Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : Com4Com (Horizon 2020, appel 2014, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Condensed matter physics
Entité participante : Max Planck Society — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : MPG
Type d'entité : Recherche
Financement ERC de l'entité : 3176850.0 €

Compounds of transition metals with 4d valence electrons (“4d metals”) play eminent roles in many areas of condensed matter physics ranging from unconventional superconductivity to oxide electronics, but fundamental questions about the interplay between the spin-orbit coupling and electronic correlations at the atomic scale remain unanswered. Momentum-resolved spectroscopies of collective electronic excitations yield detailed insight into the magnitude and spatial range of the electronic correlations, and have thus decisively shaped the conceptual understanding of quantum many-body phenomena in 3d-electron systems. We will devise and build a novel resonant inelastic x-ray scattering (RIXS) instrument capable of determining the dispersion relations of electronic collective modes in 4d-metal compounds with full momentum-space coverage, high energy resolution, and monolayer sensitivity. Data from this instrument will yield comprehensive information about the interaction parameters specifying the electronic Hamiltonians of 4d-electron materials, unique insight into the spin-orbital composition of their excited-state wavefunctions, and definitive tests of proposals to realize Kitaev models with spin-liquid states that are potentially relevant in topological quantum computation. The element-specificity of RIXS will also allow us to determine the microscopic exchange interactions in complex materials with both 3d and 4d valence electrons, and its high sensitivity will enable experiments on operational device structures comprising only a few monolayers. We will thus be able to tightly integrate momentum-resolved spectroscopy with state-of-the-art, monolayer-by-monolayer deposition methods of 4d metal-oxide films and heterostructures. The results will fuel a feedback loop comprising synthesis, characterization, and modeling, which will greatly advance our ability to design materials and devices whose functionality derives from the collective organization of electrons.
Projet ERC : Inhomogeneities (Horizon 2020, appel 2014, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Products and processes engineering
Entité participante : TU Bergakademie Freiberg — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : TUBAF
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1058886.76 €

Compressed fluid systems handled in high pressure processes feature diffusivities smaller than the kinematic viscosity. Therefore during mixing the lifetime of micro(µ)-scale(s) inhomogeneities exceeds that one of macro(m)-scale(s) inhomogeneities. Thus m-s homogeneous systems can still exhibit µ-s inhomogeneities. They affect the functioning-chain of processes, e.g. reactions and phase-transitions or –separations, which themselves also take place on a sub-macro-scale. Therefore it will be analyzed in situ how µ-s inhomogeneities influence the functioning chain of the particle generation (supercritical antisolvent technology), the reaction (high pressure combustion), and the phase-separation or phase-transition mechanisms (surfactant-free CO2-based micro-emulsions and gas hydrates) and to which extend these inhomogeneities are responsible for the characteristics of the product, such as unfavourable size distributions of particulate products and/or pollutant emissions. On this purpose the here proposed and self-developed non-invasive and in situ Raman spectroscopic technique considers the INTENSITY-ratios of Raman signals to analyze the m-s composition and the SIGNATURE of the OH stretch vibration Raman signal of water (or alcohols) to analyze the µ-s composition of fluid mixtures. The SIGNATURE of the OH stretch vibration Raman signal is influenced by the development of the hydrogen bonds -an intermolecular interaction- and thus provides the µ-s composition, though the probe volume of the Raman sensor is m-s. The signal-INTENSITY-ratio and signal-SIGNATURE are extracted both from one and the same “m-s” Raman spectrum of the mixture. This allows the comparison of the degree of mixing on m-s and µ-s simultaneously, and enables the analysis of whether a system at any instance of mixing (instance of the onset of a reaction or a phase transition or –separation) has reached the favourable µ-s homogeneity, which would result in homogeneous and uniform products.
Projet ERC : SAMSON (Horizon 2020, appel 2015, Proof of concept grants)
Entité participante : Institut national de recherche en sciences et technologies du numérique — Pays : France — Rôle : PI
Acronyme de l'entité : Inria
Type d'entité : Recherche
Financement ERC de l'entité : 149750.0 €

