Project acronym HBAR-HFS
Project Hyperfine structure of antihydrogen
Researcher (PI) Eberhard Widmann
Host Institution (HI) OESTERREICHISCHE AKADEMIE DER WISSENSCHAFTEN
Call Details Advanced Grant (AdG), PE2, ERC-2011-ADG_20110209
Summary Antihydrogen is the simplest atom consisting entirely of antimatter. Since its counterpart hydrogen is one of the best studied atoms in physics, a comparison of antihydrogen and hydrogen offers one of the most sensitive tests of CPT symmetry. CPT, the successive application of charge conjugation, parity and time reversal transformation is a fundamental symmetry conserved in the standard model (SM) of particle physics as a consequence of a mathematical theorem. These conditions for this theorem to be fulfilled are not valid any more in extensions of the SM like string theory or quantum gravity. Furthermore, even a tiny violation of CPT symmetry at the time of the big bang could be a cause of the observed antimatter absence in the universe. Thus the observation of CPT violation might offer a first indication for the validity of string theory, and would have important cosmological consequences.
This project proposes to measure the ground state hyperfine (HFS) splitting of antihydrogen (HBAR), which is known in hydrogen with relative precision of 10^–12. The experimental method pursued within the ASACUSA collaboration at CERN-AD consists in the formation of an antihydrogen beam and a measurement using a spin-flip cavity and a sextupole magnet as spin analyser like it was done initially for hydrogen. A major milestone was achieved in 2010 when antihydrogen was first synthesized by ASACUSA. In the first phase of this proposal, an antihydrogen beam will be produced and the HBAR-HFS will be measured to a precision of around 10^–7 using a single microwave cavity. In a second phase, the Ramsey method of separated oscillatory fields will be used to increase the precision further. In parallel methods will be developed towards trapping and laser cooling the antihydrogen atoms. Letting the cooled antihydrogen escape in a field free region and perform microwave spectroscopy offers the ultimate precision achievable to measure the HBAR-HFS and one of the most sensitive tests of CPT.
Summary
Antihydrogen is the simplest atom consisting entirely of antimatter. Since its counterpart hydrogen is one of the best studied atoms in physics, a comparison of antihydrogen and hydrogen offers one of the most sensitive tests of CPT symmetry. CPT, the successive application of charge conjugation, parity and time reversal transformation is a fundamental symmetry conserved in the standard model (SM) of particle physics as a consequence of a mathematical theorem. These conditions for this theorem to be fulfilled are not valid any more in extensions of the SM like string theory or quantum gravity. Furthermore, even a tiny violation of CPT symmetry at the time of the big bang could be a cause of the observed antimatter absence in the universe. Thus the observation of CPT violation might offer a first indication for the validity of string theory, and would have important cosmological consequences.
This project proposes to measure the ground state hyperfine (HFS) splitting of antihydrogen (HBAR), which is known in hydrogen with relative precision of 10^–12. The experimental method pursued within the ASACUSA collaboration at CERN-AD consists in the formation of an antihydrogen beam and a measurement using a spin-flip cavity and a sextupole magnet as spin analyser like it was done initially for hydrogen. A major milestone was achieved in 2010 when antihydrogen was first synthesized by ASACUSA. In the first phase of this proposal, an antihydrogen beam will be produced and the HBAR-HFS will be measured to a precision of around 10^–7 using a single microwave cavity. In a second phase, the Ramsey method of separated oscillatory fields will be used to increase the precision further. In parallel methods will be developed towards trapping and laser cooling the antihydrogen atoms. Letting the cooled antihydrogen escape in a field free region and perform microwave spectroscopy offers the ultimate precision achievable to measure the HBAR-HFS and one of the most sensitive tests of CPT.
Max ERC Funding
2 599 900 €
Duration
Start date: 2012-03-01, End date: 2017-02-28
Project acronym HOMOVIS
Project High-level Prior Models for Computer Vision
Researcher (PI) Thomas Pock
Host Institution (HI) TECHNISCHE UNIVERSITAET GRAZ
Call Details Starting Grant (StG), PE6, ERC-2014-STG
Summary Since more than 50 years, computer vision has been a very active research field but it is still far away from the abilities of the human visual system. This stunning performance of the human visual system can be mainly contributed to a highly efficient three-layer architecture: A low-level layer that sparsifies the visual information by detecting important image features such as image gradients, a mid-level layer that implements disocclusion and boundary completion processes and finally a high-level layer that is concerned with the recognition of objects.
