Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Rational Design of Ceria-Supported Non-Noble Metal Nanoalloys as Catalysts for the Selective Direct Conversion of Methane to Methanol (4lessCH4)

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: Spain
Call: Individual Fellowships (H2020-MSCA-IF-2018, 2018)
Start date: 2019-09-01
End date: 2021-08-31
Duration (months): 24.0
Total project cost (EUR): 172932.48
EU funding (EUR): 172932.48
Participants: 1
Project status: CLOSED

Methane (CH4) is a potent greenhouse gas that can come from many sources, both natural and manmade. The low temperature direct route to converting methane to methanol (CH3OH) a key feedstock for the production of chemicals that can also fuel vehicles or be reformed to produce hydrogen has long been a holy grail. The efficient use of CH4 emissions require catalysts that can activate the first C-H bond while suppressing complete dehydrogenation and avoiding CO/CO2 formation. The potential benefit of finding non-expensive and efficient catalysts for directly converting methane to methanol (DMTM), using only molecular oxygen, and perhaps water, is significant and new catalysts are being sought. This project aims to the rational design of such catalysts based on non-noble metal nanoalloys/reducible oxide systems. There are key challenges to be addressed, namely, to improve reactants activation, to obtain an understanding of the reaction mechanism and to improve selectivity. Real powder catalysts are too complex to enable us to disentagle the effect of the nature of the metallic phase (composition, structure, nanoparticle size), the role of the oxidic support and of metal-support interactions, and the role of alloying and water in controlling selectivity. The strategy here consists of creating and investigating model systems, which include essential parts of the real ones, but can still be studied at the atomic level using state-of-the-art computational methodology in chemistry. Calculations will be performed in close collaboration with experimental work employing well-defined model systems as well as powders. The synergistic power of theory and experiment is crucial to design new or improved catalysts. Theory will not only be used to explain experimental data, but also for pre-screening the behavior of catalysts. The goal is to develop basic principles for the rational design and optimization of nano-structured catalysts for mitigating greenhouse gases.

Keywords: computational chemistry,heterogeneous catalysts design,methane conversion,methanol reaction mechanisms,metal oxide chemistry,nanoparticles,nanoalloys,ceria,materials gap
The future of aviation is electric (aEro)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: SME instrument
Countries involved: Switzerland
Call: SME instrument (H2020-SMEInst-2018-2020-1, 2019)
Start date: 2019-07-01
End date: 2019-10-31
Duration (months): 4.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

From both a cost & environmental standpoint, the future of aviation is electric. Although the traditional aircraft fuel still provides higher energy densities than the batteries, an electric-airplane movement has begun. More than 50 companies have announced passenger carrying vertical take-off & landing (VTOL) projects & the sector has never received so much coverage from mainstream media. There is a global race to deliver aircraft that will be able to service the air transportation needs of modern congested cities. Yet, most of this development is done from scratch, with little regard to the already proven technologies. Moreover, aviation history shows that disruption is extremely difficult (both technologically & from the certification point of view) & that the most adopted solutions are usually modern revisits of reliable designs. This is the approach we are taking with our novel aircraft. aEro2 is built on the success of our aEro 1 electric conventional take off & landing aerobatic plane. The eVTOL aEro2 will use a modular hybrid-electric power system. Three key features differentiate it from the competition. It is: - built on proven aircraft designs; - reuses all electric propulsion already validated on our TRL 9 aEro 1; - Can take off/land both as a conventional fixed-wing aircraft & as a rotor craft. Uniquely among the VTOL manufacturers, we chose a more reliable strategy to bringing an electric aircraft to reality. We built & tested aEro 1—a fully electric conventional airplane using a retrofitted Silence Twister. We validated that all systems work as expected in 60+ hours of flight time. Now we are building aEro 2—the proper VTOL. aEro 2 is a 500kg 2-seater aircraft that can travel at 320km/h up to 800km, land and take off vertically and produces very low noise. We are planning to address 3 market segments in aerobatics, pilot training & finally urban air transportation, reaching €15m in revenues & 50 FTEs by 2023.

