Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : PhyCo (Horizon 2020, appel 2020, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Products and processes engineering
Entité participante : Polytechnic University of Turin — Pays : Italie — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 166460.5 €

About a hundred trillion bytes of data has been created in the world while reading this sentence. Central to big data is machine learning, which is an automated way of transforming information into empirical knowledge. Machine learning techniques have been applied to some fluid mechanics problems with success, but there are still three big open questions: Do machine learning algorithms scale to engineering configurations? (Are they robust?); Can we gain physical insight into the solutions? (Are they interpretable?); Can we extrapolate knowledge to other configurations, such as multi-physics problems? (Are they generalizable?). Fluid mechanics modelling has been historically enabled by both empirical approaches and physical principles. Machine learning models may not be interpretable and robust, but they excel at empirical modelling. On the other hand, physical principles are governed by equations that do not adaptively change, but they are interpretable and robust. This project will combine physical principles and empirical modelling into a unified approach: physics-constrained adaptive learning for multi-physics optimization of unsteady, unpredictable and uncertain flows. The learned solutions will not violate physical constraints. The technical objectives are to combine physical principles with machine learning; design adaptive multi-physics models by on-the-fly data assimilation; optimize turbulent flows; quantify the uncertainty; and develop a code that wraps around existing simulation software and experiments. This framework will be applied to maximize energy harvesting from aeroelastic systems to produce clean energy; optimize stable aeroengines with low emissions; and reconstruct high-resolution flow fields from low-resolution experimental measurements. We will rigorously interlace chaos theory, Bayesian inference and artificial intelligence. This project will benefit industries that work with multi-physics flows and artificial intelligence companies.

Mots-clés : adjoint equations in stability,least square shadowing,computational fluid dynamics,reacting flows,machine learning in fluid mechanics,virtualization of flows,gas turbines,reduced order models of fluids,thermoacoustic instabilities,aeroelastic instabilities,combustion instabilities,acoustic flow interaction,proper orthogonal decomposition,dynamic mode decomposition,dimensionality reduction,flow state estimator,uncertainty quantification in fluid dynamics,turbule
Projet ERC : PhyCo (Horizon 2020, appel 2020, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Products and processes engineering
Entité participante : Imperial College London — Pays : Royaume-Uni — Rôle : Partner
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1333539.5 €

About a hundred trillion bytes of data has been created in the world while reading this sentence. Central to big data is machine learning, which is an automated way of transforming information into empirical knowledge. Machine learning techniques have been applied to some fluid mechanics problems with success, but there are still three big open questions: Do machine learning algorithms scale to engineering configurations? (Are they robust?); Can we gain physical insight into the solutions? (Are they interpretable?); Can we extrapolate knowledge to other configurations, such as multi-physics problems? (Are they generalizable?). Fluid mechanics modelling has been historically enabled by both empirical approaches and physical principles. Machine learning models may not be interpretable and robust, but they excel at empirical modelling. On the other hand, physical principles are governed by equations that do not adaptively change, but they are interpretable and robust. This project will combine physical principles and empirical modelling into a unified approach: physics-constrained adaptive learning for multi-physics optimization of unsteady, unpredictable and uncertain flows. The learned solutions will not violate physical constraints. The technical objectives are to combine physical principles with machine learning; design adaptive multi-physics models by on-the-fly data assimilation; optimize turbulent flows; quantify the uncertainty; and develop a code that wraps around existing simulation software and experiments. This framework will be applied to maximize energy harvesting from aeroelastic systems to produce clean energy; optimize stable aeroengines with low emissions; and reconstruct high-resolution flow fields from low-resolution experimental measurements. We will rigorously interlace chaos theory, Bayesian inference and artificial intelligence. This project will benefit industries that work with multi-physics flows and artificial intelligence companies.

