Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : FREENERGY (Horizon 2020, appel 2018, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Synthetic Chemistry and Materials
Entité participante : Helmholtz-Zentrum Berlin für Materialien und Energie — Pays : Allemagne — Rôle : PI
Type d'entité : Recherche
Financement ERC de l'entité : 401250.0 €

Achieving zero net carbon emissions by the end of the century is the challenge for capping global warming. The largest share of carbon emissions belongs to the production of electric energy from fossil fuels, which renewable energies are progressively replacing. Sunlight is an ideal renewable energy source since it is most abundant and available worldwide. Photovoltaic solar cells can directly convert the sunlight into electric energy by making use of the photovoltaic effect in semiconductors. Halide perovskites are emerging crystalline semiconducting materials with among the strongest light absorption and the most effective electric charge generation needed to design the highest efficient photovoltaic solar cells. The PI has the ambition to reinvent halide perovskites as environmentally friendly photovoltaic material, aiming at: (i) Removing lead: state-of-the-art perovskite solar cells are based on lead, which is in the list of hazardous substances of the European Union. The PI will prepare new tin-based perovskites and prove them in the highest efficient solar cells. (ii) Solvent-free crystallisation: organic solvents drive the crystallisation of the perovskite in the most efficient solar cells. However, crystallising the perovskite without using solvents is more environmentally friendly. The PI will establish physical vapour deposition as a solvent-free method for preparing the perovskite and the other materials comprising the solar cell. (iii) Durable power output: the long-term power output defines the solar energy yield and thus the return on investment. The PI aims to make stable tin-based perovskites addressing the oxidative instability of tin directly. The quantified target of FREENERGY is demonstrating a tin-based perovskite solar cell with power conversion efficiency over 20% and stability for 25 years. The research strategy to enable this disruptive outcome comprises innovative perovskites formulations and unconventional supramolecular interactions

Mots-clés : photovoltaic
Projet ERC : NANO-DECTET (Horizon 2020, appel 2020, 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 : 2709688.0 €

Across the global energy economy only about 1/3 of primary energy is converted into useful energy services, the other 2/3 are wasted as heat in the various industrial, transportation, residential energy conversion and electricity generation processes. Given the urgent need for transitioning to a zero-carbon energy supply in order to mitigate dangerous consequences of climate change a waste of energy on this scale is scandalous. Thermoelectric waste-heat-to-electricity conversion could offer a potential solution but the performance of thermoelectric materials is currently insufficient, particularly for the majority of heat that is generated at low heat source temperatures below 300-400°C. Based on a recent scientific breakthrough I have become convinced that the unique characteristics of molecular, organic semiconductors (OSCs) could make them ideal, low-temperature thermoelectric materials, but the thermoelectric physics of this class of soft materials with complex microstructures and strong electron-phonon coupling remains as yet largely unexplored and poorly understood. The aim of this proposal is (a) to develop novel experimental methods for the nanoscale characterisation of the thermoelectric properties of a very promising new generation of molecular thermoelectric materials, (b) to achieve a clear fundamental understanding of their thermoelectric physics and how thermoelectric transport coefficients can be decoupled and enhanced independently in these materials and (c) to translate this into the design of high performance molecular thermoelectric materials with unprecedented performance ZT > 2-3 at temperatures < 300-400°C. This is a fundamental and interdisciplinary, high-risk research programme stretching across theory, condensed matter physics, chemistry and materials science as well device engineering. If successful the project could make a significant contribution to improved energy efficiency and a successful transition to a zero-carbon energy economy.
Projet ERC : ActiDrops (Horizon 2020, appel 2019, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Synthetic Chemistry and Materials
Entité participante : Technical University of Munich — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : TUM
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1491350.0 €

