Data-Gouv-ML/pcri-actions-marie-curie-participations-et-projets-laureats huggingface dataset:
Projet SUPER-QD (Horizon Europe, appel à projets 2023)
Action : Postdoctoral Fellowships - Global Fellowships
Panel : Chemistry
Statut du projet : SIGNED

Photonic integrated chips are key for the EU’s pursuit of faster and more efficient computers, aiming to support the Digital Revolution while reducing the costs of ICT. However, progress in photonic devices is held back by challenges in the miniaturization of on-chip light sources. SUPER-QD aims to tackle these challenges by using Superlattices of lead halide perovskite Quantum Dots as micron-size on-chip emitters. Thanks to their color-tunable and bright fluorescence, these nanocrystals solids are efficient micron-size light down-converters, that will allow implementing more color channels per device without compromising miniaturization. Moreover, the coupling between quantum dots results in superior exciton mobility and emission from collective quantum states (superfluorescence), which are promising for future applications in transceivers and quantum computers. SUPER-QD comprises four tasks: 1) Quantum Dots prepared via wet chemistry are assembled into Superlattices with tunable structure. 2) Innovative diffraction techniques are employed to characterize Superlattices, with a focus on structural and energetic disorder. 3) Collective optical properties are studied via space- and time-resolved spectroscopies to discover new structure-coupling relations, with the goal of tuning the Superlattices quantum light emission through their structure. 4) Finally, Superlattices with optimized properties will be installed in Integrated Photonic Chips, to demonstrate on-chip down-converting optical amplification upon photoexcitation from an integrated blue laser. These proof-of-concept devices will create new connections between colloidal nanomaterials and photonic integrated chips, leading to groundbreaking advancements in both fields. SUPER-QD will be hosted by Lund University and the Massachusetts Institute of Technology, leveraging the Fellows’ and Host Institutions’ expertise to ensure a mutual benefit from the Action and the success of the ambitious goals of the project.

Mots clés : nanocrystal, quantum dot, superlattice, self assembly, lead halide, perovskite, exciton diffusion, superfluorescence, structure property relation, photonic integrated chip, x ray diffraction, disorder

Participants :
- Université de Lund (Suède) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 282168.0 €
- Institut de technologie du Massachusetts (Etats-Unis) — Partner, associated partner, Enseignement supérieur ou secondaire, subvention : 0.0 €
Projet NoF-LiME (Horizon Europe, appel à projets 2023)
Action : Postdoctoral Fellowships - Global Fellowships
Panel : Chemistry
Statut du projet : SIGNED

In the pursuit of the EU Green Deal’s carbon neutrality goals, there's an immediate need for advanced energy storage systems. Lithium-metal batteries (LMBs) present a promising solution, offering nearly double the energy density of current Li-ion batteries, although they currently suffer from a reduced cycle life. This is due to the inefficient lithium plating/stripping and the eventual formation of Li dendrites.  Current trends in electrolyte engineering for LMBs focus on fluorinated salts and additives, which produce a LiF-rich solid-electrolyte interphase (SEI). However, recent studies suggest that Li2O might be a more desirable SEI component. The NoF-LiME project builds on this change of paradigm by focusing on fluorine-free salts for LMB electrolytes, with the aim of producing a Li2O-rich SEI. The project involves the synthesis and evaluation of novel sulfonimide salts, including the study of the cation-anion interactions in solution and their electrochemical performance. Success in this venture will mark a substantial leap away from the conventional reliance on F-rich compounds, showcasing the potential to formulate more sustainable and environmentally friendly electrolytes for next-generation batteries. Additionally, beyond its scientific contributions, the project will equip the researcher, Dr. Juan Forero-Saboya, with a distinctive skill set in battery electrolyte research and development, complementary to his current expertise. Guiding the NoF-LiME project is a team of recognized experts in the field with complementary knowledge: Dr. Montserrat Casas-Cabanas at CIC energiGUNE in Spain (specializing in cathode materials), Prof. Betar Gallant at the Massachusetts Institute of Technology (experienced in SEI analysis and quantification), and Prof. Alexis Grimaud at Boston College (expert in battery electrolyte formulation and assessment).

