Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : EIRENE (Horizon 2020, appel 2016, Advanced grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The study of the human past
Entité participante : University of Ljubljana — Pays : Slovénie — Rôle : PI
Acronyme de l'entité : UL
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2266067.0 €

The EIRENE project’s purpose is to think afresh 20th-century post-war transitions by taking into account a gendered perspective. Namely, the historiographic consideration of gender thoroughly alters the understanding of social dynamics in multi-ethnic areas during the post-war transitions. They will be observed in the North-Eastern Adriatic region, an overlooked European space, marked by border redefinitions, changes of political systems, and high interethnic conflict intensity, but also by genuine cooperation among ethnic groups. The region has all the qualities of a “laboratory environment” for the study of gender positions and interrelations after World Wars I and II and after the Yugoslav wars in the 1990s. The project will differ substantially from previous attempts to analyse post-war transitions in these aspects: a) longitudinal approach, comparing three post-war periods in order to detect their specifics and (dis)continuities; b) transnational approach, by overcoming nation-centric frameworks of analysis; c) by combining conceptual political and social sciences with historiography; and finally, d) by examining post-war transitions through the prism of gender. Focusing on four research-fields (politics, political violence, work, family), the project will validate innovative analytical concepts of the “inclusion-exclusion paradox” of women in post-war transitions, and women as “cross-boundary mediators”. Within the category of gender, focal attention will be given to women as they are often invisible in historical accounts and remain neglected in historicizing. By aggregating empirical sources, the project will approach the proposed subject matter by investigating the processes of identification across the lines of ethnic origin, class, generations, marital status, profession/occupation, language of use, migratory processes, etc. The project’s added value is its novel conceptual applicability to other comparable geopolitical areas.

Mots-clés : post war transition,gender,transnational history,north eastern adriatic,20th century
Projet ERC : THEMIS (Horizon 2020, appel 2016, Proof of concept grants)
Entité participante : University of Leeds — Pays : Royaume-Uni — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 149580.0 €

The ERC Advanced grant ‘TOSCA’ (grant number: 247375) focussed on the development of terahertz (THz) frequency science and technology, and in particular, investigated the electronic and photonic engineering of THz quantum cascade lasers (QCLs), and the underlying physics of these sophisticated devices. This Proof of Concept grant (THEMIS) builds on this pioneering research, and in particular on our breakthrough developments in QCL self-mixing imaging. We will increase the technology readiness level of the patented optical-bench-based THz QCL systems developed under ‘TOSCA’, and develop a demonstrator suitable for translation of this technology to industrial end-users. The focus is on delivering a compact, inexpensive, THz frequency imaging system, which exploits self-mixing technology to deliver amplitude- and phase-resolved images whilst dispensing with an external detector. Specific objectives are to: construct a compact and robust optical-breadboard-based self-mixing system; demonstrate the technology outside the laboratory environment, both in the field with commercial end-users, and at conferences/workshops/trade shows; and, evaluate opportunities for THz self-mixing imaging, identifying end-user applications. To achieve this, we will engineer our current optical-bench-based technology onto a robust and compact optical breadboard with a cryogen-free cooler, and develop integrated ‘plug-and-play’ electronics and software for image reconstruction. The complete system will be suitable for transport to commercial partners, allowing demonstration and evaluation of the technology. Furthermore, we will incorporate a near-field microscopy capability, enabling sub-micron THz imaging – more than 100 times smaller than the THz free-space wavelength. By the end of the programme, we will have identified an exploitation path by liaising directly with THz instrument manufacturers and with at least one targeted end-user

Mots-clés : terahertz,quantum cascade lasers,self mixing imaging
Projet ERC : SOLACYLIN (Horizon 2020, appel 2014, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Synthetic Chemistry and Materials
Entité participante : University of Erlangen-Nuremberg — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : FAU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1938655.0 €

