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
Country United Kingdom
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 ACRCC
Project Understanding the atmospheric circulation response to climate change
Researcher (PI) Theodore Shepherd
Host Institution (HI) THE UNIVERSITY OF READING
Country United Kingdom
Call Details Advanced Grant (AdG), PE10, ERC-2013-ADG
Summary Computer models based on known physical laws are our primary tool for predicting climate change. Yet the state-of-the-art models exhibit a disturbingly wide range of predictions of future climate change, especially when examined at the regional scale, which has not decreased as the models have become more comprehensive. The reasons for this are not understood. This represents a basic challenge to our fundamental understanding of climate.
The divergence of model projections is presumably related to systematic model errors in the large-scale fluxes of heat, moisture and momentum that control regional aspects of climate. That these errors stubbornly persist in spite of increases in the spatial resolution of the models suggests that they are associated with errors in the representation of unresolved processes, whose effects must be parameterised.
Most attention in climate science has hitherto focused on the thermodynamic aspects of climate. Dynamical aspects, which involve the atmospheric circulation, have received much less attention. However regional climate, including persistent climate regimes and extremes, is strongly controlled by atmospheric circulation patterns, which exhibit chaotic variability and whose representation in climate models depends sensitively on parameterised processes. Moreover the dynamical aspects of model projections are much less robust than the thermodynamic ones. There are good reasons to believe that model bias, the divergence of model projections, and chaotic variability are somehow related, although the relationships are not well understood. This calls for studying them together.
My proposed research will focus on this problem, addressing these three aspects of the atmospheric circulation response to climate change in parallel: (i) diagnosing the sources of model error; (ii) elucidating the relationship between model error and the spread in model projections; (iii) understanding the physical mechanisms of atmospheric variability.
Summary
Computer models based on known physical laws are our primary tool for predicting climate change. Yet the state-of-the-art models exhibit a disturbingly wide range of predictions of future climate change, especially when examined at the regional scale, which has not decreased as the models have become more comprehensive. The reasons for this are not understood. This represents a basic challenge to our fundamental understanding of climate.
The divergence of model projections is presumably related to systematic model errors in the large-scale fluxes of heat, moisture and momentum that control regional aspects of climate. That these errors stubbornly persist in spite of increases in the spatial resolution of the models suggests that they are associated with errors in the representation of unresolved processes, whose effects must be parameterised.
Most attention in climate science has hitherto focused on the thermodynamic aspects of climate. Dynamical aspects, which involve the atmospheric circulation, have received much less attention. However regional climate, including persistent climate regimes and extremes, is strongly controlled by atmospheric circulation patterns, which exhibit chaotic variability and whose representation in climate models depends sensitively on parameterised processes. Moreover the dynamical aspects of model projections are much less robust than the thermodynamic ones. There are good reasons to believe that model bias, the divergence of model projections, and chaotic variability are somehow related, although the relationships are not well understood. This calls for studying them together.
My proposed research will focus on this problem, addressing these three aspects of the atmospheric circulation response to climate change in parallel: (i) diagnosing the sources of model error; (ii) elucidating the relationship between model error and the spread in model projections; (iii) understanding the physical mechanisms of atmospheric variability.
Max ERC Funding
2 489 151 €
Duration
Start date: 2014-03-01, End date: 2020-02-29
Project acronym ALUNIF
Project Algorithms and Lower Bounds: A Unified Approach
Researcher (PI) Rahul Santhanam
Host Institution (HI) THE CHANCELLOR, MASTERS AND SCHOLARS OF THE UNIVERSITY OF OXFORD
Country United Kingdom
Call Details Consolidator Grant (CoG), PE6, ERC-2013-CoG
Summary One of the fundamental goals of theoretical computer science is to
understand the possibilities and limits of efficient computation. This
quest has two dimensions. The
theory of algorithms focuses on finding efficient solutions to
problems, while computational complexity theory aims to understand when
and why problems are hard to solve. These two areas have different
philosophies and use different sets of techniques. However, in recent
years there have been indications of deep and mysterious connections
between them.
