Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : Preprint (Horizon 2020, appel 2020, Proof of concept grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Systems and communication engineering
Entité participante : University of Pisa — Pays : Italie — Rôle : PI
Acronyme de l'entité : UniPi
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 52000.0 €

The aim of the PREPRINT project is to obtain the much-needed improvement in terms of resolution of materials printers, in order to achieve the far-reaching goal of fabricating integrated circuits with Large Scale of Integration (LSI, i.e., thousands of transistors, the same level of integration of the first INTEL microprocessors) in printed electronic systems on wearable/flexible substrates. The number of transistors on a substrate is mainly determined by the resolution of the printing machines, which, today, is at most of the order of tens of micrometres. The PI has successfully demonstrated within the PEP2D project (Contract No. 770047) that printed devices and simple circuits on flexible substrate as paper can be obtained with outstanding performance, while leveraging the exceptional electrical and mechanical properties of two-dimensional materials. Being able to pack thousands of these devices on the same substrate would path the way towards the realization of systems with improved performance and capabilities, while unleashing the full potential of printable and flexible electronics on a wide range of applications (from bio, to smart patches, anticounterfeiting, lab-on-a-chip, just to cite few). A step-forward in this direction has already been done by the PI through the demonstration of a material printer prototype with resolutions better (i.e., few micrometres) than those available in the market. Within the PREPRINT project, the technical and economic viability of obtaining printing resolution smaller than 1 micrometre will be explored: it is our belief that such a goal is at reach, while boosting the performance of the fabricated prototype, which will allow us to compete and early enter the fast-growing market of printable electronics and material printers.

Mots-clés : printable electronics,2d materials,wearable electronics
Projet ERC : Preprint (Horizon 2020, appel 2020, Proof of concept grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Systems and communication engineering
Entité participante : Quantavis srl — Pays : Italie — Rôle : Partner
Acronyme de l'entité : Quantavis
Type d'entité : Organismes privés (hors enseignement)
Financement ERC de l'entité : 98000.0 €

The aim of the PREPRINT project is to obtain the much-needed improvement in terms of resolution of materials printers, in order to achieve the far-reaching goal of fabricating integrated circuits with Large Scale of Integration (LSI, i.e., thousands of transistors, the same level of integration of the first INTEL microprocessors) in printed electronic systems on wearable/flexible substrates. The number of transistors on a substrate is mainly determined by the resolution of the printing machines, which, today, is at most of the order of tens of micrometres. The PI has successfully demonstrated within the PEP2D project (Contract No. 770047) that printed devices and simple circuits on flexible substrate as paper can be obtained with outstanding performance, while leveraging the exceptional electrical and mechanical properties of two-dimensional materials. Being able to pack thousands of these devices on the same substrate would path the way towards the realization of systems with improved performance and capabilities, while unleashing the full potential of printable and flexible electronics on a wide range of applications (from bio, to smart patches, anticounterfeiting, lab-on-a-chip, just to cite few). A step-forward in this direction has already been done by the PI through the demonstration of a material printer prototype with resolutions better (i.e., few micrometres) than those available in the market. Within the PREPRINT project, the technical and economic viability of obtaining printing resolution smaller than 1 micrometre will be explored: it is our belief that such a goal is at reach, while boosting the performance of the fabricated prototype, which will allow us to compete and early enter the fast-growing market of printable electronics and material printers.

Mots-clés : printable electronics,2d materials,wearable electronics
Projet ERC : Sequence Barcodes (Horizon 2020, appel 2015, 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 : 149784.0 €

The aim of the project Sequence Barcodes will be to study the market potential of sequence-encoded oligomers developed and patented in the frame of the ERC starting grant project SEQUENCES (grant agreement n°258593, End-date: October 2014). In particular, we propose to use monodisperse oligomers with defined chain-lengths and monomer sequences as molecular barcodes for product identification. A code can be written in the oligomers using different monomers as an alphabet, for example using two (i.e. binary code), three, four or more monomers. The barcodes can also be read using sequencing techniques such as tandem mass spectrometry and nanopore sequencing. All the fundamental knowledge for preparing and sequencing these polymers has been identified in the frame of the project SEQUENCES and is available for a technological transfer to industry. Moreover, these synthetic polymers possess valuable advantages over DNA, which is often used in product identification technologies. Indeed, they are much simpler to synthesize and to use than natural biomacromolecules. Perhaps more importantly, our chemistry is very versatile and the molecular structure of the oligomers can be adapted to a customer need. Among possible applications, these oligomers can be used as molecular labels to tag high-value products. At present, there is limited prior art in this area of research using synthetic polymers. Therefore, the present project may open up important technological and commercial opportunities. Practically speaking, a business manager and a post-doctoral researcher will be hired in this project in order to bridge the gap between fundamental research and commercialization. For instance, a detailed market analysis, including a survey of potential industrial partners, will be done by the business manager. This will help to identify the most appropriate solution for commercializing our technology.

