Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : THEAGENT (Horizon Europe, appel 2021, Consolidator grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Texts and Concepts
Entité participante : American university of Paris — Pays : France — Rôle : Partner
Acronyme de l'entité : AUP
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 172215.0 €

Since the European Middle Ages, the fates of theatre and the city have been intertwined. Mystery plays thrived amidst the urban guilds of medieval Paris, city comedies heralded merchant capitalism in seventeenth-century London, and Ottoman shadow puppetry shaped coffeehouse culture in nineteenth-century Istanbul. The emergence of the modern European city in particular was linked to the development of both state-sponsored and independent theatre institutions; theatre and performance practices drew on the human proximity that city living made possible, and shaped the visions of cultural heterogeneity that emerged from urban cohabitation. Today, unprecedented dynamics of migration, globalization, and rapid gentrification are fundamentally changing theatre’s importance in the urban environment. Theatre and performance practices are all but absent from urban studies, however, and theatre scholarship often views the urban question through a limited analytic lens. Combining multi-sited ethnographic and archival research, this interdisciplinary research project will focus on the key cities of London, Paris, Berlin, Warsaw and Istanbul to analyze the complicated and often ambivalent relationship between theatre practices and urban transformation in twenty-first-century Europe. Following key thematic threads like migration and memory, Theatre and Gentrification’s original case studies will illustrate the diversity of property relations and housing tenure across the European continent, as well as the complex roles that theatre and performance practices play in producing urban subjectivities and structuring the cultural politics of gentrification. Groundbreaking in its use of theatre as its vantage point, this ambitious project will change the way we think about the contradictions of culture in the twenty-first century city, from its role in securing claims to global urban stature, to its position within imaginaries of authentic local resistance.

Mots-clés : theatre,urbanity,gentrification,memory,migration
Projet ERC : MixClouds (Horizon Europe, appel 2023, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Products and Processes Engineering
Entité participante : École polytechnique Chalmers — Pays : Suède — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1998531.0 €

Mixed-phase clouds—atmospheric complex three-phase systems containing suspended ice particles, supercooled water droplets, and water vapor—are responsible for most of the precipitations reaching the Earth’s surface. In addition, these clouds play a primary role in the planet’s radiative energy budget and the water cycle. Despite their relevance, there is a lack of a basic understanding of the complex hydrodynamics, heat, and mass transfer between the different water components with numerous scientific open questions. In the last decades, many scientific works have shown a significant impact of turbulence in “warm” (ice-free) clouds and “warm” rain formation in enhancing condensation/evaporation of rain droplets and promoting collisions. On the other hand, the role of turbulence in mixed-phase clouds has never been properly quantified; consequently, up to now, this topic has been nearly exclusively a subject pertaining to atmospheric physics rather than fluid dynamics. I want to change this perspective and analyze the rich dynamics of mixed-phase clouds using a combination of theoretical and numerical tools developed for general multiphase flows. MixClouds is a multidisciplinary project aiming to: i) understand the impact of turbulence in mixed-phase cloud microphysics of water hydrometeors, ii) quantify this impact by determining typical ice and water droplet size distributions at given temperature, humidity, and turbulence levels, iii) developing the next generation of numerical tools to couple multiphase turbulent dynamics at different scales, iv) developing novel sub-grid models to parametrize mixed-phase cloud microphysics and test against known atmospheric observations. The final results can potentially generate a ground-breaking impact not only in the areas of turbulent multiphase flows and cloud physics but also in climatology and in all environmental and industrial applications involving suspensions of three-phase flows in the presence of phase changes.

Mots-clés : turbulence,cloud microphysics,cloud physics,multiphase flows,dns,les
Projet ERC : 3DCuT (Horizon Europe, appel 2023, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Condensed Matter Physics
Entité participante : Université de Naples - Frédéric-II — Pays : Italie — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1178125.0 €

