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
Country Germany
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 ALEXANDRIA
Project "Foundations for Temporal Retrieval, Exploration and Analytics in Web Archives"
Researcher (PI) Wolfgang Nejdl
Host Institution (HI) GOTTFRIED WILHELM LEIBNIZ UNIVERSITAET HANNOVER
Country Germany
Call Details Advanced Grant (AdG), PE6, ERC-2013-ADG
Summary "Significant parts of our cultural heritage are produced on the Web, yet only insufficient opportunities exist for accessing and exploring the past of the Web. The ALEXANDRIA project aims to develop models, tools and techniques necessary to archive and index relevant parts of the Web, and to retrieve and explore this information in a meaningful way. While the easy accessibility to the current Web is a good baseline, optimal access to Web archives requires new models and algorithms for retrieval, exploration, and analytics which go far beyond what is needed to access the current state of the Web. This includes taking into account the unique temporal dimension of Web archives, structured semantic information already available on the Web, as well as social media and network information.
Within ALEXANDRIA, we will significantly advance semantic and time-based indexing for Web archives using human-compiled knowledge available on the Web, to efficiently index, retrieve and explore information about entities and events from the past. In doing so, we will focus on the concurrent evolution of this knowledge and the Web content to be indexed, and take into account diversity and incompleteness of this knowledge. We will further investigate mixed crowd- and machine-based Web analytics to support long- running and collaborative retrieval and analysis processes on Web archives. Usage of implicit human feedback will be essential to provide better indexing through insights during the analysis process and to better focus harvesting of content.
The ALEXANDRIA Testbed will provide an important context for research, exploration and evaluation of the concepts, methods and algorithms developed in this project, and will provide both relevant collections and algorithms that enable further research on and practical application of our research results to existing archives like the Internet Archive, the Internet Memory Foundation and Web archives maintained by European national libraries."
Summary
"Significant parts of our cultural heritage are produced on the Web, yet only insufficient opportunities exist for accessing and exploring the past of the Web. The ALEXANDRIA project aims to develop models, tools and techniques necessary to archive and index relevant parts of the Web, and to retrieve and explore this information in a meaningful way. While the easy accessibility to the current Web is a good baseline, optimal access to Web archives requires new models and algorithms for retrieval, exploration, and analytics which go far beyond what is needed to access the current state of the Web. This includes taking into account the unique temporal dimension of Web archives, structured semantic information already available on the Web, as well as social media and network information.
Within ALEXANDRIA, we will significantly advance semantic and time-based indexing for Web archives using human-compiled knowledge available on the Web, to efficiently index, retrieve and explore information about entities and events from the past. In doing so, we will focus on the concurrent evolution of this knowledge and the Web content to be indexed, and take into account diversity and incompleteness of this knowledge. We will further investigate mixed crowd- and machine-based Web analytics to support long- running and collaborative retrieval and analysis processes on Web archives. Usage of implicit human feedback will be essential to provide better indexing through insights during the analysis process and to better focus harvesting of content.
The ALEXANDRIA Testbed will provide an important context for research, exploration and evaluation of the concepts, methods and algorithms developed in this project, and will provide both relevant collections and algorithms that enable further research on and practical application of our research results to existing archives like the Internet Archive, the Internet Memory Foundation and Web archives maintained by European national libraries."
Max ERC Funding
2 493 600 €
Duration
Start date: 2014-03-01, End date: 2019-02-28
Project acronym BATNMR
Project Development and Application of New NMR Methods for Studying Interphases and Interfaces in Batteries
Researcher (PI) Clare GREY
Host Institution (HI) THE CHANCELLOR MASTERS AND SCHOLARSOF THE UNIVERSITY OF CAMBRIDGE
Country United Kingdom
Call Details Advanced Grant (AdG), PE4, ERC-2018-ADG
Summary The development of longer lasting, higher energy density and cheaper rechargeable batteries represents one of the major technological challenges of our society, batteries representing the limiting components in the shift from gasoline-powered to electric vehicles. They are also required to enable the use of more (typically intermittent) renewable energy, to balance demand with generation. This proposal seeks to develop and apply new NMR metrologies to determine the structure and dynamics of the multiple electrode-electrolyte interfaces and interphases that are present in these batteries, and how they evolve during battery cycling. New dynamic nuclear polarization (DNP) techniques will be exploited to extract structural information about the interface between the battery electrode and the passivating layers that grow on the electrode materials (the solid electrolyte interphase, SEI) and that are inherent to the stability of the batteries. The role of the SEI (and ceramic interfaces) in controlling lithium metal dendrite growth will be determined in liquid based and all solid state batteries.