The ERC Consolidator Grant project SOLACYLIN aims at providing experimental insight into the function of 'third-generation' photovoltaic systems by generating materials stacks structured in a well-defined, accurately tunable, nanocylindrical geometry. To this goal, we will develop and exploit advanced preparative methods based on two fundamental ingredients: (a) ordered 'anodic' porous oxides and (b) atomic layer deposition (ALD). The former solids will be generated as templates providing ordered arrays of straight, cyclindrical pores, the diameter and length of which can be varied between 20 nm and 300 nm and between 0.5 microns and 50 microns, respectively. The latter method will be used to coat the inner pore walls with one or several layers of the photovoltaic stack, each with a thickness set to values chosen between 1 nm and 30 nm. We will invent and characterize novel surface reaction schemes for the deposition in ALD mode (from the gas phase and from solutions) of functional materials (doped semiconductors and intrinsic light absorbers) with tailored chemical and physical properties. We will investigate the experimental conditions in which they can be combined in a way that optimizes the quality of their interfaces. Finally, we will quantify the electrical and photovoltaic performance of p-i-n junctions prepared with our methods. We will have the unique capability of describing in a systematic, accurate manner how the experimental photovoltaic parameters depend on the individual thicknesses of the individual layers and on the length of the cylinders. This direct experimental handle on the amount of light absorbed, on the one hand, and the charge carrier transport distances to the electrical contacts, on the other hand, will be correlated with the relevant material parameters (absorption coefficients, carrier mobilities). This information will unveil the phenomena limiting the efficiency of each type of solar cell, and suggest avenues to remedy them.
Projet ERC : iEBDD (Horizon 2020, appel 2016, Proof of concept grants)
Entité participante : University of Edinburgh — Pays : Royaume-Uni — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 119326.0 €

The ERC project EBDD was funded to bring about a new generation of computer algorithms to implement accurate molecular simulations of biomolecules and their interactions with man-made molecules that are potential new therapeutics. First results from the EBDD project (ERC-StG-2013-336289) indicate the ground-breaking potential of the academic software generated for supporting pre-clinical drug discovery R&D in the pharmaceutical and biotech sectors. Building on these early results from the EBDD project, this proposal aims to prototype an innovative interactive human-computer drug design workflow that will enhance the value of the academic software, and enable new types of R&D processes (hit discovery, hit-to-lead and lead-optimisation) in a preclinical drug discovery environment. To be commercially viable the prototype must be equipped with an intuitive and robust graphical user interface to enable high quality 3D data visualisation, and that also enable real-time user interactions with large-scale computer simulations executed on remote high-performance computing resources. The computer simulation protocols need to be standardised for ease of use by non-experts, and validated for robustness on industry benchmarks. The prototype will developed in partnership with a professional software SME specialised in interactive scientific data visualization, and a large EU biopharmaceutical company that will test multiple versions of the prototype and feedback on improvements over current processes. This close collaboration with the software SME and pharmaceutical companies will ensure that the resulting prototype will be of high value, meets industry standards, and is ready for commercialisation.

Mots-clés : molecular simulations,computer aided drug design,pre clinical drug discovery,user interface,software
Projet ERC : ARTIV1 (Horizon 2020, appel 2016, 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 : 136395.0 €

The ERC starting grant GECOMETHODS, on which this POC is based, tackled problems of diffusion equations via geometric control methods. One of the most striking achievements of the project has been the development of an algorithm of image reconstruction based mainly on non-isotropic diffusion. This algorithm is bio-mimetic in the sense that it replicates the way in which the primary visual cortex V1 of mammals processes the signals arriving from the eyes. It has performances that are at the state of the art in image processing. These results together with others obtained in the ERC project show that image processing algorithms based on the functional architecture of V1 can go very far. However, the exceptional performances of the primary visual cortex V1 rely not only on the particular algorithm used, but also on the fact that such algorithm “runs” on a dedicated hardware having the following features: 1. an exceptional level of parallelism; 2. connections that are well adapted to transmit information in a non-isotropic way as it is required by the algorithms of image reconstruction and recognition. The idea of this POC is to create a dedicated hardware (called ARTIV1) emulating the functional architecture of V1 and hence having on one hand a huge degree of parallelism and on the other hand connections among the CPUs that reflect the non-isotropic structure of the visual cortex V1. Such a hardware that we plan to build as an integrated circuit with an industrial partner will be a veritable artificial visual cortex. It will be fully programmable and it will be able to perform many biomimetic image processing tasks that we expect to be exceptionally performant. ARTIV1 will come to the marked accompanied by some dedicated software for image reconstruction and image recognition. However we expect that other applications will be developed by customers, as for instance softwares for optical flow estimation or for sound processing.

