Project acronym 2D-4-CO2
Project DESIGNING 2D NANOSHEETS FOR CO2 REDUCTION AND INTEGRATION INTO vdW HETEROSTRUCTURES FOR ARTIFICIAL PHOTOSYNTHESIS
Researcher (PI) Damien VOIRY
Host Institution (HI) CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS
Call Details Starting Grant (StG), PE8, ERC-2018-STG
Summary CO2 reduction reaction (CO2RR) holds great promise for conversion of the green-house gas carbon dioxide into chemical fuels. The absence of catalytic materials demonstrating high performance and high selectivity currently hampers practical demonstration. CO2RR is also limited by the low solubility of CO2 in the electrolyte solution and therefore electrocatalytic reactions in gas phase using gas diffusion electrodes would be preferred. 2D materials have recently emerged as a novel class of electrocatalytic materials thanks to their rich structures and electronic properties. The synthesis of novel 2D catalysts and their implementation into photocatalytic systems would be a major step towards the development of devices for storing solar energy in the form of chemical fuels. With 2D-4-CO2, I propose to: 1) develop novel class of CO2RR catalysts based on conducting 2D nanosheets and 2) demonstrate photocatalytic conversion of CO2 into chemical fuels using structure engineered gas diffusion electrodes made of 2D conducting catalysts. To reach this goal, the first objective of 2D-4-CO2 is to provide guidelines for the development of novel cutting-edge 2D catalysts towards CO2 conversion into chemical fuel. This will be possible by using a multidisciplinary approach based on 2D materials engineering, advanced methods of characterization and novel designs of gas diffusion electrodes for the reduction of CO2 in gas phase. The second objective is to develop practical photocatalytic systems using van der Waals (vdW) heterostructures for the efficient conversion of CO2 into chemical fuels. vdW heterostructures will consist in rational designs of 2D materials and 2D-like materials deposited by atomic layer deposition in order to achieve highly efficient light conversion and prolonged stability. This project will not only enable a deeper understanding of the CO2RR but it will also provide practical strategies for large-scale application of CO2RR for solar fuel production.
Summary
CO2 reduction reaction (CO2RR) holds great promise for conversion of the green-house gas carbon dioxide into chemical fuels. The absence of catalytic materials demonstrating high performance and high selectivity currently hampers practical demonstration. CO2RR is also limited by the low solubility of CO2 in the electrolyte solution and therefore electrocatalytic reactions in gas phase using gas diffusion electrodes would be preferred. 2D materials have recently emerged as a novel class of electrocatalytic materials thanks to their rich structures and electronic properties. The synthesis of novel 2D catalysts and their implementation into photocatalytic systems would be a major step towards the development of devices for storing solar energy in the form of chemical fuels. With 2D-4-CO2, I propose to: 1) develop novel class of CO2RR catalysts based on conducting 2D nanosheets and 2) demonstrate photocatalytic conversion of CO2 into chemical fuels using structure engineered gas diffusion electrodes made of 2D conducting catalysts. To reach this goal, the first objective of 2D-4-CO2 is to provide guidelines for the development of novel cutting-edge 2D catalysts towards CO2 conversion into chemical fuel. This will be possible by using a multidisciplinary approach based on 2D materials engineering, advanced methods of characterization and novel designs of gas diffusion electrodes for the reduction of CO2 in gas phase. The second objective is to develop practical photocatalytic systems using van der Waals (vdW) heterostructures for the efficient conversion of CO2 into chemical fuels. vdW heterostructures will consist in rational designs of 2D materials and 2D-like materials deposited by atomic layer deposition in order to achieve highly efficient light conversion and prolonged stability. This project will not only enable a deeper understanding of the CO2RR but it will also provide practical strategies for large-scale application of CO2RR for solar fuel production.
Max ERC Funding
1 499 931 €
Duration
Start date: 2019-01-01, End date: 2023-12-31
Project acronym 2DNANOCAPS
Project Next Generation of 2D-Nanomaterials: Enabling Supercapacitor Development
Researcher (PI) Valeria Nicolosi
Host Institution (HI) THE PROVOST, FELLOWS, FOUNDATION SCHOLARS & THE OTHER MEMBERS OF BOARD OF THE COLLEGE OF THE HOLY & UNDIVIDED TRINITY OF QUEEN ELIZABETH NEAR DUBLIN
Call Details Starting Grant (StG), PE8, ERC-2011-StG_20101014
Summary Climate change and the decreasing availability of fossil fuels require society to move towards sustainable and renewable resources. 2DNanoCaps will focus on electrochemical energy storage, specifically supercapacitors. In terms of performance supercapacitors fill up the gap between batteries and the classical capacitors. Whereas batteries possess a high energy density but low power density, supercapacitors possess high power density but low energy density. Efforts are currently dedicated to move supercapacitors towards high energy density and high power density performance. Improvements have been achieved in the last few years due to the use of new electrode nanomaterials and the design of new hybrid faradic/capacitive systems. We recognize, however, that we are reaching a newer limit beyond which we will only see small incremental improvements. The main reason for this being the intrinsic difficulty in handling and processing materials at the nano-scale and the lack of communication across different scientific disciplines. I plan to use a multidisciplinary approach, where novel nanomaterials, existing knowledge on nano-scale processing and established expertise in device fabrication and testing will be brought together to focus on creating more efficient supercapacitor technologies. 2DNanoCaps will exploit liquid phase exfoliated two-dimensional nanomaterials such as transition metal oxides, layered metal chalcogenides and graphene as electrode materials. Electrodes will be ultra-thin (capacitance and thickness of the electrodes are inversely proportional), conductive, with high dielectric constants. Intercalation of ions between the assembled 2D flakes will be also achievable, providing pseudo-capacitance. The research here proposed will be initially based on fundamental laboratory studies, recognising that this holds the key to achieving step-change in supercapacitors, but also includes scaling-up and hybridisation as final objectives.
Summary
Climate change and the decreasing availability of fossil fuels require society to move towards sustainable and renewable resources. 2DNanoCaps will focus on electrochemical energy storage, specifically supercapacitors. In terms of performance supercapacitors fill up the gap between batteries and the classical capacitors. Whereas batteries possess a high energy density but low power density, supercapacitors possess high power density but low energy density. Efforts are currently dedicated to move supercapacitors towards high energy density and high power density performance. Improvements have been achieved in the last few years due to the use of new electrode nanomaterials and the design of new hybrid faradic/capacitive systems. We recognize, however, that we are reaching a newer limit beyond which we will only see small incremental improvements. The main reason for this being the intrinsic difficulty in handling and processing materials at the nano-scale and the lack of communication across different scientific disciplines. I plan to use a multidisciplinary approach, where novel nanomaterials, existing knowledge on nano-scale processing and established expertise in device fabrication and testing will be brought together to focus on creating more efficient supercapacitor technologies. 2DNanoCaps will exploit liquid phase exfoliated two-dimensional nanomaterials such as transition metal oxides, layered metal chalcogenides and graphene as electrode materials. Electrodes will be ultra-thin (capacitance and thickness of the electrodes are inversely proportional), conductive, with high dielectric constants. Intercalation of ions between the assembled 2D flakes will be also achievable, providing pseudo-capacitance. The research here proposed will be initially based on fundamental laboratory studies, recognising that this holds the key to achieving step-change in supercapacitors, but also includes scaling-up and hybridisation as final objectives.
Max ERC Funding
1 501 296 €
Duration
Start date: 2011-10-01, End date: 2016-09-30
Project acronym 2G-CSAFE
Project Combustion of Sustainable Alternative Fuels for Engines used in aeronautics and automotives
Researcher (PI) Philippe Dagaut
Host Institution (HI) CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS
Call Details Advanced Grant (AdG), PE8, ERC-2011-ADG_20110209
Summary This project aims at promoting sustainable combustion technologies for transport via validation of advanced combustion kinetic models obtained using sophisticated new laboratory experiments, engines, and theoretical computations, breaking through the current frontier of knowledge. It will focus on the unexplored kinetics of ignition and combustion of 2nd generation (2G) biofuels and blends with conventional fuels, which should provide energy safety and sustainability to Europe. The motivation is that no accurate kinetic models are available for the ignition, oxidation and combustion of 2G-biofuels, and improved ignition control is needed for new compression ignition engines. Crucial information is missing: data from well characterised experiments on combustion-generated pollutants and data on key-intermediates for fuels ignition in new engines.