Variational methods are certainly one of the most successful methods for low-level vision. However, it is very unlikely that these methods can be further improved without the integration of high-level prior models. Therefore, we propose a unified mathematical framework that allows for a natural integration of high-level priors into low-level variational models. In particular, we propose to represent images in a higher-dimensional space which is inspired by the architecture for the visual cortex. This space performs a decomposition of the image gradients into magnitude and direction and hence performs a lifting of the 2D image to a 3D space. This has several advantages: Firstly, the higher-dimensional embedding allows to implement mid-level tasks such as boundary completion and disocclusion processes in a very natural way. Secondly, the lifted space allows for an explicit access to the orientation and the magnitude of image gradients. In turn, distributions of gradient orientations – known to be highly effective for object detection – can be utilized as high-level priors. This inverts the bottom-up nature of object detectors and hence adds an efficient top-down process to low-level variational models.
The developed mathematical approaches will go significantly beyond traditional variational models for computer vision and hence will define a new state-of-the-art in the field.
Summary
Since more than 50 years, computer vision has been a very active research field but it is still far away from the abilities of the human visual system. This stunning performance of the human visual system can be mainly contributed to a highly efficient three-layer architecture: A low-level layer that sparsifies the visual information by detecting important image features such as image gradients, a mid-level layer that implements disocclusion and boundary completion processes and finally a high-level layer that is concerned with the recognition of objects.
Variational methods are certainly one of the most successful methods for low-level vision. However, it is very unlikely that these methods can be further improved without the integration of high-level prior models. Therefore, we propose a unified mathematical framework that allows for a natural integration of high-level priors into low-level variational models. In particular, we propose to represent images in a higher-dimensional space which is inspired by the architecture for the visual cortex. This space performs a decomposition of the image gradients into magnitude and direction and hence performs a lifting of the 2D image to a 3D space. This has several advantages: Firstly, the higher-dimensional embedding allows to implement mid-level tasks such as boundary completion and disocclusion processes in a very natural way. Secondly, the lifted space allows for an explicit access to the orientation and the magnitude of image gradients. In turn, distributions of gradient orientations – known to be highly effective for object detection – can be utilized as high-level priors. This inverts the bottom-up nature of object detectors and hence adds an efficient top-down process to low-level variational models.
The developed mathematical approaches will go significantly beyond traditional variational models for computer vision and hence will define a new state-of-the-art in the field.
Max ERC Funding
1 473 525 €
Duration
Start date: 2015-06-01, End date: 2020-05-31
Project acronym HYPROTIN
Project Hyperpolarized Nuclear Magnetic Resonance Spectroscopy for Time-Resolved Monitoring of Interactions of Intrinsically Disordered Breast-Cancer Proteins
Researcher (PI) Dennis Christian Benjamin Arthur KURZBACH
Host Institution (HI) UNIVERSITAT WIEN
Call Details Starting Grant (StG), PE4, ERC-2018-STG
Summary HYPROTIN proposes a pioneering research platform for hyperpolarized magnetic resonance of breast-cancer related proteins that will revolutionize our view on tumorigenesis at the atomic level, through bottom-up reconstitution of medicinal relevant interaction pathways involving the breast cancer susceptibility protein 1 (BRCA1).
The risk to develop a hereditary breast or ovarian cancer (HBOC) increases to 55-65 % upon mutation of the BRCA1 gene. Yet, little is known about the biochemistry of tumorigenesis, so that drugs directed towards molecular targets are not satisfactory. To date, mastectomy remains the only preventive treatment. This dramatic lack of knowledge is a consequence of BRCA1 being an intrinsically disordered protein (IDP). Recognizing the importance of IDPs has revolutionized structural biology in the last decade, but this also represents a huge experimental challenge. To date, nuclear magnetic resonance (NMR) is the only technique available to study IDPs at high resolution. However, several limits of the technique must be overcome. Its low sensitivity impedes investigations under biologically meaningful conditions, so that new approaches are required.
The HYPROTIN project aims to achieve two methodological goals: 1) Residue-resolved studies of the BRCA1 IDP under physiological conditions; and 2) real-time monitoring of BRCA1-ligand binding, thereby adding a time-resolved dimension to the NMR characterization of IDPs. This systematic approach will provide unprecedented insight into the BRCA1 interactome, provide medically relevant data and residue-resolved protein interaction kinetics. This will open a new knowledge base for rational drug design.