New DNP approaches will be developed that are compatible with the heterogeneous and reactive species that are present in conventional, all-solid state, Li-air and redox flow batteries. Method development will run in parallel with the use of DNP approaches to determine the structures of the various battery interfaces and interphases, testing the stability of conventional biradicals in these harsh oxidizing and reducing conditions, modifying the experimental approaches where appropriate. The final result will be a significantly improved understanding of the structures of these phases and how they evolve on cycling, coupled with strategies for designing improved SEI structures. The nature of the interface between a lithium metal dendrite and ceramic composite will be determined, providing much needed insight into how these (unwanted) dendrites grow in all solid state batteries. DNP approaches coupled with electron spin resonance will be use, where possible in situ, to determine the reaction mechanisms of organic molecules such as quinones in organic-based redox flow batteries in order to help prevent degradation of the electrochemically active species.
This proposal involves NMR method development specifically designed to explore a variety of battery chemistries. Thus, this proposal is interdisciplinary, containing both a strong emphasis on materials characterization, electrochemistry and electronic structures of materials, interfaces and nanoparticles, and on analytical and physical chemistry. Some of the methodology will be applicable to other materials and systems including (for example) other electrochemical technologies such as fuel cells and solar fuels and the study of catalysts (to probe surface structure).
Summary
The development of longer lasting, higher energy density and cheaper rechargeable batteries represents one of the major technological challenges of our society, batteries representing the limiting components in the shift from gasoline-powered to electric vehicles. They are also required to enable the use of more (typically intermittent) renewable energy, to balance demand with generation. This proposal seeks to develop and apply new NMR metrologies to determine the structure and dynamics of the multiple electrode-electrolyte interfaces and interphases that are present in these batteries, and how they evolve during battery cycling. New dynamic nuclear polarization (DNP) techniques will be exploited to extract structural information about the interface between the battery electrode and the passivating layers that grow on the electrode materials (the solid electrolyte interphase, SEI) and that are inherent to the stability of the batteries. The role of the SEI (and ceramic interfaces) in controlling lithium metal dendrite growth will be determined in liquid based and all solid state batteries.
New DNP approaches will be developed that are compatible with the heterogeneous and reactive species that are present in conventional, all-solid state, Li-air and redox flow batteries. Method development will run in parallel with the use of DNP approaches to determine the structures of the various battery interfaces and interphases, testing the stability of conventional biradicals in these harsh oxidizing and reducing conditions, modifying the experimental approaches where appropriate. The final result will be a significantly improved understanding of the structures of these phases and how they evolve on cycling, coupled with strategies for designing improved SEI structures. The nature of the interface between a lithium metal dendrite and ceramic composite will be determined, providing much needed insight into how these (unwanted) dendrites grow in all solid state batteries. DNP approaches coupled with electron spin resonance will be use, where possible in situ, to determine the reaction mechanisms of organic molecules such as quinones in organic-based redox flow batteries in order to help prevent degradation of the electrochemically active species.
This proposal involves NMR method development specifically designed to explore a variety of battery chemistries. Thus, this proposal is interdisciplinary, containing both a strong emphasis on materials characterization, electrochemistry and electronic structures of materials, interfaces and nanoparticles, and on analytical and physical chemistry. Some of the methodology will be applicable to other materials and systems including (for example) other electrochemical technologies such as fuel cells and solar fuels and the study of catalysts (to probe surface structure).