Keywords: vtol,ctol,tiltwing,notar,aircraft,electric
Dynamics of thought and thought disorders (DynaT)

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: Social Sciences and Humanities
Countries involved: United Kingdom
Call: Individual Fellowships (H2020-MSCA-IF-2020, 2020)
Start date: 2021-10-01
End date: 2023-09-30
Duration (months): 24.0
Total project cost (EUR): 224933.76
EU funding (EUR): 224933.76
Participants: 1
Project status: SIGNED

Psychiatric disorders are often characterized by maladaptive thought patterns. Whereas most research focuses on the distinct contents of maladaptive thoughts, abnormalities in the process by which thoughts come to mind are often overlooked. One exception is formal thought disorder (FTD), defined as a disruption in the form and organization of thought (e.g., loose associations). FTD is considered a hallmark feature of psychosis. Furthermore, recent evidence suggests that FTDs are found in other psychiatric disorders. Despite progress in the research of FTD in the recent decades, FTD remains one of the least understood symptoms in psychosis (all the more so in other disorders), with no established treatments. One key issue is that most FTD research focuses on language and communication impairments (e.g., disorganized speech), and not on actual thoughts. The overall aim of 'Dynamics of thought and thought disorders' (DynaT) is to dissociate impairments in thought dynamics from impairments in the communication or expression of thought, without relying on introspective self-report. To deal with the challenge of measuring covert thought, DynaT will use state-of-the-art computational psychiatry methods. First, DynaT will use mathematical modelling to gain insight into the covert thoughts preceding participants' observed responses. Second, DynaT wil use machine-learning algorithms to tap thought dynamics from the participant's brain activity in real-time. DynaT will isolate and characterise several component processes of FTD in schizophrenia and across the wider, transdiagnostic psychopathological spectrum, including: a) semantic disorganization; b) impaired inhibitory control of thoughts; c) inflexible reliance on predominant, local associations. As the first investigation to dissociate (objectively measured) covert thoughts from overt speech, DynaT has the potential to significantly advance the conceptualization and understanding of FTDs across disorders.

Keywords: formal thought disorder,schizophrenia,psychosis,transdiagnostic,computational modelling,neural decoding,computational psychiatry,free association
Consortium for Hall Effect Orbital Propulsion System (CHEOPS)

Framework: Horizon 2020 — Industrial Leadership
Programme: Space
Theme: Enabling European competitiveness, non-dependence and innovation of the European space sector
Action type: Innovation actions
Countries involved: Spain,Germany,Italy,Italy,Germany,Germany,Sweden,Belgium,Greece,Sweden,Belgium,France,France,France,Netherlands
Call: SRC - In-Space electrical propulsion and station keeping - Incremental Technologies (H2020-COMPET-2016, 2016)
Start date: 2016-11-01
End date: 2021-04-30
Duration (months): 54.0
Total project cost (EUR): 14792359.43
EU funding (EUR): 10960028.89
Participants: 17
Project status: CLOSED

CHEOPS proposes to develop three different Hall Effect Thruster electric propulsion systems: a dual mode EPS for GEO applications, a low power for LEO applications and a >20 kW high thrust EPS for exploration applications. Each of these will be developed according to market needs and drivers applying incremental technology changes to existing EPS products. The development approach will follow the ESA ECSS approach and the dual mode and low power are targeting a System PDR review with 42 months from the project start. Development will cover the following elements: thruster, cathode, PPU and FMS. The project is perfectly aligned to the SRC guidelines published with the call. Through a detailed development plan the project will demonstrate their ability to achieve by the end of CHEOPS Phase II (2023) the following: a) TRL7-8 for dual mode and low power b) high power HET EPS TRL6. Common transverse activities will include advanced numerical design tools for electric propulsion which will further the understanding of the observable behaviour and interactions with the satellite platform and predict performances of a given design. This includes alternative propellants and the ability to estimate the system lifetime. Finally significant progress will be made in establishing a HET performances measurement standard and developing advanced non-intrusive tests for measuring thruster erosion. The CHEOPS consortium is led by SNECMA and is comprised of representatives of the biggest European Prime satellite makers, the full EPS supply chain and supported by academia.

Keywords: hall effect,competitiveness,in space propulsion,electric propulsion
SOUTHPARK - SOcial and Universal Technology HelPing to detect ARrivals via sdK (SOUTHPARK)

Framework: Horizon 2020 — Societal Challenges
Programme: Smart, green and integrated transport
Action type: SME instrument
Countries involved: Germany
Call: Small business innovation research for Transport (H2020-SMEINST-2-2014, 2014)
Start date: 2015-08-01
End date: 2018-07-31
Duration (months): 36.0
Total project cost (EUR): 1984718.56
EU funding (EUR): 1389297.7
Participants: 1
Project status: CLOSED