The project will employ cutting-edge equipment that is unique worldwide, and will represent the first facility in Europe suited for these ground-breaking experiments. The PI has unique interdisciplinary experience enabling the demanding hyperpolarization approach to IDPs.
Summary
HYPROTIN proposes a pioneering research platform for hyperpolarized magnetic resonance of breast-cancer related proteins that will revolutionize our view on tumorigenesis at the atomic level, through bottom-up reconstitution of medicinal relevant interaction pathways involving the breast cancer susceptibility protein 1 (BRCA1).
The risk to develop a hereditary breast or ovarian cancer (HBOC) increases to 55-65 % upon mutation of the BRCA1 gene. Yet, little is known about the biochemistry of tumorigenesis, so that drugs directed towards molecular targets are not satisfactory. To date, mastectomy remains the only preventive treatment. This dramatic lack of knowledge is a consequence of BRCA1 being an intrinsically disordered protein (IDP). Recognizing the importance of IDPs has revolutionized structural biology in the last decade, but this also represents a huge experimental challenge. To date, nuclear magnetic resonance (NMR) is the only technique available to study IDPs at high resolution. However, several limits of the technique must be overcome. Its low sensitivity impedes investigations under biologically meaningful conditions, so that new approaches are required.
The HYPROTIN project aims to achieve two methodological goals: 1) Residue-resolved studies of the BRCA1 IDP under physiological conditions; and 2) real-time monitoring of BRCA1-ligand binding, thereby adding a time-resolved dimension to the NMR characterization of IDPs. This systematic approach will provide unprecedented insight into the BRCA1 interactome, provide medically relevant data and residue-resolved protein interaction kinetics. This will open a new knowledge base for rational drug design.
The project will employ cutting-edge equipment that is unique worldwide, and will represent the first facility in Europe suited for these ground-breaking experiments. The PI has unique interdisciplinary experience enabling the demanding hyperpolarization approach to IDPs.
Max ERC Funding
1 990 728 €
Duration
Start date: 2019-03-01, End date: 2024-02-29
Project acronym INFIBRENANOSTRUCTURE
Project Fabrication and characterization of dielectric encapsulated millions of ordered kilometer-long nanostructures and their applications
Researcher (PI) Mehmet Bayindir
Host Institution (HI) BILKENT UNIVERSITESI VAKIF
Call Details Starting Grant (StG), PE5, ERC-2012-StG_20111012
Summary The objective of this project is the realization of a radically new nanowire fabrication technique, and exploration of its potential for nanowire based science and technology. The proposed method involves fabrication of unusually long, ordered nanowire and nanotube arrays in macroscopic fibres by means of an iterative thermal co-drawing process. Starting with a macroscopic rod with an annular hole tightly fitted with another rod of another compatible material, by successive thermal drawing we obtain arrays of nanowires embedded in fibres. With the method, wide range of materials, e.g. semiconductors, polymers, metals, can be turned into ordered nanorods, nanowires, nanotubes in various cross-sectional geometries. Main challenges are the thermal drawing steps that require critical matching of the viscoelastic properties of the protective cover with the encapsulated materials, and the liquid instability problems and phase intermixing with higher temperatures and smaller feature sizes that require high thermal and mechanical precision. Initially, fabrication by drawing will begin with soft amorphous semiconductors, phase change materials, polymers of interest in high temperature polymers, followed by a wider range of materials, low melting temperature metals, metals and common semiconductors (Si, Ge) in silica glass matrices. In this way nanowires that are ordered, easily accessible and hermetically sealed in a dielectric encapsulation will be obtained in high volumes. Potentially, these nanowires are advantages over on-chip nanowires in building flexible out of plane geometries, light weight, wearable and disposable devices. Ultimately, attaining ordered arrays of 1-D nanostructures in an extended flexible fibre with high yields will facilitate sought-after but up-to-now difficult applications such as the large area nanowire electronics and photonics, nanowire based scalable phase-change memory, nanowire photovoltaics, and emerging cell-nanowire interfacing.