Max ERC Funding
3 498 219 €
Duration
Start date: 2019-10-01, End date: 2024-09-30
Project acronym BAYES-KNOWLEDGE
Project Effective Bayesian Modelling with Knowledge before Data
Researcher (PI) Norman Fenton
Host Institution (HI) QUEEN MARY UNIVERSITY OF LONDON
Country United Kingdom
Call Details Advanced Grant (AdG), PE6, ERC-2013-ADG
Summary This project aims to improve evidence-based decision-making. What makes it radical is that it plans to do this in situations (common for critical risk assessment problems) where there is little or even no data, and hence where traditional statistics cannot be used. To address this problem Bayesian analysis, which enables domain experts to supplement observed data with subjective probabilities, is normally used. As real-world problems typically involve multiple uncertain variables, Bayesian analysis is extended using a technique called Bayesian networks (BNs). But, despite many great benefits, BNs have been under-exploited, especially in areas where they offer the greatest potential for improvements (law, medicine and systems engineering). This is mainly because of widespread resistance to relying on subjective knowledge. To address this problem much current research assumes sufficient data are available to make the expert’s input minimal or even redundant; with such data it may be possible to ‘learn’ the underlying BN model. But this approach offers nothing when there is limited or no data. Even when ‘big’ data are available the resulting models may be superficially objective but fundamentally flawed as they fail to capture the underlying causal structure that only expert knowledge can provide.
Our solution is to develop a method to systemize the way expert driven causal BN models can be built and used effectively either in the absence of data or as a means of determining what future data is really required. The method involves a new way of framing problems and extensions to BN theory, notation and tools. Working with relevant domain experts, along with cognitive psychologists, our methods will be developed and tested experimentally on real-world critical decision-problems in medicine, law, forensics, and transport. As the work complements current data-driven approaches, it will lead to improved BN modelling both when there is extensive data as well as none.
Summary
This project aims to improve evidence-based decision-making. What makes it radical is that it plans to do this in situations (common for critical risk assessment problems) where there is little or even no data, and hence where traditional statistics cannot be used. To address this problem Bayesian analysis, which enables domain experts to supplement observed data with subjective probabilities, is normally used. As real-world problems typically involve multiple uncertain variables, Bayesian analysis is extended using a technique called Bayesian networks (BNs). But, despite many great benefits, BNs have been under-exploited, especially in areas where they offer the greatest potential for improvements (law, medicine and systems engineering). This is mainly because of widespread resistance to relying on subjective knowledge. To address this problem much current research assumes sufficient data are available to make the expert’s input minimal or even redundant; with such data it may be possible to ‘learn’ the underlying BN model. But this approach offers nothing when there is limited or no data. Even when ‘big’ data are available the resulting models may be superficially objective but fundamentally flawed as they fail to capture the underlying causal structure that only expert knowledge can provide.
Our solution is to develop a method to systemize the way expert driven causal BN models can be built and used effectively either in the absence of data or as a means of determining what future data is really required. The method involves a new way of framing problems and extensions to BN theory, notation and tools. Working with relevant domain experts, along with cognitive psychologists, our methods will be developed and tested experimentally on real-world critical decision-problems in medicine, law, forensics, and transport. As the work complements current data-driven approaches, it will lead to improved BN modelling both when there is extensive data as well as none.