predict.io has been set up as a company to address individual, as well as societal problems related to urban mobility and road congestion by building a smart, integrated, technology-based, easy to use system that renders the traffic more efficient thereby decreasing negative effects on humans and the environment while at the same time fulfilling today's need for fast and individualised urban mobility. The technology is based upon an elaborated set of algorithms that can detect on mobile devices when a user arrives at a location in order to improve different kinds of traffic and mobility apps. The SOUTHPARK project is set up to fulfil two overall objectives: First, predicto.io will integrate the technology, with its automated start and stop detection in different mobility apps (including parking apps). This will be achieved when the SDK generates at least 1 million mobility data points a day for real-time applications as well as business analytics. These efforts will cover countries across the European Union. The goal is to enable more convenient, more reliable, safer, environmentally friendlier, and efficient mobility solutions. Second, the SOUTHPARK project will bring the arrival detection close to perfection. This will be reached by the reduction of localisation costs and implementation time. predcit.io will build up significant machine learning capacities that constantly improve the existing algorithms in order to provide faster, better anticipating, more adaptive and less battery consuming STOP detection. Fulfilling this objective will reduce the adaptation costs and time to localise to new settings by estimated 75%. The outcome of the project will be an ensemble of algorithms that had been tested on large scale in the operational environment. The arrival detection can be used in various mobility use cases and provide data that helps city planners and public transport authorities to better plan the future of urban transportation.

Keywords: social parking,crowdsourcing,machine learning
Active Surface Processes On Mars: A Laboratory, Field And Remote Sensing Study (ACTIVE_MARS)

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: Environment and Geosciences
Countries involved: United Kingdom
Call: Marie Skłodowska-Curie Individual Fellowships (IF-EF) (H2020-MSCA-IF-2014, 2014)
Start date: 2016-03-01
End date: 2018-02-28
Duration (months): 24.0
Total project cost (EUR): 183454.8
EU funding (EUR): 183454.8
Participants: 1
Project status: CLOSED

This study will identify and analyse ongoing geological activity across the whole of Mars in the form of the changing morphology of kilometre-scale “classical gullies” (Fig. 1). From this, we aim to determine whether these changes are caused by the action of liquid water, or dry frost (water or carbon dioxide). Such a study addresses key questions of ongoing martian habitability, planetary protection (i.e. limiting access for future missions to possible ‘wet’ environments) and current climate. Jan Raack, the Experienced Researcher (ER), has just published a study of one such gully: this can be used as a methodological template for a more ambitious project. The core of the project is a global search for change in martian gullies using 25cm/pixel HiRISE images. Thermal and spectral data will be used to determine the types of volatiles that are present as changes occur, thus constraining the triggering mechanism for flow. The core task is supported by Earth-based field work and laboratory experiments using a Mars simulation chamber. This multidisciplinary approach, combining remote sensing, field, and laboratory work is a powerful methodology, and also provides great skills development for the ER. Significant outreach and communication activities are a vital part of the project. We will use a variety of media (blogs, Twitter, conference presentations, press-releases of papers etc.), and also apply to the UK Royal Society to be part of the annual Summer Science Exhibition. Preparing for the proposal and the exhibition will provide a key learning experience for the ER, and develop proposal writing, public communication and project management skills. The three key outcomes of the project will be two peer-reviewed papers describing the distribution and triggering mechanism of martian gullies based on a synthesis of field, remote sensing and laboratory studies, and the Exhibition at the Royal Society, where the project results will be communicated to thousands people.
Nacelle cowl NExt generation Opening System (NNEOS)

Framework: Horizon 2020 — Societal Challenges
Programme: Smart, green and integrated transport
Theme: Public-private partnerships
Destination: Clean Sky 2
Action type: Innovation actions
Partnership: CS2 (Art-187)
Countries involved: Spain
Call: Innovative Nacelle cowl opening system (H2020-CS2-CFP09-2018-02, 2018)
Start date: 2019-10-01
End date: 2022-12-31
Duration (months): 39.0
Total project cost (EUR): 1026440.0
EU funding (EUR): 718508.0
Participants: 1
Project status: SIGNED

NNEOS (Nacelle cowl NExt generation Opening System) NNEOS project is born to enable the use of new engines architectures like the UHBR (Ultra-High Bypass Ratio) that require shorter and slimmer nacelles and as a result a new approach to mainteinability and accessibility of the engine. Main objectives of the project: -Improve safety and accessibility to engine zones for maintenance/reparation through the development of an electromechanical actuator that integrates the functionalities of opening/closing the cowls as well as holding them at the open position during maintenance task -Optimize weight and dimensions with a design that favours the integration within the nacelle available space envelope: -At a system level, provide a potential reduction for the volume required for the equipment by 15% -At a system level, the aim is to achieve a 10% weight reduction associated to the system and connections when compared to the current systems being used. -Contribute to the reduction of the development time of the future engine architectures by 10%, through the optimisation of system integration for the power plant systems Provide a friendly design that is easy to use but ensures a safe operation of the nacelles -Bring the technology to TRL5.

