Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Deep learning enhanced numerical simulations of mixed-dimensional models for subsurface flow (MiDiROM)

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: Mathematics
Countries involved: Italy
Call: Individual Fellowships (H2020-MSCA-IF-2020, 2020)
Start date: 2022-01-16
End date: 2024-01-15
Duration (months): 24.0
Total project cost (EUR): 171473.28
EU funding (EUR): 171473.28
Participants: 1
Project status: SIGNED

Exploiting the subsurface as an energy storage site is a crucial step to meet some of the challenges arising from energy production by renewable sources. For such applications, a proper understanding of the subsurface flow is essential and calls for efficient and effective computational models. The main difficulties in the mathematical modeling arise from the highly varying material parameters as well as the presence of fracture networks, the latter aspect being crucial due to its leading impact on flow characteristics. These features are a leading source of computational complexity, often making it infeasible to use full order simulation models in real-life situations, particularly when there is the need to investigate different scenarios and/or quantify uncertainties. In this project, I will build on my acquired expertise in mixed-dimensional models of fractured porous media, where fractures are represented as a collection of immersed, lower-dimensional manifolds. Although these models lead to accurate numerical methods, the computational cost remains impractically high. To overcome this, I propose to develop reduced order models for mixed-dimensional flow problems. In particular, I will investigate how to properly capture non-linear dependencies on model parameters such as the fracture network configuration by extending and adapting the deep learning enhanced reduced order modeling techniques recently investigated by researchers of the host institution. The combination of research fields is reflected by the composition of the project: the proponent has a strong theoretical background in analyzing and discretizing mixed-dimensional models whereas the supervisor and associated host institute are leading experts in fractured porous media flow and application-driven reduced order modeling. Additionally, the host institution offers the necessary research and complementary skill training for the proponent to further develop and thrive as an independent researcher.

Keywords: reduced order modeling,machine learning,mixed dimensional computational models
Security In trusted SCADA and smart-grids (SCISSOR)

Framework: Horizon 2020 — Industrial Leadership
Programme: Information and Communication Technologies
Action type: Research and Innovation actions
Countries involved: Italy,Italy,Austria,Italy,Belgium,Poland,Switzerland,France
Call: Cybersecurity, Trustworthy ICT (H2020-ICT-2014-1, 2014)
Start date: 2015-01-01
End date: 2018-02-28
Duration (months): 38.0
Total project cost (EUR): 3989850.0
EU funding (EUR): 3534850.0
Participants: 10
Project status: CLOSED

In traditional industrial control systems and critical infrastructures, security was implicitly assumed by the reliance on proprietary technologies (security by obscurity), physical access protection and disconnection from the Internet. The massive move, in the last decade, towards open standards and IP connectivity, the growing integration of Internet of Things technologies, and the disruptiveness of targeted cyber-attacks, calls for novel, designed-in, cyber security means. Taking an holistic approach, SCISSOR designs a new generation SCADA security monitoring framework, comprising four layers: i) a monitoring layer supporting traffic probes providing programmable traffic analyses up to layer 7, new ultra low cost/energy pervasive sensing technologies, system and software integrity verification, and smart camera surveillance solutions for automatic detection and object classification; ii) a control and coordination layer adaptively orchestrating remote probes/sensors, providing a uniform representation of monitoring data gathered from heterogeneous sources, and enforcing cryptographic data protection, including certificate-less identity/attribute-based encryption schemes; iii) a decision and analysis layer in the form of an innovative SIEM fed by both highly heterogeneous monitoring events as well as the native control processes’ signals, and supporting advanced correlation and detection methodologies; iv) a human-machine layer devised to present in real time the system behavior to the human end user in a simple and usable manner. SCISSOR’s framework will leverage easy-to-deploy cloud-based development and integration, and will be designed with resilience and reliability in mind (no single point of failure). SCISSOR will be assessed via i) an off-field SCADA platform, to highlight its ability to detect and thwart targeted threats, and ii) an on-field, real world deployment within a running operational smart grid, to showcase usability, viability and deployability.

Keywords: critical infrastructures,scada,industrial control systems,attribute based encryption and access control,security monitoring,embedded cloud,system security,environmental sensing,surveillance
Extreme Quantum Matter in Solids (ExQuiSid)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Advanced grants
Action type: ERC actions
Panel: Condensed matter physics
Panel description: Structure, electronic properties, fluids, nanosciences, biological physics
Countries involved: Germany
Call: ERC Advanced Grant (ERC-2017-ADG, 2017)
Start date: 2018-06-01
End date: 2024-05-31
Duration (months): 72.0
Total project cost (EUR): 2500000.0
EU funding (EUR): 2500000.0
Participants: 1
Project status: SIGNED