Max ERC Funding
1 572 562 €
Duration
Start date: 2014-04-01, End date: 2018-03-31
Project acronym BIOVIB
Project Electric Interactions and Structural Dynamics of Hydrated Biomolecules Mapped by Ultrafast Vibrational Probes
Researcher (PI) Thomas ELSAESSER
Host Institution (HI) FORSCHUNGSVERBUND BERLIN EV
Country Germany
Call Details Advanced Grant (AdG), PE4, ERC-2018-ADG
Summary Biomolecules exist in an aqueous environment of dipolar water molecules and solvated ions. Their structure and biological function are strongly influenced by electric interactions with the fluctuating water shell and ion atmosphere. Understanding such interactions at the molecular level is a major scientific challenge; presently, their strengths, spatial range and interplay with other non-covalent interactions are barely known. Going far beyond existing methods, this project introduces the new paradigm of a direct time-resolved mapping of molecular electric forces on sub-nanometer length scales and at the genuine terahertz (THz) fluctuation frequencies. Vibrational excitations of biomolecules at the interface to the water shell act as sensitive noninvasive probes of charge dynamics and local electric fields. The new method of time resolved vibrational Stark shift spectroscopy with THz external fields calibrates vibrational frequencies as a function of absolute field strength and separates instantaneous from retarded environment fields. Based on this knowledge, multidimensional vibrational spectroscopy gives quantitative insight in the biomolecular response to electric fields, discerning contributions from water and ions in a site-specific way. The experiments and theoretical analysis focus on single- and double-stranded RNA and DNA structures at different hydration levels and with ion atmospheres of controlled composition, structurally characterized by x-ray scattering. As a ground-breaking open problem, the role of magnesium and other ions in RNA structure definition and folding will be addressed by following RNA folding processes with vibrational probes up to milliseconds. The impact of site-bound versus outer ions will be dynamically separated to unravel mechanisms stabilizing secondary and tertiary RNA structures. Beyond RNA research, the present approach holds strong potential for fundamental insight in transmembrane ion channels and channel rhodopsins.
Summary
Biomolecules exist in an aqueous environment of dipolar water molecules and solvated ions. Their structure and biological function are strongly influenced by electric interactions with the fluctuating water shell and ion atmosphere. Understanding such interactions at the molecular level is a major scientific challenge; presently, their strengths, spatial range and interplay with other non-covalent interactions are barely known. Going far beyond existing methods, this project introduces the new paradigm of a direct time-resolved mapping of molecular electric forces on sub-nanometer length scales and at the genuine terahertz (THz) fluctuation frequencies. Vibrational excitations of biomolecules at the interface to the water shell act as sensitive noninvasive probes of charge dynamics and local electric fields. The new method of time resolved vibrational Stark shift spectroscopy with THz external fields calibrates vibrational frequencies as a function of absolute field strength and separates instantaneous from retarded environment fields. Based on this knowledge, multidimensional vibrational spectroscopy gives quantitative insight in the biomolecular response to electric fields, discerning contributions from water and ions in a site-specific way. The experiments and theoretical analysis focus on single- and double-stranded RNA and DNA structures at different hydration levels and with ion atmospheres of controlled composition, structurally characterized by x-ray scattering. As a ground-breaking open problem, the role of magnesium and other ions in RNA structure definition and folding will be addressed by following RNA folding processes with vibrational probes up to milliseconds. The impact of site-bound versus outer ions will be dynamically separated to unravel mechanisms stabilizing secondary and tertiary RNA structures. Beyond RNA research, the present approach holds strong potential for fundamental insight in transmembrane ion channels and channel rhodopsins.
Max ERC Funding
2 330 493 €
Duration
Start date: 2019-05-01, End date: 2024-04-30
Project acronym CASCAT
Project Catalytic cascade reactions. From fundamentals of nanozymes to applications based on gas-diffusion electrodes
Researcher (PI) Wolfgang Werner SCHUHMANN
Host Institution (HI) RUHR-UNIVERSITAET BOCHUM
Country Germany
Call Details Advanced Grant (AdG), PE4, ERC-2018-ADG
Summary Nanoparticles with etched substrate channels are proposed as a simplified enzyme mimic, nanozymes, for electrocatalysis providing concave catalytically active sites together with the local modulation of electrolyte composition. This concept will be extended to bimetallic core-shell structures with etched channels to provide locally confined catalyst surfaces with varying selectivity. The first catalytic reaction at the channel entrance selectively generates a product, which is further converted in a follow-up reaction catalysed at the core material at the bottom of the channel. The endeavour to locally assemble catalysts with different properties in nano-confined reaction volumes to actualise cascade reaction pathways will be extended to layered nanoparticle structures. Together with an anisotropic provision of a gaseous reactant through a hydrophobic/hydrophilic phase boundary of specifically designed gas diffusion electrodes multi-step catalytic cascade reactions become feasible. The development and extensive evaluation of multi-catalyst gas-diffusion electrodes using operando electrochemistry/spectroscopy and nano-electrochemical tools as well as multi flow-through electrolysers will provide the fundamental knowledge concerning the relative location of different catalyst particles, which synergistically perform chemical cascade reaction with high selectivity and at high current densities. These gas-diffusion electrodes will be integrated in novel electrolyser concepts targeting CO2 recycling at high current density in alkaline solution under suppression of H2 competition with previously unprecedented selectivity for the formation of higher hydrocarbons envisioning contributions to a closed carbon cycle economy and a substantial decrease of CO2 emission. Additionally, a novel tree-type rotating electrolyser design is proposed for the removal of hazardous gaseous pollutants from air e.g. at street crossings in cities as exemplified by NOx reduction to N2 or NH3.