Mots clés : non aqueous electrolytes, li metal batteries, solid electrolyte interphase sei , lithium electroplating

Participants :
- Boston College (Etats-Unis) — Partner, associated partner, Enseignement supérieur ou secondaire, subvention : 0.0 €
- CIC energigune (Espagne) — Coordinator, beneficiary, Recherche, subvention : 261380.64 €
- Institut de technologie du Massachusetts (Etats-Unis) — Partner, associated partner, Enseignement supérieur ou secondaire, subvention : 0.0 €
Projet QuARTEC (Horizon Europe, appel à projets 2024)
Action : Postdoctoral Fellowships - Global Fellowships
Panel : Physics
Statut du projet : SIGNED

A major focus of current quantum technology research is noise mitigation, whether through material improvements, decoupling strategies, or the design of noise-resistant quantum devices. Traditional non-adaptive methods struggle with unpredictable errors, such as solid-state defects, quantum information leakage, and correlated noise across qubits, limiting their efficiency. In the Quantum Adaptive Real-time Error Correction (QuARTEC) project, I will implement a novel approach that continuously monitors noise fluctuations and dynamically adjusts qubit control signals, optimizing quantum error correction (QEC) in real time. This builds upon my experience in real-time quantum feedback with single quantum bits (qubits).  By employing adaptive real-time techniques, QuARTEC addresses the limitations of conventional methods, significantly enhancing the stability and scalability of quantum processors while relaxing demanding error correction thresholds. I will receive high-fidelity multi-qubit operation training from experts at MIT and the University of Regensburg. The training provided through QuARTEC, with support from the MSCA-PF, will equip me to pursue a leadership role in the quantum field, whether in academia or industry.  The project will shift the burden of noise resilience from fragile quantum hardware to robust classical control systems. QuARTEC will leverage the synergy between quantum control, computation, and computer science to drive the next generation of quantum computing technologies.

Mots clés : quantum computing, quantum feedback, quantum control, superconducting qubits, spin qubits

Participants :
- University of Regensburg (Allemagne) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 401232.0 €
- Institut de technologie du Massachusetts (Etats-Unis) — Partner, associated partner, Enseignement supérieur ou secondaire, subvention : 0.0 €
Projet HydroMOF (Horizon Europe, appel à projets 2021)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Chemistry
Statut du projet : CLOSED

Hydrogen storage is a key technological barrier to the development and widespread use of hydrogen energy in transportation, stationary, and portable applications. The safe and efficient storage of H2 is an important and still challenging issue. In this regard, metal-organic frameworks (MOFs) possessing large surface areas, a variety of topological/chemical structures, high porosities, and high stabilities are considered promising nanoporous materials for gas storage applications. Theoretical studies have shown that electric fields can promote gas storage in MOFs by inducing controlled structural changes, which has recently been experimentally confirmed.  To unravel the underlying mechanisms at the atomic level, I aim to investigate the H2 storage characteristics of electric field responsive MOFs by combining machine learning (ML) and molecular modeling methods. In order to model switchable MOFs, I will construct machine learning potentials and use them in Molecular Dynamics (MD) simulations in order to overcome the restricted time and length scales of ab-Initio MD, and the accuracy and reliability concerns of MD. In order to determine the H2 uptakes of the MOFs, I will push the limits further and combine machine learning potentials with the Grand Canonical Monte Carlo (GCMC) simulations. The main research objectives are to generate accurate machine learning potentials with a low computational time cost, determine how selected MOFs react to an applied electric field, control pore opening/closing, control and improve H2 uptake by switching electric field, determine the impact of an electric field on the interaction between the host and H2 as well as on the presence of different adsorption sites. This project has the potential to be a “door-opener” for fast and accurate design of switchable MOFs and boosting their applications in H2 storage by providing a fundamental perspective.

