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 : University of Cambridge — Pays : Royaume-Uni — Rôle : Partner
Acronyme de l'entité : U. Cambridge
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 0.0 €

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 : CatDT (Horizon 2020, appel 2017, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Mathematics
Entité participante : University of Glasgow — Pays : Royaume-Uni — Rôle : Partner
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 17663.46 €

According to string theory, coherent sheaves on three-dimensional Calabi-Yau spaces encode fundamental properties of the universe. On the other hand, they have a purely mathematical definition. We will develop and use the new field of categorified Donaldson-Thomas (DT) theory, which counts these objects. Via the powerful perspective of noncommutative algebraic geometry, this theory has found application in recent years in a wide variety of contexts, far from classical algebraic geometry. Categorification has proved tremendously powerful across mathematics, for example the entire subject of algebraic topology was started by the categorification of Betti numbers. The categorification of DT theory leads to the replacement of the numbers of DT theory by vector spaces, of which these numbers are the dimensions. In the area of categorified DT theory we have been able to prove fundamental conjectures upgrading the famous wall crossing formula and integrality conjecture in noncommutative algebraic geometry. The first three projects involve applications of the resulting new subject: 1. Complete the categorification of quantum cluster algebras, proving the strong positivity conjecture. 2. Use cohomological DT theory to prove the outstanding conjectures in the nonabelian Hodge theory of Riemann surfaces, and the subject of Higgs bundles. 3. Prove the comparison conjecture, realising the study of Yangian quantum groups and the geometric representation theory around them as a special case of DT theory. The final objective involves coming full circle, and applying our recent advances in noncommutative DT theory to the original theory that united string theory with algebraic geometry: 4. Develop a generalised theory of categorified DT theory extending our results in noncommutative DT theory, proving the integrality conjecture for categories of coherent sheaves on Calabi-Yau 3-folds.
Projet ERC : PULTAR (Horizon 2020, appel 2014, Proof of concept grants)
Entité participante : University of Glasgow — Pays : Royaume-Uni — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 149791.0 €

According to the WHO 235 million people suffer from asthma and 64M people have chronic obstructive pulmonary disease, leading to 3M deaths per year worldwide. The cost of treating patients with all forms of lung disease is ~ €380B p.a., leading to the loss of >50M DALYS. Generally, patients with such respiratory diseases are treated by inhalation of medicines within aerosols, where the therapy (including medicine or biologics used in gene therapy) can be targeted directly to the lung. The accepted wisdom is that such pulmonary delivery requires aerosol droplet sizes of between 1 and 5 μm. We have now shown that by using a new ultrasonic technology, we can create monodisperse aerosol droplets, which could be used for therapeutic delivery of medicines, genes and RNA to specific regions in the lungs. In one strand of the work we aim to demonstrate that this precise nebulisation technology improves the efficacy of treatment through enhanced drug uptake. In a second strand, we will demonstrate selective targeting of different tissue types in the lungs. For example, the epithelium in cystic fibrosis patients is currently extremely difficult to access leading to limitations in the amount and quality of data obtained for pre-clinical and clinical gene therapies. Similarly, targeting vascular cells is an appealing treatment for patients with pulmonary arterial hypertension, although, again, effective delivery necessitates that the therapeutic system transits defined and substantial anatomical barriers. The overall aim is to demonstrate that this new technology can define routes to new therapies, improve clinical outcomes and reduce healthcare costs. To achieve this we will develop a prototype nebuliser based upon proprietary technology and show that different medicines and gene therapies can be delivered effectively to the lungs of a model mouse. We will also start to build a commercial team and work closely with industry to deliver impact and innovation to the market.
Projet ERC : FREEDLES (Horizon 2020, appel 2017, Consolidator grants)
Domaine scientifique : Life Science
Panel : Biotechnology and Biosystems Engineering
Entité participante : Aalto University — Pays : Finlande — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1963590.0 €