To provide that knowledge new well-instrumented complementary experiments and kinetic modelling will be used. Measurements of key-intermediates, stables species, and pollutants will be performed. New ignition control strategies will be designed, opening new technological horizons. Kinetic modelling will be used for rationalising the results. Due to the complexity of 2G-biofuels and their unusual composition, innovative surrogates will be designed. Kinetic models for surrogate fuels will be generalised for extension to other compounds. The experimental results, together with ab-initio and detailed modelling, will serve to characterise the kinetics of ignition, combustion, and pollutants formation of fuels including 2G biofuels, and provide relevant data and models.
This research is risky because this is (i) the 1st effort to measure radicals by reactor/CRDS coupling, (ii) the 1st effort to use a μ-channel reactor to build ignition databases for conventional and bio-fuels, (iii) the 1st effort to design and use controlled generation and injection of reactive species to control ignition/combustion in compression ignition engines
Summary
This project aims at promoting sustainable combustion technologies for transport via validation of advanced combustion kinetic models obtained using sophisticated new laboratory experiments, engines, and theoretical computations, breaking through the current frontier of knowledge. It will focus on the unexplored kinetics of ignition and combustion of 2nd generation (2G) biofuels and blends with conventional fuels, which should provide energy safety and sustainability to Europe. The motivation is that no accurate kinetic models are available for the ignition, oxidation and combustion of 2G-biofuels, and improved ignition control is needed for new compression ignition engines. Crucial information is missing: data from well characterised experiments on combustion-generated pollutants and data on key-intermediates for fuels ignition in new engines.
To provide that knowledge new well-instrumented complementary experiments and kinetic modelling will be used. Measurements of key-intermediates, stables species, and pollutants will be performed. New ignition control strategies will be designed, opening new technological horizons. Kinetic modelling will be used for rationalising the results. Due to the complexity of 2G-biofuels and their unusual composition, innovative surrogates will be designed. Kinetic models for surrogate fuels will be generalised for extension to other compounds. The experimental results, together with ab-initio and detailed modelling, will serve to characterise the kinetics of ignition, combustion, and pollutants formation of fuels including 2G biofuels, and provide relevant data and models.
This research is risky because this is (i) the 1st effort to measure radicals by reactor/CRDS coupling, (ii) the 1st effort to use a μ-channel reactor to build ignition databases for conventional and bio-fuels, (iii) the 1st effort to design and use controlled generation and injection of reactive species to control ignition/combustion in compression ignition engines
Max ERC Funding
2 498 450 €
Duration
Start date: 2011-12-01, End date: 2016-11-30
Project acronym 3D Reloaded
Project 3D Reloaded: Novel Algorithms for 3D Shape Inference and Analysis
Researcher (PI) Daniel Cremers
Host Institution (HI) TECHNISCHE UNIVERSITAET MUENCHEN
Call Details Consolidator Grant (CoG), PE6, ERC-2014-CoG
Summary Despite their amazing success, we believe that computer vision algorithms have only scratched the surface of what can be done in terms of modeling and understanding our world from images. We believe that novel image analysis techniques will be a major enabler and driving force behind next-generation technologies, enhancing everyday life and opening up radically new possibilities. And we believe that the key to achieving this is to develop algorithms for reconstructing and analyzing the 3D structure of our world.
In this project, we will focus on three lines of research:
A) We will develop algorithms for 3D reconstruction from standard color cameras and from RGB-D cameras. In particular, we will promote real-time-capable direct and dense methods. In contrast to the classical two-stage approach of sparse feature-point based motion estimation and subsequent dense reconstruction, these methods optimally exploit all color information to jointly estimate dense geometry and camera motion.
B) We will develop algorithms for 3D shape analysis, including rigid and non-rigid matching, decomposition and interpretation of 3D shapes. We will focus on algorithms which are optimal or near-optimal. One of the major computational challenges lies in generalizing existing 2D shape analysis techniques to shapes in 3D and 4D (temporal evolutions of 3D shape).
C) We will develop shape priors for 3D reconstruction. These can be learned from sample shapes or acquired during the reconstruction process. For example, when reconstructing a larger office algorithms may exploit the geometric self-similarity of the scene, storing a model of a chair and its multiple instances only once rather than multiple times.
Advancing the state of the art in geometric reconstruction and geometric analysis will have a profound impact well beyond computer vision. We strongly believe that we have the necessary competence to pursue this project. Preliminary results have been well received by the community.
Summary
Despite their amazing success, we believe that computer vision algorithms have only scratched the surface of what can be done in terms of modeling and understanding our world from images. We believe that novel image analysis techniques will be a major enabler and driving force behind next-generation technologies, enhancing everyday life and opening up radically new possibilities. And we believe that the key to achieving this is to develop algorithms for reconstructing and analyzing the 3D structure of our world.
In this project, we will focus on three lines of research:
A) We will develop algorithms for 3D reconstruction from standard color cameras and from RGB-D cameras. In particular, we will promote real-time-capable direct and dense methods. In contrast to the classical two-stage approach of sparse feature-point based motion estimation and subsequent dense reconstruction, these methods optimally exploit all color information to jointly estimate dense geometry and camera motion.
B) We will develop algorithms for 3D shape analysis, including rigid and non-rigid matching, decomposition and interpretation of 3D shapes. We will focus on algorithms which are optimal or near-optimal. One of the major computational challenges lies in generalizing existing 2D shape analysis techniques to shapes in 3D and 4D (temporal evolutions of 3D shape).
C) We will develop shape priors for 3D reconstruction. These can be learned from sample shapes or acquired during the reconstruction process. For example, when reconstructing a larger office algorithms may exploit the geometric self-similarity of the scene, storing a model of a chair and its multiple instances only once rather than multiple times.
Advancing the state of the art in geometric reconstruction and geometric analysis will have a profound impact well beyond computer vision. We strongly believe that we have the necessary competence to pursue this project. Preliminary results have been well received by the community.
Max ERC Funding
2 000 000 €
Duration
Start date: 2015-09-01, End date: 2020-08-31
Project acronym 3D-E
Project 3D Engineered Environments for Regenerative Medicine
Researcher (PI) Ruth Elizabeth Cameron
Host Institution (HI) THE CHANCELLOR MASTERS AND SCHOLARS OF THE UNIVERSITY OF CAMBRIDGE
Call Details Advanced Grant (AdG), PE8, ERC-2012-ADG_20120216
Summary "This proposal develops a unified, underpinning technology to create novel, complex and biomimetic 3D environments for the control of tissue growth. As director of Cambridge Centre for Medical Materials, I have recently been approached by medical colleagues to help to solve important problems in the separate therapeutic areas of breast cancer, cardiac disease and blood disorders. In each case, the solution lies in complex 3D engineered environments for cell culture. These colleagues make it clear that existing 3D scaffolds fail to provide the required complex orientational and spatial anisotropy, and are limited in their ability to impart appropriate biochemical and mechanical cues.
I have a strong track record in this area. A particular success has been the use of a freeze drying technology to make collagen based porous implants for the cartilage-bone interface in the knee, which has now been commercialised. The novelty of this proposal lies in the broadening of the established scientific base of this technology to enable biomacromolecular structures with:
(A) controlled and complex pore orientation to mimic many normal multi-oriented tissue structures
(B) compositional and positional control to match varying local biochemical environments,
(C) the attachment of novel peptides designed to control cell behaviour, and
(D) mechanical control at both a local and macroscopic level to provide mechanical cues for cells.
These will be complemented by the development of
(E) robust characterisation methodologies for the structures created.
These advances will then be employed in each of the medical areas above.
This approach is highly interdisciplinary. Existing working relationships with experts in each medical field will guarantee expertise and licensed facilities in the required biological disciplines. Funds for this proposal would therefore establish a rich hub of mutually beneficial research and opportunities for cross-disciplinary sharing of expertise."
Summary
"This proposal develops a unified, underpinning technology to create novel, complex and biomimetic 3D environments for the control of tissue growth. As director of Cambridge Centre for Medical Materials, I have recently been approached by medical colleagues to help to solve important problems in the separate therapeutic areas of breast cancer, cardiac disease and blood disorders. In each case, the solution lies in complex 3D engineered environments for cell culture. These colleagues make it clear that existing 3D scaffolds fail to provide the required complex orientational and spatial anisotropy, and are limited in their ability to impart appropriate biochemical and mechanical cues.