Summary
The objective of this project is the realization of a radically new nanowire fabrication technique, and exploration of its potential for nanowire based science and technology. The proposed method involves fabrication of unusually long, ordered nanowire and nanotube arrays in macroscopic fibres by means of an iterative thermal co-drawing process. Starting with a macroscopic rod with an annular hole tightly fitted with another rod of another compatible material, by successive thermal drawing we obtain arrays of nanowires embedded in fibres. With the method, wide range of materials, e.g. semiconductors, polymers, metals, can be turned into ordered nanorods, nanowires, nanotubes in various cross-sectional geometries. Main challenges are the thermal drawing steps that require critical matching of the viscoelastic properties of the protective cover with the encapsulated materials, and the liquid instability problems and phase intermixing with higher temperatures and smaller feature sizes that require high thermal and mechanical precision. Initially, fabrication by drawing will begin with soft amorphous semiconductors, phase change materials, polymers of interest in high temperature polymers, followed by a wider range of materials, low melting temperature metals, metals and common semiconductors (Si, Ge) in silica glass matrices. In this way nanowires that are ordered, easily accessible and hermetically sealed in a dielectric encapsulation will be obtained in high volumes. Potentially, these nanowires are advantages over on-chip nanowires in building flexible out of plane geometries, light weight, wearable and disposable devices. Ultimately, attaining ordered arrays of 1-D nanostructures in an extended flexible fibre with high yields will facilitate sought-after but up-to-now difficult applications such as the large area nanowire electronics and photonics, nanowire based scalable phase-change memory, nanowire photovoltaics, and emerging cell-nanowire interfacing.
Max ERC Funding
1 495 400 €
Duration
Start date: 2012-10-01, End date: 2017-09-30
Project acronym INTELHYB
Project Next generation of complex metallic materials with intelligent hybrid structures
Researcher (PI) Jürgen Eckert
Host Institution (HI) OESTERREICHISCHE AKADEMIE DER WISSENSCHAFTEN
Call Details Advanced Grant (AdG), PE8, ERC-2013-ADG
Summary In a modern society, metallic materials are crucially important (e.g. energy, safety, infrastructure, transportation, health, medicine, life sciences, IT). Contemporary examples with inherent challenges to be overcome are the design of ultrahigh specific strength materials. There is a critical need for successful developments in this area in particular for reduced energy consumption, reduction of pollutant emissions and passenger safety. Alternative approaches include improved thermal stability and creep resistance of high-temperature alloys for energy conversion, which are generally used in power plants and turbine engines, high temperature process technology, and fossil-fuel driven engines. The ageing European society makes biomedical materials for implant and stent design also crucially important. A drawback of nearly all current high strength metallic materials is that they lack ductility (i.e. are brittle and hard to form)- or on the opposite side, they may be highly ductile but lack strength. The key concept behind INTELHYB is to define new routes for creation of tailored metallic materials based on scale-bridging intelligent hybrid structures enabling property as well as function optimization. The novelty of this proposal as compared to conventional ideas is that they apply to monolithic amorphous materials or bulk microcrystalline. The basis will be founded on innovative strategies for the design, synthesis and characterization of intrinsic length-scale modulation and phase transformation under highly non-equilibrium conditions. This will include the incorporation of dispersed phases which are close to or beyond their thermodynamic and mechanical stability limit thus forming a hierarchically structured hybrid and ductile/tough alloys. Alternatively, the material itself will be designed in a manner such that it is at the verge of its thermodynamic/mechanical stability.
Summary
In a modern society, metallic materials are crucially important (e.g. energy, safety, infrastructure, transportation, health, medicine, life sciences, IT). Contemporary examples with inherent challenges to be overcome are the design of ultrahigh specific strength materials. There is a critical need for successful developments in this area in particular for reduced energy consumption, reduction of pollutant emissions and passenger safety. Alternative approaches include improved thermal stability and creep resistance of high-temperature alloys for energy conversion, which are generally used in power plants and turbine engines, high temperature process technology, and fossil-fuel driven engines. The ageing European society makes biomedical materials for implant and stent design also crucially important. A drawback of nearly all current high strength metallic materials is that they lack ductility (i.e. are brittle and hard to form)- or on the opposite side, they may be highly ductile but lack strength. The key concept behind INTELHYB is to define new routes for creation of tailored metallic materials based on scale-bridging intelligent hybrid structures enabling property as well as function optimization. The novelty of this proposal as compared to conventional ideas is that they apply to monolithic amorphous materials or bulk microcrystalline. The basis will be founded on innovative strategies for the design, synthesis and characterization of intrinsic length-scale modulation and phase transformation under highly non-equilibrium conditions. This will include the incorporation of dispersed phases which are close to or beyond their thermodynamic and mechanical stability limit thus forming a hierarchically structured hybrid and ductile/tough alloys. Alternatively, the material itself will be designed in a manner such that it is at the verge of its thermodynamic/mechanical stability.