Summary
Nanoparticles with etched substrate channels are proposed as a simplified enzyme mimic, nanozymes, for electrocatalysis providing concave catalytically active sites together with the local modulation of electrolyte composition. This concept will be extended to bimetallic core-shell structures with etched channels to provide locally confined catalyst surfaces with varying selectivity. The first catalytic reaction at the channel entrance selectively generates a product, which is further converted in a follow-up reaction catalysed at the core material at the bottom of the channel. The endeavour to locally assemble catalysts with different properties in nano-confined reaction volumes to actualise cascade reaction pathways will be extended to layered nanoparticle structures. Together with an anisotropic provision of a gaseous reactant through a hydrophobic/hydrophilic phase boundary of specifically designed gas diffusion electrodes multi-step catalytic cascade reactions become feasible. The development and extensive evaluation of multi-catalyst gas-diffusion electrodes using operando electrochemistry/spectroscopy and nano-electrochemical tools as well as multi flow-through electrolysers will provide the fundamental knowledge concerning the relative location of different catalyst particles, which synergistically perform chemical cascade reaction with high selectivity and at high current densities. These gas-diffusion electrodes will be integrated in novel electrolyser concepts targeting CO2 recycling at high current density in alkaline solution under suppression of H2 competition with previously unprecedented selectivity for the formation of higher hydrocarbons envisioning contributions to a closed carbon cycle economy and a substantial decrease of CO2 emission. Additionally, a novel tree-type rotating electrolyser design is proposed for the removal of hazardous gaseous pollutants from air e.g. at street crossings in cities as exemplified by NOx reduction to N2 or NH3.
Max ERC Funding
2 499 462 €
Duration
Start date: 2019-09-01, End date: 2024-08-31
Project acronym ChemNav
Project Magnetic sensing by molecules, birds, and devices
Researcher (PI) Peter John Hore
Host Institution (HI) THE CHANCELLOR, MASTERS AND SCHOLARS OF THE UNIVERSITY OF OXFORD
Country United Kingdom
Call Details Advanced Grant (AdG), PE4, ERC-2013-ADG
Summary The sensory mechanisms that allow birds to perceive the direction of the Earth’s magnetic field for the purpose of navigation are only now beginning to be understood. One of the two leading hypotheses is founded on magnetically sensitive photochemical reactions in the retina. It is thought that transient photo-induced radical pairs in cryptochrome, a blue-light photoreceptor protein, act as the primary magnetic sensor. Experimental and theoretical support for this mechanism has been accumulating over the last few years, qualifying chemical magnetoreception for a place in the emerging field of Quantum Biology.
In this proposal, we aim to determine the detailed principles of efficient chemical sensing of weak magnetic fields, to elucidate the biophysics of animal compass magnetoreception, and to explore the possibilities of magnetic sensing technologies inspired by the coherent dynamics of entangled electron spins in cryptochrome-based radical pairs.
We will:
(a) Establish the fundamental structural, kinetic, dynamic and magnetic properties that allow efficient chemical sensing of Earth-strength magnetic fields in cryptochromes.
(b) Devise new, sensitive forms of optical spectroscopy for this purpose.
(c) Design, construct and iteratively refine non-natural proteins (maquettes) as versatile model systems for testing and optimising molecular magnetoreceptors.
(d) Characterise the spin dynamics and magnetic sensitivity of maquette magnetoreceptors using specialised magnetic resonance and optical spectroscopic techniques.