2D superconductors can be used to build ultra-clean interfaces for Josephson junctions, the superconducting analog of a transistor. A small twist in the relative crystal orientation of 2D superconductors could become a new platform for topological superconductivity, an exotic state of matter that holds great promise for quantum computing at high temperatures. Based on my methodological developments for the realization of twisted cuprate ultra-clean interfaces, the field is rapidly evolving, and these interfaces are now the leading candidate for the implementation of high-temperature topological superconductivity. However, the combination of well-controlled twisted cuprate heterostructures and complex circuits calls for new experimental methodologies.  3DCuT will develop micro/nanodevices and techniques to fabricate and control cuprate van der Waals twisted heterostructures in three-dimensional nanoarchitectures: 1) We will develop novel fabrication tools to integrate complex thermal and superconducting circuits in fragile twisted cuprate bilayers. We will explore if a topological gap opens near ´magic´ angles in twisted bilayers by studying the Josephson effect. 2) We will fabricate trilayers cuprate heterostructures with different twist angle symmetries, where the topological gap is amplified and time-reversal symmetry broken states appear across a wide range of angles. 3) We will create a heterostructure between a superconducting cuprate twisted heterostructure and a topological insulating crystal, allowing us to create a chiral Majorana edge mode. At the end of this project, we will have provided a brand-new solid-state tool for emerging quantum technologies in computation, metrology, secure communication, single-photon imaging, methodologies for the entire field of 2D materials, and a comprehensive understanding of the governing principles and ingredients for topological superconductivity at high temperatures.
Projet ERC : NACAREI (Horizon Europe, appel 2021, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Physical and Analytical Chemical Sciences
Entité participante : École polytechnique Chalmers — Pays : Suède — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2341250.0 €

How can we “see” a catalytic reaction on a single nanoparticle? While our eyes use visible light to create a vivid perception of our world, they are unable to resolve the nanoscale. Now imagine light yet allowing us to equally vividly see a chemical process and thereby enabling us to witness how structure or chemical composition of a single nanoparticle control the rate of a catalytic reaction on its surface. To date, the lack of a suitable technique prevents this ultimate level of insight at technically relevant conditions. At the same time, to gain such insight is the ultimate goal of catalysis science and a key enabler for the rational design of next-generation catalyst materials needed to address some of humanity’s grand challenges in the energy, environmental clean-up and health sectors. NACAREI therefore develops a nanoimaging method that realizes this ultimate goal. As the key ingredients for achieving the necessary unprecedented resolution, it relies on the combined nano-confinement of reaction products in, and the ultrahigh optical sensitivity of, nanofluidic structures. Particular focus will also be put on the development of methods to fabricate or trap size-, shape- and composition-controlled single sub-10 nm metal nanoparticles inside nanofluidic channels by combining key traits of top-down nanofabrication and colloidal synthesis. The developed nanoimaging platform will be applied to scientific case studies related to catalyst function with respect to the roles of particle structure, surface state, chemical composition and interaction with the support, and thereby uncover the next generation of catalyst design rules. In the long term, I envision the developed nanoscale imaging platform to enable the study of other nanoscale processes, for example in biochemistry, thereby enabling high impact also at other vibrant scientific frontiers.

Mots-clés : nanofluidics,nano optics,nanofabrication
Projet ERC : ProFreeOpt (Horizon Europe, appel 2024, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer Science and Informatics
Entité participante : Technion - Institut de technologie d'Israël — Pays : Israël — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1785000.0 €

Efficient algorithms for continuous and in particular convex optimization have revolutionized science and engineering in the past decades, providing the engine that drives numerous key technical and computational practices used across almost every scientific and engineering discipline. In particular, it is one of the main pillars of the ongoing data science and AI revolution. For many important large scale optimization problems that include constraints that are complex yet highly-structured, the algorithmic weapon of choice are so-called projection-free methods, which are mostly based on the classical Frank-Wolfe method. Despite vast interest and progress in recent years on scaling up projection-free methods, their optimization oracle complexity remains significantly inferior to their projection-based counterparts. This shortcoming prevails throughout almost every optimization paradigm of interest and is often the bottleneck in further scaling-up this important family of optimization methods. The overarching goal of this project is the foundational and systematic study of the landscape of continuous optimization with computationally efficient (projection-free) optimization oracles. My goal is to develop an understanding, across a variety of central optimization paradigms, of how far can we push methods that rely only on simple and efficient optimization steps towards matching the complexities of state-of-the-art projection-based methods (that rely on computationally-expensive optimization steps). I envision that the novel algorithmic and methodological results that will come out of this research will lay the foundations to a new generation of far more advanced algorithms for continuous optimization with structured constraints. These will allow to tackle on a practical scale a much richer variety of optimization settings, and will be built to leverage, in a more specialized fine-grained manner, favorable and plausible structure of optimization problems.

