analyser,food grade recycled plastics,innovative compostable materials,circular economy,food waste,eco friendliness assessment
Real-time (co)evolution in a multitrophic community under current and future climates (EvolCommunity)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: Environmental B iology, Ecology  and E volution
Panel description: For all organisms : Ecology, biodiversity, environmental change , evolutionary biology, behavioural ecology, microbial ecology , marine biology, ecophysiology, theoretical developments and mod elling
Countries involved: Germany
Call: ERC CONSOLIDATOR GRANTS (ERC-2023-COG, 2023)
Start date: 2024-02-01
End date: 2029-01-31
Duration (months): 60.0
Total project cost (EUR): 1998383.0
EU funding (EUR): 1998383.0
Participants: 1
Project status: SIGNED

In nature, organisms live in communities and form complex trophic interactions. Understanding how multitrophic communities evolve and respond to environmental changes is a fundamental and pressing challenge in face of global change. While research in evolutionary biology revealed that a warming climate can drive adaptive evolution of individual organisms in the community, studies from community ecology showed that a warming climate can alter trophic interactions and community structure, which in turn changes the (co)evolutionary trajectory of interacting species. Thus, integrating evolutionary and ecological responses is crucial to understand the climate responses of individual species and communities. However, methodological challenges have hampered empirical studies until now. EvolCommunity will address these challenges by experimentally evolving populations of three interacting species (aphid, duckweed, and daphnia) in their native communities using outdoor mesocosms with different climate conditions. We will quantify how warming shapes the function and evolution of the multitrophic community in real-time. By manipulating climate-driven plant evolution, we will determine whether plant evolution alters the community’s response to climate change. We will also assess whether the interacting species coevolve in the community by quantifying the reciprocal selection imposed from their evolutionary changes. We will investigate the molecular mechanisms underlying (co)evolution using state-of-the-art genetic tools. Using a combination of experimental evolution, community manipulation, and cutting-edge genetic and analytic tools, EvolCommunity will push the research boundaries of evolutionary ecology by revealing the mechanisms and processes of community evolution at work. The outcomes will open new research avenues in evolutionary ecology by establishing a new methodological framework that integrates evolutionary biology and community ecology in natural communities.

Keywords: community evolution plant herbivore interactions
Biomechanical modelling and computational imaging to identify different causes of back pain in large epidemiological studies (iBack-epic)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: Prevention,  Diagnosis and T reatment of Human Diseases
Panel description: Medical technologies  and tools for prevention, diagnosis and treatment of human diseases, therapeutic approaches and interventions , pharmacology, preventative  medicine, epidemiology and public health , digital medicine
Countries involved: Germany
Call: ERC CONSOLIDATOR GRANTS (ERC-2021-COG, 2021)
Start date: 2022-05-01
End date: 2027-04-30
Duration (months): 60.0
Total project cost (EUR): 1999993.0
EU funding (EUR): 1999993.0
Participants: 1
Project status: SIGNED

Chronic back pain is a major burden and source of disability worldwide. It is primarily attributed to different biomechanical factors, but can also have inflammatory, neurological or psychological causes. Clinical findings and conventional imaging cannot reliably distinguish different causes of back pain. In contrast, individual biomechanical models can quantify diverse (pathologic) loading patterns and thus could be used to distinguish different aetiologies of back pain, to better understand individual pathophysiology and guide preventive strategies. During my recent ERC-StG “iBack”, I developed quantitative imaging methods and deep-learning based image processing to automatically generate a fully individualized biomechanical model of the thoracolumbar spine. Simultaneously, two large-scale epidemiologic studies collected clinical and high-resolution imaging data of the spine of more than 15,000 participants so far, aiming at more than 35,000 participants by mid 2022 The high-level objective of iBack-epic is to use such novel image analysis techniques to identify different biomechanical and inflammatory causes of back pain in study participants. I will adopt and extend my recently developed deep-learning based spine labelling and segmentation algorithms to fully automatically calculate individual biomechanical, functional and morphometric parameters of the spine. In this large-scale population data, I will identify different biomechanical loading patterns, use quantitative image-based parameters to discriminate normal ageing from pathologic degeneration and identify pathological conditions that are linked to back pain or subsequent development of chronic back pain. Such a differentiation – for the first time based on quantitative image data – will allow for a better understanding of the underlying pathophysiology of back pain, an improved risk stratification, a tailored investigation of genetic causes and thus will help to better guide preventive strategies.