I have a strong track record in this area. A particular success has been the use of a freeze drying technology to make collagen based porous implants for the cartilage-bone interface in the knee, which has now been commercialised. The novelty of this proposal lies in the broadening of the established scientific base of this technology to enable biomacromolecular structures with:
(A) controlled and complex pore orientation to mimic many normal multi-oriented tissue structures
(B) compositional and positional control to match varying local biochemical environments,
(C) the attachment of novel peptides designed to control cell behaviour, and
(D) mechanical control at both a local and macroscopic level to provide mechanical cues for cells.
These will be complemented by the development of
(E) robust characterisation methodologies for the structures created.
These advances will then be employed in each of the medical areas above.
This approach is highly interdisciplinary. Existing working relationships with experts in each medical field will guarantee expertise and licensed facilities in the required biological disciplines. Funds for this proposal would therefore establish a rich hub of mutually beneficial research and opportunities for cross-disciplinary sharing of expertise."
Max ERC Funding
2 486 267 €
Duration
Start date: 2013-04-01, End date: 2018-03-31
Project acronym 3D-FABRIC
Project 3D Flow Analysis in Bijels Reconfigured for Interfacial Catalysis
Researcher (PI) Martin F. HAASE
Host Institution (HI) UNIVERSITEIT UTRECHT
Call Details Starting Grant (StG), PE8, ERC-2018-STG
Summary The objective of this proposal is to determine the unknown criteria for convective cross-flow in bicontinuous interfacially jammed emulsion gels (bijels). Based on this, we will answer the question: Can continuously operated interfacial catalysis be realized in bijel cross-flow reactors? Demonstrating this potential will introduce a broadly applicable chemical technology, replacing wasteful chemical processes that require organic solvents. We will achieve our objective in three steps:
(a) Control over bijel structure and properties. Bijels will be formed with a selection of functional inorganic colloidal particles. Nanoparticle surface modifications will be developed and extensively characterized. General principles for the parameters determining bijel structures and properties will be established based on confocal and electron microscopy characterization. These principles will enable unprecedented control over bijel formation and will allow for designing desired properties.
(b) Convective flow in bijels. The mechanical strength of bijels will be tailored and measured. With mechanically robust bijels, the influence of size and organization of oil/water channels on convective mass transfer in bijels will be investigated. To this end, a bijel mass transfer apparatus fabricated by 3d-printing of bijel fibers and soft photolithography will be introduced. In conjunction with the following objective, the analysis of convective flows in bijels will facilitate a thorough description of their structure/function relationships.
(c) Biphasic chemical reactions in STrIPS bijel cross-flow reactors. First, continuous extraction in bijels will be realized. Next, conditions to carry out continuously-operated, phase transfer catalysis of well-known model reactions in bijels will be determined. Both processes will be characterized in-situ and in 3-dimensions by confocal microscopy of fluorescent phase transfer reactions in transparent bijels.
Summary
The objective of this proposal is to determine the unknown criteria for convective cross-flow in bicontinuous interfacially jammed emulsion gels (bijels). Based on this, we will answer the question: Can continuously operated interfacial catalysis be realized in bijel cross-flow reactors? Demonstrating this potential will introduce a broadly applicable chemical technology, replacing wasteful chemical processes that require organic solvents. We will achieve our objective in three steps:
(a) Control over bijel structure and properties. Bijels will be formed with a selection of functional inorganic colloidal particles. Nanoparticle surface modifications will be developed and extensively characterized. General principles for the parameters determining bijel structures and properties will be established based on confocal and electron microscopy characterization. These principles will enable unprecedented control over bijel formation and will allow for designing desired properties.
(b) Convective flow in bijels. The mechanical strength of bijels will be tailored and measured. With mechanically robust bijels, the influence of size and organization of oil/water channels on convective mass transfer in bijels will be investigated. To this end, a bijel mass transfer apparatus fabricated by 3d-printing of bijel fibers and soft photolithography will be introduced. In conjunction with the following objective, the analysis of convective flows in bijels will facilitate a thorough description of their structure/function relationships.
(c) Biphasic chemical reactions in STrIPS bijel cross-flow reactors. First, continuous extraction in bijels will be realized. Next, conditions to carry out continuously-operated, phase transfer catalysis of well-known model reactions in bijels will be determined. Both processes will be characterized in-situ and in 3-dimensions by confocal microscopy of fluorescent phase transfer reactions in transparent bijels.
Max ERC Funding
1 905 000 €
Duration
Start date: 2019-06-01, End date: 2024-05-31
Project acronym 3D2DPrint
Project 3D Printing of Novel 2D Nanomaterials: Adding Advanced 2D Functionalities to Revolutionary Tailored 3D Manufacturing
Researcher (PI) Valeria Nicolosi
Host Institution (HI) THE PROVOST, FELLOWS, FOUNDATION SCHOLARS & THE OTHER MEMBERS OF BOARD OF THE COLLEGE OF THE HOLY & UNDIVIDED TRINITY OF QUEEN ELIZABETH NEAR DUBLIN
Call Details Consolidator Grant (CoG), PE8, ERC-2015-CoG
Summary My vision is to establish, within the framework of an ERC CoG, a multidisciplinary group which will work in concert towards pioneering the integration of novel 2-Dimensional nanomaterials with novel additive fabrication techniques to develop a unique class of energy storage devices.
Batteries and supercapacitors are two very complementary types of energy storage devices. Batteries store much higher energy densities; supercapacitors, on the other hand, hold one tenth of the electricity per unit of volume or weight as compared to batteries but can achieve much higher power densities. Technology is currently striving to improve the power density of batteries and the energy density of supercapacitors. To do so it is imperative to develop new materials, chemistries and manufacturing strategies.
3D2DPrint aims to develop micro-energy devices (both supercapacitors and batteries), technologies particularly relevant in the context of the emergent industry of micro-electro-mechanical systems and constantly downsized electronics. We plan to use novel two-dimensional (2D) nanomaterials obtained by liquid-phase exfoliation. This method offers a new, economic and easy way to prepare ink of a variety of 2D systems, allowing to produce wide device performance window through elegant and simple constituent control at the point of fabrication. 3D2DPrint will use our expertise and know-how to allow development of advanced AM methods to integrate dissimilar nanomaterial blends and/or “hybrids” into fully embedded 3D printed energy storage devices, with the ultimate objective to realise a range of products that contain the above described nanomaterials subcomponent devices, electrical connections and traditional micro-fabricated subcomponents (if needed) ideally using a single tool.
Summary
My vision is to establish, within the framework of an ERC CoG, a multidisciplinary group which will work in concert towards pioneering the integration of novel 2-Dimensional nanomaterials with novel additive fabrication techniques to develop a unique class of energy storage devices.
Batteries and supercapacitors are two very complementary types of energy storage devices. Batteries store much higher energy densities; supercapacitors, on the other hand, hold one tenth of the electricity per unit of volume or weight as compared to batteries but can achieve much higher power densities. Technology is currently striving to improve the power density of batteries and the energy density of supercapacitors. To do so it is imperative to develop new materials, chemistries and manufacturing strategies.
3D2DPrint aims to develop micro-energy devices (both supercapacitors and batteries), technologies particularly relevant in the context of the emergent industry of micro-electro-mechanical systems and constantly downsized electronics. We plan to use novel two-dimensional (2D) nanomaterials obtained by liquid-phase exfoliation. This method offers a new, economic and easy way to prepare ink of a variety of 2D systems, allowing to produce wide device performance window through elegant and simple constituent control at the point of fabrication. 3D2DPrint will use our expertise and know-how to allow development of advanced AM methods to integrate dissimilar nanomaterial blends and/or “hybrids” into fully embedded 3D printed energy storage devices, with the ultimate objective to realise a range of products that contain the above described nanomaterials subcomponent devices, electrical connections and traditional micro-fabricated subcomponents (if needed) ideally using a single tool.
Max ERC Funding
2 499 942 €
Duration
Start date: 2016-10-01, End date: 2021-09-30
Project acronym 3DAddChip
Project Additive manufacturing of 2D nanomaterials for on-chip technologies
Researcher (PI) Cecilia Mattevi
Host Institution (HI) IMPERIAL COLLEGE OF SCIENCE TECHNOLOGY AND MEDICINE
Call Details Consolidator Grant (CoG), PE8, ERC-2018-COG
Summary The realization of “the internet of things” is inevitably constrained at the level of miniaturization that can be achieved in the electronic devices. A variety of technologies are now going through a process of miniaturization from micro-electromechanical systems (MEMS) to biomedical sensors, and actuators. The ultimate goal is to combine several components in an individual multifunctional platform, realizing on-chip technology. Devices have to be constrained to small footprints and exhibit high performance. Thus, the miniaturization process requires the introduction of new manufacturing processes to fabricate devices in the 3D space over small areas. 3D printing via robocasting is emerging as a new manufacturing technique, which allows shaping virtually any materials from polymers to ceramic and metals into complex architectures.