Computer-aided design of macrosystems has greatly contributed to reduce production costs of cars, planes, etc., by replacing drawing boards and physical mock-ups with virtual modeling and simulation tools. Similarly, computational nanoscience is expected to have an increasingly essential impact on biology, chemistry, physics, material science, electronics, etc., by complementing experiments to reduce research and development cycles, lower costs, increase quality, etc. Unfortunately, while numerous software tools have already been developed, they are currently very fragmented, domain specific, and a significant effort is still needed to address the needs emerging from the convergence trends in nanoscience. Indeed, boundaries that used to clearly delimitate application domains (biology, chemistry, etc.) are now becoming blurred: nanoparticles are being functionalized with antibodies, nanomechanisms are built out of DNA strands, etc. My group has been developing SAMSON, a software platform for modeling and simulation of nanosystems, with three main design characteristics in mind: generality, adaptivity and openness. Unlike existing commercial tools, which are mostly closed and “monolithic”, we believe the open architecture of SAMSON, combined with the distribution model enabled by SAMSON Connect, an associated online platform to distribute SAMSON Elements (modules for SAMSON), is the most appropriate foundation to integrate computational tools and help move forward nanoscience and nanotechnology. The goal of this Proof of Concept proposal is to explore the potential of SAMSON as a software platform for federating computational nanoscience able to sustain a viable business model.

Mots-clés : samson,samson connect,computational nanoscience,modeling and simulation,open architecture,app store
Projet ERC : SMILE (Horizon 2020, appel 2016, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Condensed matter physics
Entité participante : Centre national de la recherche scientifique — Pays : France — Rôle : Partner
Acronyme de l'entité : CNRS
Type d'entité : Recherche
Financement ERC de l'entité : 747041.64 €

Computers are now able to recognize people, to tell a dog from a cat, or to process speech so efficiently that they can answer complicated questions. This was still impossible only a decade ago. This progress is largely due to the development of the artificial “deep-learned neural networks”. Nowadays, “deep learning” is revolutionizing our life, prompting an economic battle between internet giants and the creation of a myriad of start-ups. As attractive and performant as it is, however, many agree that deep learning is largely an empirical field that lacks a theoretical understanding of its capacity and limitations. The algorithms used to "train" these networks explore a very complex and non-convex energy landscape that eludes most of the present theoretical methodology in machine learning. The behavior of the dynamics in such complicated "glassy" landscape is, however, similar to those that have been studied for decades in the physics of disordered systems such as molecular and spin glasses. In this project we pursue this analogy and use advanced methods of disordered systems to develop a statistical mechanics approach to deep neural networks. Our first main objective is to create a model for learning features from data via a multi-level neural network. We then regard this model as a kind of a spin glass system amenable to an exact asymptotic analysis via the replica and cavity method. Analyzing its phase diagram and phase transitions shall bring theoretical understanding of the principles behind the empirical success of deep neural networks. This approach will also lead to our second objective: the creation of a new class of fast, efficient, and asymptotically optimal message passing algorithms for deep learning. It is the synergy between the theoretical statistical physics approach and scientific questions from computer science that makes the project’s objectives feasible and enables a leap forward in our understanding of learning from data.

Mots-clés : spin glasses,artificial neural networks,bethe approximation,replica method,cavity method,message passing algorithms,belief propagation,unsupervised learning,graphical models,feature learning
Projet ERC : MarsFirstWater (Horizon 2020, appel 2018, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Universe sciences
Entité participante : Autonomous University of Madrid — Pays : Espagne — Rôle : Partner
Acronyme de l'entité : UAM
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 500000.0 €

Concepts of large bodies of glacial ice and liquid standing water, a robust hydrological cycle, and a rich Martian history of climate change are part of the current consensus model for early Mars. However, questions still poorly constrained include: a precise understanding of the inventory of water during the first billion years of Mars history and its early evolution on both global and local scales; whether liquid or solid H2O dominated, for what duration of time and where the water resided; what were the host-rock weathering rates and patterns and the physicochemical parameters defining such interactions; what specific landforms and mineralogies were generated during those periods; and what implications all these processes had on the possible inception of life on Mars. These fundamental questions represent large uncertainties and knowledge gaps. Therefore, a quantitative understanding of the basic characteristics of water on early Mars is very much needed and is the focus of this proposal. This application outlines a plan for my research in the next five years, and explains how I propose to fully characterize the aqueous environments of early Mars through a quantitative and truly interdisciplinary investigation. Spacecraft mission-derived datasets will be consistently used to test hypotheses through paleogeomorphological reconstructions, geochemical modeling, mineralogical studies, and astrobiological investigations. The derived results will produce hard constraints on the physical evolution, chemical alteration and habitability of surface and near-surface aqueous environments on early Mars. The planned investigations will benefit from the combination of working with first-hand data from ongoing Mars missions and with the state-of-the-art laboratory tools at the host institution. The final expected result will be a complete understanding of the physicochemical nature of water on early Mars, also opening new paths for the astrobiological exploration of the planet.