Max ERC Funding
2 499 920 €
Duration
Start date: 2014-02-01, End date: 2019-01-31
Project acronym isoineqintgeo
Project Isoperimetric Inequalities and Integral Geometry
Researcher (PI) Franz Ewald Schuster
Host Institution (HI) TECHNISCHE UNIVERSITAET WIEN
Call Details Starting Grant (StG), PE1, ERC-2012-StG_20111012
Summary "Among several trends in convex geometric analysis, two have undergone an explosive development in recent years: the theory of affine isoperimetric and analytic inequalities, and the enhanced understanding of fundamental concepts of the subject as a whole lent by the theory of valuations. The proposal concerns both of these trends.
The connections between convex body valued valuations and isoperimetric inequalities (like, the Petty projection inequality or affine Sobolev inequalities and their Lp extensions) have attracted the interest of first-rate research groups in the world. However, the underlying bigger picture behind these strong relations has yet to be discovered. A goal of the proposed research program is to systematically exploit the ""valuations point of view"" to reshape not only the way (affine) isoperimetric inequalities are thought of and applied but also the way these powerful inequalities are established.
Through the introduction of new algebraic structures on the space of translation invariant scalar valued valuations substantial inroads have been made towards a fuller understanding of the integral geometry of groups acting transitively on the sphere. An aim of the proposed program is to introduce a corresponding algebraic machinery in the theory of convex body valued valuations which would provide the means to attack long standing major open problems in the area of affine isoperimetric inequalities.
It is the PI's strong belief that over the next years it will become clear that many classical inequalities from affine geometry hold in a much more general setting than is currently understood. This will not only lead to the discovery of new inequalities but also should reveal the full strength of affine inequalities compared to their counterparts from Euclidean geometry. The proposed research goals of this ERC grant proposal would therefore represent a huge step towards advancing these developments that will alter two main subjects at the same time."
Summary
"Among several trends in convex geometric analysis, two have undergone an explosive development in recent years: the theory of affine isoperimetric and analytic inequalities, and the enhanced understanding of fundamental concepts of the subject as a whole lent by the theory of valuations. The proposal concerns both of these trends.
The connections between convex body valued valuations and isoperimetric inequalities (like, the Petty projection inequality or affine Sobolev inequalities and their Lp extensions) have attracted the interest of first-rate research groups in the world. However, the underlying bigger picture behind these strong relations has yet to be discovered. A goal of the proposed research program is to systematically exploit the ""valuations point of view"" to reshape not only the way (affine) isoperimetric inequalities are thought of and applied but also the way these powerful inequalities are established.
Through the introduction of new algebraic structures on the space of translation invariant scalar valued valuations substantial inroads have been made towards a fuller understanding of the integral geometry of groups acting transitively on the sphere. An aim of the proposed program is to introduce a corresponding algebraic machinery in the theory of convex body valued valuations which would provide the means to attack long standing major open problems in the area of affine isoperimetric inequalities.
It is the PI's strong belief that over the next years it will become clear that many classical inequalities from affine geometry hold in a much more general setting than is currently understood. This will not only lead to the discovery of new inequalities but also should reveal the full strength of affine inequalities compared to their counterparts from Euclidean geometry. The proposed research goals of this ERC grant proposal would therefore represent a huge step towards advancing these developments that will alter two main subjects at the same time."
Max ERC Funding
982 461 €
Duration
Start date: 2012-11-01, End date: 2017-10-31
Project acronym L3VISU
Project Life Long Learning for Visual Scene Understanding (L3ViSU)
Researcher (PI) Christoph Lampert
Host Institution (HI) INSTITUTE OF SCIENCE AND TECHNOLOGYAUSTRIA
Call Details Starting Grant (StG), PE6, ERC-2012-StG_20111012
Summary "My goal in the project is to develop and analyze algorithms that use continuous, open-ended machine learning from visual input data (images and videos) in order to interpret visual scenes on a level comparable to humans.