Accounting for vegetation structure – clumping of foliage into shoots or crowns – is the largest remaining challenge in modelling scattered and absorbed radiation in complex vegetation canopies such as forests. Clumping controls the radiation regime of forest canopies, yet it is poorly quantified. Currently, the communities working with vegetation structure and optical measurements do not have a common understanding of the concept. The FREEDLES project sets out to develop a universal method for quantifying clumping of foliage in forests based on detailed 3D structure and spectral reflectance data. Clumping will be linked to photon recollision probability, an exciting new development in the field of photon transport modelling. Photon recollision probability will, in turn, be used to develop a spectral scaling algorithm which will connect the spectra of vegetation at all hierarchical levels from needles and leaves to crowns, stands and landscapes. The spectral scaling algorithm will be validated with detailed reference measurements in both laboratory and natural conditions, and applied to interpret forest variables from satellite images at different spatial resolutions. The proposed approach is contrary to many other lines of current development where more complexity is favoured in canopy radiation models. If successful, the approach will significantly improve estimates of absorbed and scattered radiation fields in forests and retrieval results of forest biophysical variables from satellite data. Future applications can also be expected in global radiation and carbon balance estimation and in chlorophyll fluorescence models for forests. Most importantly, the spectral scaling model will open new horizons for our scientific understanding of photon-vegetation interactions.

Mots-clés : forest,canopy,coniferous,radiation regime,clumping,remote sensing,recollision probability,spectral invariants
Projet ERC : UV-LASE (Horizon 2020, appel 2019, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Systems and communication engineering
Entité participante : Chalmers University of Technology — Pays : Suède — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1996276.0 €

Achieving ultraviolet (UV) emission has proven to be difficult, in particular for microcavity lasers due to high optical losses and defect densities. Our group, with a world-leading position in microcavity laser research, has identified new possibilities to combat these challenges in both ultraviolet and blue-emitting devices. By using these breakthroughs, we aim to develop the first electrically injected blue microcavity laser with good enough performance to be useful in real-world applications and project out of the blue and into the ultraviolet to realize the very first electrically injected UV microcavity laser. Our two recent breakthroughs are: 1. The discovery of an overlooked loss mechanism in microcavities and schemes to circumvent it. Our proposed designs to circumvent this unintentional anti-guiding are being implemented worldwide and have led to a tenfold increase in optical output power in blue lasers. 2. A unique membrane technique to enable microcavity lasers with highly reflective dielectric mirrors on both sides of the cavity – a device concept previously un-realizable for UV-lasers. The method is based upon electrochemical etching of the chemically inert material AlGaN (the material of choice for UV), which enables lift-off of device membranes with smooth surfaces from the substrate and mirror-deposition on the bottom side. Our recent demonstration of the world’s first thin-film, flip-chip UV-B LED with this technique holds great promises for microcavity lasers. These two new approaches will be combined with a focused effort to circumvent the problem of low electrical conductivity of p-doped materials. We will strengthen our capabilities by developing tunnel junctions, allowing highly conductive n-doped material to be used throughout virtually the entire laser. This will drastically reduce losses, which cause degradation within minutes in blue microcavity lasers, and might be the only solution to electrically driven UV microcavity lasers.

Mots-clés : vcsel algan ultraviolet blue gan  vertical cavity surface emitting laser,electrochemical etching  uvb microcavity laser  optical guiding  antiguiding  tunnel junction
Projet ERC : HOLOMAN (Horizon 2020, appel 2017, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Products and processes engineering
Entité participante : Heidelberg University — Pays : Allemagne — Rôle : Partner
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 625000.0 €