Mots-clés : mars,geomorphology,geochemistry,mineralogy
Projet ERC : MarsFirstWater (Horizon 2020, appel 2018, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Universe sciences
Entité participante : Spanish National Research Council — Pays : Espagne — Rôle : PI
Acronyme de l'entité : CSIC
Type d'entité : Recherche
Financement ERC de l'entité : 1498368.0 €

Concepts of large bodies of glacial ice and liquid standing water, a robust hydrological cycle, and a rich Martian history of climate change are part of the current consensus model for early Mars. However, questions still poorly constrained include: a precise understanding of the inventory of water during the first billion years of Mars history and its early evolution on both global and local scales; whether liquid or solid H2O dominated, for what duration of time and where the water resided; what were the host-rock weathering rates and patterns and the physicochemical parameters defining such interactions; what specific landforms and mineralogies were generated during those periods; and what implications all these processes had on the possible inception of life on Mars. These fundamental questions represent large uncertainties and knowledge gaps. Therefore, a quantitative understanding of the basic characteristics of water on early Mars is very much needed and is the focus of this proposal. This application outlines a plan for my research in the next five years, and explains how I propose to fully characterize the aqueous environments of early Mars through a quantitative and truly interdisciplinary investigation. Spacecraft mission-derived datasets will be consistently used to test hypotheses through paleogeomorphological reconstructions, geochemical modeling, mineralogical studies, and astrobiological investigations. The derived results will produce hard constraints on the physical evolution, chemical alteration and habitability of surface and near-surface aqueous environments on early Mars. The planned investigations will benefit from the combination of working with first-hand data from ongoing Mars missions and with the state-of-the-art laboratory tools at the host institution. The final expected result will be a complete understanding of the physicochemical nature of water on early Mars, also opening new paths for the astrobiological exploration of the planet.

Mots-clés : mars,geomorphology,geochemistry,mineralogy
Projet ERC : ConquerIons (Horizon 2020, appel 2019, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Physical and analytical chemical sciences
Entité participante : Universidad Católica San Antonio de Murcia — Pays : Espagne — Rôle : PI
Acronyme de l'entité : UCAM
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1283460.0 €

ConquerIons is seeking a definitive solution for the detection of ions in real scenarios by innovatively addressing the limitations of traditional ion-sensing concepts in terms of effectiveness, sensitiveness, robustness and downscaled platforms. The project proposes a new generation of voltammetric, amperometric and optical ion sensors based on calibration-free selective membranes inspired by conventional membranes used in the well-established potentiometry field but with a thickness at the nanoscale. The uniqueness of the dynamic electrochemical tuning of ion-transfer processes across these nano-membranes opens up a revolutionary approach that allows for the monitoring of ion concentration in a sample with unprecedented analytical performance. Thus, the project combines efforts from the synthetic chemistry, material science, nanoscience, electrochemistry and analytical chemistry disciplines resulting in a universal concept for the reliable detection of ions. ConquerIons is based on a research approach carefully designed mainly considering the following challenges: (i) the use of novel materials to afford a robust and universal detection; (ii) the implementation of thin-layer concepts of electrochemical and/or optical-sensing platforms to achieve reduced limits of detection and calibration-free methodology; (iii) the translation of the developed concepts to the single-entity scale (i.e. single nanoparticles) towards the study of ion-transfer processes employing, for the first time, ‘nanocoulometry’ readout; and (iv) exploitation of sensors from the laboratory context based on relevant cases as the next step towards the final use as daily smart informers operating in real scenarios. This latter purpose will lead to a series of extraordinary analytical applications from a long-term perspective related to very distinct fields, such as cell-scale therapies and speciation of trace ion levels in environmental analysis.

Mots-clés : smart informers,ion detection,selective membranes,calibration free,thin layer samples,single entity,nanocoulometry
Projet ERC : COR-RAND (Horizon 2020, appel 2019, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Mathematics
Entité participante : Sorbonne Université — Pays : France — Rôle : PI
Acronyme de l'entité : Sorbonne U
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1207500.0 €