Mots clés : machine learning methods in chemistry

Participants :
- Université de la Ruhr à Bochum (Allemagne) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 142265.52 €
Projet ACROBAT (Horizon Europe, appel à projets 2021)
Action : Postdoctoral Fellowships - Global Fellowships
Panel : Information Science and Engineering
Statut du projet : CLOSED

Deep Neural Networks (DNNs) are the fundamental component in most artificial intelligence applications. With the increasing number of applications based on artificial intelligence, the performance and energy efficiency of architectures running these algorithms have become crucial, especially for battery-powered platforms. In this work, I propose an energy optimizing memory design framework with a special SRAM/in-memory-computing structure. It also utilizes datapath optimization techniques like quantization and pruning with a fine-level assignment. Compared to other hardware accelerator studies for DNN processing, in this work, I will show that this special memory design, together with the architectural datapath optimization techniques, will have a much better capability of finding the Pareto optimal point in the energy-accuracy trade-off and increase the profitability of the final design.

Mots clés : in memory computing, sram, low power, deep neural networks, hardware acceleration

Participants :
- Université Bilkent (Turquie) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 239282.64 €
- Stmicroelectronics (crolles 2) sas (France) — Partner, associated partner, Organismes privés (hors enseignement), subvention : 0.0 €
- Institut de technologie du Massachusetts (Etats-Unis) — Partner, associated partner, Enseignement supérieur ou secondaire, subvention : 0.0 €
Projet ACCELERATE-PER (Horizon Europe, appel à projets 2021)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Physics
Statut du projet : SIGNED

The development of sustainable energy production technologies, such as new types of solar cells, has traditionally taken decades. These research cycles need to be accelerated in order to respond to the urgent climate change crisis. Perovskite solar cells (PSCs) are a recent technology that boast high electricity production efficiencies, however they suffer from insufficient lifetimes. Since there are thousands of material candidates even for a single layer of a PSC, it is challenging to search for stable materials and infer device degradation mechanisms. This project aims to implement machine learning (ML) as a part of the solution. I will create an accelerated, ML-assisted research cycle for improving the lifetime of PSCs: I will focusing on optimizing the composition of the light absorbing layer – perovskite – for stability. I will show the resulting stability improvements in full PSCs and develop faster inference of the remaining PSC degradation mechanisms. The acceleration in the cycle arises from i) using ML to save experimental bandwidth, ii) designing experiments that are directly compatible with ML (opposed to first collecting data and then figuring out how to use it with ML), and iii) maximizing effectiveness by teaching physics to the ML algorithm. For example, at the materials level, the algorithm needs to know that certain perovskite compositions do not exist as mixed materials according to density functional theory. The physics integration aligns ML algorithms with physical reality and alleviates data scarcity that has traditionally hindered the use of ML in experimental science. My highly collaborative and interdisciplinary project demonstrates the potential of integrated ML-assisted research cycles in accelerating stability research, and develops applied ML methods applicable to optimization in both research and industry. The project leads to more stable PSCs, thus taking us closer to sustainable energy production.

Mots clés : accelerated research, machine learning, perovskite, solar cells, stability, physics informed machine learning, bayesian methods

Participants :
- Université Friedrich-Alexander d'Erlangen-Nuremberg (Allemagne) — Partner, associated partner, Enseignement supérieur ou secondaire, subvention : 0.0 €
- Université Aalto (Finlande) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 199694.4 €
- Institut de technologie du Massachusetts (Etats-Unis) — Partner, associated partner, Enseignement supérieur ou secondaire, subvention : 0.0 €
Projet SEAFRONT (Horizon Europe, appel à projets 2021)
Action : Postdoctoral Fellowships - Global Fellowships
Panel : Information Science and Engineering
Statut du projet : SIGNED