Acoustic waves exert forces when they interact with matter. Sound, and in particular ultrasound, which has a wavelength of a few hundred microns in water, is a benign and versatile tool, that has been successfully used to manipulate, trap and levitate microparticles and cells. The acoustic contrast between the material and the medium, and the spatial variation of the ultrasound field determine the interaction. Resonators and arrays of a few hundred transducers have thus far been used to generate the sound fields, but the former only yields highly symmetrical pressure patterns, and the latter cannot be scaled to achieve complex fields. Our radically new approach uses a finely contoured 3D printed acoustic hologram to generate pressure fields with orders of magnitude higher complexity than what has been possible to date. The acoustic hologram technology is a route towards truly sophisticated and 3D sound fields. This project will research the necessary computational and experimental tools to generate designed 3D ultrasound fields. We will investigate ways to use acoustic holograms for rapid manufacturing, the controlled manipulation of microrobots, and the assembly of cells. The 3D pressure fields promise the assembly and fabrication of an entire 3D object in “one shot”, something that has not been realized to date. We will also study the formation of 3D cellular assemblies, and more realistic 3D tumour models. This project will develop the technology, materials, processes, and understanding needed for the generation and use of sophisticated 3D ultrasound fields, which opens up entirely new possibilities in physical acoustics and the manipulation of matter with sound.

Mots-clés : holography,directed assembly,rapid 3d fabrication,cells
Projet ERC : HOLOMAN (Horizon 2020, appel 2017, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Products and processes engineering
Entité participante : Max Planck Society — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : MPG
Type d'entité : Recherche
Financement ERC de l'entité : 1432625.0 €

Acoustic waves exert forces when they interact with matter. Sound, and in particular ultrasound, which has a wavelength of a few hundred microns in water, is a benign and versatile tool, that has been successfully used to manipulate, trap and levitate microparticles and cells. The acoustic contrast between the material and the medium, and the spatial variation of the ultrasound field determine the interaction. Resonators and arrays of a few hundred transducers have thus far been used to generate the sound fields, but the former only yields highly symmetrical pressure patterns, and the latter cannot be scaled to achieve complex fields. Our radically new approach uses a finely contoured 3D printed acoustic hologram to generate pressure fields with orders of magnitude higher complexity than what has been possible to date. The acoustic hologram technology is a route towards truly sophisticated and 3D sound fields. This project will research the necessary computational and experimental tools to generate designed 3D ultrasound fields. We will investigate ways to use acoustic holograms for rapid manufacturing, the controlled manipulation of microrobots, and the assembly of cells. The 3D pressure fields promise the assembly and fabrication of an entire 3D object in “one shot”, something that has not been realized to date. We will also study the formation of 3D cellular assemblies, and more realistic 3D tumour models. This project will develop the technology, materials, processes, and understanding needed for the generation and use of sophisticated 3D ultrasound fields, which opens up entirely new possibilities in physical acoustics and the manipulation of matter with sound.

Mots-clés : holography,directed assembly,rapid 3d fabrication,cells
Projet ERC : PHOCCS (Horizon 2020, appel 2014, Proof of concept grants)
Entité participante : Centre national de la recherche scientifique — Pays : France — Rôle : PI
Acronyme de l'entité : CNRS
Type d'entité : Recherche
Financement ERC de l'entité : 149984.0 €

Across Europe, nearly 250,000 people die every year of sepsis, a severe bloodstream infection. Detecting molecular biomarkers indicative of bacterial infection within a limited time is vital to enable targeted antibiotics therapy, limit the risk of antimicrobial resistance and reduce hospitalization costs. The key to success to fight sepsis is a fast detection technology that avoids the need for nucleic acid amplification processes and circumvents the limitations of fluorescence labelling. The PHOCCS project aims at exploiting novel concepts based on PHOton Cross Correlation Spectroscopy to develop a breakthrough platform for ultra-sensitive detection of DNA biomolecules and assess its transferability into the large molecular diagnostics market. With its unique technology based on dynamic light scattering of noble metal nanoparticles, PHOCCS has several key advantages to enable commercial success: it is fast, quantitative, sensitive, specific and simple to operate. Based upon original and patented intellectual property, PHOCCS is fully targeted to the development of a disruptive technology fundamental in strategic applications of molecular diagnostics to fulfil the industrial market needs. The PHOCCS project will bring the technology to a pre-demonstration stage for DNA sensing to strengthen the commercialization and licensing opportunities.