Mots-clés : continuous optimization,convex optimization,projection free optimization,frank wolfe algorithm,conditional gradient method,large scale optimization,structural optimization
Projet ERC : FAST (Horizon Europe, appel 2021, Consolidator grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Human Mobility, Environment, and Space
Entité participante : Université de technologie d'Eindhoven — Pays : Pays-Bas — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1999995.0 €

Staying within a maximum global warming of 1.5 degrees requires an acceleration of the transition to a low carbon society. Current theory views such sustainability transitions as inevitably slow as they require interdependent changes throughout socio-technical systems. The observation that energy transition scenarios systematically underestimate the diffusion of key technologies challenges this view. Existing models that form the basis for energy transition scenarios do not include the positive feedbacks resulting from the interactions between civil society and energy transitions. Yet these interactions have been identified as important drivers and barriers of energy transitions, and as crucial in triggering the social tipping dynamics that can accelerate the energy transition. Social tipping dynamics in energy transitions occur when a small change or intervention has a large effect on emission reductions. To date, some examples of social tipping dynamics have been identified, but both a systematic understanding of the mechanisms underlying social tipping dynamics and an evaluation of their potential policy leverage is missing.  The overall objective of the FAST project is to explain and model social tipping dynamics and interventions in energy transitions. This requires a model that explains how the social factors influencing sustainability transitions scale up to realize social tipping dynamics. To this end I will use a novel combination of bottom-up agent-based modelling and top-down diffusion modelling to capture the interactions in socio-technical systems that create tipping dynamics. This will bridge the qualitative field of sustainability transitions and the quantitative field of energy transitions modelling. A team consisting of the PI, 3 PhD students, a postdoc and a research assistant will conduct the proposed study over five years. This is the first study that systematically integrates social tipping dynamics in quantitative models of energy transitions.

Mots-clés : sustainability transitions,energy transitions,agent based models,social tipping dynamics,socio technical transitions
Projet ERC : Gen-TSM (Horizon Europe, appel 2023, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Products and Processes Engineering
Entité participante : Université Gottfried-Wilhelm-Leibniz de Hanovre — Pays : Allemagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1996920.0 €

As a physical fact, randomness is an inherent and ineliminable aspect in all physical measurements and engineering production. Hence, all material parameters are subject to stochastic fluctuations. However, highly accurate predictions are key to achieving the goals of resource-efficiency and sustainability in engineering and construction. In this context, randomness in material parameters constitutes a severe problem: if we can experimentally quantify the magnitude of fluctuations of material parameters, how can we numerically include this information to predict fluctuations in the reactions of construction parts or processes?  All existing strategies for the inclusion of stochasticity in engineering design share the drawback of large numerical costs, leading to inefficiencies, e.g., an increase in simulation time by orders of magnitude. This prevents their industrial application and, consequently, stochastic fluctuations are not factored into design. This is compensated for by adding buffers, e.g., overestimated safety factors, oversized wall thickness, or higher maintenance frequencies, all leading to increased economic and environmental costs.  Thus, a step change in engineering design is required to allow the inclusion of stochasticity into material modelling and engineering simulation, while minimising the numerical extra cost. Gen-TSM aims to meet this challenge by developing a novel strategy for efficient stochastic modelling of highly complex problems and creating a computational framework for the automated formulation of stochastic versions of existing material models. My vision is to unlock the currently untapped potential of material modelling and enable computing stochastic behaviour to become the new standard in engineering design. This would revolutionise current state of the art, allowing access to the full information field by including stochasticity into simulations at low computational costs.

Mots-clés : continuum mechanics computational mechanics stochastic material modelling finite element analysis
Projet ERC : Fenometal (Horizon Europe, appel 2022, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Synthetic Chemistry and Materials
Entité participante : Technion - Institut de technologie d'Israël — Pays : Israël — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1996250.0 €

The functionalization of C=C and C–X bonds (X = I, Cl, Br, and H) is fundamental in organic chemistry for making carbon-carbon bonds or for introducing molecular complexity. Chemists have traditionally relied on precious metals catalyst such as palladium, platinum, and iridium to facilitate these transformations. Some of these metals, if not all of them, are one of the rarest on earth, leading to increasingly high prices and uncertainty in future supply chains. As their availability continues to decline it is important to address the scarcity of these metals to secure a sustainable future. One solution is to develop new technologies that allow one to substitute the precious metal catalysts for those that are abundantly available (e.g., iron), without sacrificing on performance and selectivity. Because of the fundamental differences between the properties of iron (one-electron chemistry) and the second/third-row transition metals (two-electron chemistry), this approach has shown to be a daunting task. If, however, it could be shown that iron could reliably engage in two-electron chemistry, then the reactivity of precious metals could be unlocked for iron. Through bespoke ligand design we will attempt to unlock this two-electron chemistry and apply it to three of the most common reactions in organic synthesis; (i) cross-coupling, (ii) alkene metathesis, and (iii) C–H bond functionalization. By relying on a distinct two-electron mechanism, a treasure trove of possibilities for selective bond forming reactions is generated. Overall, this work is expected to result in new avenues in earth-abundant metal catalysis and provide new methodologies to construct ever important C-C and C-N that can be used to induce molecular complexity.