Keywords: back pain,computational imaging,machine learning,magnetic resonance imaging,
Lectibodies to Eliminate Tumours (Lectibodies)

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: France
Call: ERC PROOF OF CONCEPT GRANTS1 (ERC-2022-POC1, 2022)
Start date: 2022-06-01
End date: 2024-11-30
Duration (months): 30.0
Total project cost (EUR): 150000.0
EU funding (EUR): 150000.0
Participants: 1
Project status: CLOSED

Antibody-mediated delivery of therapeutic compounds to tumor cells for the treatment of cancer is a rapidly growing multibillion-euro market. One class of tumor markers, the glycosphingolipids (GSLs), are only rarely addressed in this context, due to the difficulty of obtaining antibodies against them. In this proof-of-concept program, we will develop a novel class of products — lectibodies — for the delivery of therapeutic compounds to tumor-specific GSLs. Our lectibodies are based on a naturally occurring GSL-binding protein with intrinsic tumor targeting capacity. We will rely on a proprietary phage library technology to isolate lectibodies against GSLs (or cocktails thereof). In this PoC program we will optimize and apply our technology to specifically target O-acetyl GD2, a GSL highly expressed in neuroblastoma tissues. This will enable us to generate lectibody-based therapeutics against neuroblastoma in children, a devastating disease for which the drug market is predicted to reach 118€ million in 2022. We will explore two options for further business development: a) building off of our current partnership with OGD2 Pharma (a biotech based n Nantes, France) and b)creation of a spin-off company which will license deals to several pharmaceutical partners based on pathology. We will capitalize on the expertise in launching start-ups of our principle investigator and on close links with clinicians and industry partners. Our technology has truly groundbreaking potential as, in principle, chimeric lectibodies can be developed against virtually any tumor-specific cocktail of GSLs thus opening the door for the development of novel therapies for several cancers. Thus, following the development of neuroblastoma-specific lectibodies, we foresee a wider range of future applications for our technology.
Lab-to-tech transition of the current best low temperature electrolyser technology for CO2 reduction to CO using solar energy (SolarCO2Value)

Framework: Horizon Europe — Innovative Europe
Programme: The European Innovation Council (EIC)
Theme: EIC Transition
Destination: Open to supporting projects in all areas of science, technology,...
Action type: EIC actions
Countries involved: Hungary
Call: EIC Transition Open 2022 (HORIZON-EIC-2022-TRANSITION-01, 2022)
Start date: 2022-12-01
End date: 2025-05-31
Duration (months): 30.0
Total project cost (EUR): 2373125.0
EU funding (EUR): 2373125.0
Participants: 1
Project status: CLOSED

One of the most important challenges of humanity is to maintain economic growth and wellbeing in an environmentally sustainable way. The European Green Deal addresses this issue and it aims at making Europe climate neutral by 2050. To reach this aim, a high priority opportunity is the utilisation of waste carbon dioxide to produce valuable chemicals (e.g. energy carriers, fine chemicals, pharmaceuticals) in an environmentally and economically sustainable manner. In our previous ERC Proof of concept project, we have demonstrated that the most viable approach where sunlight is first converted to electricity by a solar photovoltaic (PV) cell and CO2 is then reduced electrochemically to carbon monoxide, which can be further processed to valuable chemicals. The technoeconomic analysis performed during the ERC PoC project confirmed the competitiveness of this solar energy conversion approach. Our team developed the current best performing low temperature CO2 electrolyser cell at laboratory scale, published the results in Nature Energy and filed two PCT patent applications regarding this technology. The aim of this project is to translate our scientific and technological excellence to a commercially appealing value proposition. Our objective is to develop, build and operate a containerised demonstrator scale CO2 electrolyser unit (capable of processing 100 t CO2/year) as well as to validate its performance using photovoltaic power. We aim to perform a detailed technoeconomic assessment and develop a business plan to attract investors in order to scale the technology further and start its commercialization. By the end of the project, we aim to become ready for Series A investment and/or EIC-Accelerator blended finance. The success of this project will represent a genuine breakthrough in the field of Carbon capture and utilization (CCU); enhancing European leadership in this emerging market, and a significant contribution to Green Deal objectives.

