Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : Orbital Cinema (Horizon Europe, appel 2022, Synergy grants)
Entité participante : Forschungszentrum Jülich — Pays : Allemagne — Rôle : CO-PI
Acronyme de l'entité : FZJ
Type d'entité : Recherche
Financement ERC de l'entité : 2714366.25 €

Directly watching in slow-motion videos how electrons move in quantum mechanical orbitals and how this motion shapes the functionalities of condensed matter has been a dream shared by all natural and life sciences. Yet, this vision comes with the daunting challenge of mapping the microscopic structure of electronic orbitals with simultaneous ultrafast time resolution. We will turn orbital cinematography into reality. This seminal breakthrough will rely on the unique synergies between photoemission orbital tomography (POT), ultrafast photoelectron spectroscopy, lightwave electronics and advanced theory, developed and pioneered by us. Secured by our recent proof-of-principle studies, we will combine these aspects to transform POT to a cinematography at unprecedented time scales, faster than a single oscillation period of light. This will allow us to systematically explore the nanocosmos on its intrinsic femto- to attosecond (the billionth part of a billionth of a second) scales. We will take actual slow-motion movies of molecular orbitals during charge transfer processes, surface chemical reactions, and wave packet motion driven by lightwaves. Orbital Cinema will thus resolve key questions related to a wide range of applications, from next-generation optoelectronics, energy conversion, photochemistry and catalysis to prospective electronics at optical clock rates. We expect it to revolutionize our understanding of the nanocosmos by elucidating–on elementary spatio-temporal scales–the inner structure of quantum leaps, strong-field control of electrons, charge transfer processes, and chemical reactions as well as their control by electric fields and light. Since the dawn of quantum mechanics, the temporal evolution of electronic orbitals has been among the most sought-after, yet elusive quantum processes. Our model-free observation of orbital motion establishes an unprecedented ultrafast wave function lab that will carry us to the very foundations of quantum science.

Mots-clés : photoemission orbital tomography,ultrafast photoemission,lightwave electronics,time dependent density functional theory,charge transfer,chemical reactions,nuclear motion,wave packet dynamics
Projet ERC : FireSpace (Horizon Europe, appel 2025, Synergy grants)
Entité participante : Centrale Lille Institut — Pays : France — Rôle : CO-PI
Acronyme de l'entité : Centrale Lille Institut
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2310601.51 €

The "FireSpace" research proposal aims to address the critical challenge of fire safety in space exploration, particularly in environments with increased oxygen concentrations, reduced pressure, and reduced gravity. The main objective is to generate fundamental knowledge on the fire behavior of materials used in spacecraft and habitats under these extreme conditions and to develop strategies for mitigating fire risks. This will be achieved through a combination of experimental investigations, the development of fire-retardant (FR) materials, and advanced numerical simulations. The key objectives of the project are to: 1. Passive fire mitigation: Understand the fire behavior of FR materials in reduced gravity and oxygen-rich environments. Develop new FR materials and advanced diagnostics for testing these materials in microgravity. 2. Active fire mitigation: Formulate strategies for controlling flame spread through environmental perturbations such as acoustic or electromagnetic waves. 3. Numerical simulations: Perform detailed simulations of fire spread from material to compartment scales, predicting the effectiveness of fire safety strategies in spacecraft and space habitats. 4. Risk management: Consider the interplay between fire safety and other critical habitation systems, ensuring a balanced approach to risk management in space missions. The research will be structured into seven work packages (WPs) involving the design of FR materials, development of experimental rigs for microgravity platforms, and integration of fire safety into spacecraft design. This holistic approach will generate groundbreaking knowledge to enhance the fire safety of future space missions.

Mots-clés : fire retardancy,flame retardant,flammability,fire safety,combustion,fire spread,cfd modeling,numerical simulation,reduced gravity,space exploration,spacecraft,diagnostics
Projet ERC : SmartX (Horizon Europe, appel 2024, Synergy grants)
Entité participante : Conseil supérieur de la recherche scientifique — Pays : Espagne — Rôle : PI
Acronyme de l'entité : CSIC
Type d'entité : Recherche
Financement ERC de l'entité : 2952801.25 €