In this project, we propose to explore and develop the connections between
algorithmic analysis and complexity lower bounds in a systematic way.
On the one hand, we plan to use complexity lower bound techniques as inspiration
to design new and improved algorithms for Satisfiability and other
NP-complete problems, as well as to analyze existing algorithms better.
On the other hand, we plan to strengthen implications yielding circuit
lower bounds from non-trivial algorithms for Satisfiability, and to derive
new circuit lower bounds using these stronger implications.
This project has potential for massive impact in both the areas of algorithms
and computational complexity. Improved algorithms for Satisfiability could lead
to improved SAT solvers, and the new analytical tools would lead to a better
understanding of existing heuristics. Complexity lower bound questions are
fundamental
but notoriously difficult, and new lower bounds would open the way to
unconditionally secure cryptographic protocols and derandomization of
probabilistic algorithms. More broadly, this project aims to initiate greater
dialogue between the two areas, with an exchange of ideas and techniques
which leads to accelerated progress in both, as well as a deeper understanding
of the nature of efficient computation.
Summary
One of the fundamental goals of theoretical computer science is to
understand the possibilities and limits of efficient computation. This
quest has two dimensions. The
theory of algorithms focuses on finding efficient solutions to
problems, while computational complexity theory aims to understand when
and why problems are hard to solve. These two areas have different
philosophies and use different sets of techniques. However, in recent
years there have been indications of deep and mysterious connections
between them.
In this project, we propose to explore and develop the connections between
algorithmic analysis and complexity lower bounds in a systematic way.
On the one hand, we plan to use complexity lower bound techniques as inspiration
to design new and improved algorithms for Satisfiability and other
NP-complete problems, as well as to analyze existing algorithms better.
On the other hand, we plan to strengthen implications yielding circuit
lower bounds from non-trivial algorithms for Satisfiability, and to derive
new circuit lower bounds using these stronger implications.
This project has potential for massive impact in both the areas of algorithms
and computational complexity. Improved algorithms for Satisfiability could lead
to improved SAT solvers, and the new analytical tools would lead to a better
understanding of existing heuristics. Complexity lower bound questions are
fundamental
but notoriously difficult, and new lower bounds would open the way to
unconditionally secure cryptographic protocols and derandomization of
probabilistic algorithms. More broadly, this project aims to initiate greater
dialogue between the two areas, with an exchange of ideas and techniques
which leads to accelerated progress in both, as well as a deeper understanding
of the nature of efficient computation.
Max ERC Funding
1 274 496 €
Duration
Start date: 2014-03-01, End date: 2019-02-28
Project acronym AMPHIBIANS
Project All Optical Manipulation of Photonic Metasurfaces for Biophotonic Applications in Microfluidic Environments
Researcher (PI) Andrea DI FALCO
Host Institution (HI) THE UNIVERSITY COURT OF THE UNIVERSITY OF ST ANDREWS
Country United Kingdom
Call Details Consolidator Grant (CoG), PE7, ERC-2018-COG
Summary The current trend in biophotonics is to try and replicate the same ease and precision that our hands, eyes and ears offer at the macroscopic level, e.g. to hold, observe, squeeze and pull, rotate, cut and probe biological specimens in microfluidic environments. The bidding to get closer and closer to the object of interest has prompted the development of extremely advanced manipulation techniques at scales comparable to that of the wavelength of light. However, the fact that the optical beam can only access the microfluidic chip from the narrow aperture of a microscopic objective limits the versatility of the photonic function that can be realized.
With this project, the applicant proposes to introduce a new biophotonic platform based on the all optical manipulation of flexible photonic metasurfaces. These artificial two-dimensional materials have virtually arbitrary photonic responses and have an intrinsic exceptional mechanical stability. This cross-disciplinary project, bridging photonics, material sciences and biology, will enable the adoption of the most modern and advanced photonic designs in microfluidic environments, with transformative benefits for microscopy and biophotonic applications at the interface of molecular and cell biology.