Active droplets are made of molecular building blocks that are activated and deactivated by a chemical reaction cycle. In the activation, a precursor is converted into a building block for droplets driven by the consumption of fuel. In the deactivation, the building blocks react back to the precursor. In other words, active droplets emerge when fuel is supplied, but decay when fuel is depleted. Theoretical studies show active droplets all evolve to the same size. Another work predicts that the droplets can spontaneously self-divide when energy is abundant. All of these exciting properties, i.e., emergence, decay, collective behavior, and self-division are pivotal to the functioning of life. If we could engineer these behaviors in synthetic materials, we would obtain a better understanding of active assembly which is directly relevant to biology and the origin of life. I thus aim to synthesize active droplets and study their life-like properties. Two types of active droplets will be investigated; one type based on oil-molecules that phase separate in water, and one type based on cationic peptides in a complex coacervate with RNA. My team will develop reaction cycles that drive the droplet formation, thereby making them active. We will study their spontaneous emergence in response to energy, and disappearance when energy is scarce. Moreover, we study their collective behavior, like how they grow into one large droplet, or all converge to the same droplet volume. Finally, we test their division into daughter droplets. Our systematic approach will test how kinetic parameters, like the activation rate, affect the behavior of the droplets. The results will mark a massive step forward in the engineering of materials with life-like behaviors, which can also serve as experimental models for membrane-less organelles. We expect to elucidate mechanisms that could have played a role in the origin of life. Finally, our findings could form stepping stones towards a synthetic cel.

Mots-clés : self assembly,supramolecular chemistry,active materials,droplets,emulsion,active droplets
Projet ERC : ONCOMECHAML (Horizon 2020, appel 2014, Starting grants)
Domaine scientifique : Life Science
Panel : Prevention, Diagnosis and Treatment of Human Diseases
Entité participante : University of Veterinary Medicine Vienna — Pays : Autriche — Rôle : PI
Acronyme de l'entité : VUW
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 513990.75 €

Acute Myeloid Leukemia (AML) is the most frequent cancer of the blood system, with >80% mortality within 5 years of diagnosis. Straightforward clinical decisions are complicated by the genetic complexity of AML. In particular, fusion proteins arising from chromosomal aberrations are recurrently found in AML and often act as strong driver oncogenes. In “Multi-Partner Translocation” (MPT) families, one specific gene is fused to many recipient loci. Due to this modular architecture, MPT families are of particular interest to comparative studies of oncogenic mechanisms. The three most common MPT families in AML represent translocations of the MLL, RUNX1 and NUP98 genes. Despite their clinical significance, the molecular mechanism of transformation remains unknown for the majority of fusion proteins and it is unclear if transforming mechanisms are conserved within and across different MPT families. We hypothesize that common oncogenic mechanisms of fusion proteins are encoded in physical and genetic cellular interaction networks that are specific to MPT families. We propose to delineate critical common effectors of oncogenic mechanisms in AML driven by MPT families through a comprehensive, comparative, functional analysis of 20 clinically representative MLL-, RUNX1- and NUP98-fusion proteins using a unique experimental pipeline. Characterization of protein interactomes and their effects on gene expression will identify common cellular denominators of MPT families, whose functional contribution will be assessed through pooled shRNA screens in clinically relevant model systems. High-confidence hits will be validated in mouse models and primary cells from AML patients. This project will generate large informative datasets and novel experimental systems that are of relevance for basic and clinical cancer research. It will contribute to improved understanding of oncogenic mechanisms, which may directly impact on diagnostic and therapeutic strategies in the management of AML.

Mots-clés : acute myeloid leukemia,fusion proteins,molecular medicine,oncogenic mechanism,proteomics,transcriptomics,rnai,common molecular mechanisms,diagnosis,treatment
Projet ERC : AdOptEx (Horizon 2020, appel 2020, Proof of concept grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Systems and communication engineering
Entité participante : University of Oxford — Pays : Royaume-Uni — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 150000.0 €

Adaptive optics (AO) is an important technology for high-resolution microscopy that overcomes imaging problems when focusing inside biological specimens. Through the ERC Advanced Grant AdOMiS we have developed and experimentally validated new, broadly applicable AO tools that make integration of this technology more practical for a range of different microscopy techniques. We have also accumulated significant know-how about effective implementation of this technology. The challenge now is to translate these laboratory-based methods and know-how outside the academic research environment. This project will facilitate access to the products of our research to potential research and commercial adopters so that they can successfully deploy our AO methods in their systems.