Quantum stochastic processes in solids, representing many-body systems par excellence, are believed to lead to extreme forms of quantum entanglement and non-local correlations (extreme quantum matter), that offer a well-defined starting point for an understanding of a wide range of anomalous materials properties, as well as emergent electronic phases such as magnetically mediated superconductivity or partial spin and charge order. While overwhelming experimental evidence clearly suggests a breakdown of traditional concepts such as well-defined quasi-particle excitations, the striking present-day disagreement between experiment and theory may be traced to the lack of experimental information on the spectrum of quantum stochastic many-body processes in solids in the low-energy and low-temperature limit close to and far from equilibrium. ExQuiSid will advance the understanding of the nature of extreme quantum matter in the most extensively studied model systems, notably simple magnetic materials (insulators and metals) tuned through a quantum phase transition. For the proposed studies my group has implemented a new generation of methods covering for the first time neutron spectroscopy with an unprecedented nano-eV resolution even under large magnetic fields, transverse-field vector magnetometry, calorimetry and transport down to milli-Kelvin temperatures, and, ultra-high purity single-crystal growth combined with advanced materials characterisation. ExQuiSid will (i) solve long-standing mysteries in model-systems of extreme quantum phase transitions, (ii) experimentally enable and permit pioneering studies on the creation, nature and classification of non-equilibrium quantum matter in solids at ultra-low energies and temperatures, and (iii) experimentally enable and permit pioneering studies of quantum matter driven periodically out of equilibrium to identify dynamical quantum instabilities and dynamical quantum phases such as many body localisation.

Keywords: advanced neutron spectroscopy,low temperature physics,bulk properties,transport properties single crystal growth,quantum phase transitions,quantum materials,emergent phenomena,topology
Analytics for Biologics (A4B)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Innovative Training Networks (ITN)-European Training Networks
Action type: Marie Skłodowska-Curie actions
Panel: Chemistry
Countries involved: Austria,Germany,Germany,Germany,Norway,Sweden,Netherlands,Netherlands,Denmark,United Kingdom
Call: Innovative Training Networks (H2020-MSCA-ITN-2017, 2017)
Start date: 2017-10-01
End date: 2022-03-31
Duration (months): 54.0
Total project cost (EUR): 3933617.4
EU funding (EUR): 3933617.4
Participants: 11
Project status: CLOSED

Qualitative and quantitative analysis and purification of therapeutic protein species (TP-S) – coded by the same gene, thus chemically often very similar – is one of the most challenging problems in analytical chemistry today. This problem is of huge impact in the area of therapeutic proteins (TPs) – a rapidly growing market – causing a high demand in specialists in the field of TP manufacturing. This demand can currently not be met by single European universities. In an Europe-wide joint research and training network the graduate school A4B will offer a specific training program yielding the required specialists. A4B-PhD students will develop solutions for the most urgent problems in TP production and analysis. Production of TPs is associated with the generation of poorly effective or even harmful species. For an effective removal of these species, A4B-students will develop improved purification methods based on advanced affinity and displacement chromatography. For controlling effectiveness and design of experiments, fast and reliable qualitative and quantitative detection methods are required. The development of these analytical methods will focus on the chemical composition of TP-S including their glycans and other posttranslational modifications (PTMs). We will use high-end electrophoretic, liquid chromatographic, and mass spectrometry approaches in combination with bioinformatics. The developed methods will be tested and used for improving protein production processes and therapy control. All A4B students will receive a basic education in manufacturing and marketing of TPS. Through their research projects the students will develop in depth expertise in one of the areas covered by the consortium. This project will thus generate urgently needed new methods for an improved analysis and purification of TP-S, while at the same time ensuring that well qualified young researchers are available for this rapidly growing area of the pharmaceutical industry.

Keywords: therapeutic proteins,mass spectrometry,glycosylation,post translational modifications,bioreactors,protein purification,down stream processing
THOR – Total solution for High throughput surface enhanced Raman spectroscopy (THOR)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Proof of concept grants
Action type: ERC actions
Countries involved: Denmark
Call: ERC Proof of Concept Grant (ERC-2015-PoC, 2015)
Start date: 2016-05-01
End date: 2017-10-31
Duration (months): 18.0
Total project cost (EUR): 148333.75
EU funding (EUR): 148333.75
Participants: 1
Project status: CLOSED

