Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : SECANS (Horizon 2020, appel 2019, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Physical and analytical chemical sciences
Entité participante : Technical University of Munich — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : TUM
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1933750.0 €

As photovoltaic technologies gain prominence, an outstanding challenge is the development of systems that can robustly store solar energy with high density. Within this context, the capture of sunlight and its direct conversion to chemical fuels in artificial photosystems provides a promising route for sustainably meeting future energy demands. However, a central challenge is the lack of systems that can efficiently direct light excitations towards desired chemical products with high efficiency and stability under harsh reaction conditions. In recent years, advances in using thin films to protect chemically sensitive light absorbers have relaxed the requirement for intrinsically stable semiconductors and motivate an entirely new perspective for rational design of materials and interfaces. Within this context, SECANS aims to create the scientific basis for solar-to-chemical devices that achieve unprecedented combinations of efficiency and stability, enabled by targeted exploration and rational optimization of an underexplored class of materials – transition metal nitride semiconductors. The electronic structures of these materials can enable a favourable balance between large charge carrier mobility and high defect tolerance. However, due to the high stability of molecular nitrogen, the expansive range of possible nitrides is largely unexplored and their basic properties poorly understood. SECANS overcomes these challenges through an interdisciplinary approach that couples non-equilibrium semiconductor deposition and newly developed interface engineering methods, supported by advanced operando spectroscopies, to enable high efficiency light harvesting systems with self-healing interfaces. This project will develop novel nitride semiconductors optimized for solar-to-chemical energy conversion, elucidate the roles of defects and disorder on competitive kinetics within photochemical reaction cycles, and provide new insights into the science of photochemical stability.

Mots-clés : photoelectrochemistry,artificial photosynthesis,semiconductors,interface engineering,in situ and operando spectroscopy,metastable materials,non equilibrium synthesis of materials,disorder engineering,electrocatalysis
Projet ERC : SmartIR (Horizon 2020, appel 2019, Proof of concept grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Systems and communication engineering
Entité participante : University of Manchester — Pays : Royaume-Uni — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 150000.0 €

As satellites get more miniaturized, they place unique thermal control challenges. Because of their low masses, they experience large temperature variations in the very tough and rapidly varying outer space environment. However, due to the lack of efficient active infrared materials, dynamic control of thermal radiation from satellites has been a challenge. As a result of the research undertaken in the SmartGraphene (ERC-CoG-2016-682723), we have successfully demonstrated graphene-based active infrared (IR) surfaces which can electrically control its thermal emissivity over the entire IR spectra. These active IR surfaces can provide new enabling technologies for active control of thermal radiation and heat management for outer space applications. This project (SmartIR) aims to develop a prototype for adaptive thermal blankets using multilayer graphene. The proposed thermal blankets will consist of electrically reconfigurable and flexible active graphene layers integrated with radiation sensors and control electronics that can be conformally wrapped onto solid objects to dynamically modulate their thermal emission and absorption. This project will focus on demonstrating prototype thermal sheets, performance characterization in a space simulator and conducting a market feasibility study of the developed technology. The expected outcome of the project is to bring the technology to a development stage TRL 5-6 that could enable novel active thermal management

Mots-clés : graphene,thermal management,satellites,smart surfaces
Projet ERC : COMMUNICATE-HEAL-TH (Horizon 2020, appel 2020, Proof of concept grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Human Mind and Its Complexity
Entité participante : Leiden University — Pays : Pays-Bas — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 150000.0 €

As shown in the EXPECT-HEALTH project (617700), positive treatment expectations lead to improved health outcomes, while negative expectations have the opposite effect. To make use of this phenomenon in clinical practice, interventions have been developed to improve treatment expectations in patients, but these thus far only target the patient. A novel application would be to instead train healthcare professionals to optimize the expectations of their patients. This allows a much bigger audience to be reached with less investment. To make the training as efficient and effective as possible, state-of-the-art technological means must be used. We therefore propose an innovative virtual reality-based training tool for healthcare professionals, that will teach them to optimize expectations in their patients. In this project, the virtual training tool will be developed and brought to the pre-demonstration phase by a team of experts in expectancy effects on health and eHealth intervention development.