Mots-clés : sub riemannian geometry,artificial visual cortex,image processing,image reconstruction,image recognition,fpga,asic
Projet ERC : UltimateMembranes (Horizon 2020, appel 2018, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Products and processes engineering
Entité participante : Board of the Swiss Federal Institutes of Technology — Pays : Suisse — Rôle : PI
Acronyme de l'entité : ETH Zurich
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1875000.0 €

The EU integrated strategic energy technology plan, SET-plan, in its 2016 progress report, has called for urgent measures on the carbon capture, however, the high energy-penalty and environmental issues related to the conventional capture process (amine-based scrubbing) has been a major bottleneck. High-performance membranes can reduce the energy penalty for the capture, are environment-friendly (no chemical is used, no waste is generated), can intensify chemical processes, and can be employed for the capture in a decentralized fashion. However, a technological breakthrough is needed to realize such chemically and thermally stable, high-performance membranes. This project seeks to develop the ultimate high-performance membranes for H2/CO2 (pre-combustion capture), CO2/N2 (post-combustion capture), and CO2/CH4 separations (natural gas sweetening). Based on calculations, these membranes will yield a gigantic gas permeance (1 and 0.1 million GPU for the H2 and the CO2 selective membranes, respectively), 1000 and 10-fold higher than that of the state-of-the-art polymeric and nanoporous membranes, respectively, reducing capital expenditure per unit performance and the needed membrane area. For this, we introduce three novel concepts, combining the top-down and the bottom-up crystal engineering approaches to develop size-selective, chemically and thermally stable, nanoporous two-dimensional membranes. First, exfoliated nanoporous 2d nanosheets will be stitched in-plane to synthesize the truly-2d membranes. Second, metal-organic frameworks will be confined across a nanoporous 2d matrix to prepare a composite 2d membrane. Third, atom-thick graphene films with tunable, uniform and size-selective nanopores will be crystallized using a novel thermodynamic equilibrium between the lattice growth and etching. Overall, the innovative concepts developed here will open up several frontiers on the synthesis of high-performance membranes for a wide-range of separation processes.

Mots-clés : two dimensional membranes,carbon capture,crystal engineering,gas separation,exfoliation,top down synthesis,bottom up synthesis,metal organic frameworks,graphene,chemical vapor deposition
Projet ERC : CoCEAL (Horizon 2020, appel 2015, Advanced grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Institutions, Governance and Legal Systems
Entité participante : University of Rome Tor Vergata — Pays : Italie — Rôle : Partner
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 403440.14 €

The European dimension of administrative law is the focus of a flurry of initiatives aiming to investigate similarities and differences, and to shape common legal scenarios. A codification of the administrative procedures of the EU has been envisaged by the European Parliament in its resolution of February 2013. A broader proposal of codification, including rule-making and contractual procedures, has been elaborated by ReNEUAL and has been discussed in a series of workshops in 2015. The issues that arise are both practical and theoretical: - it is important to understand whether the method traditionally followed by the European Court of Justice in order to identify the principles that are general and common to national legal systems, only applies when all those systems recognize such principles; - whether national systems of public law share the same idea of what an administrative procedure is is another question; whether the specific principles governing administrative procedures, such as the right to be heard and the duty to give reasons, are the same is still another question; - finally, if any commonality exists, the question that arises is whether it is limited to the level of general principles of law or it includes the which govern procedures. The research project is innovative on grounds of method, because: - it aims at ascertaining whether, and the extent to that, the well-established methodology developed under the ‘Common Core of European Private Law’ project can be applied to EU administrative law; - it permits to distinguish between ‘operative rules’, ‘descriptive formants’, and ‘meta-legal formants’; - it also allows to understand whether the specific nature of the interests recognized and protected by the rules of public law require legal methodologies that are distinct and distant from those of private law.

Mots-clés : administrative law,comparative public law,administrative procedures
Projet ERC : RESPONDER (Horizon 2020, appel 2015, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Earth system science
Entité participante : Aberystwyth University — Pays : Royaume-Uni — Rôle : Partner
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 824645.0 €

The Greenland Ice Sheet is losing mass at a growing rate and has since 2010 caused sea level rise of 1 mm/year. The most severe changes occur in the drainage basins of marine-terminating glaciers, which flow rapidly and drain 88% of the ice sheet. The latest report by the Intergovernmental Panel on Climate Change concluded that the widespread acceleration of these glaciers in recent years was a response to interaction with the ocean and unrelated to basal lubrication of ice flow; yet, observations have since shown that many of these glaciers respond to the growing volume of surface meltwater, which reaches the bed when surface lakes drain. This basal lubrication mechanism is unknown, but exhibits contrasting control on ice flow at the coast and in the interior where surface melting increasingly forms lakes. This lack of vital knowledge is a major source of uncertainty in the current generation of ice sheet models used to predict sea level change. The fundamental goal of RESPONDER is to understand how hydrological networks at the base of the Greenland Ice Sheet evolve over seasons and over multiple years, and how this evolution impacts on ice flow in the interior and at the coast. The project has the following aims: AIM 1 is to identify glaciological ‘hotspots’ and sites for subglacial access drilling and borehole exploration by tracking hydrological pathways beneath Store Glacier, a large marine-terminating glacier in Uummannaq Fjord, using novel geophysical imaging techniques and unmanned aerial vehicles (UAVs). AIM 2 is to observe and quantify the hydrological networks of Store Glacier while measuring basal slip and strain within ice with probes and sensors installed in boreholes drilled at ‘coastal’ and ‘interior’ targets. AIM 3 is to predict the co-evolution of ice flow and hydrological networks in the Store Glacier drainage basin, and assess the vulnerability of the Greenland Ice Sheet, by integrating field observations in state-of-the-art ice sheet models.