The aim of the PoC project is to develop a portable, low-cost device for highly sensitive and fast identification of molecules. For demonstration of the capability of the device we will focus on (i) toxic compounds in food and home environment, and (ii) compounds that are important for the cosmetics research industry. These applications all have the need of sample pretreatment, scalability, sensitivity, speed and ease of use that the device will offer. In addition, detection of both compound classes is commercially important. The aim is to, within the project period, to identify the most viable commercialization process. The device consist of two major parts: (i) microfluidics disc and (ii) Raman scattering detection system. (i) Microfluidics disc. Fluids that contain target molecules can be guided through microfluidics channels using controlled centrifugation. Analyte can be manipulated and introduced into reservoirs that contain so-called surface-enhanced Raman scattering (SERS) substrates. SERS substrate is a nanostructured surface that is used to amplify the Raman scattering signal. Amplification of the Raman scattering signal enables identification of compounds at extremely low concentrations. We employ world-leading SERS substrates (“amplifiers”) that are successfully sold worldwide. (ii) Molecular identification is recorded using a portable Raman scattering system. The detection system is designed to collect large amounts of data to perform a more reliable statistical analysis. Every component in the readout system is based on existing technologies which dramatically reduces device manufacturing costs. To the best of our knowledge, there are no similar SERS-based commercial products. Compared to existing Raman scattering systems, our technology will offer a much cheaper, automated solution for molecular identification.

Keywords: microfluidics,portable raman device,surface enhanced raman scattering,sers
High-performance biomechanical model of combined immunotherapy and anti-angiogenic cancer treatment (ImmunoMECH)

Framework: Horizon 2020 — Spreading excellence and widening participation
Programme: Widening participation and spreading excellence
Theme: Other Widening
Action type: Marie Skłodowska-Curie actions
Countries involved: Cyprus
Call: Widening Fellowships (H2020-WF-01-2018, 2018)
Start date: 2019-06-17
End date: 2021-06-16
Duration (months): 24.0
Total project cost (EUR): 145941.12
EU funding (EUR): 145941.12
Participants: 1
Project status: CLOSED

Inefficient delivery of cellular and molecular medicines to solid tumors can reduce dramatically the efficacy of treatment and affect negatively patient’s survival. This explains in large part why standard chemo- and immune-therapies often fail to treat specific cancer types, even though these therapies are potent enough to eradicate cancer cells. Abnormalities in the structure of the tumor vasculature hinder tumor perfusion and as a result the systemic delivery of the medicines. In many tumor types, blood vessels are hyper-permeable, leaving large interendothelial openings, which causes fluid loss from the vascular to the interstitial tumor space. Vessel hyper-permeability can reduce tumor blood flow, rendering tumors hypo-perfused and hypoxic. Impaired blood supply and hypoxia help cancer cells evade the immune system and increase their invasive and metastatic potential. Normalization of the tumor vasculature is a clinical strategy to repair vascular abnormalities in order to improve perfusion, oxygenation and delivery of medicines. Immunotherapy is gaining interest as an effective therapeutic approach against cancer, but only a subset of patients receiving immunotherapy exhibit sustained tumor shrinkage. Here, we hypothesize that vascular normalization can improve immunotherapy. The objective of the proposed research is the optimal design of the combined immunotherapy and vascular normalization therapeutic approach. To this end, a numerical and experimental study is proposed to model and experimentally validate the vascular normalization procedure, focusing on its combined effects with immunotherapeutic drugs. The proposed research/training will complement the Applicant’s skills in high-performance computing, advanced optimization algorithms and artificial neural networks with the Host’s expertise in tumor microenvironment and cancer drug delivery to enhance his professional maturity and promote international collaborations.

Keywords: cancer mathematical modeling,vascular normalization,immunotherapy,stochastic optimization,data driven simulation,high performance computing
Prototype system for a Copernicus CO2 service (CoCO2)

Framework: Horizon 2020 — Industrial Leadership
Programme: Space
Theme: Enabling exploitation of space data
Action type: Coordination and support actions
Countries involved: Germany,Germany,Germany,Spain,Italy,Germany,Cyprus,Switzerland,Poland,Sweden,Norway,Belgium,Finland,Greece,France,France,France,France,Netherlands,Netherlands,Netherlands,United Kingdom,Portugal,United Kingdom
Call: Copernicus evolution – Research activities in support of a European operational monitoring support capacity for fossil CO2 emissions (H2020-IBA-SPACE-CHE2-2019, 2019)
Start date: 2021-01-01
End date: 2023-12-31
Duration (months): 36.0
Total project cost (EUR): 8999718.75
EU funding (EUR): 8999718.75
Participants: 26
Project status: SIGNED