Mots-clés : sequence controlled polymers,polymer chemistry,oligomers,identification technologies,high value products
Projet ERC : ICON-BIO (Horizon 2020, appel 2017, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer science and informatics
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 : 106540.0 €

The aim of the project is to develop a comprehensive framework for generalizing network analytics and fusion paradigms of non-negative matrix factorization to medical data. Heterogeneous, interconnected, systems-level omics data are becoming increasingly available and important in precision medicine. We are seeking to better stratify and subtype patients into risk groups, discover new biomarkers for complex and rare diseases, personalize medical treatment based on genomics and exposures of an individual, and repurpose known drugs to different patient groups. Existing methodologies for dealing with these big data are limited and a paradigm shift is needed to achieve quantitatively and qualitatively better results. The project is motivated by the recent success of non-negative matrix tri-factorization (NMTF) based methods for fusion of heterogeneous data in biomedicine. Though these methods have been known for some time, the availability of large datasets, coupled with modern computational power and efficient optimization methods, allowed for creation and efficient training of complex models that can make a qualitative breakthrough. For example, NMTF has recently achieved unprecedented performance on exceptionally hard problems of simultaneously utilizing the wealth of diverse molecular and clinical data in precision medicine. However, research thus far has been limited to special variants of this problem and used only fixed point methods to address these exciting examples of hard non-convex high-dimensional non-linear optimization problems. The ambition of the project is to develop general data fusion methods, from mathematical models to efficient and scalable software implementation, and apply them to the domain of biomedical informatics. The project will lead to a paradigm shift in biomedical and computational understanding of data and diseases that will open up ways to solving some of the major bottlenecks in precision medicine and other domains.

Mots-clés : molecular networks
Projet ERC : LEMAN (Horizon 2020, appel 2016, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer science and informatics
Entité participante : Università della Svizzera italiana — Pays : Suisse — Rôle : Partner
Acronyme de l'entité : USI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 87624.9 €

The aim of the project is to develop a geometrically meaningful framework that allows generalizing deep learning paradigms to data on non-Euclidean domains. Such geometric data are becoming increasingly important in a variety of fields including computer graphics and vision, sensor networks, biomedicine, genomics, and computational social sciences. Existing methodologies for dealing with geometric data are limited, and a paradigm shift is needed to achieve quantitatively and qualitatively better results. Our project is motivated by the recent dramatic success of deep learning methods in a wide range of applications, which has literally shaken the academic and industrial world. Though these methods have been known for decades, the computational power of modern computers, availability of large datasets, and efficient optimization methods allowed creating and effectively training complex models that made a qualitative breakthrough. In particular, in computer vision, deep neural networks have achieved unprecedented performance on notoriously hard problems such as object recognition. However, so far research has mainly focused on developing deep learning methods for Euclidean data such as acoustic signals, images, and videos. In fields dealing with geometric data, the adoption of deep learning has been lagging behind, primarily since the non-Euclidean nature of objects dealt with makes the very definition of basic operations used in deep networks rather elusive. The ambition of the project is to develop geometric deep learning methods all the way from a mathematical model to an efficient and scalable software implementation, and apply them to some of today’s most important and challenging problems from the domains of computer graphics and vision, genomics, and social network analysis. We expect the proposed framework to lead to a leap in performance on several known tough problems, as well as to allow addressing new and previously unthinkable problems.