Mots-clés : adjoint equations in stability,least square shadowing,computational fluid dynamics,reacting flows,machine learning in fluid mechanics,virtualization of flows,gas turbines,reduced order models of fluids,thermoacoustic instabilities,aeroelastic instabilities,combustion instabilities,acoustic flow interaction,proper orthogonal decomposition,dynamic mode decomposition,dimensionality reduction,flow state estimator,uncertainty quantification in fluid dynamics,turbule
Projet ERC : MERIR (Horizon 2020, appel 2018, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Earth system science
Entité participante : Ben-Gurion University of the Negev — Pays : Israël — Rôle : PI
Acronyme de l'entité : BGU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2000000.0 €

About one-third of annual methane (CH4) emissions to the atmosphere originate from natural, nonanthropogenic sources. However, if all the naturally produced methane actually did reach the atmosphere, its levels would increase by an order of magnitude, dwarfing anthropogenic CO2 emissions. Fortunately, natural scavengers of this methane near its production zone limit its release. One of these scavengers, iron (Fe) oxide, can become a major sink for methane when sulfate concentrations are low. Methane-iron couplings in established sediments, however, are poorly understood. Specifically, significant iron oxide reduction has been observed in many aquatic sediments at depths well below its expected redox zone, where methane is produced by methanogenesis, often accompanied by decreases in methane concentrations. These observations challenge our understandings of iron-methane couplings and microbial players in the deep methanogenic zone and their impacts on the carbon, iron and other cycles. I aim in the proposed research to elucidate the unexplored mechanisms of methane-related iron reduction (MERIR) in the methanogenic zone of established sedimentary profiles under various environmental conditions and their impact on global biogeochemical cycles. I will resolve two striking yet unexplained phenomena: (1) the active involvement of aerobic methanotrophs in iron-coupled anaerobic oxidation of methane (AOM), and (2) the unusual reactivity of iron minerals toward reduction that is accompanied by intensive authigenic magnetite precipitation, and the effects of this mineralogy change on sedimentary magnetism. My expertise will enable me to achieve the objectives of this interdisciplinary proposed work using novel approaches from different fields. The project will likely lead to breakthroughs in our understanding of microbial survival strategies, reveal novel pathways for aerobic methanotrophs, and change our perspectives on iron mineral reactivities and sedimentary magnetism.

Mots-clés : sediment,methane,iron,sulfur,isotope,aom  anaerobic oxidation of methane,redox,lipid,cryptic cycle,authigenic magnetite
Projet ERC : CONSPIRATORIALMEMORY (Horizon 2020, appel 2020, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Cultures and cultural production
Entité participante : University of Amsterdam — Pays : Pays-Bas — Rôle : PI
Acronyme de l'entité : UvA
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1487090.0 €

Academic inquiry into conspiracy theories is unquestionably on the rise. Since the turn of the millennium, a new generation of scholars has released conspiracy theory from its earlier associations with individual pathologies, and has shifted attention to its wider social and cultural functioning. Notwithstanding these developments, existing research still tends to treat conspiracy theories in historical and cultural isolation, overlooking their reliance on earlier events and narrative templates, and neglecting their – increasingly digital – transnational dynamic. Focusing on conspiratorial stories and images in Central and East European literature, film, television, commemorative rituals and online culture, during the period 2010-2020, CONSPIRATORIALMEMORY aims to overcome these limitations. The project elucidates the historical references, the transnational interactions and the online circulations that give conspiracy theories their rhetorical and emotional momentum in the post-socialist era. Relying on a theoretical framework that enriches the emerging field of conspiracy theory studies with affect studies and cultural memory studies, the project zooms in on conspiracy-based cultural imaginations from Poland, Russia, Ukraine and Belarus regarding three transnational events that have recently been at the center of international political tensions. Subprojects 1, 2 and 3 each focus on the conspiracy cultures around one of these events, employing the qualitative methodology of Cultural Analysis to examine the intersecting discourses of memory and suspicion. Subproject 4 uses quantitative digital media research methods to analyze the medium-specific contributions of online platforms to memory-based conspiratorial imaginations. The Project Synthesis compares the modes and media of expression in the examined cases, and addresses their parallels with cultural imaginations of conspiracy from Western Europe and the United States.

Mots-clés : cultural memory,post socialism,central and eastern europe,conspiracy theory,online media,film,literature,television,smolensk air disaster,donbass,chernobyl
Projet ERC : CoQuake (Horizon 2020, appel 2017, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Products and processes engineering
Entité participante : École nationale des ponts et chaussées — Pays : France — Rôle : Partner
Acronyme de l'entité : ENPC
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 80906.98 €

