Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Active topological photonic insulators based on Mie-resonators (TOPOMIE)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Global Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Physics
Countries involved: Germany,United States
Call: Individual Fellowships (H2020-MSCA-IF-2018, 2018)
Start date: 2020-03-01
End date: 2023-05-02
Duration (months): 36.0
Total project cost (EUR): 246669.12
EU funding (EUR): 246669.12
Participants: 2
Project status: TERMINATED

I will carry out an individual fellowship to push forward disruptive advances in enhanced light-matter interactions at the nanoscale. I will explore ways of control light-emission from quantum dots (QDs) combining them with all-dielectric 2D metamaterials that support non-trivial topological properties. The fellowship will be carried out for 2 years in the host organization, the Advanced Science Research Center (ASRC) at the Graduate Center of the City University of New York (CUNY), under the supervision of Prof. Andrea Alù. In the third year, I will return to the beneficiary organization, Martin-Luther University of Halle-Wittenberg (MLU) in Germany, and work under the supervision of Prof. Joerg Schilling. The research includes the development of theory, numerical design, sample fabrication and optical characterization. The combination of - my present experience with active emitters incorporated with nanostructures, - the ASRC-supervisor’s expertise in topological nanophotonics, - ASRC’s unique fabrication and characterization facilities, - the MLU-supervisor’s expertise in nonlinear nanophotonics provides a unique synergy to push forward in disruptive ways the field of nanophotonics and topological optics. I will use near-infrared (NIR) QDs integrated into Silicon as the material platform of interest. The research will contribute to fundamental discoveries in the field of light-matter interactions and topological photonics, and pave the way to compact all-dielectric light-sources for data-processing and telecommunication applications.

Keywords: topological photonics,silicon,nir quantum dots,light matter interaction,all dielectric metamaterials,topological photonic insulator,optical resonators,purcell,nonlinear photonics,edge states
Probing the deep Earth's interior by synergistic use of observations of the magnetic and gravity fields, and of the rotation of the Earth. (GRACEFUL)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Synergy grants
Action type: ERC actions
Countries involved: Belgium,France,France
Call: ERC Synergy Grant (ERC-2019-SyG, 2019)
Start date: 2020-09-01
End date: 2025-02-28
Duration (months): 54.0
Total project cost (EUR): 4595075.0
EU funding (EUR): 4595074.0
Participants: 3
Project status: SIGNED

To understand the processes involved in the deep interior of the Earth and explaining its evolution, in particular the dynamics of the Earth’s fluid iron-rich outer core, only indirect satellite and ground observations are available. They each provide invaluable information about the core flow but are incomplete on their own: - The time dependent magnetic field, originating mainly within the core, can be used to infer the motions of the fluid at the top of the core on decadal and subdecadal time scales. - The time dependent gravity field variations that reflect changes in the mass distribution within the Earth and at its surface occur on a broad range of time scales. Decadal and interannual variations include the signature of the flow inside the core, though they are largely dominated by surface contributions related to the global water cycle and climate-driven land ice loss. - Earth rotation changes (or variations in the length of the day) also occur on these timescales, and are largely related to the core fluid motions through exchange of angular momentum between the core and the mantle. The GRACEFUL project will go beyond the potential of individual satellite and ground observations and will combine the information about the core deduced from the gravity field, from the magnetic field and from the Earth rotation in synergy, in order to examine in unprecedented depth the dynamical processes occurring inside the core and at the core-mantle boundary. We will develop cutting-edge algorithms to process observational data and use up-to-date numerical models of the core flow to infer its dynamics. This interdisciplinary approach will challenge our current understanding of the core dynamics and provide a step change in our understanding of the deep Earth’s interior. The pioneering approach of GRACEFUL will provide an innovative template to obtain totally novel information about the dynamic processes inside the fluid core and core-mantle boundary of the Earth.