To support EU countries in assessing their progress for reaching their targets agreed in the Paris Agreement, the European Commission has clearly stated that a way to monitor anthropogenic CO2 emissions is needed. Such a capacity would deliver consistent and reliable information to support policy- and decision-making processes. To maintain Europe’s independence in this domain, it is imperative that the EU establishes an observation-based operational anthropogenic CO2 emissions Monitoring and Verification Support (MVS) capacity as part of its Copernicus programme. The CoCO2 Coordination and Support Action is intended as a continuation of the CO2 Human Emissions (CHE) project, led by ECMWF. In the Work Programme, ECMWF is identified as the predefined beneficiary tasked to further develop the prototype system for the foreseen MVS capacity together with partners principally based on the CHE consortium. In addition, ECMWF will continue some of the work initiated in the VERIFY project as well. The main objective of CoCO2 is to perform R&D activities identified as a need in the CHE project and strongly recommended by the European Commission's CO2 monitoring Task Force. The activities shall sustain the development of a European capacity for monitoring anthropogenic CO2 emissions. The activities will address all components of the system, such as atmospheric transport models, re-analysis, data assimilation techniques, bottom-up estimation, in-situ networks and ancillary measurements needed to address the attribution of CO2 emissions. The aim is to have prototype systems at the required spatial scales ready by the end of the project as input for the foreseen Copernicus CO2 service element.

Keywords: capacity building,anthropogenic emissions monitoring system
Gas Diffusion Electrodes and Flow Cells for Photoelectrochemical CO2 Conversion into Multicarbon Alcohols (SolarFUEL)

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-2018, 2018)
Start date: 2020-12-01
End date: 2022-11-30
Duration (months): 24.0
Total project cost (EUR): 212933.76
EU funding (EUR): 212933.76
Participants: 1
Project status: CLOSED

Artificial photosynthesis, in which solar energy is directly used to generate fuels and useful chemicals from CO2 and water, is a promising solution to both energy crisis and global warming issues now-a-days. However, implementation of such a sustainable solar-fuel technology requires efficient light harvester and catalyst materials to power the uphill reaction. The proposed project is aimed to develop a novel flow cell set up with gas diffusion photocathode (GDP) for photoelectrochemical CO2 conversion into multicarbon alcohols (high energy density fuels). A layer by layer electrode fabrication method (systematic assembly of diffusion layer, photo-sensitizer, and co-catalyst materials) will be employed to develop a gas diffusion photocathode. Novel co-catalyst activation processes will be used to make the photocathodes active for multicarbon alcohol production. The innovative aspect of “SolarFUEL” is to employ a flow cell/GDP set up for the first time in photoelectrochemistry to produce alcohols from CO2. The cathodic solar CO2 conversion process will be coupled to an anodic solar water oxidation process. Operando spectroscopy studies (Raman, IR, and UV-Vis) will be carried out to monitor the catalyst systems and reaction pathways. The project being at the interface of material synthesis, photo-, electro-chemistry, and spectroscopy, will provide an excellent opportunity for the experienced researcher (ER) to develop profound scientific and technical expertise. In addition, the fellowship will allow the ER to gain complementary skills such as, manuscript preparation, public outreach, networking and collaboration which will be substantially helpful for his future independent career. The combination of the cutting-edge science and training excellence of the project will enhance the ER’s academic career prospect as well as improve the host’s international reputation.

Keywords: photoelectrochemistry,gas diffusion electrode,flow cell,co2 conversion,operando spectroscopy
Question Answering for MonitoRed Fuel Cell systEms (QuAre)

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: Information Science and Engineering
Countries involved: Greece
Call: Individual Fellowships (H2020-MSCA-IF-2020, 2020)
Start date: 2022-01-01
End date: 2023-12-31
Duration (months): 24.0
Total project cost (EUR): 165085.44
EU funding (EUR): 165085.44
Participants: 1
Project status: SIGNED

Modern advanced and high value fuel cell systems are monitored by multiple embedded sensors which transmit a large amount of data every few seconds. Unfortunately, service engineers are still faced with the challenging task of identifying the causes of a failure by manually investigating not only the streaming sensor data but also a wide range of structured, semi-structured and unstructured monitoring data. At the same time, they are required to have a thorough knowledge of the full operating mechanism. Our overarching aim is to utilise next generation deep learning and knowledge technology paradigms (i.e. ontology-based systems, knowledge-graph based systems) to represent this monitoring knowledge in a human and machine processible form such that decision-making processes can be automated and deeper engineering insights can be obtained. To achieve this, we will implement a radically cross-disciplinary methodological approach, by developing new spatio-temporal knowledge representations and reasoning and instilling them with natural language processing techniques. This will result in a novel paradigm for truly intelligent cyber physical systems. The QuAre paradigm will be put to test and fine tuned on the diagnosis and prognosis of polymer electrolyte fuel cell systems. On the training side, this project is designed to instill the applicant with a niche set of core skills on question answering over knowledge graph embeddings, knowledge management retrieval, and natural language generation; these will position the researcher at the fore-front of intelligent knowledge representation and establish her as a leading researcher in the field of question answering. The project is further designed to provide the researcher with cutting edge teaching, leadership, and communication skills so that by the end of this project she will be ready to pursue her first permanent academic position.

Keywords: question answering,knowledge representation and reasoning,fuel cell systems,diagnosis and prognosis,ontology