Summary
The current trend in biophotonics is to try and replicate the same ease and precision that our hands, eyes and ears offer at the macroscopic level, e.g. to hold, observe, squeeze and pull, rotate, cut and probe biological specimens in microfluidic environments. The bidding to get closer and closer to the object of interest has prompted the development of extremely advanced manipulation techniques at scales comparable to that of the wavelength of light. However, the fact that the optical beam can only access the microfluidic chip from the narrow aperture of a microscopic objective limits the versatility of the photonic function that can be realized.
With this project, the applicant proposes to introduce a new biophotonic platform based on the all optical manipulation of flexible photonic metasurfaces. These artificial two-dimensional materials have virtually arbitrary photonic responses and have an intrinsic exceptional mechanical stability. This cross-disciplinary project, bridging photonics, material sciences and biology, will enable the adoption of the most modern and advanced photonic designs in microfluidic environments, with transformative benefits for microscopy and biophotonic applications at the interface of molecular and cell biology.
Max ERC Funding
1 999 524 €
Duration
Start date: 2019-02-01, End date: 2024-01-31
Project acronym ANTI-ATOM
Project Many-body theory of antimatter interactions with atoms, molecules and condensed matter
Researcher (PI) Dermot GREEN
Host Institution (HI) THE QUEEN'S UNIVERSITY OF BELFAST
Country United Kingdom
Call Details Starting Grant (StG), PE2, ERC-2018-STG
Summary The ability of positrons to annihilate with electrons, producing characteristic gamma rays, gives them important use in medicine via positron-emission tomography (PET), diagnostics of industrially-important materials, and in elucidating astrophysical phenomena. Moreover, the fundamental interactions of positrons and positronium (Ps) with atoms, molecules and condensed matter are currently under intensive study in numerous international laboratories, to illuminate collision phenomena and perform precision tests of fundamental laws.
Proper interpretation and development of these costly and difficult experiments requires accurate calculations of low-energy positron and Ps interactions with normal matter. These systems, however, involve strong correlations, e.g., polarisation of the atom and virtual-Ps formation (where an atomic electron tunnels to the positron): they significantly effect positron- and Ps-atom/molecule interactions, e.g., enhancing annihilation rates by many orders of magnitude, and making the accurate description of these systems a challenging many-body problem. Current theoretical capability lags severely behind that of experiment. Major theoretical and computational developments are required to bridge the gap.
One powerful method, which accounts for the correlations in a natural, transparent and systematic way, is many-body theory (MBT). Building on my expertise in the field, I propose to develop new MBT to deliver unique and unrivalled capability in theory and computation of low-energy positron and Ps interactions with atoms, molecules, and condensed matter. The ambitious programme will provide the basic understanding required to interpret and develop the fundamental experiments, antimatter-based materials science techniques, and wider technologies, e.g., (PET), and more broadly, potentially revolutionary and generally applicable computational methodologies that promise to define a new level of high-precision in atomic-MBT calculations.
Summary
The ability of positrons to annihilate with electrons, producing characteristic gamma rays, gives them important use in medicine via positron-emission tomography (PET), diagnostics of industrially-important materials, and in elucidating astrophysical phenomena. Moreover, the fundamental interactions of positrons and positronium (Ps) with atoms, molecules and condensed matter are currently under intensive study in numerous international laboratories, to illuminate collision phenomena and perform precision tests of fundamental laws.
Proper interpretation and development of these costly and difficult experiments requires accurate calculations of low-energy positron and Ps interactions with normal matter. These systems, however, involve strong correlations, e.g., polarisation of the atom and virtual-Ps formation (where an atomic electron tunnels to the positron): they significantly effect positron- and Ps-atom/molecule interactions, e.g., enhancing annihilation rates by many orders of magnitude, and making the accurate description of these systems a challenging many-body problem. Current theoretical capability lags severely behind that of experiment. Major theoretical and computational developments are required to bridge the gap.