The goal of this research is to establish a 3D printing paradigm to produce miniaturized complex shape devices with diversified functions for on-chip technologies adaptable to “smart environment” such as flexible substrates, smart textiles and biomedical sensors. The elementary building blocks of the devices will be two-dimensional nanomaterials, which present unique optical, electrical, chemical and mechanical properties. The synergistic combination of the intrinsic characteristics of the 2D nanomaterials and the specific 3D architecture will enable advanced performance of the 3D printed objects. This research programme will demonstrate 3D miniaturized energy storage and energy conversion units fabricated with inks produced using a pilot plant. These units are essential components of any on-chip platform as they ensure energy autonomy via self-powering. Ultimately, this research will initiate new technologies based on miniaturized 3D devices.
Summary
The realization of “the internet of things” is inevitably constrained at the level of miniaturization that can be achieved in the electronic devices. A variety of technologies are now going through a process of miniaturization from micro-electromechanical systems (MEMS) to biomedical sensors, and actuators. The ultimate goal is to combine several components in an individual multifunctional platform, realizing on-chip technology. Devices have to be constrained to small footprints and exhibit high performance. Thus, the miniaturization process requires the introduction of new manufacturing processes to fabricate devices in the 3D space over small areas. 3D printing via robocasting is emerging as a new manufacturing technique, which allows shaping virtually any materials from polymers to ceramic and metals into complex architectures.
The goal of this research is to establish a 3D printing paradigm to produce miniaturized complex shape devices with diversified functions for on-chip technologies adaptable to “smart environment” such as flexible substrates, smart textiles and biomedical sensors. The elementary building blocks of the devices will be two-dimensional nanomaterials, which present unique optical, electrical, chemical and mechanical properties. The synergistic combination of the intrinsic characteristics of the 2D nanomaterials and the specific 3D architecture will enable advanced performance of the 3D printed objects. This research programme will demonstrate 3D miniaturized energy storage and energy conversion units fabricated with inks produced using a pilot plant. These units are essential components of any on-chip platform as they ensure energy autonomy via self-powering. Ultimately, this research will initiate new technologies based on miniaturized 3D devices.
Max ERC Funding
1 999 968 €
Duration
Start date: 2019-09-01, End date: 2024-08-31
Project acronym AArteMIS
Project Aneurysmal Arterial Mechanics: Into the Structure
Researcher (PI) Pierre Joseph Badel
Host Institution (HI) ASSOCIATION POUR LA RECHERCHE ET LE DEVELOPPEMENT DES METHODES ET PROCESSUS INDUSTRIELS
Call Details Starting Grant (StG), PE8, ERC-2014-STG
Summary The rupture of an Aortic Aneurysm (AA), which is often lethal, is a mechanical phenomenon that occurs when the wall stress state exceeds the local strength of the tissue. Our current understanding of arterial rupture mechanisms is poor, and the physics taking place at the microscopic scale in these collagenous structures remains an open area of research. Understanding, modelling, and quantifying the micro-mechanisms which drive the mechanical response of such tissue and locally trigger rupture represents the most challenging and promising pathway towards predictive diagnosis and personalized care of AA.
The PI's group was recently able to detect, in advance, at the macro-scale, rupture-prone areas in bulging arterial tissues. The next step is to get into the details of the arterial microstructure to elucidate the underlying mechanisms.
Through the achievements of AArteMIS, the local mechanical state of the fibrous microstructure of the tissue, especially close to its rupture state, will be quantitatively analyzed from multi-photon confocal microscopy and numerically reconstructed to establish quantitative micro-scale rupture criteria. AArteMIS will also address developing micro-macro models which are based on the collected quantitative data.
The entire project will be completed through collaboration with medical doctors and engineers, experts in all required fields for the success of AArteMIS.
AArteMIS is expected to open longed-for pathways for research in soft tissue mechanobiology which focuses on cell environment and to enable essential clinical applications for the quantitative assessment of AA rupture risk. It will significantly contribute to understanding fatal vascular events and improving cardiovascular treatments. It will provide a tremendous source of data and inspiration for subsequent applications and research by answering the most fundamental questions on AA rupture behaviour enabling ground-breaking clinical changes to take place.
Summary
The rupture of an Aortic Aneurysm (AA), which is often lethal, is a mechanical phenomenon that occurs when the wall stress state exceeds the local strength of the tissue. Our current understanding of arterial rupture mechanisms is poor, and the physics taking place at the microscopic scale in these collagenous structures remains an open area of research. Understanding, modelling, and quantifying the micro-mechanisms which drive the mechanical response of such tissue and locally trigger rupture represents the most challenging and promising pathway towards predictive diagnosis and personalized care of AA.
The PI's group was recently able to detect, in advance, at the macro-scale, rupture-prone areas in bulging arterial tissues. The next step is to get into the details of the arterial microstructure to elucidate the underlying mechanisms.
Through the achievements of AArteMIS, the local mechanical state of the fibrous microstructure of the tissue, especially close to its rupture state, will be quantitatively analyzed from multi-photon confocal microscopy and numerically reconstructed to establish quantitative micro-scale rupture criteria. AArteMIS will also address developing micro-macro models which are based on the collected quantitative data.
The entire project will be completed through collaboration with medical doctors and engineers, experts in all required fields for the success of AArteMIS.
AArteMIS is expected to open longed-for pathways for research in soft tissue mechanobiology which focuses on cell environment and to enable essential clinical applications for the quantitative assessment of AA rupture risk. It will significantly contribute to understanding fatal vascular events and improving cardiovascular treatments. It will provide a tremendous source of data and inspiration for subsequent applications and research by answering the most fundamental questions on AA rupture behaviour enabling ground-breaking clinical changes to take place.
Max ERC Funding
1 499 783 €
Duration
Start date: 2015-04-01, End date: 2020-03-31
Project acronym ACCORD
Project Algorithms for Complex Collective Decisions on Structured Domains
Researcher (PI) Edith Elkind
Host Institution (HI) THE CHANCELLOR, MASTERS AND SCHOLARS OF THE UNIVERSITY OF OXFORD
Call Details Starting Grant (StG), PE6, ERC-2014-STG
Summary Algorithms for Complex Collective Decisions on Structured Domains.
The aim of this proposal is to substantially advance the field of Computational Social Choice, by developing new tools and methodologies that can be used for making complex group decisions in rich and structured environments. We consider settings where each member of a decision-making body has preferences over a finite set of alternatives, and the goal is to synthesise a collective preference over these alternatives, which may take the form of a partial order over the set of alternatives with a predefined structure: examples include selecting a fixed-size set of alternatives, a ranking of the alternatives, a winner and up to two runner-ups, etc. We will formulate desiderata that apply to such preference aggregation procedures, design specific procedures that satisfy as many of these desiderata as possible, and develop efficient algorithms for computing them. As the latter step may be infeasible on general preference domains, we will focus on identifying the least restrictive domains that enable efficient computation, and use real-life preference data to verify whether the associated restrictions are likely to be satisfied in realistic preference aggregation scenarios. Also, we will determine whether our preference aggregation procedures are computationally resistant to malicious behavior. To lower the cognitive burden on the decision-makers, we will extend our procedures to accept partial rankings as inputs. Finally, to further contribute towards bridging the gap between theory and practice of collective decision making, we will provide open-source software implementations of our procedures, and reach out to the potential users to obtain feedback on their practical applicability.
Summary
Algorithms for Complex Collective Decisions on Structured Domains.
The aim of this proposal is to substantially advance the field of Computational Social Choice, by developing new tools and methodologies that can be used for making complex group decisions in rich and structured environments. We consider settings where each member of a decision-making body has preferences over a finite set of alternatives, and the goal is to synthesise a collective preference over these alternatives, which may take the form of a partial order over the set of alternatives with a predefined structure: examples include selecting a fixed-size set of alternatives, a ranking of the alternatives, a winner and up to two runner-ups, etc. We will formulate desiderata that apply to such preference aggregation procedures, design specific procedures that satisfy as many of these desiderata as possible, and develop efficient algorithms for computing them. As the latter step may be infeasible on general preference domains, we will focus on identifying the least restrictive domains that enable efficient computation, and use real-life preference data to verify whether the associated restrictions are likely to be satisfied in realistic preference aggregation scenarios. Also, we will determine whether our preference aggregation procedures are computationally resistant to malicious behavior. To lower the cognitive burden on the decision-makers, we will extend our procedures to accept partial rankings as inputs. Finally, to further contribute towards bridging the gap between theory and practice of collective decision making, we will provide open-source software implementations of our procedures, and reach out to the potential users to obtain feedback on their practical applicability.