Mots-clés : greenland,ice sheet,rapid dynamics,hydrology,climate change
Projet ERC : Grenadyn (Horizon 2020, appel 2020, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Condensed matter physics
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 : 2462587.0 €

The Grenadyn project will demonstrate that assemblies of imperfect, dynamical nanodevices can self-learn through physical principles, like biological neurons and synapses do, with performance comparable to the best artificial intelligence (AI) algorithms. For this, Grenadyn’s networks will minimize their effective energy together with the recognition error when learning. The starting point of Grenadyn is an algorithm called Equilibrium Propagation, developed by AI pioneer Yoshua Bengio, that takes its roots in physics. We will assemble memristive as well as spintronic nanocomponents in neural networks that perform pattern recognition through Equilibrium Propagation. We will show that these dynamical networks learn by nudging their outputs towards the desired solution through a spring-like force, and letting nano-synapses and neurons reorganize themselves towards equilibrium. We will show that they can also learn directly from the data, without supervision. We will induce a high resilience to imperfections in these networks through self-adaptation and digitization. We will demonstrate by experiments and simulations that our physical neural networks made of variable elements compute with an accuracy similar to software neural networks trained with backpropagation. We will produce a chip integrating nanosynaptic devices on CMOS and achieve state-of-the-art recognition rates on AI image benchmarks. We will enhance the network functionalities by leveraging their dynamical properties through synchronization and time-delayed feedback. Finally, we extend Grenadyn’s in-materio self-learning to any assembly of coupled dynamical nanodevices, providing novel horizons for multifunctional materials and devices. Grenadyn’s scientific advances in condensed-matter physics, non-linear dynamics, electronics, and AI will give the foundations for deep network chips that contain billions of nano-synapses and nano-neurons and self-learn with state-of-the-art accuracy.

Mots-clés : memristors,neuromorphic computing,artificial intelligence
Projet ERC : HIV ECLIPSE (Horizon 2020, appel 2017, Starting grants)
Domaine scientifique : Life Science
Panel : Immunity, Infection and Immunotherapy
Entité participante : University of London — Pays : Royaume-Uni — Rôle : Partner
Acronyme de l'entité : U. London
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 810531.0 €

The HIV eclipse phase typically refers to the time between a virus entering a sexually exposed person and detection of viral RNA in their plasma. Of the four phases of HIV-1 infection (eclipse, acute, chronic and AIDS), the eclipse phase is currently the only window of opportunity for viral clearance. Systemic infection is currently irreversible after the onset of the acute phase. Preventing systemic HIV infection after exposure, therefore, requires understanding and targeting the eclipse phase. Information on this phase, however, is partial and indirect, with fundamental gaps in our knowledge of its role in limiting transmission, in determining the efficacy of infection control strategies, and in governing later infection. Mathematical modelling, when combined with statistical inference, is a useful tool for hypothesis testing and prediction using incomplete information. To date, however, there are no mathematical models that are particularly suitable because current models do not account for two important characteristics of eclipse phase infection. First, none of these models reconcile the very small per-exposure HIV-1 acquisition probability with the high estimate of the basic reproductive number, R0, during acute phase infection. Second, models of acute phase plasma viral load obscure early local dynamics of HIV when the virus forms local, heterogeneous clusters of infection in the genital mucosa before entering the lymphatic and blood systems. My research programme will develop novel models of HIV that are calibrated to diverse data sources to ascertain whether eclipse phase dynamics determine the acquisition of HIV and later infection dynamics. I will use phylogenetic analysis of HIV samples to quantify the role of the transmitting partner in determining viral inoculum dose size, eclipse phase dynamics and HIV acquisition. This research will generate testable predictions for exposed populations and aim to propose novel methods for infection prevention.