(e) Develop efficient and accurate methods for simulating the coherent spin dynamics of realistic radical pairs in order to interpret experimental data, guide the implementation of new experiments, test concepts of magnetoreceptor function, and guide the design of efficient sensors.
(f) Explore the feasibility of electronically addressable, organic semiconductor sensors inspired by radical pair magnetoreception.
Summary
The sensory mechanisms that allow birds to perceive the direction of the Earth’s magnetic field for the purpose of navigation are only now beginning to be understood. One of the two leading hypotheses is founded on magnetically sensitive photochemical reactions in the retina. It is thought that transient photo-induced radical pairs in cryptochrome, a blue-light photoreceptor protein, act as the primary magnetic sensor. Experimental and theoretical support for this mechanism has been accumulating over the last few years, qualifying chemical magnetoreception for a place in the emerging field of Quantum Biology.
In this proposal, we aim to determine the detailed principles of efficient chemical sensing of weak magnetic fields, to elucidate the biophysics of animal compass magnetoreception, and to explore the possibilities of magnetic sensing technologies inspired by the coherent dynamics of entangled electron spins in cryptochrome-based radical pairs.
We will:
(a) Establish the fundamental structural, kinetic, dynamic and magnetic properties that allow efficient chemical sensing of Earth-strength magnetic fields in cryptochromes.
(b) Devise new, sensitive forms of optical spectroscopy for this purpose.
(c) Design, construct and iteratively refine non-natural proteins (maquettes) as versatile model systems for testing and optimising molecular magnetoreceptors.
(d) Characterise the spin dynamics and magnetic sensitivity of maquette magnetoreceptors using specialised magnetic resonance and optical spectroscopic techniques.
(e) Develop efficient and accurate methods for simulating the coherent spin dynamics of realistic radical pairs in order to interpret experimental data, guide the implementation of new experiments, test concepts of magnetoreceptor function, and guide the design of efficient sensors.
(f) Explore the feasibility of electronically addressable, organic semiconductor sensors inspired by radical pair magnetoreception.
Max ERC Funding
2 997 062 €
Duration
Start date: 2013-12-01, End date: 2018-11-30
Project acronym CONTROL
Project Laser control over crystal nucleation
Researcher (PI) Klaas Wijnne
Host Institution (HI) UNIVERSITY OF GLASGOW
Country United Kingdom
Call Details Advanced Grant (AdG), PE4, ERC-2018-ADG
Summary The CONTROL programme I propose here is a five-year programme of frontier research to develop a novel platform for the manipulation of phase transitions, crystal nucleation, and polymorph control based on a novel optical-tweezing technique and plasmonics. About 20 years ago, it was shown that lasers can nucleate crystals in super-saturated solution and might even be able to select the polymorph that crystallises. However, no theoretical model was found explaining the results and little progress was made.
In a recent publication (Nat. Chem. 10, 506 (2018)), we showed that laser-induced nucleation can be understood in terms of the harnessing of concentration fluctuations near a liquid–liquid critical point using optical tweezing. This breakthrough opens the way to a research programme with risky, ambitious, and ground-breaking long-term aims: full control over crystal nucleation including chirality and polymorphism.
New optical and microscopic techniques will be developed to allow laser manipulation on a massively parallel scale and chiral nucleation using twisted light. Systematically characterising and manipulating the phase behaviour of mixtures, will allow the use of the optical-tweezing effect to effectively control the crystallisation of small molecules, peptides, proteins, and polymers. Exploiting nanostructures will allow parallelisation on a vast scale and fine control over chirality and polymorph selection through plasmonic tweezing. Even partial success in the five years of the programme will lead to fundamental new insights and technological breakthroughs. These breakthroughs will be exploited for future commercial applications towards the end of the project.
Summary
The CONTROL programme I propose here is a five-year programme of frontier research to develop a novel platform for the manipulation of phase transitions, crystal nucleation, and polymorph control based on a novel optical-tweezing technique and plasmonics. About 20 years ago, it was shown that lasers can nucleate crystals in super-saturated solution and might even be able to select the polymorph that crystallises. However, no theoretical model was found explaining the results and little progress was made.