One powerful method, which accounts for the correlations in a natural, transparent and systematic way, is many-body theory (MBT). Building on my expertise in the field, I propose to develop new MBT to deliver unique and unrivalled capability in theory and computation of low-energy positron and Ps interactions with atoms, molecules, and condensed matter. The ambitious programme will provide the basic understanding required to interpret and develop the fundamental experiments, antimatter-based materials science techniques, and wider technologies, e.g., (PET), and more broadly, potentially revolutionary and generally applicable computational methodologies that promise to define a new level of high-precision in atomic-MBT calculations.
Max ERC Funding
1 318 419 €
Duration
Start date: 2019-02-01, End date: 2024-01-31
Project acronym ARYLATOR
Project New Catalytic Reactions and Exchange Pathways: Delivering Versatile and Reliable Arylation
Researcher (PI) Guy Charles Lloyd-Jones
Host Institution (HI) THE UNIVERSITY OF EDINBURGH
Country United Kingdom
Call Details Advanced Grant (AdG), PE5, ERC-2013-ADG
Summary This proposal details the mechanism-based discovery of ground-breaking new catalyst systems for a broad range of arylation processes that will be of immediate and long-lasting utility to the pharmaceutical, agrochemical, and materials chemistry industries. These industries have become highly dependent on coupling technologies employing homogeneous late transition metal catalysis and this reliance will grow further, particularly if the substrate scope can be broadened, the economics, in terms of reagents and catalyst, made more favourable, the reliability at scale-up improved, and the generation of side-products, of particular importance for optical and electronic properties of materials, minimized or eliminated.
This proposal addresses these issues by conducting a detailed and comprehensive mechanistic investigation of direct arylation, so that a substantial expansion of the reaction scope can be achieved. At present, the regioselectivity can be very high, however catalyst turnover rates are moderate, and the arene is required to be in a fairly narrow window of activity. Specific aspects to be addressed in terms of mechanistic study are: catalyst speciation and pathways for deactivation; pathways for homocoupling; influence of anions and dummy ligands; protodemetalloidation pathways. Areas proposed for mechanism-informed development are: expansion of metalloid tolerance; expansion of arene scope; use of traceless activators and directors, new couplings via ligand exchange, the evolution of simpler / cheaper and more selective / active catalysts; expansion to oxidative double arylations (Ar-H + Ar’-H) with control, and without resort to super-stoichiometric bias.
The long-term legacy of these studies will be detailed insight for current and emerging systems, as well as readily extrapolated information for the design of new, more efficient catalyst systems in academia, and their scaleable application in industry
Summary
This proposal details the mechanism-based discovery of ground-breaking new catalyst systems for a broad range of arylation processes that will be of immediate and long-lasting utility to the pharmaceutical, agrochemical, and materials chemistry industries. These industries have become highly dependent on coupling technologies employing homogeneous late transition metal catalysis and this reliance will grow further, particularly if the substrate scope can be broadened, the economics, in terms of reagents and catalyst, made more favourable, the reliability at scale-up improved, and the generation of side-products, of particular importance for optical and electronic properties of materials, minimized or eliminated.
This proposal addresses these issues by conducting a detailed and comprehensive mechanistic investigation of direct arylation, so that a substantial expansion of the reaction scope can be achieved. At present, the regioselectivity can be very high, however catalyst turnover rates are moderate, and the arene is required to be in a fairly narrow window of activity. Specific aspects to be addressed in terms of mechanistic study are: catalyst speciation and pathways for deactivation; pathways for homocoupling; influence of anions and dummy ligands; protodemetalloidation pathways. Areas proposed for mechanism-informed development are: expansion of metalloid tolerance; expansion of arene scope; use of traceless activators and directors, new couplings via ligand exchange, the evolution of simpler / cheaper and more selective / active catalysts; expansion to oxidative double arylations (Ar-H + Ar’-H) with control, and without resort to super-stoichiometric bias.