Mots-clés : patient provider interaction,placebo effects,nocebo effects,ehealth,virtual reality,virtual patients,intervention development,expectancy
Projet ERC : PROSANCT (Horizon 2020, appel 2016, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Institutions, Governance and Legal Systems
Entité participante : Graduate Institute of International and Development Studies — Pays : Suisse — Rôle : PI
Acronyme de l'entité : IHEID
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1499788.0 €

As the critical sanctions against Iran’s nuclear program demonstrate, the implementation of sanctions (SANCT) against nuclear proliferators (PRO) has lead to the creation of a global system of surveillance of the financial dealings of all states, banks and individuals, fostered by the United Nations Security Council (UNSC) resolutions. This is a new and unprecedented development in transnational governance. This research will apply a sociological perspective to the study of this new “transnational legal order” by analyzing how new actors, institutions and legal technologies shape the processes of norm-creation and rules-implementation in the field of nuclear nonproliferation. PROSANCT asks: How have the social characteristics of the actors in charge of designing and implementing sanctions influenced the creation of new norms in the field of nonproliferation? Which legal technologies and which discursive practices have these new actors developed to impose their authority and their legitimacy on the regulation of global financial transactions? Answering these questions will generate a better understanding of key processes in global governance: 1) the increasing role of the UNSC as a global legislator through top-down processes of norms diffusion; 2) the “financialization” of global regulation, with the increasing role played by international financial institutions, which were historically foreign to the field of nuclear nonproliferation; and 3) the “judicialization” of the enforcement of sanctions, and the associated reconfiguration of relations between executive and judicial authorities in charge of punishing nuclear proliferators and sanctions-evaders at the domestic level. To study these legal processes in various contexts (the United States and Europe), PROSANCT applies a multi-methods approach that combines interview-based methods with politicians, high-level bureaucrats and diplomats, and experts, and archival research.

Mots-clés : transnational legal fields,norms and sanctions,nuclear nonproliferation,financial regulation
Projet ERC : OPIOIDREWARD (Horizon 2020, appel 2018, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Human Mind and Its Complexity
Entité participante : University of Oslo — Pays : Norvège — Rôle : PI
Acronyme de l'entité : UiO
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1436014.0 €

As the opioid epidemic escalates, we must ask: why are opioids so addictive? Non-human animal research links addiction with the powerful relief opioids can offer to animals in distress. In humans, epidemiological and clinical studies converge upon social stressors and a poor social support network as key risk factors for addiction. Despite this, it is currently unknown how pre-drug distress might alter opioid drug effects. Tremendous resources are dedicated to charting how people feel after taking a drug, sidestepping the potentially profound influence of how people feel before they take the drug. Here, I will turn the current approach on its head. Using acute social distress induction before morphine administration in healthy humans, I will create a human model to determine the psychological, physiological and brain underpinnings of how social stressors increase opioids’ abuse liability. First, I will test the hypothesis that pre-drug distress enhances drug wanting (self-administration) but not drug liking (self-report) compared to drug effects in a control condition. Second, I will use opioid blockade to confirm or falsify the hypothesis that opioid drugs ‘hijack’ brain mechanisms underpinning social support. Third, I will determine to what extent opioid drug effects are dopamine-dependent by blocking dopamine before morphine administration. I will also apply computational modelling and functional imaging to elucidate the underlying brain mechanisms. Thus, the proposal offers a powerful new methodology for resolving hotly debated questions on the independent contributions of opioids and dopamine for reward and abuse liability. In sum, the project aims to achieve a breakthrough in our understanding of how a pre-drug social distress state can alter opioid drug mechanisms. The mechanistic understanding arising from this project could have profound implications for science, as well as for clinical care and new policies designed to contain the opioid epidemic.

Mots-clés : reward,social,addiction,opioid,distress,pain,psychopharmacology,neuroimaging,human
Projet ERC : e-NeuroPharma (Horizon 2020, appel 2018, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Synthetic Chemistry and Materials
Entité participante : Linköping University — Pays : Suède — Rôle : PI
Acronyme de l'entité : LiU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 3237335.0 €