Mots-clés : optical microscopes,adaptive optics
Projet ERC : PRE-ECO (Horizon 2020, appel 2019, 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 : 1477901.0 €

Additive manufacturing and Automated Fibre Placement (AFP) processes brought to the emergence of a new class of fibre-reinforced materials; namely, the Variable Angle Tow (VAT) composites. AFP machines allow the fibres to be relaxed along curvilinear paths within the lamina, thus implying a point-wise variation of the material properties. In theory, the designer can conceive VAT structures with unexplored capabilities and tailor materials with optimized stiffness-to-weight ratios. In practise, steering brittle fibres, generally made of glass or carbon, is not trivial. Printing must be performed at the right combination of temperature, velocity, curvature radii and pressure to preserve the integrity of fibres. The lack of information on how the effect of these parameters propagates through the scales, from fibres to the final structure, represents the missing piece in the puzzle of VAT composites, which today are either costly or difficult to design because affected by unpredictable failure mechanisms and unwanted defects (gaps, overlaps, and fibre kinking). This proposal is for an exploratory study into a radical new approach to the problem of design, manufacturing and analysis of tow-steered printed composite materials. The program will act as a pre-echo, a precursor, to: 1) implement global/local models for the simulation and analysis of VATs with unprecedented accuracy from fibre-matrix to component scales; 2) develop a (hybrid) metamodeling platform based on machine learning for defect sensitivity and optimization; and 3) set new rules and best-practices to design for manufacturing. A 5-year, highly inter-disciplinary programme is planned, encompassing structural mechanics, numerical calculus, 3D printing and AFP, measurements and testing of advanced composites, data science and artificial intelligence, and constrained optimization problems to finally fill the gap between the design and the digital manufacturing chain of advanced printed materials.

Mots-clés : additive manufacturing,3d printing,variable angle tow,composites,metamodels,automated fibre placement,functionally graded structures
Projet ERC : PROSOCIAL (Horizon 2020, appel 2015, Consolidator grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Human Mind and Its Complexity
Entité participante : Leiden University — Pays : Pays-Bas — Rôle : Partner
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1330876.3 €

Adolescence is an important transition period in life, where individuals gain independence from their caregivers and develop into adults who pursue their own goals. Our understanding of this transition period has benefited from two decades of research on brain development, in which it was discovered that adolescence represents a period of risk for heightened emotional reactivity, and that the developing brain in adolescence is much more plastic than previously thought. The existing models, however, have often ignored how these aspects of normative development have adaptive functions. In this proposal, I will use the original approach of testing for the first time the hypothesis that the very same emotional reactivity that was previously argued to create risks for potential negative developmental trajectories (including risk for substance abuse, delinquency) may under other circumstances create opportunities for prosocial developmental trajectories (voluntary behavior to benefit others) – such as by fostering cooperation, sharing and helping. For this purpose, I will measure functional and structural brain development longitudinally across the age range 10-21 years. I will test linear versus non-linear developmental patterns of brain activity for three key aspects of prosocial development (cooperation, sharing, and helping). This focus on positive development will provide a turning point in our understanding of adolescent brain development. The program will make the additional step of testing an intervention for prosocial development. An experimental longitudinal intervention study is crucial for the question whether adolescence is a window of opportunity for prosocial development. A mechanistic understanding of the different phases of adolescent development will prove useful not only for theory development, but also for teachers and youth workers to shape educational and health programs around opportunities for prosocial development, affecting all adolescents.

Mots-clés : development,adolescence
Projet ERC : ScoliStorm (Horizon 2020, appel 2020, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Products and processes engineering
Entité participante : Eindhoven University of Technology — Pays : Pays-Bas — Rôle : PI
Acronyme de l'entité : TU/e
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1824687.5 €

Adolescent idiopathic scoliosis (AIS) is a 3D deformity of the spine affecting previously healthy children, substantially reducing their quality of life and creating a life-long burden of disease. Although it has been indentified since the time of Hippocrates (400 BC), we have not been able to rationally develop effective treatments and provide a cure for these children suffering from AIS because its cause and mechanism of disease are still unknown. ScoliStorm will create a paradigm shift in AIS research by uncovering its complex perfect storm of anatomical, biomechanical and mechanobiological causes in the intervertebral disc and exploring this disease mechanism whereby predictive triggers are identified that can be used for prevention and early treatment. We will study human subjects non-invasively through disease initiation and progression, creating for the first time a comprehensive dataset of healthy and scoliotic human spines that can be used for early detection and treatment of juvenile spine conditions. We will create safe non-radiographic accurate imaging of the osseous spine, available in most hospitals, which can become the standard for diagnosis and monitoring of osseous injury and disease in juveniles. We will develop high-throughput creation and use of subject specific in silico models, allowing simulation of organ and tissue function such that morphological imaging data can provide functional analysis of the patient for diagnosis and treatment. Mechanisms affecting tissue adaptation will be mapped and show that normal processes by their coincidence can create an aberrant response and disease, providing an explanation applicable for other multifactorial diseases. Thus, a unique dedicated and complete multidisciplinary process, combining 1) bioengineering analysis, exploiting imaging, in silico modeling, in vitro and ex vivo approaches in humans, and 2) clinical medicine, also applicable for exploring other multifactorial diseases, will be created.