Keywords: co2 valorisation,carbon capture and utilisation,fine chemicals,electrical grid balancing,electrifying the industry,business plan development,investor readiness
Multiscale Modeling of Glassy Electrolytes for Solid-State Batteries (MultiBat)

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: Denmark
Call: MSCA Postdoctoral Fellowships 2023 (HORIZON-MSCA-2023-PF-01, 2023)
Start date: 2025-02-01
End date: 2027-01-31
Duration (months): 24.0
Total project cost (EUR): 230774.4
EU funding (EUR): 230774.4
Participants: 1
Project status: SIGNED

New energy storage solutions are required for enabling a sustainable society. Solid-state batteries (SSBs) are promising candidates due to their safety and higher energy density compared to conventional batteries. Particularly, the adoption of solid-state electrolytes with a disordered structure, i.e., glassy electrolytes, has garnered attention due to their superior ionic conductivity, interfacial stability, and reduced dendrite formation compared to crystal electrolytes. However, challenges related to brittle fracture, scalable production, and multiscale modeling impede large-scale commercialization of SSBs. This project aims to establish a multiscale, multiphysics model for glassy electrolytes in SSBs across varying length and time scales. Initially, deep learning force fields for two glassy electrolyte families, namely lithium-aluminum-titanium-phosphate and lithium thiosilicate, will be developed based on training data generated using ab initio molecular dynamics (Work Package 1). Based on this, large-scale molecular dynamics simulations will be used to clarify the lithium diffusion and fracture mechanisms within the glassy electrolytes at the atomic scale (Work Package 2). Lastly, a multiscale, multiphysics model will be constructed by integrating finite element methods with macro atomistic ab initio dynamics simulations to simultaneously account for electrochemical reactions, heat transfer, and mechanical deformation (Work Package 3). Aalborg University's excellent research environment and the expertise of the fellow applicant (multiphysics modeling) and supervisor (molecular dynamics, glasses) will ensure the achievement of the project’s objectives and the broad dissemination of the findings. By advancing theoretical insights into the behavior of glassy electrolytes, the study will contribute to safer and more efficient batteries. The fellow applicant will also emerge from the project with new skills and the ability to lead an independent research group.

Keywords: amorphous materials,solid state battery,md simulations,fem simulations,machine learning force field,mechanical properties
Renewable Energy Sources Power FOrecasting and SyNchronisation for Smart GriD NEtworks MaNagemenT (RESPONDENT)

Framework: Horizon Europe — Global Challenges and European Industrial Competitiveness
Programme: Digital, Industry and Space
Theme: EU Space
Destination: EU Space
Action type: Innovation actions
Countries involved: Greece,Spain,Ireland
Call: EGNSS and Copernicus applications fostering the European Green deal (HORIZON-EUSPA-2021-SPACE, 2021)
Start date: 2022-11-01
End date: 2025-04-30
Duration (months): 30.0
Total project cost (EUR): 2745275.0
EU funding (EUR): 2147112.5
Participants: 8
Project status: CLOSED

Renewable Energy Sources Power FOrecasting and SyNchronisation for Smart GriD NEtworks MaNagemenT. Renewable energy sources (RES) play a major role to the EU’s aspiration to transform to a climate-neutral economy. Their integration into the power grid is pivotal to the green transition and to the decarbonisation of the energy sector. However, as the most commonly used RES (solar, wind and hydropower) are also weather-dependent, their power generation capacity varies according to the local microclimatic conditions. This power production variability makes RES difficult to integrate into the power grid and to provide seamless, stable and secure amounts of power. On the other hand, power demand also affects the power grid operation, since there must always be a supply/demand balance in the power grid. Grid power imbalances can cause frequency fluctuations and other unwanted transient phenomena, which can compromise grid stability and operation. For that matter, advanced grid monitoring techniques have been developed, employing phasor measurement units (PMUs) to measure the electrical signals in a precise and synchronised way, based on a reliable timing reference. Yet, currently, no Galileo-based applications on PMU timing exist. In the above framework, RESPONDENT comes to address the challenges of RES power generation forecasting, demand forecasting and smart power grid monitoring and supply/demand balancing. An AI/ML RES power generation forecasting algorithm is proposed, exploiting both Copernicus EO and site-specific weather data, along with renewable energy power conversion models. Furthermore, an AI/ML – multiphysics model for power demand of certain communities is also developed. Lastly, RESPONDENT will build a Galileo-enabled PMU and develop a monitoring module, in order to test and verify the advantages offered from the Galileo timing and synchronization services in smart grid monitoring, power balancing and overall operation.

Keywords: renewable energy,energy generation forecasting,energy production forecasting,timing and synchronisation