In a recent publication (Nat. Chem. 10, 506 (2018)), we showed that laser-induced nucleation can be understood in terms of the harnessing of concentration fluctuations near a liquid–liquid critical point using optical tweezing. This breakthrough opens the way to a research programme with risky, ambitious, and ground-breaking long-term aims: full control over crystal nucleation including chirality and polymorphism.
New optical and microscopic techniques will be developed to allow laser manipulation on a massively parallel scale and chiral nucleation using twisted light. Systematically characterising and manipulating the phase behaviour of mixtures, will allow the use of the optical-tweezing effect to effectively control the crystallisation of small molecules, peptides, proteins, and polymers. Exploiting nanostructures will allow parallelisation on a vast scale and fine control over chirality and polymorph selection through plasmonic tweezing. Even partial success in the five years of the programme will lead to fundamental new insights and technological breakthroughs. These breakthroughs will be exploited for future commercial applications towards the end of the project.
Max ERC Funding
2 488 162 €
Duration
Start date: 2019-09-01, End date: 2024-08-31
Project acronym DISEASES
Project The Diseases of Modern Life: Nineteenth-Century Perspectives
Researcher (PI) Sally Shuttleworth
Host Institution (HI) THE CHANCELLOR, MASTERS AND SCHOLARS OF THE UNIVERSITY OF OXFORD
Country United Kingdom
Call Details Advanced Grant (AdG), SH5, ERC-2013-ADG
Summary "In our current ‘Information Age’ we suffer as never before, it is claimed, from the stresses of an overload of information, and the speed of global networks. The Victorians diagnosed similar problems in the nineteenth century. The medic James Crichton Browne spoke in 1860 of the ‘velocity of thought and action’ now required, and of the stresses imposed on the brain forced to process in a month more information ‘than was required of our grandfathers in the course of a lifetime’. This project will explore the phenomena of stress and overload, and other disorders associated in the nineteenth century with the problems of modernity, as expressed in the literature, science and medicine of the period, tracking the circulation of ideas across these diverse areas. Taking its framework from Diseases of Modern Life (1876) by the medical reformer, Benjamin Ward Richardson, it will explore ‘diseases from worry and mental strain’, as experienced in the professions, ‘lifestyle’ diseases such as the abuse of alcohol and narcotics, and also diseases from environmental pollution. This study will return to the holistic, integrative vision of the Victorians, as expressed in the science and in the great novels of the period, exploring the connections drawn between physiological, psychological and social health, or disease. Particular areas of focus will be: diseases of finance and speculation; diseases associated with particular professions; alcohol and drug addiction amidst the middle classes; travel for health; education and over-pressure in the classroom; the development of phobias and nervous disorders; and the imaginative construction of utopias and dystopias, in relation to health and disease. In its depth and range the project will take scholarship into radically new ground, breaking through the compartmentalization of psychiatric, environmental or literary history, and offering new ways of contextualising the problems of modernity facing us in the twenty-first century."
Summary
"In our current ‘Information Age’ we suffer as never before, it is claimed, from the stresses of an overload of information, and the speed of global networks. The Victorians diagnosed similar problems in the nineteenth century. The medic James Crichton Browne spoke in 1860 of the ‘velocity of thought and action’ now required, and of the stresses imposed on the brain forced to process in a month more information ‘than was required of our grandfathers in the course of a lifetime’. This project will explore the phenomena of stress and overload, and other disorders associated in the nineteenth century with the problems of modernity, as expressed in the literature, science and medicine of the period, tracking the circulation of ideas across these diverse areas. Taking its framework from Diseases of Modern Life (1876) by the medical reformer, Benjamin Ward Richardson, it will explore ‘diseases from worry and mental strain’, as experienced in the professions, ‘lifestyle’ diseases such as the abuse of alcohol and narcotics, and also diseases from environmental pollution. This study will return to the holistic, integrative vision of the Victorians, as expressed in the science and in the great novels of the period, exploring the connections drawn between physiological, psychological and social health, or disease. Particular areas of focus will be: diseases of finance and speculation; diseases associated with particular professions; alcohol and drug addiction amidst the middle classes; travel for health; education and over-pressure in the classroom; the development of phobias and nervous disorders; and the imaginative construction of utopias and dystopias, in relation to health and disease. In its depth and range the project will take scholarship into radically new ground, breaking through the compartmentalization of psychiatric, environmental or literary history, and offering new ways of contextualising the problems of modernity facing us in the twenty-first century."