Max ERC Funding
1 395 933 €
Duration
Start date: 2015-07-01, End date: 2020-06-30
Project acronym ACDC
Project Algorithms and Complexity of Highly Decentralized Computations
Researcher (PI) Fabian Daniel Kuhn
Host Institution (HI) ALBERT-LUDWIGS-UNIVERSITAET FREIBURG
Call Details Starting Grant (StG), PE6, ERC-2013-StG
Summary "Many of today's and tomorrow's computer systems are built on top of large-scale networks such as, e.g., the Internet, the world wide web, wireless ad hoc and sensor networks, or peer-to-peer networks. Driven by technological advances, new kinds of networks and applications have become possible and we can safely assume that this trend is going to continue. Often modern systems are envisioned to consist of a potentially large number of individual components that are organized in a completely decentralized way. There is no central authority that controls the topology of the network, how nodes join or leave the system, or in which way nodes communicate with each other. Also, many future distributed applications will be built using wireless devices that communicate via radio.
The general objective of the proposed project is to improve our understanding of the algorithmic and theoretical foundations of decentralized distributed systems. From an algorithmic point of view, decentralized networks and computations pose a number of fascinating and unique challenges that are not present in sequential or more standard distributed systems. As communication is limited and mostly between nearby nodes, each node of a large network can only maintain a very restricted view of the global state of the system. This is particularly true if the network can change dynamically, either by nodes joining or leaving the system or if the topology changes over time, e.g., because of the mobility of the devices in case of a wireless network. Nevertheless, the nodes of a network need to coordinate in order to achieve some global goal.
In particular, we plan to study algorithms and lower bounds for basic computation and information dissemination tasks in such systems. In addition, we are particularly interested in the complexity of distributed computations in dynamic and wireless networks."
Summary
"Many of today's and tomorrow's computer systems are built on top of large-scale networks such as, e.g., the Internet, the world wide web, wireless ad hoc and sensor networks, or peer-to-peer networks. Driven by technological advances, new kinds of networks and applications have become possible and we can safely assume that this trend is going to continue. Often modern systems are envisioned to consist of a potentially large number of individual components that are organized in a completely decentralized way. There is no central authority that controls the topology of the network, how nodes join or leave the system, or in which way nodes communicate with each other. Also, many future distributed applications will be built using wireless devices that communicate via radio.
The general objective of the proposed project is to improve our understanding of the algorithmic and theoretical foundations of decentralized distributed systems. From an algorithmic point of view, decentralized networks and computations pose a number of fascinating and unique challenges that are not present in sequential or more standard distributed systems. As communication is limited and mostly between nearby nodes, each node of a large network can only maintain a very restricted view of the global state of the system. This is particularly true if the network can change dynamically, either by nodes joining or leaving the system or if the topology changes over time, e.g., because of the mobility of the devices in case of a wireless network. Nevertheless, the nodes of a network need to coordinate in order to achieve some global goal.
In particular, we plan to study algorithms and lower bounds for basic computation and information dissemination tasks in such systems. In addition, we are particularly interested in the complexity of distributed computations in dynamic and wireless networks."
Max ERC Funding
1 148 000 €
Duration
Start date: 2013-11-01, End date: 2018-10-31
Project acronym ACOULOMODE
Project Advanced coupling of low order combustor simulations with thermoacoustic modelling and controller design
Researcher (PI) Aimee Morgans
Host Institution (HI) IMPERIAL COLLEGE OF SCIENCE TECHNOLOGY AND MEDICINE
Call Details Starting Grant (StG), PE8, ERC-2012-StG_20111012
Summary "Combustion is essential to the world’s energy generation and transport needs, and will remain so for the foreseeable future. Mitigating its impact on the climate and human health, by reducing its associated emissions, is thus a priority. One significant challenge for gas-turbine combustion is combustion instability, which is currently inhibiting reductions in NOx emissions (these damage human health via a deterioration in air quality). Combustion instability is caused by a two-way coupling between unsteady combustion and acoustic waves - the large pressure oscillations that result can cause substantial mechanical damage. Currently, the lack of fast, accurate modelling tools for combustion instability, and the lack of reliable ways of suppressing it are severely hindering reductions in NOx emissions.
This proposal aims to make step improvements in both fast, accurate modelling of combustion instability, and in developing reliable active control strategies for its suppression. It will achieve this by coupling low order combustor models (these are fast, simplified models for simulating combustion instability) with advances in analytical modelling, CFD simulation, reduced order modelling and control theory tools. In particular:
* important advances in accurately incorporating the effect of entropy waves (temperature variations resulting from unsteady combustion) and non-linear flame models will be made;
* new active control strategies for achieving reliable suppression of combustion instability, including from within limit cycle oscillations, will be developed;
* an open-source low order combustor modelling tool will be developed and widely disseminated, opening access to researchers worldwide and improving communications between the fields of thermoacoustics and control theory.
Thus the proposal aims to use analytical and computational methods to contribute to achieving low NOx gas-turbine combustion, without the penalty of damaging combustion instability."
Summary
"Combustion is essential to the world’s energy generation and transport needs, and will remain so for the foreseeable future. Mitigating its impact on the climate and human health, by reducing its associated emissions, is thus a priority. One significant challenge for gas-turbine combustion is combustion instability, which is currently inhibiting reductions in NOx emissions (these damage human health via a deterioration in air quality). Combustion instability is caused by a two-way coupling between unsteady combustion and acoustic waves - the large pressure oscillations that result can cause substantial mechanical damage. Currently, the lack of fast, accurate modelling tools for combustion instability, and the lack of reliable ways of suppressing it are severely hindering reductions in NOx emissions.
This proposal aims to make step improvements in both fast, accurate modelling of combustion instability, and in developing reliable active control strategies for its suppression. It will achieve this by coupling low order combustor models (these are fast, simplified models for simulating combustion instability) with advances in analytical modelling, CFD simulation, reduced order modelling and control theory tools. In particular:
* important advances in accurately incorporating the effect of entropy waves (temperature variations resulting from unsteady combustion) and non-linear flame models will be made;
* new active control strategies for achieving reliable suppression of combustion instability, including from within limit cycle oscillations, will be developed;
* an open-source low order combustor modelling tool will be developed and widely disseminated, opening access to researchers worldwide and improving communications between the fields of thermoacoustics and control theory.
Thus the proposal aims to use analytical and computational methods to contribute to achieving low NOx gas-turbine combustion, without the penalty of damaging combustion instability."
Max ERC Funding
1 489 309 €
Duration
Start date: 2013-01-01, End date: 2017-12-31
Project acronym ACROSS
Project 3D Reconstruction and Modeling across Different Levels of Abstraction
Researcher (PI) Leif Kobbelt
Host Institution (HI) RHEINISCH-WESTFAELISCHE TECHNISCHE HOCHSCHULE AACHEN
Call Details Advanced Grant (AdG), PE6, ERC-2013-ADG
Summary "Digital 3D models are gaining more and more importance in diverse application fields ranging from computer graphics, multimedia and simulation sciences to engineering, architecture, and medicine. Powerful technologies to digitize the 3D shape of real objects and scenes are becoming available even to consumers. However, the raw geometric data emerging from, e.g., 3D scanning or multi-view stereo often lacks a consistent structure and meta-information which are necessary for the effective deployment of such models in sophisticated down-stream applications like animation, simulation, or CAD/CAM that go beyond mere visualization. Our goal is to develop new fundamental algorithms which transform raw geometric input data into augmented 3D models that are equipped with structural meta information such as feature aligned meshes, patch segmentations, local and global geometric constraints, statistical shape variation data, or even procedural descriptions. Our methodological approach is inspired by the human perceptual system that integrates bottom-up (data-driven) and top-down (model-driven) mechanisms in its hierarchical processing. Similarly we combine algorithms operating on different levels of abstraction into reconstruction and modeling networks. Instead of developing an individual solution for each specific application scenario, we create an eco-system of algorithms for automatic processing and interactive design of highly complex 3D models. A key concept is the information flow across all levels of abstraction in a bottom-up as well as top-down fashion. We not only aim at optimizing geometric representations but in fact at bridging the gap between reconstruction and recognition of geometric objects. The results from this project will make it possible to bring 3D models of real world objects into many highly relevant applications in science, industry, and entertainment, greatly reducing the excessive manual effort that is still necessary today."