L3ViSU is based on the hypothesis that we can only significantly improve the state of the art in computer vision algorithms by giving them access to background and contextual knowledge about the visual world, and that the most feasible way to obtain such knowledge is by extracting it (semi-) automatically from incoming visual stimuli. Consequently, at the core of L3ViSU lies the idea of life-long visual learning.
Sufficient data for such an effort is readily available, e.g. through digital TV-channels and media-
sharing Internet platforms, but the question of how to use these resources for building better computer vision systems is wide open. In L3ViSU we will rely on modern machine learning concepts, representing task-independent prior knowledge as prior distributions and function regularizers. This functional form allows them to help solving specific tasks by guiding the solution to ""reasonable"" ones, and to suppress mistakes that violate ""common sense"". The result will not only be improved prediction quality, but also a reduction in the amount of manual supervision necessary, and the possibility to introduce more semantics into computer vision, which has recently been identified as one of the major tasks for the next decade.
L3ViSU is a project on the interface between computer vision and machine learning. Solving it requires expertise in both areas, as it is represented in my research group at IST Austria. The life-long learning concepts developed within L3ViSU, however, will have impact outside of both areas, let it be as basis of life-long learning system with a different focus, such as in bioinformatics, or as a foundation for projects of commercial value, such as more intelligent driver assistance or video surveillance systems."
Summary
"My goal in the project is to develop and analyze algorithms that use continuous, open-ended machine learning from visual input data (images and videos) in order to interpret visual scenes on a level comparable to humans.
L3ViSU is based on the hypothesis that we can only significantly improve the state of the art in computer vision algorithms by giving them access to background and contextual knowledge about the visual world, and that the most feasible way to obtain such knowledge is by extracting it (semi-) automatically from incoming visual stimuli. Consequently, at the core of L3ViSU lies the idea of life-long visual learning.
Sufficient data for such an effort is readily available, e.g. through digital TV-channels and media-
sharing Internet platforms, but the question of how to use these resources for building better computer vision systems is wide open. In L3ViSU we will rely on modern machine learning concepts, representing task-independent prior knowledge as prior distributions and function regularizers. This functional form allows them to help solving specific tasks by guiding the solution to ""reasonable"" ones, and to suppress mistakes that violate ""common sense"". The result will not only be improved prediction quality, but also a reduction in the amount of manual supervision necessary, and the possibility to introduce more semantics into computer vision, which has recently been identified as one of the major tasks for the next decade.
L3ViSU is a project on the interface between computer vision and machine learning. Solving it requires expertise in both areas, as it is represented in my research group at IST Austria. The life-long learning concepts developed within L3ViSU, however, will have impact outside of both areas, let it be as basis of life-long learning system with a different focus, such as in bioinformatics, or as a foundation for projects of commercial value, such as more intelligent driver assistance or video surveillance systems."
Max ERC Funding
1 464 712 €
Duration
Start date: 2013-01-01, End date: 2018-06-30
Project acronym LEBMEC
Project Laser-engineered Biomimetic Matrices with Embedded Cells
Researcher (PI) Aleksandr Ovsianikov
Host Institution (HI) TECHNISCHE UNIVERSITAET WIEN
Call Details Starting Grant (StG), PE8, ERC-2012-StG_20111012
Summary Traditional 2D cell culture systems used in biology do not accurately reproduce the 3D structure, function, or physiology of living tissue. Resulting behaviour and responses of cells are substantially different from those observed within natural extracellular matrices (ECM). The early designs of 3D cell-culture matrices focused on their bulk properties, while disregarding individual cell environment. However, recent findings indicate that the role of the ECM extends beyond a simple structural support to regulation of cell and tissue function. So far the mechanisms of this regulation are not fully understood, due to technical limitations of available research tools, diversity of tissues and complexity of cell-matrix interactions.
The main goal of this project is to develop a versatile and straightforward method, enabling systematic studies of cell-matrix interactions. 3D CAD matrices will be produced by femtosecond laser-induced polymerization of hydrogels with cells in them. Cell embedment results in a tissue-like intimate cell-matrix contact and appropriate cell densities right from the start.