Mots-clés : geometric deep learning,convolutional neural networks,intrinsic geometry,shape analysis,shape correspondence,signal processing on graphs,spectral methods,face analysis,social network analysis
Projet ERC : DNR (Horizon 2020, appel 2016, Proof of concept grants)
Entité participante : University of Konstanz — Pays : Allemagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 147000.0 €

The aim of the proposed transfer project is to develop the blended learning course „Death Notification with Responsibility“ (DNR) for police officers. In situations of unnatural death (accidents, suicides, terror attacks or other forms of violence), police officers have to deliver a death notification to the family members of the deceased. Unnatural death is the worst possible message to be delivered. It will change the lives of those informed decisively and will remain in their memories forever. The core findings of the ERC project „Narratives of Terror and Disappearance“ (NoT-240984) established the devastating social effects of uncertainty caused by non-information and the material absence of bodies in confrontation with violent death. Police officers have a big impact on the way the bereaved can cope with this event. Psychological disorders like depressions are among the long-lasting effects on victims, if communication in this situation fails. At present, no sufficient training is offered at police academies that would ensure the systematic implementation of victims’ right to information as protected by EU Directive 2012/29. DNR will enable police officers to prepare for death notification delivery through a multi-layered approach, integrating classroom education and group-work as well as interactive e-learning components on a range of topics related to death and communication in highly sensitive situations. DNR will be produced with the IT department of Stuttgart police headquarters. Asides from the technological production the collaboration with police is crucial for developing the content of DNR modules. The prototype will be tested and evaluated in the police academy of Duisburg/Germany where it will be integrated into a semester-based course on ethics and social skills. In case of success, DNR markets will be expanded to other professional groups and prepared for use in other countries.

Mots-clés : victims  protection,death notification,police professionalization,blended learning,unnatural death,mourning cultures,stress prevention,communication skills
Projet ERC : SQH (Horizon 2020, appel 2016, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Condensed matter physics
Entité participante : Aalto University — Pays : Finlande — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2418002.0 €

The aim of the proposed work is to realize experimentally the first genuinely quantum mechanical refrigerator/heat engine in the solid state, and test whether one can boost its performance by information/feedback, optimized control, and merely by exploiting the quantum coherences vs the classical dynamics. To achieve this goal, we will investigate experimentally and theoretically the thermodynamics of open quantum systems. For the experimental realization, we will develop calorimetry with superior energy and time resolution and build competitive quantum circuits based on superconducting quantum bits (qubits). In order to achieve the ultimate goal, we will, for the first time, implement a test for quantum fluctuation relations in a truly open quantum system, and demonstrate an implementation of the so-called quantum Maxwell's Demon by controlling a qubit in an optimal way. In our studies we will utilize the state-of-the-art nanofabrication and measurement facilities of the national OtaNano research infrastructure that I coordinate. This project presents a serious effort to investigate experimentally open quantum systems from the point of view of thermodynamics. It brings the classical field of research, thermodynamics, to the quantum regime, where experiments are in their infancy. Beyond the direct fundamental significance of this endeavor, the outcome of this project will technologically benefit the performance of both current and novel devices that is often limited by our present understanding of fluctuation relations and the characteristics of open quantum systems.

Mots-clés : quantum heat engines,quantum refrigerators,superconductors,open quantum systems,information,thermodynamics,work,heat,fluctuations,solid state physics
Projet ERC : ICONICAL (Horizon 2020, appel 2014, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Physical and analytical chemical sciences
Entité participante : Delft University of Technology — Pays : Pays-Bas — Rôle : PI
Acronyme de l'entité : TU Delft
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2000000.0 €

The aim of the work proposed here is to achieve control over charge and excited state dynamics in organic crystalline materials and in this way to come to solid state materials with explicit built-in functionality. The charge and excited state dynamics do not only depend on the properties of individual molecules but are to a large extent determined by the interactions between multiple molecules. By careful engineering of the properties of individual molecules and of the way they aggregate in the solid crystalline state it is in principle possible to design materials that exhibit a specific functionality. Examples of this are materials that are optimized to give high charge carrier mobilities and high exciton diffusion coefficients. It is also possible to design more complex functionality. An example of this is singlet exciton fission, a process by which one singlet excited state transforms into a combination of two triplet states. This spin-allowed process can in principle increase the efficiency of organic solar cells by a factor 1.5. A second example is upconversion of low energy photons into higher energy photons. This is possible by combining two low-energy triplet excited states into a single singlet excited state by triplet-triplet annihilation. Finally, it is possible gain control over charge separation on the interface of two different materials to increase the charge separation efficiency in photovoltaic cells. In this work, we will explore ways to achieve control of charge and exciton dynamics in a combined effort including organic synthesis, computational chemistry and time-resolved spectroscopy and conductivity experiments. This research represents a major step forward in the understanding of the relation between molecular and solid state structure and the electronic properties of organic crystalline materials. This is of considerable fundamental interest but also has direct implications for the utilization of these materials in electronic devices.
Projet ERC : Ig-QPD (Horizon 2020, appel 2014, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Physical and analytical chemical sciences
Entité participante : University of Groningen — Pays : Pays-Bas — Rôle : PI
Acronyme de l'entité : RUG
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2000000.0 €