The main objective of this project is to improve the early detection and accuracy of lung disease diagnosis by developing a novel detector concept for dark-field X-ray imaging - a novel method with great potential for the assessment of pathological changes in the alveolar microstructure of the lung as recently discovered in initial patient studies. Our research will focus on chronic obstructive pulmonary disease (COPD), the third leading cause of death worldwide, responsible for more than 3.2 million deaths each year. Traditional chest X-rays, while critical for diagnosis, are often inadequate for the early and accurate detection of mild to moderate COPD due to their limited sensitivity. Similarly, computed tomography (CT) scans are limited in detecting early stages of COPD and are associated with much higher radiation doses. This highlights a significant diagnostic need, as current methods, including spirometry and conventional imaging, cannot reliably assess the severity of COPD.  Our goal is to develop a breakthrough detector technology that overcomes the key challenge of darkfield imaging: the need for a 50% absorbing grating. By utilizing the latest advances in nanoscintillation materials and single photon avalanche diode (SPAD) sensor technology, we intend to directly resolve the interference patterns characteristic of darkfield imaging. This new technology not only promises to reduce the radiation dose required by current darkfield techniques by 50%, but also enables integration with single-photon spectral detection.  This initiative is a high-risk, high-reward project with the potential to revolutionize X-ray imaging technology, particularly lung imaging, after more than 125 years of practice. Most notably, it will lay the technological foundation for routine integration into the next generation of medical X-ray and CT imaging technology.

Mots-clés : x ray darkfield imaging,lung diseases,x ray detection technologies,photonics,computed tomography,respiratory diseases,scintillation materials
Projet ERC : CartoHostBug (Horizon Europe, appel 2023, Synergy grants)
Entité participante : Leiden University Medical Center — Pays : Pays-Bas — Rôle : PI
Acronyme de l'entité : LUMC
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2498875.0 €

Microbiome-host crosstalk is crucial for gut homeostasis and its dysregulation is a hallmark of diseases such as colorectal cancer (CRC) and inflammatory bowel disease (IBD). Despite its key relevance for a holistic understanding of the human superorganism and its (patho-)physiology, how local host-microbiome interactions form specific niches in the gut and how these niches function at the cellular and molecular level remains unexplored, mainly due to a lack of suitable technologies. To fill this gap, we propose to jointly reconstruct the host transcriptional and microbiome compositional landscape of the human gut across a large number of healthy individuals as well as IBD and CRC patients. For this, we will leverage a combination of novel spatial profiling technologies for unbiased transcriptome sequencing and microbiome profiling at single-cell resolution in situ. First, we will spatially delineate local niches formed of specific microbes and host cells. To dissect this complex crosstalk into specific interactions, we will secondly use in vitro and in vivo models to introduce perturbations either on the host or the microbiome side. Finally, we will integrate the resulting data to deconvolute host-microbiome circuits computationally and to predict functional niches, in particular host responses to pathogens of relevance in IBD and CRC. Interesting predictions will be tested in organoid and animal models. Developing a spatially resolved computational model of the gut ecosystem will allow us to predict early local events in disease onset; from these we will identify and validate prognostic IBD and CRC biomarkers for future clinical translation.  This work will revolutionize our understanding of intestinal host-microbiome interactions by adding a first-ever functionally resolved spatial dimension with clinical relevance for the future diagnosis and treatment of intestinal disorders.

Mots-clés : spatial transcriptomics spatial microbiome analysis host microbiome interactions mucosal immunology intestinal diseases colorectal cancer gut
Projet ERC : D2Smell (Horizon Europe, appel 2023, Synergy grants)
Entité participante : Institut Weizmann — Pays : Israël — Rôle : CO-PI
Acronyme de l'entité : WIS
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 3562883.0 €

This proposal is framed by a technological goal: We aim to digitize smell. Achieving this is currently prevented by gaps in basic science. We aim to fill these gaps, culminating in a proof of concept for our model. The primary gap we identify is lack of data on what humans typically smell. Phrased conceptually, in Aim 1 we ask what are the natural statistics of human olfactory perceptual space. We address this in a series of three experiments, highlighted by one where we equip participants with a wearable sampling apparatus we designed and built for this proposal. The apparatus measures sniffing behaviour to identify odor sampling, measures neural activity to verify olfactory perception, takes video of the visual scene, analyses total levels of volatile organic compounds in real time, and collects odor samples for detailed analysis off line. In other words, we generate an olfactory equivalent of Google Street View, with the addition of chemical, perceptual and neural data. Using this we will characterise the natural statistics of human olfactory perceptual space. Moreover, a major contribution of this proposal will be in posting this massive data as a publicly available recourse. Next, in Aim 2 we will use this data to digitize human olfactory perceptual space. We build on a model that allows us to recreate odors using a restricted set of odor primaries. We will test our model in two frameworks: One we call SmelloVision, where we develop the algorithmic framework to generate an odor to match any digital image, and one we call TelleSmell, where we develop a device to sense the environment, the algorithmic framework to transfer the data, and a device to generate the corresponding odor remotely. We provide pilot data for Aim 2 where we sensed an odor in Mainz (Germany), transmitted the data over IP to Rehovot (Israel), where we successfully recreated the smell. This was, as far as we know, the first transmission of odor over IP.