The long-term legacy of these studies will be detailed insight for current and emerging systems, as well as readily extrapolated information for the design of new, more efficient catalyst systems in academia, and their scaleable application in industry
Max ERC Funding
2 114 223 €
Duration
Start date: 2014-02-01, End date: 2019-01-31
Project acronym ASIBIA
Project Arctic sea ice, biogeochemistry and impacts on the atmosphere: Past, present, future
Researcher (PI) Roland Von Glasow
Host Institution (HI) UNIVERSITY OF EAST ANGLIA
Country United Kingdom
Call Details Consolidator Grant (CoG), PE10, ERC-2013-CoG
Summary The Arctic Ocean is a vast expanse of sea ice. Most of it is snow covered as are large continental regions for about half of the year. However, Global Change is arguably greatest in the Arctic, where temperatures have risen more than anywhere else in the last few decades. New record lows occurred in snow extent in June 2012 and sea ice extent in September 2012. Many observations show that widespread and sustained change is occurring in the Arctic driving this unique environmental system into a new state. This project focuses on the biogeochemical links between sea ice and snow and the composition and chemistry of the troposphere (the lowest ~10km of the atmosphere). This is an important topic because the concentrations of greenhouse gases and aerosol particles, which scatter sunlight directly and influence cloud properties, play key roles for our climate. Additionally, changes in the composition of the troposphere also affect the so-called oxidation capacity, the capability of the atmosphere to cleanse itself from pollutants.
This project aims to deliver a step change improvement in our quantitative understanding of chemical exchanges between ocean, sea ice, snow and the atmosphere in polar regions, especially the Arctic and of Arctic tropospheric chemistry. Answering these fundamental questions is essential to predict future change in the Arctic and globally. To this end a unique sea ice chamber will be constructed in the laboratory and used to quantify exchange processes in sea ice. Furthermore a hierarchy of numerical models will be used, operating at different spatial and temporal scales and degree of process description from a very detailed 1D to a global Earth System model. This will allow a breakthrough in our understanding of the importance of the changes for the composition and oxidation capacity of the atmosphere and climate and will allow us to calculate adjusted Greenhouse Warming Potentials that include these processes.
Summary
The Arctic Ocean is a vast expanse of sea ice. Most of it is snow covered as are large continental regions for about half of the year. However, Global Change is arguably greatest in the Arctic, where temperatures have risen more than anywhere else in the last few decades. New record lows occurred in snow extent in June 2012 and sea ice extent in September 2012. Many observations show that widespread and sustained change is occurring in the Arctic driving this unique environmental system into a new state. This project focuses on the biogeochemical links between sea ice and snow and the composition and chemistry of the troposphere (the lowest ~10km of the atmosphere). This is an important topic because the concentrations of greenhouse gases and aerosol particles, which scatter sunlight directly and influence cloud properties, play key roles for our climate. Additionally, changes in the composition of the troposphere also affect the so-called oxidation capacity, the capability of the atmosphere to cleanse itself from pollutants.
This project aims to deliver a step change improvement in our quantitative understanding of chemical exchanges between ocean, sea ice, snow and the atmosphere in polar regions, especially the Arctic and of Arctic tropospheric chemistry. Answering these fundamental questions is essential to predict future change in the Arctic and globally. To this end a unique sea ice chamber will be constructed in the laboratory and used to quantify exchange processes in sea ice. Furthermore a hierarchy of numerical models will be used, operating at different spatial and temporal scales and degree of process description from a very detailed 1D to a global Earth System model. This will allow a breakthrough in our understanding of the importance of the changes for the composition and oxidation capacity of the atmosphere and climate and will allow us to calculate adjusted Greenhouse Warming Potentials that include these processes.