Summary
"Digital 3D models are gaining more and more importance in diverse application fields ranging from computer graphics, multimedia and simulation sciences to engineering, architecture, and medicine. Powerful technologies to digitize the 3D shape of real objects and scenes are becoming available even to consumers. However, the raw geometric data emerging from, e.g., 3D scanning or multi-view stereo often lacks a consistent structure and meta-information which are necessary for the effective deployment of such models in sophisticated down-stream applications like animation, simulation, or CAD/CAM that go beyond mere visualization. Our goal is to develop new fundamental algorithms which transform raw geometric input data into augmented 3D models that are equipped with structural meta information such as feature aligned meshes, patch segmentations, local and global geometric constraints, statistical shape variation data, or even procedural descriptions. Our methodological approach is inspired by the human perceptual system that integrates bottom-up (data-driven) and top-down (model-driven) mechanisms in its hierarchical processing. Similarly we combine algorithms operating on different levels of abstraction into reconstruction and modeling networks. Instead of developing an individual solution for each specific application scenario, we create an eco-system of algorithms for automatic processing and interactive design of highly complex 3D models. A key concept is the information flow across all levels of abstraction in a bottom-up as well as top-down fashion. We not only aim at optimizing geometric representations but in fact at bridging the gap between reconstruction and recognition of geometric objects. The results from this project will make it possible to bring 3D models of real world objects into many highly relevant applications in science, industry, and entertainment, greatly reducing the excessive manual effort that is still necessary today."
Max ERC Funding
2 482 000 €
Duration
Start date: 2014-03-01, End date: 2019-02-28
Project acronym ActiveWindFarms
Project Active Wind Farms: Optimization and Control of Atmospheric Energy Extraction in Gigawatt Wind Farms
Researcher (PI) Johan Meyers
Host Institution (HI) KATHOLIEKE UNIVERSITEIT LEUVEN
Call Details Starting Grant (StG), PE8, ERC-2012-StG_20111012
Summary With the recognition that wind energy will become an important contributor to the world’s energy portfolio, several wind farms with a capacity of over 1 gigawatt are in planning phase. In the past, engineering of wind farms focused on a bottom-up approach, in which atmospheric wind availability was considered to be fixed by climate and weather. However, farms of gigawatt size slow down the Atmospheric Boundary Layer (ABL) as a whole, reducing the availability of wind at turbine hub height. In Denmark’s large off-shore farms, this leads to underperformance of turbines which can reach levels of 40%–50% compared to the same turbine in a lone-standing case. For large wind farms, the vertical structure and turbulence physics of the flow in the ABL become crucial ingredients in their design and operation. This introduces a new set of scientific challenges related to the design and control of large wind farms. The major ambition of the present research proposal is to employ optimal control techniques to control the interaction between large wind farms and the ABL, and optimize overall farm-power extraction. Individual turbines are used as flow actuators by dynamically pitching their blades using time scales ranging between 10 to 500 seconds. The application of such control efforts on the atmospheric boundary layer has never been attempted before, and introduces flow control on a physical scale which is currently unprecedented. The PI possesses a unique combination of expertise and tools enabling these developments: efficient parallel large-eddy simulations of wind farms, multi-scale turbine modeling, and gradient-based optimization in large optimization-parameter spaces using adjoint formulations. To ensure a maximum impact on the wind-engineering field, the project aims at optimal control, experimental wind-tunnel validation, and at including multi-disciplinary aspects, related to structural mechanics, power quality, and controller design.
Summary
With the recognition that wind energy will become an important contributor to the world’s energy portfolio, several wind farms with a capacity of over 1 gigawatt are in planning phase. In the past, engineering of wind farms focused on a bottom-up approach, in which atmospheric wind availability was considered to be fixed by climate and weather. However, farms of gigawatt size slow down the Atmospheric Boundary Layer (ABL) as a whole, reducing the availability of wind at turbine hub height. In Denmark’s large off-shore farms, this leads to underperformance of turbines which can reach levels of 40%–50% compared to the same turbine in a lone-standing case. For large wind farms, the vertical structure and turbulence physics of the flow in the ABL become crucial ingredients in their design and operation. This introduces a new set of scientific challenges related to the design and control of large wind farms. The major ambition of the present research proposal is to employ optimal control techniques to control the interaction between large wind farms and the ABL, and optimize overall farm-power extraction. Individual turbines are used as flow actuators by dynamically pitching their blades using time scales ranging between 10 to 500 seconds. The application of such control efforts on the atmospheric boundary layer has never been attempted before, and introduces flow control on a physical scale which is currently unprecedented. The PI possesses a unique combination of expertise and tools enabling these developments: efficient parallel large-eddy simulations of wind farms, multi-scale turbine modeling, and gradient-based optimization in large optimization-parameter spaces using adjoint formulations. To ensure a maximum impact on the wind-engineering field, the project aims at optimal control, experimental wind-tunnel validation, and at including multi-disciplinary aspects, related to structural mechanics, power quality, and controller design.
Max ERC Funding
1 499 241 €
Duration
Start date: 2012-10-01, End date: 2017-09-30
Project acronym ACTIVIA
Project Visual Recognition of Function and Intention
Researcher (PI) Ivan Laptev
Host Institution (HI) INSTITUT NATIONAL DE RECHERCHE ENINFORMATIQUE ET AUTOMATIQUE
Call Details Starting Grant (StG), PE6, ERC-2012-StG_20111012
Summary "Computer vision is concerned with the automated interpretation of images and video streams. Today's research is (mostly) aimed at answering queries such as ""Is this a picture of a dog?"", (classification) or sometimes ""Find the dog in this photo"" (detection). While categorisation and detection are useful for many tasks, inferring correct class labels is not the final answer to visual recognition. The categories and locations of objects do not provide direct understanding of their function i.e., how things work, what they can be used for, or how they can act and react. Such an understanding, however, would be highly desirable to answer currently unsolvable queries such as ""Am I in danger?"" or ""What can happen in this scene?"". Solving such queries is the aim of this proposal.
My goal is to uncover the functional properties of objects and the purpose of actions by addressing visual recognition from a different and yet unexplored perspective. The main novelty of this proposal is to leverage observations of people, i.e., their actions and interactions to automatically learn the use, the purpose and the function of objects and scenes from visual data. The project is timely as it builds upon the two key recent technological advances: (a) the immense progress in visual recognition of objects, scenes and human actions achieved in the last ten years, as well as (b) the emergence of a massive amount of public image and video data now available to train visual models.
ACTIVIA addresses fundamental research issues in automated interpretation of dynamic visual scenes, but its results are expected to serve as a basis for ground-breaking technological advances in practical applications. The recognition of functional properties and intentions as explored in this project will directly support high-impact applications such as detection of abnormal events, which are likely to revolutionise today's approaches to crime protection, hazard prevention, elderly care, and many others."
Summary
"Computer vision is concerned with the automated interpretation of images and video streams. Today's research is (mostly) aimed at answering queries such as ""Is this a picture of a dog?"", (classification) or sometimes ""Find the dog in this photo"" (detection). While categorisation and detection are useful for many tasks, inferring correct class labels is not the final answer to visual recognition. The categories and locations of objects do not provide direct understanding of their function i.e., how things work, what they can be used for, or how they can act and react. Such an understanding, however, would be highly desirable to answer currently unsolvable queries such as ""Am I in danger?"" or ""What can happen in this scene?"". Solving such queries is the aim of this proposal.
My goal is to uncover the functional properties of objects and the purpose of actions by addressing visual recognition from a different and yet unexplored perspective. The main novelty of this proposal is to leverage observations of people, i.e., their actions and interactions to automatically learn the use, the purpose and the function of objects and scenes from visual data. The project is timely as it builds upon the two key recent technological advances: (a) the immense progress in visual recognition of objects, scenes and human actions achieved in the last ten years, as well as (b) the emergence of a massive amount of public image and video data now available to train visual models.
ACTIVIA addresses fundamental research issues in automated interpretation of dynamic visual scenes, but its results are expected to serve as a basis for ground-breaking technological advances in practical applications. The recognition of functional properties and intentions as explored in this project will directly support high-impact applications such as detection of abnormal events, which are likely to revolutionise today's approaches to crime protection, hazard prevention, elderly care, and many others."