Consider a partial differential equation (PDE) with random coefficients as in engineering or applied physics: When combined with a spatial scale separation, the randomness and the differential operator interact to give rise to some effective behavior. The recent growing mathematical activity in this domain has led to a ``seemingly'' complete theory of stochastic homogenization of linear elliptic operators. Central to this theory is the so-called corrector equation, a degenerate elliptic equation posed on the (infinite-dimensional) probability space. The context of linear elliptic operators yields the simplest such equation. Time-dependent and/or nonlinear PDEs also involve corrector equations (or a family thereof), albeit with a significantly more complex structure. Their study and use to characterize the large-scale/time behavior of solutions of PDEs with random coefficients are at the heart of this project. Whereas the relevance of corrector equations is clear in problems such as diffusion in random media, sedimentation of randomly placed particles in a fluid, or water waves on a rough bottom, it is less obvious for the long-time behavior of waves in disordered media. The latter is related to the spectrum of the associated random elliptic operator, the characterization of which still remains a largely open question today. We propose to relate the long-time behavior of waves to the properties of a family of corrector equations. These corrector equations are widely unstudied and offer many analytical challenges. They constitute the first half of the project. Even in the ``well-understood'' setting of linear elliptic operators, this requires to revisit the corrector equation in the light of much weaker topologies than considered before. The second half of the project aims at using correctors to establish the large-scale behavior of solutions as random objects. This may involve surprising quantities such as the recently introduced ``homogenization commutator".

Mots-clés : pdes with random coefficients,homogenization,effective behavior,fluctuations,waves
Projet ERC : Genesis (Horizon 2020, appel 2019, Consolidator 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 : 1999577.0 €

Constant search of new solids is required to advance our knowledge in materials science, and then to stimulate progresses in fields like energy and environment. Genesis aims at expanding the collection of functional inorganic solids as nanoparticles by rational exploratory synthesis. The pivotal idea is to draw inspiration from the processes of solid formation encountered in natural geological processes, in order to set a framework of synthesis conditions prone to yield new nanoscaled solids. I focus on kinetically stabilized, metastable solids, which yield novel, sometimes surprising properties prone to deliver new functions. However, conventional solid-state syntheses use high temperatures that yield thermodynamic products, hence hampering the synthesis of metastable inorganic solids. This obstacle is even more significant when the solids possess complex structures, as is the case of non-oxides made of transition metals and boron, silicon or phosphorus. The known members of these families are made of covalent bonds that bring unique electrocatalytic properties. This motivates the search of ternary solids joining these elements. Their quest is a synthetic challenge that I will address by the discovery of new metastable covalent solids. To do so, I will set an original inorganic synthesis methodology by taking inspiration from the processes of crystallization of gems in molten salts, of lavas at high rate and of metamorphic rocks at high pressures to merge nanosciences and solid-state chemistry. Genesis will operate at the crossroad of three pillars: use of the surface energy of nanoparticles to stabilize solids that would be metastable in their extended form; establishment of liquid-phase syntheses at 300-1000 °C in mild conditions; use of high-pressure chemistry to stabilize new solids. Within this frame, I will develop new methods to screen in situ the reaction pathways and I will trigger a new reactivity between boron, silicon, phosphorus and nanoparticles.
Projet ERC : E-DESIGN (Horizon 2020, appel 2017, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Condensed matter physics
Entité participante : Aalto University — Pays : Finlande — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2374922.0 €

Constructing designer materials where the atomic geometry, interactions, magnetism and other relevant parameters can be precisely controlled is becoming reality. I will reach this aim by positioning every atom with the tip of a scanning probe microscope, or by using molecular self-assembly to reach the desired structures. I will realize and engineer several novel quantum materials hosting exotic electronic phases: 2D topological insulators in metal-organic frameworks (MOF) and 2D topological superconductors in hybrid molecule-superconductor structures. These classes of materials have not yet been experimentally realized but could enable novel spintronic and quantum computing devices. In addition, we will realize a tuneable platform for quantum simulation in solid-state artificial lattices, which could open a whole new area in this field. I will employ a broad experimental approach to reach the above targets by utilizing molecular self-assembly and scanning probe microscopy -based atom/molecule manipulation. The systems are characterized using low-temperature atomic force microscopy (AFM) and scanning tunneling microscopy (STM). My group is one of the leading groups in these topics globally. We have initial results on the topics discussed in this proposal and are thus in a unique position to make ground-breaking contributions in realizing designer quantum materials. The artificial designer materials we study are characterized by the engineered electronic response with atomically precise geometries, lattice symmetries and controlled interactions. Such ingredients can result in ultimately controllable materials that have large, robust and quick responses to small stimuli with applications in nanoelectronics, flexible electronics, high-selectivity and high-sensitivity sensors, and optoelectronic components. Longer term, the biggest impact is expected through a profound change in the way we view materials and what can be achieved through designer materials approach.

Mots-clés : topological matter,topological insulators,topological superconductors,molecular self assembly,metal organic frameworks  mof,atomic force microscopy  afm,scanning tunneling microscopy  stm