As the population ages, neurodegenerative diseases (ND) will have a devastating impact on individuals and society. Despite enormous research efforts there is still no cure for these diseases, only care! The origin of ND is hugely complex, spanning from the molecular level to systemic processes, causing malfunctioning of signalling in the central nervous system (CNS). This signalling includes the coupled processing of biochemical and electrical signals, however current approaches for symptomatic- and disease modifying treatments are all based on biochemical approaches, alone. Organic bioelectronics has arisen as a promising technology providing signal translation, as sensors and modulators, across the biology-technology interface; especially, it has proven unique in neuronal applications. There is great opportunity with organic bioelectronics since it can complement biochemical pharmacology to enable a twinned electric-biochemical therapy for ND and neurological disorders. However, this technology is traditionally manufactured on stand-alone substrates. Even though organic bioelectronics has been manufactured on flexible and soft carriers in the past, current technology consume space and volume, that when applied to CNS, rule out close proximity and amalgamation between the bioelectronics technology and CNS components – features that are needed in order to reach high therapeutic efficacy. e-NeuroPharma includes development of innovative organic bioelectronics, that can be in-vivo-manufactured within the brain. The overall aim is to evaluate and develop electrodes, delivery devices and sensors that enable a twinned biochemical-electric therapy approach to combat ND and other neurological disorders. e-NeuroPharma will focus on the development of materials that can cross the blood-brain-barrier, that self-organize and -polymerize along CNS components, and that record and regulate relevant electrical, electrochemical and physical parameters relevant to ND and disorders

Mots-clés : organic electronics,organic bioelectronics
Projet ERC : M-PAC (Horizon 2020, appel 2016, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Fundamental constituents of matter
Entité participante : École polytechnique — Pays : France — Rôle : PI
Acronyme de l'entité : X
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1338172.43 €

As we push the frontier of particle physics to higher particle energies, conventional accelerator techniques are attaining their limits and new concepts are emerging. The use of an ionized gas —or plasma— circumvents the most significant barrier of conventional techniques by increasing the energy gained per unit length by several orders of magnitude. One class of plasma accelerators, relevant for high energy physics applications, consists in using a particle beam, « the driver », to excite a plasma wave, that is then used to accelerate the main particle beam. Research in this field requires large facilities, due to stringent conditions on the driver. In the M-PAC project, I propose to power plasma accelerators with laser-accelerated electron beams based on 100-TW-class laser systems, so as to miniaturize the so-called “beam-driven plasma accelerators”. The project crosses the boundary of the fields of research of laser acceleration and of beam-driven plasma acceleration. With these innovative miniature versions, the goal of the M-PAC project is then to tackle, through experiments and simulations, the next Grand Challenges facing the field of beam-driven plasma acceleration, bringing plasma accelerator technology to viability for high energy physics collider applications. They include the generation and preservation of the excellent beam quality required for high-energy colliders and next-generation light sources, the demonstration of high drive-to-main-beam energy efficiency and the acceleration of the antimatter counterpart of the electron, the positron. Finally, the miniature beam-driven plasma accelerators open new opportunities to push university-scale plasma-based light sources to the next level, both in terms of brightness and spectral range.
Projet ERC : NanoFLP (Horizon 2020, appel 2017, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Synthetic Chemistry and Materials
Entité participante : Centre national de la recherche scientifique — Pays : France — Rôle : PI
Acronyme de l'entité : CNRS
Type d'entité : Recherche
Financement ERC de l'entité : 1499875.0 €

Associating bulky and strong Lewis acid and base creates a Frustrated Lewis Pair (FLP). Traditionally, both FLP partners are molecules. Molecular FLPs have shown excellent abilities to catch and dissociate small molecules such as H2 in a heterolytic way, under mild conditions. The driving force is the destabilization of the initial acid-base adduct, sterically frustrated: it liberates a reactive pocket that catches the small molecule guest, and strongly lowers the activation energy for bond dissociation. The pristine and challenging concept of NanoFLP consists in replacing one of the molecular FLP partner, either the acid or the base, by an inorganic nanoparticle: the other molecular partner will adsorb on the surface and boosts the reactivity of the nanoparticle by creating a frustrated active site. I will demonstrate the versatility of NanoFLPs with three families of inorganic nanoparticles (metals, acidic oxides, basic oxides), illustrating the two schemes: nanoparticle is either the Lewis acid or the Lewis base. I will use probe molecules (CO2, H2, SO2 and N2O) to investigate the nature and reactivity of the active sites. All reactions should be achieved under much milder conditions (rt.-150 °C, 1-3 bars) than those required using similar nanoparticles in the absence of the molecular partner. I will fully describe the nanoparticle surface and the dynamics of the molecular partner using benchtop and synchrotron spectroscopies with in situ cells: infrared, nuclear magnetic resonance in solution, X-ray absorption and near-ambient-pressure X-ray photoelectron spectroscopy. In the last stage of the project, I will take advantage of the several active sites that one nanoparticle can bear to achieve combined reactions of two small molecules (reactants) on a single NanoFLP. NanoFLP proposes a new type of active site for utilizing small molecules as sources of C, N, S and O. It will open an avenue in the design of reactive interfaces, eg. for catalysis and sensors.