Keywords: earth rotation,earth gravity,earth magnetic field,fluid core motions
The reward value of stereotypes: Evaluating the contribution of the neural reward circuitry to the persistence of stereotypes (Rewarding Stereotype)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Reintegration panel
Action type: Marie Skłodowska-Curie actions
Panel: Social Sciences and Humanities
Countries involved: Israel
Call: Individual Fellowships (H2020-MSCA-IF-2018, 2018)
Start date: 2019-09-01
End date: 2022-02-12
Duration (months): 24.0
Total project cost (EUR): 185464.32
EU funding (EUR): 185464.32
Participants: 1
Project status: CLOSED

Social interactions are guided by stereotypical knowledge about others: Should I turn to a male or female friend for emotional support? Should I be concerned about the foreign-looking person walking behind me? In the past few decades the endeavour to reduce cultural stereotypes has proved to be very difficult and often unsuccessful. The current research program promotes a novel proposal regarding the underlying neurobiological basis of stereotype perseverance: the “rewarding stereotype hypothesis”. In an interdisciplinary integration of models and theories, I suggest that stereotypes and stereotype-consistent information evoke a neural reward response, leading to powerful feedback that reinforces culturally-pervasive stereotypes and their associated behaviors. A battery of experiments encompassing neuroimaging and computational studies utilizing state-of-the-art tools will test the core tenets of the hypothesis. This will be completed by observing the hypothesized mechanism and then by its manipulation. Importantly, the putative sensitivity of stereotypes to rewards suggests that altering the reward scheme for non-stereotypical behaviors can have a strong impact on decisions and behavior. Following initial proof of concept, I suggest several scalable intervention examples to explore the potential implications on educational, institutional and social policies promoting a just society. Effective communication of these efforts holds the potential for a long term improvement of society. Altogether, the current proposal combines the complementary strengths of the researcher and the host to establish the building blocks for a new view of stereotypes, one that suggests that we can render them less pervasive if we consider their underlying reward value.

Keywords: reward
Tribocharge: a multi-scale approach to an enduring problem in physics (Tribocharge)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Condensed matter physics
Panel description: Structure, electronic properties, fluids, nanosciences, biological physics
Countries involved: Austria
Call: ERC STARTING GRANTS (ERC-2020-STG, 2020)
Start date: 2021-01-01
End date: 2025-12-31
Duration (months): 60.0
Total project cost (EUR): 1493623.0
EU funding (EUR): 1493623.0
Participants: 1
Project status: SIGNED

Tribocharging, i.e. charge transfer during contact, is a fundamental effect of widespread importance, yet we do not understand it. For insulators, even the most basic questions are open: What are the charge carriers? How do they bind to a surface? What drives them between surfaces? The aim of this proposal is to establish the mechanism of insulator tribocharging. Building on my work to develop new experiments and test existing models, we will use a multi-scale approach to find the origin of this effect. We will address the apparent homogeneous macrophysics, through the stochastic signatures at the mesoscale, and down to individual charges at the microscale. Throughout, we will perform crucial tests for the promising ‘water island’ hypothesis. The project consists of 3 experimental work packages: WP1: At the macroscale, we will use atomic layer deposition on polymers to create clean contacts with oxides. We will compare charge transfer with measurements of water surface coverage to test the water island model. WP2: At the mesoscale, we will use acoustic levitation to measure the charge of particles colliding with a substrate. With unprecedented precision, we will analyze statistics to tease out water’s role as a charge driver vs. discharge driver. WP3: At the microscale, we will use optical tweezers to watch individual charges jump on and off a microparticle. With sub-electron resolution, we will determine the binding energy to identify the carrier. Our experiments will be interwoven with a theoretical thread to unify the physics between scales. Facing a problem that has eluded description for centuries is inherently risky. However, our multi-scale approach has not been attempted, and gives comprehensive solutions to the challenges that have existed. Beyond fundamental relevance, our work will be useful in new technologies, e.g. triboelectric nanogenerators. Understanding tribocharging, though ambitious, promises exceptional scientific and technological rewards.

Keywords: tribocharging,triboelectric charging,granular physics,soft matter physics,adsorbed water,statistical physics
EUrope-BRAzil Collaboration on BIG Data Scientific REsearch through Cloud-Centric Applications (EUBra-BIGSEA)

Framework: Horizon 2020 — Industrial Leadership
Programme: Information and Communication Technologies
Action type: Research and Innovation actions
Countries involved: Italy,Spain,Italy,Spain,Portugal,United Kingdom
Call: Cloud Computing, including security aspects (H2020-EUB-2015, 2015)
Start date: 2016-01-01
End date: 2017-12-31
Duration (months): 24.0
Total project cost (EUR): 1499625.0
EU funding (EUR): 1499625.0
Participants: 6
Project status: CLOSED