According to the Centre for Research on the Epidemiology of Disasters (CRED), earthquakes are responsible for more than half of the total human losses due to natural disasters from 1994 to 2003. There is no doubt that earthquakes are lethal and costly. CoQuake proposes an alternative, ground-breaking approach for avoiding catastrophic earthquakes by inducing them at a lower energetic level. Earthquakes are a natural phenomenon that we cannot avoid, but –for the first time– in CoQuake I will show that it is possible to control them, hence reducing the seismic risk, fatalities and economic cost. CoQuake goes beyond the state-of-the-art by proposing an innovative methodology for investigating the effect and the controllability of various stimulating techniques that can reactivate seismic faults. It involves large-scale, accurate simulations of fault systems based on constitutive laws derived from micromechanical, grain-by-grain simulations under Thermo-Hydro-Chemo-Mechanical couplings (THMC), which are not calibrated on the basis of ad-hoc empirical and inaccurate constitutive laws. A pioneer experimental research programme and the design and construction of a new apparatus of metric scale, will demonstrate CoQuake’s proof-of-principle and it will help to explore the transition from aseismic to seismic slip. CoQuake is an interdisciplinary project as it takes knowledge from various fields of engineering, computational mechanics, geomechanics, mathematics and geophysics. CoQuake opens a new field and new line of research in earthquake mechanics and engineering, with a direct impact on humanity and science.

Mots-clés : earthquake mechanics,soil dynamics
Projet ERC : CoQuake (Horizon 2020, appel 2017, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Products and processes engineering
Entité participante : Centrale Nantes — Pays : France — Rôle : PI
Acronyme de l'entité : ECN
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1357240.89 €

According to the Centre for Research on the Epidemiology of Disasters (CRED), earthquakes are responsible for more than half of the total human losses due to natural disasters from 1994 to 2003. There is no doubt that earthquakes are lethal and costly. CoQuake proposes an alternative, ground-breaking approach for avoiding catastrophic earthquakes by inducing them at a lower energetic level. Earthquakes are a natural phenomenon that we cannot avoid, but –for the first time– in CoQuake I will show that it is possible to control them, hence reducing the seismic risk, fatalities and economic cost. CoQuake goes beyond the state-of-the-art by proposing an innovative methodology for investigating the effect and the controllability of various stimulating techniques that can reactivate seismic faults. It involves large-scale, accurate simulations of fault systems based on constitutive laws derived from micromechanical, grain-by-grain simulations under Thermo-Hydro-Chemo-Mechanical couplings (THMC), which are not calibrated on the basis of ad-hoc empirical and inaccurate constitutive laws. A pioneer experimental research programme and the design and construction of a new apparatus of metric scale, will demonstrate CoQuake’s proof-of-principle and it will help to explore the transition from aseismic to seismic slip. CoQuake is an interdisciplinary project as it takes knowledge from various fields of engineering, computational mechanics, geomechanics, mathematics and geophysics. CoQuake opens a new field and new line of research in earthquake mechanics and engineering, with a direct impact on humanity and science.

Mots-clés : earthquake mechanics,soil dynamics
Projet ERC : CaLA (Horizon 2020, appel 2018, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Systems and communication engineering
Entité participante : University of Freiburg — Pays : Allemagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1999750.0 €

According to the World Health Organization more than 285 million people worldwide are visually impaired. In a world where graphics and online content (images, webpages) become increasingly important the inability to perceive information visually is the primary inhibitor for inclusion. In contrast to display technology for sighted people, tactile displays which translate text and graphics to touchable pixels (taxels) have seen little progress in recent decades. So-called Braille lines which display only a single line of text are still the norm. The reason why graphical tactile displays do not exist is the lack of a suitable actuator technology which allows generating massively parallelized individually addressable cost-effective taxel arrays. This ERC Consolidator project aims at a revolution in microactuator array technology with a fundamentally new concept termed the Capillary Lock Actuator (CaLA). CaLA is a novel bistable massively parallelizable microfluidic microactuator which overcomes many of the limitations currently associated with microactuators. It can be operated with low-voltage control signals and requires virtually no power for actuation. CaLA harnesses three concepts inherent to microfluidics: positive capillary pressure, segmented flow and controllable locally confined changes in wetting. The project will use CaLA actuator arrays for setting up the very first portable tactile graphic display with 30.000 individually addressable taxels thereby significantly outperforming the state-of-the-art. It will be based on manufacturing techniques for highly complex microstructures in glass invented by my group. CaLA will be a significant breakthrough in actuator technology and enabling for many applications in microsystem technology. Most importantly, it will be a significant step towards making the information technology inclusive for the visually impaired by providing the first robust cost-effective solution to large-scale tactile displays.