Clean freshwater is an essential ingredient for healthy human life. However, over 1.1 billion people worldwide lack access to freshwater. With our already depleted natural freshwater resources and push towards climate neutrality, outlined by the UN’s Sustainable Development Goals, there is significant stress on the world’s water purification technologies. Capillary-driven solar evaporation provides a very promising basis for the development of cost-effective, deployable, and eco-friendly freshwater solutions to deal with this pressing global challenge. Solar evaporation is energy intensive, however, and the contamination of the capillary structures can block fluid pathways, leading to a low water yield. The concept of exploiting hydrogels as capillary-driven evaporators (CDE) in carbon-free solar desalination offers the exciting prospect of high efficiencies, cost-effective materials, and longevity. However, the transport characteristics, thermo-fluidic behaviour, and in situ structural dynamics that affect freshwater generation, are not properly understood. This project aims to develop and demonstrate high-efficiency passive solar-water desalination devices by gaining an in-situ non-invasive insight into the underlying physics of hydrogel CDEs using x-ray inspection (XRI). Prof. Evelyn N. Wang’s research lab at MIT (Device Research Laboratory, DRL) is a global leader in nanoscale transport phenomena, materials chemistry, and converting nanoscale to the device-level. The DRL will train me in these areas, and provide facilities for fabrication, XRI, and device-level solar-water simulation. During the outgoing phase, I will be incorporated into MIT’s training environment, thereby enabling my personal growth and career development, understanding of climate challenges, and awareness of diversity issues. On return to the Bernal Institute, I hope to establish myself as a leading investigator in the clean water sector, creating a new research group within Europe.

Mots clés : desalination, clean water, renewable energy sources, solar evaporation, capillary driven evaporation, porous media, hydrogels, water scarcity, sustainable design

Participants :
- Université de Limerick (Irlande) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 278571.36 €
- Institut de technologie du Massachusetts (Etats-Unis) — Partner, associated partner, Enseignement supérieur ou secondaire, subvention : 0.0 €
Projet DECODE (Horizon Europe, appel à projets 2022)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Environment and Geosciences
Statut du projet : SIGNED

Earthquakes are a major threat to humankind, causing damage above 500 billion USD and more than 400,000 fatalities within the last 20 years. Nonetheless, the generation of large earthquakes remains poorly understood. Recent research suggests that the key to deciphering this preparatory phase lies in the complex interplay of seismic and aseismic processes. Three event types are of genuine interest: slow slip events (SSEs), which are episodic aseismic deformations; low-frequency earthquakes (LFEs), a type of earthquake depleted in high-frequency energy; and regular earthquakes.  A key factor limiting the understanding of the seismic-aseismic interplay are incomplete LFE catalogs, caused by the difficulty to detect these events. Therefore, in this project I will develop a novel detection method for LFEs building on recent advances in deep learning. Applying this method, I will compile comprehensive catalogs for three regions: Northern Chile, Nankai (Japan) and Nicoya (Costa Rica). These catalogs, in conjunction with continuous geodetic records, SSE catalogs and seismicity catalogs, will allow me to study the seismic-aseismic interplay. This will reveal physical driving mechanisms of the seismic-aseismic interplay and give insights into the preparation of large earthquakes. This will contribute towards the accurate assessment of seismic hazard and the preparedness for seismic events.  I will conduct this project at the Université Grenoble Alpes, with a secondment at the Massachusetts Institute of Technology. My scientific background in interdisciplinary research between deep learning and seismology, is complemented by my supervisiors: Anne Socquet, expert on aseismic processes and subduction zones; and William Frank, expert in the detection and characterisation of LFEs. The project, together with targeted training activities, will refine my scientific profile and extend my skill set, enabling me to define my independent research agenda and pursue a career in research.

Mots clés : low frequency earthquakes, slow slip events, deep learning, earthquake preparatory phases, subduction zones

Participants :
- Université Grenoble Alpes (France) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 195914.88 €
- Institut de technologie du Massachusetts (Etats-Unis) — Partner, associated partner, Enseignement supérieur ou secondaire, subvention : 0.0 €
Projet Trans Modernismo (Horizon Europe, appel à projets 2022)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Social Sciences and Humanities
Statut du projet : CLOSED