EUrope-BRAzil Collaboration on BIG Data Scientific REsearch through Cloud-Centric Applications aims at providing services in the cloud for the processing of massive data coming from highly connected societies, which impose multiple challenges on resource provision, performance, Quality of Service and privacy. Processing those data require rapidly provisioned infrastructures customised to Big Data requirements. The three main aims of the proposal will be: - The development of innovative Big Data services for capturing, federating and annotating on the order of PB of data on top of efficient programming models. Despite that MapReduce is a successful model in BigData (with a high impact on massive Geo-spatial and textual data), it has many limitations specially when dealing with real-time transactions or streamed data, the proposal would aim to introduce innovative evolutions on the capture, federation & annotation experience it can bring to the table with its partners. - The Development of advanced cloud services to support Big Data. This cloud services will address three main challenges: a) the advance on SLAs to support privacy (boundaries of protected data to be moved) and performance restrictions (convenience of moving data to computing resources or vice-versa); b) Quality of Service (vertical and horizontal elastic adjustment of resources allocates to meet deadlines and dynamic adjustment of workloads); and c) Business models (price-based dynamic re-scheduling of data searching for the best usage of resources invested). - The demonstration of such services on applications with high social and business impact, addressing main scenarios of high interest for both Europe and Brazil.

Keywords: big data,connected societies,federation,slas,quality of service,data analytics,climate change,cloud centric applications,interoperability,international standardization
Replicating the SUN through affordable, efficient and accurate LEDs (SENSEE)

Framework: Horizon 2020 — Societal Challenges
Programme: Secure, clean and efficient energy
Action type: SME instrument
Countries involved: Spain
Call: Stimulating the innovation potential of SMEs for a low carbon and efficient energy system (H2020-SMEINST-1-2016-2017, 2017)
Start date: 2017-05-01
End date: 2017-07-31
Duration (months): 3.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

Saiens Smart Energy S.L. is a company dedicated to the development of special light devices, solar simulators, that replicate sunlight for the testing of solar products which employed by research entities. The innovation stands on using the more efficient and affordable LEDs than traditional lamps. Simulators are used for the testing of solar industry products (125billion€ by 2023) and UV degradation (industry of plastics and coatings, 290M€ by 2020) Current simulators, based in Halogen and Xenon lamps, have severe limitations and we have developed SENSEE, a solar simulator based on LEDs, to respond to the actual market needs. We have demonstrated that a LED simulator is simpler, affordable (7x times cheaper than current simulators), has 93% lower maintenance costs and more precise (only 5% of deviation to sunlight). The recent EU Halogen ban (Sept. 2016) and the rapid and unexpected advancement of LEDs has bring us to seize this business opportunity and bring to the market an affordable, accurate and advanced LED-BASED SUN SIMULATOR, SENSEE. SENSEE will promote a new niche of products that covers the gap between very expensive and complex systems used by accredited labs and the uncalibrated simple lamps used by small testing industry and research entities. SENSEE will respond to current simulators limitations that are not able to test with the required precision, the new incoming technologies (i.e. multi-junction PV cells and photocatalysis). We will introduce SENSEE in the main EU actors in PV, research centres and certification labs (Germany, Italy, France and Spain) during 2020 and 2022. Within these potential markets we expect to gain a mean penetration of 2% and a business growth of 3.6M€ turnover by 2024 and supported by the creation of 28jobs.

Keywords: solar simulation,leds,solar spectrum,solar testing
Dual Catalysis for Meta Functionalisation under Mild Conditions (DCMeta)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Standard European Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Chemistry
Countries involved: United Kingdom
Call: Individual Fellowships (H2020-MSCA-IF-2017, 2017)
Start date: 2019-02-01
End date: 2021-01-31
Duration (months): 24.0
Total project cost (EUR): 183454.8
EU funding (EUR): 183454.8
Participants: 1
Project status: CLOSED

The proposal aims to integrate visible light photoredox catalysis with metal catalysed C-H functionalisation processes, with an emphasis on meta functionalisations under ruthenium catalysis. This dual catalysis approach will offer a very direct approach to addressing C-H bonds that are hard to manipulate under standard conditions. By using photoredox catalysis to control the electon transfer events that govern the metal catalytic cycle, we hope to establish new reactivity under mild conditions, that can be widely exploited in chemical synthesis. The first part of this proposal sets out our strategy to achieve this using substrates with covalently attached directing groups. We then want to advance further and develop ways of direct C-H activation using directing groups that can be installed in situ, which is described in the second part of the proposal.