The aim of this ERC proposal is to develop a highly efficient tunable interface with ion-movement-mediated gating as a rich platform for novel electronic devices by using field effect controlling of quantum phase transitions. Working beyond conventional FETs, the new transistors will be build by combining novel layered semiconductor films grown by the CVD method: newly synthesized ionic material; and a well-defined interface optimized by surface analysis techniques; which jointly are able to boost the field effect control of carrier doping to the range required for switching quantum phases such as superconductivity in electrical transport, ferromagnetism in magnetization, and chiral or coherent light sources in optical applications. The sub-topics are designed to cover sufficiently broad disciplines of material sciences, new device technologies based on electrochemical principles, and condensed-matter physics. Such a design will make the project high adaptable for success at different levels with clear defined objectives to: 1) develop new materials and material combinations for ion gated interfaces to establish a rich platform of quantum phases; 2) utilize these quantum phases for device functionalities enjoying the characteristic abrupt response in phase transitions and to establish control of magnetism by field effect; and 3) create light emitting devices for effectively correlating light emission with quantum phases. The project represents an exciting new research field that is attracting the attention of many research groups around the world. The applicant is a well-established pioneer in developing this rapid growing and highly competitive field, where he achieved major milestones in design, fabrication and operation of quantum phase devices. Embedded in the strong material researches environment of the host institute and in his new group, it is the perfect timing for the applicant to fulfil the dream of creating a new paradigm of electronic devices.

Mots-clés : field effect transistor,2d layered materials,superconductivity,quantum phase transition
Projet ERC : new-ppd-environments (Horizon 2020, appel 2014, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Universe sciences
Entité participante : University of Copenhagen — Pays : Danemark — Rôle : Partner
Acronyme de l'entité : UCPH
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1069443.94 €

The aim of this ambitious research project is to produce the most realistic computer simulations of gaseous protoplanetary accretion discs to date, and thereby define in an assertive way the environment that shapes the assembly and early evolution of planetary systems. In their role as planet nurseries, protoplanetary discs are of key interest to planet formation theory. Their dynamical, radiative and thermodynamic properties critically define the environment for embedded solids: dust grains, pebbles and planetesimals. In short, the building blocks of planet formation. The discs’ dynamics and structure in turn depend critically on the influence of magnetic fields that couple to tenuously ionised and low-density regions. Being comparatively cold and dense, the ionisation state of the disc plasma is dominated by external far-UV, X-Ray, and cosmic-ray radiation, leading to a layered vertical structure – with turbulent, magnetised surface layers and a magnetically-decoupled midplane. This classic ‘dead-zone’ picture is now turned upside-down by previously ignored micro-physical effects. For instance, ambipolar diffusion is predicted to dominate in the tenuous hot corona of the disc. It is expected that parts of the disc will thus be stabilised and a magneto-centrifugal wind will be launched. This has so far only been studied in very simplified local models that are affected by fundamental limitations. Our understanding of the structure of protoplanetary discs is about to undergo a dramatic shift, and my proposed research is at the forefront of this development. My recent successful work at the interface between MHD dynamics and planet formation theory makes me ideally skilled to lead a research group in this endeavour and to communicate advancements to a wide audience of theoreticians in planet formation. Our ambitious global simulations will furthermore provide realistic templates to interpret new observations made with the ALMA telescope array.

Mots-clés : magnetohydrodynamics  mhd,methods  numerical,planets and satellites  formation,protoplanetary disks