A unique advantage of the LeBMEC is its capability to alter on demand a multitude of individual properties of produced 3D matrices, including: geometry, stiffness, and cell adhesion properties. It allows us systematically reconstruct and identify the key biomimetic properties of the ECM in vitro. The particular focus of this project is on the role of local mechanical properties of produced hydrogel constructs. It is known that, stem cells on soft 2D substrates differentiate into neurons, stiffer substrates induce bone cells, and intermediate ones result in myoblasts. With LeBMEC, a controlled distribution of site-specific stiffness within the same hydrogel matrix can be achieved in 3D. This way, by rational design of cell-culture matrices initially embedding only stem cells, for realisation of precisely defined 3D multi-tissue constructs, is possible for the first time.
Summary
Traditional 2D cell culture systems used in biology do not accurately reproduce the 3D structure, function, or physiology of living tissue. Resulting behaviour and responses of cells are substantially different from those observed within natural extracellular matrices (ECM). The early designs of 3D cell-culture matrices focused on their bulk properties, while disregarding individual cell environment. However, recent findings indicate that the role of the ECM extends beyond a simple structural support to regulation of cell and tissue function. So far the mechanisms of this regulation are not fully understood, due to technical limitations of available research tools, diversity of tissues and complexity of cell-matrix interactions.
The main goal of this project is to develop a versatile and straightforward method, enabling systematic studies of cell-matrix interactions. 3D CAD matrices will be produced by femtosecond laser-induced polymerization of hydrogels with cells in them. Cell embedment results in a tissue-like intimate cell-matrix contact and appropriate cell densities right from the start.
A unique advantage of the LeBMEC is its capability to alter on demand a multitude of individual properties of produced 3D matrices, including: geometry, stiffness, and cell adhesion properties. It allows us systematically reconstruct and identify the key biomimetic properties of the ECM in vitro. The particular focus of this project is on the role of local mechanical properties of produced hydrogel constructs. It is known that, stem cells on soft 2D substrates differentiate into neurons, stiffer substrates induce bone cells, and intermediate ones result in myoblasts. With LeBMEC, a controlled distribution of site-specific stiffness within the same hydrogel matrix can be achieved in 3D. This way, by rational design of cell-culture matrices initially embedding only stem cells, for realisation of precisely defined 3D multi-tissue constructs, is possible for the first time.
Max ERC Funding
1 440 594 €
Duration
Start date: 2013-03-01, End date: 2018-02-28
Project acronym MATERIALIZABLE
Project MATERIALIZABLE: Intelligent fabrication-oriented Computational Design and Modeling
Researcher (PI) Bernd BICKEL
Host Institution (HI) INSTITUTE OF SCIENCE AND TECHNOLOGYAUSTRIA
Call Details Starting Grant (StG), PE6, ERC-2016-STG
Summary While access to 3D-printing technology becomes ubiquitous and provides revolutionary possibilities for fabricating complex, functional, multi-material objects with stunning properties, its potential impact is currently significantly limited due to the lack of efficient and intuitive methods for content creation. Existing tools are usually restricted to expert users, have been developed based on the capabilities of traditional manufacturing processes, and do not sufficiently take fabrication constraints into account. Scientifically, we are facing the fundamental challenge that existing simulation techniques and design approaches for predicting the physical properties of materials and objects at the resolution of modern 3D printers are too slow and do not scale with increasing object complexity. The problem is extremely challenging because real world-materials exhibit extraordinary variety and complexity.
To address these challenges, I suggest a novel computational approach that facilitates intuitive design, accurate and fast simulation techniques, and a functional representation of 3D content. I propose a multi-scale representation of functional goals and hybrid models that describes the physical behavior at a coarse scale and the relationship to the underlying material composition at the resolution of the 3D printer. My approach is to combine data-driven and physically-based modeling, providing both the required speed and accuracy through smart precomputations and tailored simulation techniques that operate on the data. A key aspect of this modeling and simulation approach is to identify domains that are sufficiently low-dimensional to be correctly sampled. Subsequently, I propose the fundamental re-thinking of the workflow, leading to solutions that allow synthesizing model instances optimized on-the-fly for a specific output device. The principal applicability will be evaluated for functional goals, such as appearance, deformation, and sensing capabilities.
Summary
While access to 3D-printing technology becomes ubiquitous and provides revolutionary possibilities for fabricating complex, functional, multi-material objects with stunning properties, its potential impact is currently significantly limited due to the lack of efficient and intuitive methods for content creation. Existing tools are usually restricted to expert users, have been developed based on the capabilities of traditional manufacturing processes, and do not sufficiently take fabrication constraints into account. Scientifically, we are facing the fundamental challenge that existing simulation techniques and design approaches for predicting the physical properties of materials and objects at the resolution of modern 3D printers are too slow and do not scale with increasing object complexity. The problem is extremely challenging because real world-materials exhibit extraordinary variety and complexity.