Mots-clés : earth abundant metals iron cross coupling alkene metathesis bond activation organometallic chemistry
Projet ERC : SpeckleCorr (Horizon Europe, appel 2021, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer Science and Informatics
Entité participante : Technion - Institut de technologie d'Israël — Pays : Israël — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2125000.0 €

When viewed under coherent imaging conditions (e.g. laser illumination), scattering materials such as biological tissues create noise-like images known as speckle. Despite their seemingly random nature, speckle patterns have strong statistical correlation properties that are highly informative of the material producing them. These can be used to enable remarkable imaging capabilities, not possible with current state of the art, for example seeing through highly scattering layers.  Unfortunately, realizing these in practical settings (tissue imaging, fluorescence microscopy) remains a challenge. Research efforts are hindered by a lack of modeling tools, resulting in an incomplete understanding of speckle properties. This project aims to use computational techniques from computer vision and computer graphics to greatly enhance our understanding of speckle statistics, and significantly expand the scope of their applications. To this end, the project will explore algorithmic tools newly-developed by the PI that can accurately and efficiently simulate speckle patterns, to formulate better models of speckle formation. We will exploit our new understanding to develop new types of computational imaging systems that can directly measure speckle correlation, rather than the traditional pipeline where one captures speckle images and estimates their correlations algorithmically in post-processing. Finally, we will exploit these tools in multiple computational imaging applications, including: (i) Acquiring material parameters: estimating the type, size and density of particles composing a material of interest. (ii) Imaging fluorescent sources deep inside scattering tissue. (iii) Adaptive optics imaging.  Potential impact is anticipated in numerous areas  where speckle-based imaging techniques hold promise, including medicine (increased depth penetration of tissue imaging techniques) and material fabrication and analysis (accurate characterization of scattering materials).

Mots-clés : computational photography,scattering,memory effect
Projet ERC : DARC MATTER (Horizon Europe, appel 2023, Consolidator grants)
Domaine scientifique : Life Science
Panel : Integrative B iology : from Genes and Genomes to S ystems
Entité participante : Human Technopole — Pays : Italie — Rôle : PI
Acronyme de l'entité : HT
Type d'entité : Recherche
Financement ERC de l'entité : 1995582.0 €

Tumours evolve, transforming from early-stage curable disease into treatment-refractory, deadly cancer. Therapy resistance is arguably the biggest problem in oncology today, and much of it remains unexplained. The central hypothesis of this proposal is that a large proportion of unexplained drug resistance is due to heritable epigenetic alterations, and non-heritable transcriptional plasticity in cancer cells. I refer to these mechanisms as the dark matter of cancer evolution. Genetic, epigenetic and transcriptional adaptation, together with changes in the tumour microenvironment, may happen at the same time in the same tumour. Lack of knowledge of these mechanisms hinders the development of new treatments strategies. Tackling drug resistance requires a unique combination of clinical cohorts, experimental models, evolutionary biology and computational methods.  I will map and quantify the mechanisms and evolutionary dynamics of genetic and non-genetic drug resistance at unprecedented scale. I will focus on colorectal cancer, the third most common cancer and second leading cause of cancer-related death worldwide. I will use patient-derived organoid models, matched to clinical cohorts followed longitudinally. I will measure organoid evolution under the pressure of cancer drugs, with and without the tumour microenvironment. I will track cell lineages with lentiviral barcoding and perform longitudinal single cell multi-omics, measuring genomes, epigenomes and transcriptomes of the same cell. I will interpret the results within a unique computational framework that brings together evolutionary theory with machine learning to measure, predict and control resistance.  This project will identify new mechanisms and dynamics of cancer drug resistance, deliver new predictive models, and find novel collateral drug sensitivities. This will allow designing rational drug combinations and schedules that will prevent or delay resistance, drastically improving patient outcome.

Mots-clés : cancer evolution,multi omics,single cell,machine learning