Max ERC Funding
1 497 420 €
Duration
Start date: 2013-01-01, End date: 2018-12-31
Project acronym ACUITY
Project Algorithms for coping with uncertainty and intractability
Researcher (PI) Nikhil Bansal
Host Institution (HI) TECHNISCHE UNIVERSITEIT EINDHOVEN
Call Details Consolidator Grant (CoG), PE6, ERC-2013-CoG
Summary The two biggest challenges in solving practical optimization problems are computational intractability, and the presence
of uncertainty: most problems are either NP-hard, or have incomplete input data which
makes an exact computation impossible.
Recently, there has been a huge progress in our understanding of intractability, based on spectacular algorithmic and lower bound techniques. For several problems, especially those with only local constraints, we can design optimum
approximation algorithms that are provably the best possible.
However, typical optimization problems usually involve complex global constraints and are much less understood. The situation is even worse for coping with uncertainty. Most of the algorithms are based on ad-hoc techniques and there is no deeper understanding of what makes various problems easy or hard.
This proposal describes several new directions, together with concrete intermediate goals, that will break important new ground in the theory of approximation and online algorithms. The particular directions we consider are (i) extend the primal dual method to systematically design online algorithms, (ii) build a structural theory of online problems based on work functions, (iii) develop new tools to use the power of strong convex relaxations and (iv) design new algorithmic approaches based on non-constructive proof techniques.
The proposed research is at the
cutting edge of algorithm design, and builds upon the recent success of the PI in resolving several longstanding questions in these areas. Any progress is likely to be a significant contribution to theoretical
computer science and combinatorial optimization.
Summary
The two biggest challenges in solving practical optimization problems are computational intractability, and the presence
of uncertainty: most problems are either NP-hard, or have incomplete input data which
makes an exact computation impossible.
Recently, there has been a huge progress in our understanding of intractability, based on spectacular algorithmic and lower bound techniques. For several problems, especially those with only local constraints, we can design optimum
approximation algorithms that are provably the best possible.
However, typical optimization problems usually involve complex global constraints and are much less understood. The situation is even worse for coping with uncertainty. Most of the algorithms are based on ad-hoc techniques and there is no deeper understanding of what makes various problems easy or hard.
This proposal describes several new directions, together with concrete intermediate goals, that will break important new ground in the theory of approximation and online algorithms. The particular directions we consider are (i) extend the primal dual method to systematically design online algorithms, (ii) build a structural theory of online problems based on work functions, (iii) develop new tools to use the power of strong convex relaxations and (iv) design new algorithmic approaches based on non-constructive proof techniques.
The proposed research is at the
cutting edge of algorithm design, and builds upon the recent success of the PI in resolving several longstanding questions in these areas. Any progress is likely to be a significant contribution to theoretical
computer science and combinatorial optimization.
Max ERC Funding
1 519 285 €
Duration
Start date: 2014-05-01, End date: 2019-04-30
Project acronym ADAPT
Project Theory and Algorithms for Adaptive Particle Simulation
Researcher (PI) Stephane Redon
Host Institution (HI) INSTITUT NATIONAL DE RECHERCHE ENINFORMATIQUE ET AUTOMATIQUE
Call Details Starting Grant (StG), PE6, ERC-2012-StG_20111012
Summary "During the twentieth century, the development of macroscopic engineering has been largely stimulated by progress in digital prototyping: cars, planes, boats, etc. are nowadays designed and tested on computers. Digital prototypes have progressively replaced actual ones, and effective computer-aided engineering tools have helped cut costs and reduce production cycles of these macroscopic systems.
The twenty-first century is most likely to see a similar development at the atomic scale. Indeed, the recent years have seen tremendous progress in nanotechnology - in particular in the ability to control matter at the atomic scale. Similar to what has happened with macroscopic engineering, powerful and generic computational tools will be needed to engineer complex nanosystems, through modeling and simulation. As a result, a major challenge is to develop efficient simulation methods and algorithms.
NANO-D, the INRIA research group I started in January 2008 in Grenoble, France, aims at developing
efficient computational methods for modeling and simulating complex nanosystems, both natural and artificial. In particular, NANO-D develops SAMSON, a software application which gathers all algorithms designed by the group and its collaborators (SAMSON: Software for Adaptive Modeling and Simulation Of Nanosystems).
In this project, I propose to develop a unified theory, and associated algorithms, for adaptive particle simulation. The proposed theory will avoid problems that plague current popular multi-scale or hybrid simulation approaches by simulating a single potential throughout the system, while allowing users to finely trade precision for computational speed.
I believe the full development of the adaptive particle simulation theory will have an important impact on current modeling and simulation practices, and will enable practical design of complex nanosystems on desktop computers, which should significantly boost the emergence of generic nano-engineering."
Summary
"During the twentieth century, the development of macroscopic engineering has been largely stimulated by progress in digital prototyping: cars, planes, boats, etc. are nowadays designed and tested on computers. Digital prototypes have progressively replaced actual ones, and effective computer-aided engineering tools have helped cut costs and reduce production cycles of these macroscopic systems.
The twenty-first century is most likely to see a similar development at the atomic scale. Indeed, the recent years have seen tremendous progress in nanotechnology - in particular in the ability to control matter at the atomic scale. Similar to what has happened with macroscopic engineering, powerful and generic computational tools will be needed to engineer complex nanosystems, through modeling and simulation. As a result, a major challenge is to develop efficient simulation methods and algorithms.
NANO-D, the INRIA research group I started in January 2008 in Grenoble, France, aims at developing
efficient computational methods for modeling and simulating complex nanosystems, both natural and artificial. In particular, NANO-D develops SAMSON, a software application which gathers all algorithms designed by the group and its collaborators (SAMSON: Software for Adaptive Modeling and Simulation Of Nanosystems).
In this project, I propose to develop a unified theory, and associated algorithms, for adaptive particle simulation. The proposed theory will avoid problems that plague current popular multi-scale or hybrid simulation approaches by simulating a single potential throughout the system, while allowing users to finely trade precision for computational speed.
I believe the full development of the adaptive particle simulation theory will have an important impact on current modeling and simulation practices, and will enable practical design of complex nanosystems on desktop computers, which should significantly boost the emergence of generic nano-engineering."
Max ERC Funding
1 476 882 €
Duration
Start date: 2012-09-01, End date: 2017-08-31
Project acronym AEROFLEX
Project AEROelastic instabilities and control of FLEXible Structures
Researcher (PI) Olivier Pierre MARQUET
Host Institution (HI) OFFICE NATIONAL D'ETUDES ET DE RECHERCHES AEROSPATIALES
Call Details Starting Grant (StG), PE8, ERC-2014-STG
Summary Aeroelastic instabilities are at the origin of large deformations of structures and are limiting the capacities of products in various industrial branches such as aeronautics, marine industry, or wind electricity production. If suppressing aeroelastic instabilities is an ultimate goal, a paradigm shift in the technological development is to take advantage of these instabilities to achieve others objectives, as reducing the drag of these flexible structures. The ground-breaking challenges addressed in this project are to design fundamentally new theoretical methodologies for (i) describing mathematically aeroelastic instabilities, (ii) suppressing them and (iii) using them to reduce mean drag of structures at a low energetic cost. To that aim, two types of aeroelastic phenomena will be specifically studied: the flutter, which arises as a result of an unstable coupling instability between two stable dynamics, that of the structures and that the flow, and vortex-induced vibrations which appear when the fluid dynamics is unstable. An aeroelastic global stability analysis will be first developed and applied to problems of increasing complexity, starting from two-dimensional free-vibrating rigid structures and progressing towards three-dimensional free-deforming elastic structures. The control of these aeroelastic instabilities will be then addressed with two different objectives: their suppression or their use for flow control. A theoretical passive control methodology will be established for suppressing linear aeroelastic instabilities, and extended to high Reynolds number flows and experimental configurations. New perturbation methods for solving strongly nonlinear problems and adjoint-based control algorithm will allow to use these aeroelastic instabilities for drag reduction. This project will allow innovative control solutions to emerge, not only in flutter or vortex-induced vibrations problems, but also in a much broader class of fluid-structure problems.