Keywords: synthetic methodology,photoredox catalysis,c h activation
Machine Learning for Catalytic Carbon Dioxide Activation (MachineCat)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Standard European Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Chemistry
Countries involved: Germany
Call: Individual Fellowships (H2020-MSCA-IF-2017, 2017)
Start date: 2018-06-01
End date: 2020-05-31
Duration (months): 24.0
Total project cost (EUR): 159460.8
EU funding (EUR): 159460.8
Participants: 1
Project status: CLOSED

The goal of MachineCat is to obtain fundamental insights into machine learning methods applied to computational chemistry problems. Machine learning methods can be used to reproduce the predictions of highly accurate electronic structure calculations at only a fraction of the original computational cost. As a consequence, it becomes possible to simulate chemical problems usually beyond the capabilities of standard computational chemistry methods. However, a routine application of machine learning methods in computational chemistry is made difficult by their inherent black box nature. MachineCat will illuminate this black box by using state-of-the-art analysis techniques to gain a deep understanding on how these learning machines operate. Based on these insights, MachineCat will then systematically improve existing machine learning methods for computational chemistry. To this end, an organocatalytic conversion reaction of carbon dioxide will be investigated. This class of reactions is highly relevant for sustainable chemistry, as it offers cheap access to value-added chemicals, potentially replacing fossil fuels as primary carbon source. By studying one particular carbon dioxide conversion reaction with machine learning methods, MachineCat will not only push the limits of these methods, but also provide a detailed mechanism for the reaction under study for the first time. MachineCat will then use this information to rationally design improved catalysts for the conversion reaction. The researcher will gain expertise in modern machine techniques and transfer expertise in computational chemistry to the host. The networks of researcher and host will profit from two interdisciplinary workshops. MachineCat will prepare the researcher for an independent career, providing him with a unique research profile, excellent teaching and presentation skills, strong management capabilities, extensive experience in public engagement and dissemination, and a wide scientific network.

Keywords: machine learning,organocatalysis,carbon fixation,quantum chemistry,catalyst design,carbon dioxide activation
Future Optical Networks for Innovation, Research and Experimentation (ONFIRE)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Innovative Training Networks (ITN)-European Industrial Doctorates
Action type: Marie Skłodowska-Curie actions
Panel: Information Science and Engineering
Countries involved: Spain,Germany,Spain
Call: Innovative Training Networks (H2020-MSCA-ITN-2017, 2017)
Start date: 2017-10-01
End date: 2021-09-30
Duration (months): 48.0
Total project cost (EUR): 495745.92
EU funding (EUR): 495745.92
Participants: 4
Project status: CLOSED

Future (5G) services will impose stringent requirements in the design and operation of transport networks: increased capacity, low latency, high availability and dynamicity, reduced service provisioning with lower OpEx, while considering end-to-end service objectives (QoS and QoT). To cope with traffic growth in a cost-effective way, an appealing strategy focuses on deploying elastic and programmable commodity optical hardware via disaggregation (white boxes) combined with transmission technologies. To address both end-to-end service objectives and traffic dynamicity, an interesting approach leverages the benefits provided by SDN/NFV control and the automated decisions and re-configuration opportunities enabled by cognitive algorithms. For this, SDN/NFV provides unified control on top of systems’/devices’ programmability, regardless of the data infrastructure (packet, optical, IT), while exploiting the large real-time monitored information dynamically to adopt actions leading to attain service end-to-end objectives and more optimal network operation and resource utilization. Those hardware and software solutions constitute ONFIRE R&D goals which basically target the design, deployment and experimental evaluation of disaggregated optical transport hardware automatically articulated by novel cognitive algorithms supported by a SDN/NFV architecture. To do so, ONFIRE proposes a three-year research programme centred on two European industrial PhDs. PhD candidates will benefit from an intensive training process combining the strengths of both: i) CTTC as research institution to acquire research tools and methodology, with UPC as associated partner offering its PhD programme; ii) ALUD as a vendor delivering a highly valuable view of research activities and its impact on industrial ecosystem. Targeted PhD training programme is devised to maximize the synergy between the collaborators and promote career opportunities of ONFIRE researchers in the European ICT Research Area.

Keywords: cognitive optical networks,sdn and nfv control,orchestration,disaggregated optical networks,white boxes,real time monitoring,elastic and programmable optical hardware,cost efficient networks