Mots-clés : scoliosis,aetiology,intervertebral disc,growth,biomechanics,mechanobiology,synthetic ct
Projet ERC : PRELICAN (Horizon 2020, appel 2016, Proof of concept grants)
Entité participante : Institut national de la santé et de la recherche médicale — Pays : France — Rôle : PI
Acronyme de l'entité : Inserm
Type d'entité : Recherche
Financement ERC de l'entité : 150000.0 €

Advanced liver disease and cancer is the only major cause of death still increasing each year. Major causes include hepatitis B and C viruses, alcohol and non-alcoholic fatty liver disease/steatohepatitis (NAFLD/NASH). A major contributing factor to the increasing incidence and mortality of liver disease is the staggering rise in obesity. The absence of effective therapeutic options for NAFLD/NASH, advanced liver disease and cancer contribute to the poor prognosis and the high cost associated with patient care. We have established a tractable and clinically relevant human cell-based model system in which viral infection, ethanol or free fatty acids induce a clinical gene expression signature robustly predicting liver disease progression and long-term HCC risk in cirrhotic patients. Using this model we identified compounds as HCC chemopreventive agents. Aiming to evaluate these compounds for future clinical development and potential commercialization we will perform proof-of-concept studies in state-of-the-art mouse models for NASH and hepatocarcinogenesis. Specifically we will assess the therapeutic effect on liver inflammation, steatosis, fibrosis and HCC development and investigate its safety in long-term administration. With the completion of this program we expect to obtain a robust proof-of-concept data package as a first- or best-in-class compound for treatment of chronic liver disease and prevention of HCC.

Mots-clés : liver disease,nafld,nash,antibody,drug development,animal model,steatosis,fibrosis,liver cancer,hepatocarcinogenesis
Projet ERC : QU-BOSS (Horizon 2020, appel 2019, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Fundamental constituents of matter
Entité participante : National Research Council — Pays : Italie — Rôle : Partner
Acronyme de l'entité : CNR
Type d'entité : Recherche
Financement ERC de l'entité : 380000.0 €

After decades of progress in quantum information science, it is widely expected that in the next few years the field will start to yield practical applications in quantum chemistry, materials and pharmaceutical research, information security, and finance. For these applications to pan out, a crucial intermediate goal is to reach the quantum advantage regime, where quantum devices experimentally outperform classical computers in some computational task. The Boson Sampling problem is an example of a task that is computationally hard for classical computers, but which can be solved with a specialized quantum device using single photons interfering in a multimode linear interferometer. The aim of QU-BOSS is to experimentally push towards the quantum advantage regime with integrated photonic technology. The key innovative ingredient is the introduction of non-linearities acting at the single photon level embedded within the Boson Sampling interferometer. We plan to provide an experimental research breakthrough along three main directions, including both “hardware” and “software” components. First, we will use complementary approaches to map out how the addition of non-linearity boosts the device ́s complexity, making it harder to simulate classically. We will use different approaches to implement these devices with hybrid integrated quantum photonics, a versatile and flexible route to the manipulation of high-dimensional quantum photonic states. Finally, we will deploy the developed technology to implement two different architectures demonstrating quantum machine learning: a hybrid model of quantum computation and an optical quantum neural network. QU- BOSS aims to position integrated photonics into the NISQ (noisy, intermediate-scale quantum) era, opening up truly new scientific horizons at the frontier of quantum information, quantum control, machine learning and integrated photonics.

Mots-clés : integrated quantum photonics,single photon sources,reconfigurable circuits,boson sampling,quantum machine learning,quantum networks,machine learning enhanced quantum information