Summary
Aeroelastic instabilities are at the origin of large deformations of structures and are limiting the capacities of products in various industrial branches such as aeronautics, marine industry, or wind electricity production. If suppressing aeroelastic instabilities is an ultimate goal, a paradigm shift in the technological development is to take advantage of these instabilities to achieve others objectives, as reducing the drag of these flexible structures. The ground-breaking challenges addressed in this project are to design fundamentally new theoretical methodologies for (i) describing mathematically aeroelastic instabilities, (ii) suppressing them and (iii) using them to reduce mean drag of structures at a low energetic cost. To that aim, two types of aeroelastic phenomena will be specifically studied: the flutter, which arises as a result of an unstable coupling instability between two stable dynamics, that of the structures and that the flow, and vortex-induced vibrations which appear when the fluid dynamics is unstable. An aeroelastic global stability analysis will be first developed and applied to problems of increasing complexity, starting from two-dimensional free-vibrating rigid structures and progressing towards three-dimensional free-deforming elastic structures. The control of these aeroelastic instabilities will be then addressed with two different objectives: their suppression or their use for flow control. A theoretical passive control methodology will be established for suppressing linear aeroelastic instabilities, and extended to high Reynolds number flows and experimental configurations. New perturbation methods for solving strongly nonlinear problems and adjoint-based control algorithm will allow to use these aeroelastic instabilities for drag reduction. This project will allow innovative control solutions to emerge, not only in flutter or vortex-induced vibrations problems, but also in a much broader class of fluid-structure problems.
Max ERC Funding
1 377 290 €
Duration
Start date: 2015-07-01, End date: 2020-06-30
Project acronym AEROSPACEPHYS
Project Multiphysics models and simulations for reacting and plasma flows applied to the space exploration program
Researcher (PI) Thierry Edouard Bertrand Magin
Host Institution (HI) INSTITUT VON KARMAN DE DYNAMIQUE DES FLUIDES
Call Details Starting Grant (StG), PE8, ERC-2010-StG_20091028
Summary Space exploration is one of boldest and most exciting endeavors that humanity has undertaken, and it holds enormous promise for the future. Our next challenges for the spatial conquest include bringing back samples to Earth by means of robotic missions and continuing the manned exploration program, which aims at sending human beings to Mars and bring them home safely. Inaccurate prediction of the heat-flux to the surface of the spacecraft heat shield can be fatal for the crew or the success of a robotic mission. This quantity is estimated during the design phase. An accurate prediction is a particularly complex task, regarding modelling of the following phenomena that are potential “mission killers:” 1) Radiation of the plasma in the shock layer, 2) Complex surface chemistry on the thermal protection material, 3) Flow transition from laminar to turbulent. Our poor understanding of the coupled mechanisms of radiation, ablation, and transition leads to the difficulties in flux prediction. To avoid failure and ensure safety of the astronauts and payload, engineers resort to “safety factors” to determine the thickness of the heat shield, at the expense of the mass of embarked payload. Thinking out of the box and basic research are thus necessary for advancements of the models that will better define the environment and requirements for the design and safe operation of tomorrow’s space vehicles and planetary probes for the manned space exploration. The three basic ingredients for predictive science are: 1) Physico-chemical models, 2) Computational methods, 3) Experimental data. We propose to follow a complementary approach for prediction. The proposed research aims at: “Integrating new advanced physico-chemical models and computational methods, based on a multidisciplinary approach developed together with physicists, chemists, and applied mathematicians, to create a top-notch multiphysics and multiscale numerical platform for simulations of planetary atmosphere entries, crucial to the new challenges of the manned space exploration program. Experimental data will also be used for validation, following state-of-the-art uncertainty quantification methods.”
Summary
Space exploration is one of boldest and most exciting endeavors that humanity has undertaken, and it holds enormous promise for the future. Our next challenges for the spatial conquest include bringing back samples to Earth by means of robotic missions and continuing the manned exploration program, which aims at sending human beings to Mars and bring them home safely. Inaccurate prediction of the heat-flux to the surface of the spacecraft heat shield can be fatal for the crew or the success of a robotic mission. This quantity is estimated during the design phase. An accurate prediction is a particularly complex task, regarding modelling of the following phenomena that are potential “mission killers:” 1) Radiation of the plasma in the shock layer, 2) Complex surface chemistry on the thermal protection material, 3) Flow transition from laminar to turbulent. Our poor understanding of the coupled mechanisms of radiation, ablation, and transition leads to the difficulties in flux prediction. To avoid failure and ensure safety of the astronauts and payload, engineers resort to “safety factors” to determine the thickness of the heat shield, at the expense of the mass of embarked payload. Thinking out of the box and basic research are thus necessary for advancements of the models that will better define the environment and requirements for the design and safe operation of tomorrow’s space vehicles and planetary probes for the manned space exploration. The three basic ingredients for predictive science are: 1) Physico-chemical models, 2) Computational methods, 3) Experimental data. We propose to follow a complementary approach for prediction. The proposed research aims at: “Integrating new advanced physico-chemical models and computational methods, based on a multidisciplinary approach developed together with physicists, chemists, and applied mathematicians, to create a top-notch multiphysics and multiscale numerical platform for simulations of planetary atmosphere entries, crucial to the new challenges of the manned space exploration program. Experimental data will also be used for validation, following state-of-the-art uncertainty quantification methods.”
Max ERC Funding
1 494 892 €
Duration
Start date: 2010-09-01, End date: 2015-08-31
Project acronym AFFINITY
Project Actuation of Ferromagnetic Fibre Networks to improve Implant Longevity
Researcher (PI) Athina Markaki
Host Institution (HI) THE CHANCELLOR MASTERS AND SCHOLARS OF THE UNIVERSITY OF CAMBRIDGE
Call Details Starting Grant (StG), PE8, ERC-2009-StG
Summary This proposal is for an exploratory study into a radical new approach to the problem of orthopaedic implant loosening. Such loosening commonly occurs because the joint between the implant and the surrounding bone is insufficiently strong and durable. It is a serious problem both for implants cemented to the bone and for those dependent on bone in-growth into a rough/porous implant surface. In the latter case, the main problem is commonly that bone in-growth is insufficiently rapid or deep for a strong bond to be established. The idea proposed in this work is that the implant should have a highly porous surface layer, made by bonding ferromagnetic fibres together, into which bone tissue growth would occur. During the post-operative period, application of a magnetic field will cause the fibre network to deform elastically, as individual fibres tend to align with the field. This will impose strains on the bone tissue as it grows into the fibre network. Such mechanical deformation is known to be highly beneficial in promoting bone growth, providing the associated strain lies in a certain range (~0.1%). Preliminary work, involving both model development and experimental studies on the effect of magnetic fields on fibre networks, has suggested that beneficial therapeutic effects can be induced using field strengths no greater than those already employed for diagnostic purposes. A comprehensive 5-year, highly inter-disciplinary programme is planned, encompassing processing, network architecture characterisation, magneto-mechanical response investigations, various modelling activities and systematic in vitro experimentation to establish whether magneto-mechanical Actuation of Ferromagnetic Fibre Networks shows promise as a new therapeutic approach to improve implant longevity.
Summary
This proposal is for an exploratory study into a radical new approach to the problem of orthopaedic implant loosening. Such loosening commonly occurs because the joint between the implant and the surrounding bone is insufficiently strong and durable. It is a serious problem both for implants cemented to the bone and for those dependent on bone in-growth into a rough/porous implant surface. In the latter case, the main problem is commonly that bone in-growth is insufficiently rapid or deep for a strong bond to be established. The idea proposed in this work is that the implant should have a highly porous surface layer, made by bonding ferromagnetic fibres together, into which bone tissue growth would occur. During the post-operative period, application of a magnetic field will cause the fibre network to deform elastically, as individual fibres tend to align with the field. This will impose strains on the bone tissue as it grows into the fibre network. Such mechanical deformation is known to be highly beneficial in promoting bone growth, providing the associated strain lies in a certain range (~0.1%). Preliminary work, involving both model development and experimental studies on the effect of magnetic fields on fibre networks, has suggested that beneficial therapeutic effects can be induced using field strengths no greater than those already employed for diagnostic purposes. A comprehensive 5-year, highly inter-disciplinary programme is planned, encompassing processing, network architecture characterisation, magneto-mechanical response investigations, various modelling activities and systematic in vitro experimentation to establish whether magneto-mechanical Actuation of Ferromagnetic Fibre Networks shows promise as a new therapeutic approach to improve implant longevity.
Max ERC Funding
1 442 756 €
Duration
Start date: 2010-01-01, End date: 2015-11-30