Max ERC Funding
1 192 911 €
Duration
Start date: 2014-05-01, End date: 2016-09-30
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 SCHOLARS OF 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 BEBOP
Project Binaries Escorted By Orbiting Planets
Researcher (PI) Amaury TRIAUD
Host Institution (HI) THE UNIVERSITY OF BIRMINGHAM
Country United Kingdom
Call Details Starting Grant (StG), PE9, ERC-2018-STG
Summary Planets orbiting both stars of a binary system -circumbinary planets- are challenging our understanding about how planets assemble, and how their orbits subsequently evolve. Long confined to science-fiction, circumbinary planets were confirmed by the Kepler spacecraft, in one of its most spectacular, and impactful result. Despite Kepler’s insights, a lot remains unknown about these planets. Kepler also suffered from intractable biases that the BEBOP project will solve.
BEBOP will revolutionise how we detect and study circumbinary planets. Conducting a Doppler survey, we will vastly improve the efficiency of circumbinary planet detection, and remove Kepler’s biases. BEBOP will construct a clearer picture of the circumbinary planet population, and free us from the inherent vagaries, and important costs of space-funding. Thanks to the Doppler method we will study dynamical effects unique to circumbinary planets, estimate their multiplicity, and compute their true occurrence rate.
Circumbinary planets are essential objects. Binaries disturbe planet formation. Any similarity, and any difference between the population of circumbinary planets and planets orbiting single stars, will bring novel information about how planets are produced. In addition, circumbinary planets have unique orbital properties that boost their probability to experience transits. BEBOP’s detections will open the door to atmospheric studies of colder worlds than presently available.
Based on already discovered systems, and on two successful proofs-of-concept, the BEBOP team will detect 15 circumbinary gas-giants, three times more than Kepler. BEBOP will provide an unambiguous measure of the efficiency of gas-giant formation in circumbinary environments. In addition the BEBOP project comes with an ambitious programme to combine three detection methods (Doppler, transits, and astrometry) in a holistic approach that will bolster investigations into circumbinary planets, and create a lasting legacy.
Summary
Planets orbiting both stars of a binary system -circumbinary planets- are challenging our understanding about how planets assemble, and how their orbits subsequently evolve. Long confined to science-fiction, circumbinary planets were confirmed by the Kepler spacecraft, in one of its most spectacular, and impactful result. Despite Kepler’s insights, a lot remains unknown about these planets. Kepler also suffered from intractable biases that the BEBOP project will solve.
BEBOP will revolutionise how we detect and study circumbinary planets. Conducting a Doppler survey, we will vastly improve the efficiency of circumbinary planet detection, and remove Kepler’s biases. BEBOP will construct a clearer picture of the circumbinary planet population, and free us from the inherent vagaries, and important costs of space-funding. Thanks to the Doppler method we will study dynamical effects unique to circumbinary planets, estimate their multiplicity, and compute their true occurrence rate.
Circumbinary planets are essential objects. Binaries disturbe planet formation. Any similarity, and any difference between the population of circumbinary planets and planets orbiting single stars, will bring novel information about how planets are produced. In addition, circumbinary planets have unique orbital properties that boost their probability to experience transits. BEBOP’s detections will open the door to atmospheric studies of colder worlds than presently available.
Based on already discovered systems, and on two successful proofs-of-concept, the BEBOP team will detect 15 circumbinary gas-giants, three times more than Kepler. BEBOP will provide an unambiguous measure of the efficiency of gas-giant formation in circumbinary environments. In addition the BEBOP project comes with an ambitious programme to combine three detection methods (Doppler, transits, and astrometry) in a holistic approach that will bolster investigations into circumbinary planets, and create a lasting legacy.
Max ERC Funding
1 186 313 €
Duration
Start date: 2018-11-01, End date: 2023-10-31