Mots-clés : biosensing,nanoparticles,light scattering,biophotonics
Projet ERC : ANewSpike (Horizon 2020, appel 2019, Consolidator grants)
Domaine scientifique : Life Science
Panel : Neuroscience and Disorders of the Nervous System
Entité participante : Humboldt-Universität zu Berlin — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : HU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2000000.0 €

Action potentials are not all equal. Despite shared biophysical principles and even similar action-potential shape, neurons with different spike generators can encode vastly different aspects of a stimulus and result in radically different behaviors of the embedding network. Differences between spike generators may be hard to discern because the information content of a spike train is not obvious to the naked eye. This is where computational analysis comes into play: theoretical research has shown that spike generation can be classified into a few dynamical types with qualitatively distinct computational properties. Among these, so-called homoclinic spikes – unlike the other commonly considered types – have been largely ignored. Yet, homoclinic spike generators are special because only they react with high sensitivity to inputs during the refractory period. Indeed, it is directly after a spike when homoclinic spikers “listen” best. As we recently demonstrated, this unique property has computationally exciting consequences: it can provoke a dramatic increase in network synchronization in response to minimal changes in physiological parameters, without requiring alterations in synaptic strength or connectivity. Supported by in-vitro evidence for homoclinic spiking in the rodent brain, ANewSpike explores the intriguing hypothesis that this “forgotten“ spike generator provides a unifying framework for the induction of epileptic activity by a wide range of physiological trigger parameters, from temperature to energy deprivation. Using a theory-experiment approach, we explore (i) the prevalence of homoclinic spiking in the brain, (ii) its ability to promote the transmission of high frequencies, and (iii) its ability to boost network synchronization. Our multi-scale study aims to add a novel dimension to our understanding of neural dynamics at the cellular and network level by revealing homoclinic spiking as an integral part of brain dynamics in both health and pathology.

Mots-clés : biophysical neuron models,nonlinear dynamics,network synchronisation,action potential,phase response curve,phase oscillator,dynamic clamp
Projet ERC : ADSNeSP (Horizon 2020, appel 2016, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Condensed matter physics
Entité participante : University of Cambridge — Pays : Royaume-Uni — Rôle : PI
Acronyme de l'entité : U. Cambridge
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2043630.0 €

Active Matter systems, such as self-propelled colloids, violate time-reversal symmetry by producing entropy locally, typically converting fuel into mechanical motion at the particle scale. Other driven systems instead produce entropy because of global forcing by external fields, or boundary conditions that impose macroscopic fluxes (such as the momentum flux across a fluid sheared between moving parallel walls). Nonequilibrium statistical physics (NeSP) is the basic toolbox for both classes of system. In recent years, much progress in NeSP has stemmed from bottom-up work on driven systems. This has provided a number of exactly solved benchmark models, and extended approximation techniques to address driven non-ergodic systems, such as sheared glasses. Meanwhile, work on fluctuation theorems and stochastic thermodynamics have created profound, model-independent insights into dynamics far from equilibrium. More recently, the field of Active Matter has moved forward rapidly, leaving in its wake a series of generic and profound NeSP questions that now need answers: When is time-reversal symmetry, broken at the microscale, restored by coarse-graining? If it is restored, is an effective thermodynamic description is possible? How different is an active system's behaviour from a globally forced one? ADSNeSP aims to distil from recent Active Matter research such fundamental questions; answer them first in the context of specific models and second in more general terms; and then, using the tools and insights gained, shed new light on longstanding problems in the wider class of driven systems. I believe these new tools and insights will be substantial, because local activity takes systems far from equilibrium in a conceptually distinct direction from most types of global driving. By focusing on general principles and on simple models of activity, I seek to create a new vantage point that can inform, and potentially transform, wider areas of statistical physics.