Mots-clés : frustrated lewis pairs,x ray spectroscopy
Projet ERC : CRACKNP (Horizon 2020, appel 2019, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer science and informatics
Entité participante : Eindhoven University of Technology — Pays : Pays-Bas — Rôle : Partner
Acronyme de l'entité : TU/e
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 0.0 €

Assuming P does not equal NP, there are no polynomial time algorithms for any NP-complete problem. This however still leaves a huge gap between anything super-polynomial and the exponential run times of trivial exhaustive search. The study of exact (exponential time) algorithms that aims to breach this gap is as old as Theoretical Computer Science (TCS) itself: Already in the 1960's, researchers found elementary (for modern standards) algorithms that greatly improve exponential the run times. But over time, TCS seems to have hit a brick wall: Somewhat embarrassingly, as of 2018 the run times of these classic algorithms are still the best known for many classic problems. This project aims to strike at the heart of this issue by designing the next generation of exact exponential time algorithms. To obtain these algorithms, we consider the most famous NP-complete problems such as Traveling Salesman, CNF-Sat and Knapsack, and we challenge ourselves to improve the classic currently best algorithms for them. These problems have served as a prototypical test bed for many algorithmic techniques with extensive applications, and thus their study provides an excellent road map towards our aim. Moreover, in the last few years it was shown that these algorithms have consequences that reach much further than originally thought: In particular, they would have a major impact on research in polynomial time algorithms, circuit complexity and parameterized complexity. Now is the right moment for this project, as recent work (partially by the PI) has given a first glimpse of a new algorithmic toolkit emerging: Advanced new tools to decompose solutions such as the representation method, the rank-based method and the polynomial method, are still barely exploited and studied in the field. In this project we will combine these (and many more) tools in novel ways that transcend existing approaches, and make cracks in the wall of NP-completeness seem entirely within reach.

Mots-clés : theoretical computer science,fixed parameter tractability,parameterized complexity,fine grained complexity,exact algorithms for np hard problems,exact exponential time algorithms
Projet ERC : CRACKNP (Horizon 2020, appel 2019, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer science and informatics
Entité participante : Utrecht University — Pays : Pays-Bas — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1499632.0 €

Assuming P does not equal NP, there are no polynomial time algorithms for any NP-complete problem. This however still leaves a huge gap between anything super-polynomial and the exponential run times of trivial exhaustive search. The study of exact (exponential time) algorithms that aims to breach this gap is as old as Theoretical Computer Science (TCS) itself: Already in the 1960's, researchers found elementary (for modern standards) algorithms that greatly improve exponential the run times. But over time, TCS seems to have hit a brick wall: Somewhat embarrassingly, as of 2018 the run times of these classic algorithms are still the best known for many classic problems. This project aims to strike at the heart of this issue by designing the next generation of exact exponential time algorithms. To obtain these algorithms, we consider the most famous NP-complete problems such as Traveling Salesman, CNF-Sat and Knapsack, and we challenge ourselves to improve the classic currently best algorithms for them. These problems have served as a prototypical test bed for many algorithmic techniques with extensive applications, and thus their study provides an excellent road map towards our aim. Moreover, in the last few years it was shown that these algorithms have consequences that reach much further than originally thought: In particular, they would have a major impact on research in polynomial time algorithms, circuit complexity and parameterized complexity. Now is the right moment for this project, as recent work (partially by the PI) has given a first glimpse of a new algorithmic toolkit emerging: Advanced new tools to decompose solutions such as the representation method, the rank-based method and the polynomial method, are still barely exploited and studied in the field. In this project we will combine these (and many more) tools in novel ways that transcend existing approaches, and make cracks in the wall of NP-completeness seem entirely within reach.

Mots-clés : theoretical computer science,fixed parameter tractability,parameterized complexity,fine grained complexity,exact algorithms for np hard problems,exact exponential time algorithms