Max ERC Funding
2 362 659 €
Duration
Start date: 2014-02-01, End date: 2019-01-31
Project acronym EAR
Project Audio-based Mobile Health Diagnostics
Researcher (PI) Cecilia MASCOLO
Host Institution (HI) THE CHANCELLOR MASTERS AND SCHOLARSOF THE UNIVERSITY OF CAMBRIDGE
Country United Kingdom
Call Details Advanced Grant (AdG), PE6, ERC-2018-ADG
Summary Mobile health is becoming the holy grail for affordable medical diagnostics. It has the potential of associating human behaviour with medical symptoms automatically and at early disease stage; it also offers cheap deployment, reaching populations generally not able to afford diagnosis and delivering a level of monitoring so fine which will likely improve diagnostic theory itself. The advancements of technology offer new ranges of sensing and computation capability with the potential of further improving the reach of mobile health. Audio sensing through microphones of mobile devices has recently being recognized as a powerful and yet underutilized source of medical information: sounds from the human body (e.g., sighs, breathing sounds and voice) are indicators of disease or disease onsets. The current pilots, while generally medically grounded, are potentially ad-hoc from the perspective of key areas of computer science; specifically, in their approaches to computational models and how the system resource demands are optimized to fit within the limits of the mobile devices, as well as in terms of robustness needed for tracking people in their daily lives. Audio sensing also comes with challenges which threaten its use in clinical context: its power hungry nature and the fact that audio data is very sensitive and the collection of this sort of data for analytics violates obvious ethical rules. This work proposes models to link sounds to disease diagnosis and to deal with the inherent issues raised by in-the-wild sensing: noise and privacy concerns. We exploit these audio models in wearable systems maximizing the use of local hardware resources with power optimization and accuracy in both near real time and sparse audio sampling. Privacy will arise as a by-product taking away the need of cloud analytics. Moreover, the framework will embed the ability to quantify the diagnostic uncertainty and consider patient context as confounding factors via additional sensors.
Summary
Mobile health is becoming the holy grail for affordable medical diagnostics. It has the potential of associating human behaviour with medical symptoms automatically and at early disease stage; it also offers cheap deployment, reaching populations generally not able to afford diagnosis and delivering a level of monitoring so fine which will likely improve diagnostic theory itself. The advancements of technology offer new ranges of sensing and computation capability with the potential of further improving the reach of mobile health. Audio sensing through microphones of mobile devices has recently being recognized as a powerful and yet underutilized source of medical information: sounds from the human body (e.g., sighs, breathing sounds and voice) are indicators of disease or disease onsets. The current pilots, while generally medically grounded, are potentially ad-hoc from the perspective of key areas of computer science; specifically, in their approaches to computational models and how the system resource demands are optimized to fit within the limits of the mobile devices, as well as in terms of robustness needed for tracking people in their daily lives. Audio sensing also comes with challenges which threaten its use in clinical context: its power hungry nature and the fact that audio data is very sensitive and the collection of this sort of data for analytics violates obvious ethical rules. This work proposes models to link sounds to disease diagnosis and to deal with the inherent issues raised by in-the-wild sensing: noise and privacy concerns. We exploit these audio models in wearable systems maximizing the use of local hardware resources with power optimization and accuracy in both near real time and sparse audio sampling. Privacy will arise as a by-product taking away the need of cloud analytics. Moreover, the framework will embed the ability to quantify the diagnostic uncertainty and consider patient context as confounding factors via additional sensors.
Max ERC Funding
2 493 724 €
Duration
Start date: 2019-10-01, End date: 2024-09-30