Mots-clés : olfaction odor sniffing perceptual space chemical space
Projet ERC : HYROPE (Horizon Europe, appel 2023, Synergy grants)
Entité participante : Université de technologie de Darmstadt — Pays : Allemagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2497708.75 €

HYROPE proposes to combine unique, fundamental skills of four European laboratories to perform atmospheric and high-pressure experiments coupled to high-performance simulations of an innovative concept for gas turbines to burn zero-carbon, hydrogen-based fuels. Due to their high-power density, it would be a potential game-changing technology that can deliver energy on demand for both power and aviation. Gas turbine technology has evolved from an abundance of hydrocarbon fossil fuels but has the unique potential to be fuel flexible and burn renewable, zero-carbon hydrogen-based fuels such as hydrogen or ammonia. However, these fuels raise several fundamental issues as they have very different combustion properties and emission properties when compared to hydrocarbon fuels. Hydrogen is highly diffusive, extremely reactive, and its turbulent burning rate exhibits an unexplained strong pressure dependence. Predicting whether hydrogen flames that are stable at atmospheric pressure will be stable at higher pressures, as needed in gas turbines, remains an unsolved fundamental problem. Ammonia is a convenient hydrogen carrier that can be partially decomposed to hydrogen but requires careful control of NOx emissions. How to handle the effects of pressure on these fuels is a major gap in our scientific knowledge. HYROPE will study the effects of pressure on the combustion of hydrogen-based fuels in a fuel flexible, staged combustion approach where the first stage is controlled by flame propagation and the second one by autoignition. This configuration offers enormous potential that has not yet been exploited for such fuels. This can only be achieved through a joint work combining state-of-the-art tools, from novel experimental facilities at high pressures, advanced optical diagnostics to high-performance computing. The project will accelerate the development of new, high-power density, fuel-flexible combustion systems and unleash the potential of zero-carbon gas turbines.

Mots-clés : hydrogen,thermal power,zero carbon fuels,power generation,gas turbine
Projet ERC : DELTA-LANG (Horizon Europe, appel 2023, Synergy grants)
Entité participante : University Medical Center Groningen — Pays : Pays-Bas — Rôle : CO-PI
Acronyme de l'entité : UMCG
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2759971.0 €

Mental life fluctuates, changing from moment to moment as the incessant and turbulent flow of thought rages. In 3% of the world’s population, the fragile equilibrium that we all hope to maintain gives way to dynamical changes resulting in psychotic episodes, which after remission tend to recur over time. A capacity to predict them at a clinically relevant temporal resolution, similar to our capacity to forecast a thunderstorm, would be a major advance in public health, with the important difference that, unlike thunderstorms, psychosis can be prevented. We test a previously untested and untestable hypothesis: that meaning encoded in spontaneous speech, translated into digitalized quantitative features, computationally analyzed with natural language processing (NLP) tools, can serve as a key personalized and interpretable predictor of phase transitions from remission to psychotic relapse. Addressing this hypothesis requires conceptual and methodological breakthroughs in our understanding of language and what signals its variability can carry for a pathophysiological process. We pursue these with a synergetic combination of linguistic, neuroimaging, psychiatric, and e-health insights. Using a hypothesis-driven approach we will (i) define generalizable language metrics relating to symptom variability cross-sectionally; (ii) identify individually-specific neural signatures of psychosis and remission related to changes in these linguistic metrics, using a dense-sampling approach; (iii) test the metrics retrospectively as predictors of relapse in an independent longitudinal cohort; and (iv) take the paradigm from the lab to the patient’s home in a prospective clinical study testing whether we can predict state change before it is catastrophic, at the temporal resolutions clinically required. DELTA-LANG (ΔLANG) thereby identifies the delta of language – a linguistic change that enables the prediction of clinically significant change, before it occurs.

Mots-clés : language,speech,psychosis,relapse,fmri,clinical decision support system,thought disorder
Projet ERC : EndoTheranostics (Horizon Europe, appel 2023, Synergy grants)
Entité participante : Université de Turin — Pays : Italie — Rôle : CO-PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 3150726.25 €