Birth of the Marimacho: Modernismo’s Trans* Cultural Productions in Latin America analyzes the emergence of a new gender expression in early-twentieth-century Latin American literature, science, and visual culture: the ‹‹marimacho››. In the Hispanic tradition, marimacho is the umbrella notion that may refer to a sexist slur as much as a modern form of non-binary gender, a transmasculine identification, or a lesbian identity. This project examines the aesthetic construction of this hybrid, counter-cultural, and gender-dissident figure in an extensive cultural repertoire that includes novels, plays, films, leaflets, medical studies, prison and mental hospital records, poems, and newspaper and tabloid articles. I seek to increase the understanding of the region’s politics of gender and sexuality during the modernizing era (1880s-1930s), that is, before the solidification of LGBTQ activism, pride literature, and minority social movements of the Global 1960s. In response to the new gender dynamics led by cosmopolitan networks of first-wave feminism, the keepers of gender normativity created the marimacho as a monstrous version of conventional masculinity. The main objective of this research is to investigate why a broad range of cultural materials named queer women, non-binary individuals, and trans* men as marimachos, as gender hackers that put at stake the futures of heteronormativity, reproduction, and family life.

Mots clés : nineteenth century studies, sexuality studies, transgender studies, lgbtq memory, medical humanities, orientalism, masculinity, history of sexology, queer popular culture, fin de si cle studies

Participants :
- Université de Cologne (Allemagne) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 173847.36 €
Projet NISP (Horizon Europe, appel à projets 2023)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Life Sciences
Statut du projet : SIGNED

Disease in crop plants is the major cause of lost productivity and economic hardship globally. New environmentally sustainable approaches for enhancing plant resistance to newly emerging pathogen strains are much needed. Recent studies by the groups of Jijie Chai (at Uni. Köln/Tsinghua University) with Jane Parker (MPIPZ) led to the discovery of four chemically related nucleotide-based compounds that are produced naturally by plants upon pathogen attack to promote immune responses against a broad range of diseases. The biochemical modes-of-action of these small molecules was determined and the chemical synthesis of several pure analogs successfully achieved. These advances provide a basis to (i) explore further the immune-potentiating activities and dynamics of nucleotide-based signals in plant cells and tissues, and (ii) develop and test modified forms of the signaling molecules for increased uptake, bioactivity and stability in plants. The aim of this proposal is to combine knowledge of nucleotide chemistry and modifications (Kath-Schorr) with in vitro and in vivo functional assays (Parker) with a view to designing a disease resistance-potentiating agent with broad efficacy on crops.

Mots clés : nucleotide based messengers, plant innate immunity, nucleotide binding domain leucine rich repeat nlr signaling, rna biology

Participants :
- Société Max-Planck pour le développement des sciences (Allemagne) — Coordinator, beneficiary, Recherche, subvention : 189687.36 €
- Université de Cologne (Allemagne) — Partner, associated partner, Enseignement supérieur ou secondaire, subvention : 0.0 €
Projet NOZONE (Horizon Europe, appel à projets 2023)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Chemistry
Statut du projet : SIGNED

Olefins are feedstocks readily available from petroleum and vegetable biomass with an integral role in the preparation of high-value materials. In particular, olefin ozonolysis used to introduce oxygen atoms and convert these molecules into a broad spectrum of synthetic intermediates like aldehydes, ketones and carboxylic acids.  So far ozonolysis reactions mostly adopted by the bulk chemical industry which uses it on simple materials. The fine chemical sectors (pharmaceutical and agrochemical industries) do not use this reactivity mostly due to safety concerns in handling ozone.  The Leonori group has recently demonstrated that photoexcited nitroarenes can be used as ozone surrogates for the oxidative cleavage of olefins. This project seeks to understand the key mechanistic factors that govern the reactivity so that generalization and application by the broad chemical community might be possible.  The completion of such a timely and relevant mechanistic project at RWTH Aachen University will be facilitated by generating, transferring, sharing and disseminating knowledge, and will enhance The Researcher’s future career following the training plan envisioned.

Mots clés : photoexcited nitroarene, flash laser photolysis, mechanistic studies

Participants :
- Université technique de Rhénanie-Westphalie à Aix-la-Chapelle (Allemagne) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 173847.36 €