To address these challenges, I suggest a novel computational approach that facilitates intuitive design, accurate and fast simulation techniques, and a functional representation of 3D content. I propose a multi-scale representation of functional goals and hybrid models that describes the physical behavior at a coarse scale and the relationship to the underlying material composition at the resolution of the 3D printer. My approach is to combine data-driven and physically-based modeling, providing both the required speed and accuracy through smart precomputations and tailored simulation techniques that operate on the data. A key aspect of this modeling and simulation approach is to identify domains that are sufficiently low-dimensional to be correctly sampled. Subsequently, I propose the fundamental re-thinking of the workflow, leading to solutions that allow synthesizing model instances optimized on-the-fly for a specific output device. The principal applicability will be evaluated for functional goals, such as appearance, deformation, and sensing capabilities.
Max ERC Funding
1 497 730 €
Duration
Start date: 2017-02-01, End date: 2022-01-31
Project acronym MICROBONE
Project Multiscale poro-micromechanics of bone materials, with links to biology and medicine
Researcher (PI) Christian Hellmich
Host Institution (HI) TECHNISCHE UNIVERSITAET WIEN
Call Details Starting Grant (StG), PE8, ERC-2010-StG_20091028
Summary "Modern computational engineering science allows for reliable design of the most breathtaking high-rise buildings, but it has hardly entered the fracture risk assessment of biological structures like bones. Is it only an engineering scientist's dream to decipher mathematically the origins and the evolution of the astonishingly varying mechanical properties of hierarchical biological materials? Not quite: By means of micromechanical theories, we could recently show in a quantitative fashion how ""universal"" elementary building blocks (being independent of tissue type, species, age, or anatomical location) govern the elastic properties of bone materials across the entire vertebrate kingdom, from the super-molecular to the centimetre scale. Now is the time to drive forward these developments beyond elasticity, striving for scientific breakthroughs in multiscale bone strength. Through novel, experimentally validated micromechanical theories, we will aim at predicting tissue-specific inelastic
properties of bone materials, from the ""universal"" mechanical properties of the nanoscaled elementary components (hydroxyapatite, collagen, water), their tissue-specific dosages, and the ""universal"" organizational patterns they build up. Moreover, we will extend cell population models of contemporary systems biology, towards biomineralization kinetics,in
order to quantify evolutions of bone mass and composition in living organisms. When using these evolutions as input for the aforementioned micromechanics models, the latter will predict the mechanical implications of biological processes. This will open unprecedented avenues in bone disease therapies, including patient-specific bone fracture risk assessment relying on micromechanics-based Finite Element analyses."
Summary
"Modern computational engineering science allows for reliable design of the most breathtaking high-rise buildings, but it has hardly entered the fracture risk assessment of biological structures like bones. Is it only an engineering scientist's dream to decipher mathematically the origins and the evolution of the astonishingly varying mechanical properties of hierarchical biological materials? Not quite: By means of micromechanical theories, we could recently show in a quantitative fashion how ""universal"" elementary building blocks (being independent of tissue type, species, age, or anatomical location) govern the elastic properties of bone materials across the entire vertebrate kingdom, from the super-molecular to the centimetre scale. Now is the time to drive forward these developments beyond elasticity, striving for scientific breakthroughs in multiscale bone strength. Through novel, experimentally validated micromechanical theories, we will aim at predicting tissue-specific inelastic
properties of bone materials, from the ""universal"" mechanical properties of the nanoscaled elementary components (hydroxyapatite, collagen, water), their tissue-specific dosages, and the ""universal"" organizational patterns they build up. Moreover, we will extend cell population models of contemporary systems biology, towards biomineralization kinetics,in
order to quantify evolutions of bone mass and composition in living organisms. When using these evolutions as input for the aforementioned micromechanics models, the latter will predict the mechanical implications of biological processes. This will open unprecedented avenues in bone disease therapies, including patient-specific bone fracture risk assessment relying on micromechanics-based Finite Element analyses."
Max ERC Funding
1 493 399 €
Duration
Start date: 2010-11-01, End date: 2015-10-31