Colorectal cancer (CRC) represents a significant proportion of malignant diseases. Interventions are often carried out during the latter stages of development, leading to low patient survival rates and poor quality of life. In 2022 a European Commission report stated that “colonoscopy-based screening has higher sensitivity than testing for blood in stool, but it is less acceptable to participants”. At the same time, effective methods to treat polyps in the colon are limited. Current approaches are often associated with unsafe oncological margins and high complication rates, requiring life-changing surgery. EndoTheranostics will usher in a new era for screening colonoscopy, advancing the frontiers of medical imaging and robotics. A tip-growing or eversion robot with a sleeve-like structure will be created to extend deep into hollow spaces while perceiving the environment through multimodal imaging and sensing. It will also act as a conduit to transfer miniaturised instruments to the remote site within the colon for diagnosis and therapy (theranostics). With these capabilities, the system will be able to offer: 1. painless colon cleansing in preparation for endoscopy; 2. real-time polyp detection and tissue characterisation through AI-assisted multimodal imaging; 3. effective removal of polyps by conveying a “miniature mobile operating chamber” equipped with microsurgical tools to the target through the lumen of the eversion robot. The unique technical and clinical challenges will be tackled by the PIs, each bringing complementary skills, backed by their institutions with wide expertise and exceptional facilities. The synergy and added value evident in this team will lead to breakthroughs not possible through independent research. The outcomes of EndoTheranostics will revolutionise the theranostics of CRC, impacting the quality of life of millions of individuals. Ultimately it will launch a new era for endoluminal intervention with applications beyond medicine.

Mots-clés : soft robotics,inflatable robots,medical imaging and perception,tissue characterisation and registration,microsurgery,natural orifices translumenal endoscopic surgery notes,autonomous control and manipulation,intervention shared control
Projet ERC : SWIMS (Horizon Europe, appel 2023, Synergy grants)
Entité participante : Université technologique de Dresde — Pays : Allemagne — Rôle : CO-PI
Acronyme de l'entité : TU Dresden
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2072693.25 €

SWIMS vision is to propose a bio-inspired paradigm change for the design and hardware of future smart wireless multimodal sensory systems that will operate with stochastic spikes, offering a breakthrough with unrivalled energy efficiency at system level, for event detections and communication. The scientific breakthroughs proposed here are sine qua non advancements for a sustainable deployment of billions of future Internet of Things nodes to support smart economy and society development, with large energy savings and limited impact on environment. The synergistic interaction of four complementary skilled PIs enables the realization of a radically-novel end-to-end stochastic analog spiking neuromorphic concept for SWIMS nodes, offering solutions to challenges of sensor spiking signal generation, processing and communication with disruptive innovations at all levels, inspired by the biological model of a small insect. SWIMS involves many beyond state-of-the-art scientific advancements from technology to system level to enable a neuromorphic architecture with i) as input neuron layer, new heterostructure spiking sensor arrays based on transition metal oxides/2D semiconductor, covering infrared, ultraviolet, acoustic and electromagnetic detections, ii) hidden layers in tiny spiking neural networks based on novel CMOS Fe-FET concepts capable of efficiently dealing with inherent stochastic noise when processing spiking signals on-chip, iii) a spiking emitter as output layer for event-driven wireless transmission using optimized spike modulation and encoding, and iv) a modelling framework embedding stochastic effects in task-based electronic system design and biologically inspired recurrent neural networks. The synergistic interaction will enable unique design and experimental validations of first of their kind event-driven demonstrators with optimized all spiking multi-modal sensor nodes and energy consumption more than 100x lower than existing state of the art.

Mots-clés : cmos,iot edge nodes,integrated circuits,ultra low power,phase change and ferroelectric devices,modulation and coding,non gaussian uncertainties,stochastic spiking sensors
Projet ERC : ADDI (Horizon Europe, appel 2024, Synergy grants)
Entité participante : Université Toulouse Capitole — Pays : France — Rôle : CO-PI
Acronyme de l'entité : UT Capitole
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2558600.0 €

The Advancing Digital Democratic Innovation (ADDI) project will pioneer the study of digitally augmented forms of civic participation for preference formation and elicitation. While digital technology has, for some time now, been widely seen as being in direct conflict with the needs of a well-functioning democracy, ADDI will realise the true potential of digital technologies in the democratic space. The project will be led by four well-known researchers with expertise in participatory platform design, deliberative democracy, and computational social choice. It will be organised around three methodological pillars - technology, empirics, and theory - and it will serve three core objectives: designing technologies and procedures for citizen deliberation and participation; experimentally testing the impact of digital platforms in deliberative and participatory forums; and understanding the structure of the preferences collected through digitally augmented instances of civic participation and deliberation. The technology track will lead the creation of interventions in the form of open-source platforms designed to digitally augment deliberation and participation. The empirical track will test these interventions using randomised trials in deliberative and participatory forums and will explore the statistical patterns of the preferences elicited in them. The theoretical track, finally, will contribute conceptual and algorithmic tools to elicit, present, and combine preferences in real-world environments, including situations where participants provide incomplete preferences and that involve under-represented minorities. At the end of the project, we will have charted the potential of digital technologies in supporting and improving democratic practices, while also providing a robust suite of scientifically validated open-source tools designed to distribute these capabilities at a global scale.

Mots-clés : computational social choice,collective intelligence,collective will formation