Mots-clés : microactuator,microfluidics,braille display,tactile display,bistable actuator,glass microstructuring,3d printingmanufacturing technology,smart materials,material engineering,polymer synthesis
Projet ERC : COLLEXISM (Horizon 2020, appel 2018, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Universe sciences
Entité participante : Université de Rennes — Pays : France — Rôle : PI
Acronyme de l'entité : UNIVRENNES
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1561804.34 €

Accurate determination of physical conditions of interstellar molecular clouds is a crucial step to better understand the life cycle of the interstellar matter and particularly the formation of stars and planets as well as the synthesis of organic molecules that may lead to emergence of life in the universe. A key parameter for the determination of these conditions from interstellar spectra is the calculation of accurate collisional rate coefficients of interstellar molecules with the most abundant species (H, He, H2 and e-). Whereas the knowledge of collisional processes has reached a certain level of maturity for collisions involving non-reactive molecules, very few reliable data exist for collisions involving reactive radicals and ions. The computation of such data is a real challenge since inelastic and reactive processes compete during collisions. In this project, we plan to overcome this complex problem and to provide collisional data for these radicals and ions in order to derive as much information as possible from the molecular spectra collected by current telescopes. As it is hardly possible to consider both collisional and reactive processes simultaneously, we will set up a new methodology based on quantum approach that allows obtaining accurate data. We will focus on molecular hydrides that are good candidates because of both their astrophysical importance and their quantum accessibility. We will carry out the determination of interaction potentials using quantum chemistry ab initio methods while the treatment of the dynamics of the nuclei will primarily be done using quantum time-independent reactive and non-reactive approaches. When exact quantum calculations will not be usable, innovative statistical quantum mechanical methods will also be explored. The new data will then be used in radiative transfer models and the predictions will be finally compared to observations in order to derive the abundances of reactive radicals with unprecedented accuracy.

Mots-clés : laboratory astrophysics,collisional rate coefficients,molecular abundances,radiative transfer
Projet ERC : RECEPIANCE (Horizon 2020, appel 2014, Advanced grants)
Domaine scientifique : Life Science
Panel : Molecules of Life: Biological Mechanisms, Structures and Functions
Entité participante : Max Planck Society — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : MPG
Type d'entité : Recherche
Financement ERC de l'entité : 2064583.0 €

Accurate segregation of the parental genome to the daughter cells during mitosis is essential for cell and organismal viability, protecting against cell death or cellular transformation. Kinetochores are crucial for accurate chromosome segregation because they link chromosomes to spindle microtubules. Kinetochores sprout from unique chromosomal loci named centromeres. In most eukaryotes, centromere specification does not rely on defined DNA sequences. Rather, centromere specification relies on epigenetic mechanisms, the most prominent of which is identified in the enrichment at centromeres of the histone H3 variant CENP-A. Deposition of new CENP-A at every cell cycle is vital for centromere maintenance through cell division. RECEPIANCE aims to dissect the molecular mechanism of CENP-A deposition through reductionist approach based on two main pillars, biochemical reconstitution and structural analysis. The CENP-A deposition machinery consists of chromatin-remodelling factors, histone chaperones, and accessory factors, including the Mis18 complex, HJURP, RbAb46/48, the FACT complex, RSF, CHD1, and additional currently less characterized proteins. The CENP-A deposition machinery is recruited to centromeres in a cell cycle-regulated manner by inner kinetochore proteins associated with CENP-A, most notably CENP-C. The hypothesis inspiring this proposal is that the CENP-A deposition machinery operates on a unit containing at least one CENP-A nucleosome and a neighboring canonical H3 nucleosome, with the latter being the target for exchange with new CENP-A. Our ability to reconstitute the centromere-inner kinetochore interface puts us in an ideal position to study how the CENP-A deposition machinery is recruited to centromeres in vitro, dissecting the crucial binding interfaces and studying them biochemically and structurally. The ultimate goal of RECEPIANCE is to reconstitute the ATP-dependent exchange of H3 with CENP-A in vitro exclusively with recombinant proteins.

Mots-clés : centromere,kinetochore,constitutive centromere associated network,ccan,mis12,ndc80,cenp a,nucleosome,epigenetics,cenp c,chromatin,fact,chd1,chromatin remodelling