Keywords: nacelle door,electromechanical,trl6,hold open rod,uhbr,maintenance
Cyber security 4.0: protecting the Industrial Internet Of Things (C4IIoT)

Framework: Horizon 2020 — Industrial Leadership
Programme: Information and Communication Technologies
Action type: Innovation actions
Countries involved: Germany,Italy,Israel,Italy,Germany,Serbia,Serbia,Switzerland,Greece,Greece,France,France,United Kingdom
Call: Dynamic countering of cyber-attacks (H2020-SU-ICT-2018, 2018)
Start date: 2019-06-01
End date: 2022-05-31
Duration (months): 36.0
Total project cost (EUR): 6288708.75
EU funding (EUR): 4993533.75
Participants: 14
Project status: CLOSED

Recent trends in industrial technology and the adaptation of Industrial Internet of Things (ΙIοΤ), has emerged by the convergence of Operations Technology (i.e., traditional hardware and software systems) and Information Technology (i.e., advanced computing, data aggregation/analysis, and ubiquitous communication systems). IIoT has great potential to enable significant advances in optimizing operations among large number of increasingly autonomous control systems and devices, and can have a profound impact on many industry domains, where smart factories and logistics are among most notable cases. However, a major barrier towards IIoT adoption lies in cybersecurity issues that makes it extremely difficult to harness its full potential: IIoT systems dramatically increase the attack surface (introducing new security threats due to newly connected devices and protocols, making them more vulnerable to interference), the disruption of process controls, the theft of intellectual property, the loss of corporate data, and the industrial espionage. C4IIoT will build and demonstrate a novel and unified IIoT cybersecurity framework for malicious and anomalous behavior anticipation, detection, mitigation, and end-user informing. The framework provides a holistic and disruptive security-enabling solution for minimizing attack surfaces in IIoT systems, by exploiting i) emerging security software and hardware protection mechanisms; ii) state of the art machine and deep learning and privacy-aware analytics; iii) novel encrypted network flow analysis; iv) secure-by-design IIoT device fabrication; and v) blockchain technologies, to provide a viable scheme for enabling security and accountability, preserving privacy, enabling reliability and assuring trustworthiness within IIoT applications. The C4IIoT framework will be demonstrated and validated on two carefully selected use cases in real world environments, namely Enabling security IIoT in i) Inbound Logistics and ii) a Smart Factory

Keywords: industrial internet of things iiot,industry 4 0,logistics 4 0,edge to cloud security,hardware enabled security,machine learning,behavioural analysis,accountability,trustworthiness,assurance
Robotic embodiment of a meta-learning neural model of human decision-making (MetaBot)

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: Life Sciences
Countries involved: Italy
Call: Individual Fellowships (H2020-MSCA-IF-2017, 2017)
Start date: 2018-05-01
End date: 2020-04-30
Duration (months): 24.0
Total project cost (EUR): 168277.2
EU funding (EUR): 168277.2
Participants: 1
Project status: CLOSED

The combination of empirical testing with computational modeling is the most promising path in neuroscience of decision-making. Nonetheless, neuro-computational models of decision-making are still affected by two main limitations. First, computer simulations, typically used for testing neural models, represent the environment in a very simplistic way, exposing the computational models to “toy problems”. Second, computational neuroscience often neglects that bodily processes do not simply “execute” what is decided centrally, but are part of cognitive processing itself (embodied cognition). The main goal of this project is to solve these two limitations and to open a new path in cognitive and computational neuroscience of decision-making. We plan the embodiment in a humanoid robotic platform (iCub) of a novel neuro-computational model, representing the state of the art in modeling neurobiology of decision-making. This neural model, the Reinforcement Meta-Learner (RML), generates emergent (i.e., homunculus-free) cognitive control signals and supports learning to solve complex decision problems by self-regulating its internal parameters (meta-learning). In simplified and disembodied computer simulations, the RML already revealed to be exceptionally successful in explaining many different experimental data sets (both neural and behavioural) from different domains. The RML embodiment would represent one of the few cases where a neural model, born completely in the domain of cognitive neuroscience, would be embodied in a humanoid robot. The fusion of cognitive neuroscience and humanoid robotics will allow to investigate the role of embodiment in decision-making in real world problems (contribution to neuroscience), and it also would represent a unique opportunity to test the effectiveness of the RML to be a new way for developing genuinely autonomous decision-making in robots (contribution to robotics).

Keywords: neuroscience of decision making,reinforcement learning,embodied cognition,intelligent robotics