Project acronym 3D-CAP
Project 3D micro-supercapacitors for embedded electronics
Researcher (PI) David Sarinn PECH
Host Institution (HI) CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS
Country France
Call Details Consolidator Grant (CoG), PE7, ERC-2017-COG
Summary The realization of high-performance micro-supercapacitors is currently a big challenge but the ineluctable applications requiring such miniaturized energy storage devices are continuously emerging, from wearable electronic gadgets to wireless sensor networks. Although they store less energy than micro-batteries, micro-supercapacitors can be charged and discharged very rapidly and exhibit a quasi-unlimited lifetime. The global scientific research is consequently largely focused on the improvement of their capacitance and energetic performances. However, to date, they are still far from being able to power sensors or electronic components.
Here I propose a 3D paradigm shift of micro-supercapacitor design to ensure increased energy storage capacities. Hydrous ruthenium dioxide (RuO2) is a pseudocapacitive material for supercapacitor electrode well-known for its high capacitance. A thin-film of ruthenium will be deposited by atomic layer deposition (ALD), followed by an electrochemical oxidation process, onto a high-surface-area 3D current collector prepared via an ingenious dynamic template built with hydrogen bubbles. The structural features of these 3D architectures will be controllably tailored by the processing methodologies. These electrodes will be combined with an innovative electrolyte in solid form (a protic ionogel) able to operate over an extended cell voltage. In a parallel investigation, we will develop a fundamental understanding of electrochemical reactions occurring at the nanoscale with a FIB-patterned (Focused Ion Beam) RuO2 nano-supercapacitor. The resulting 3D micro-supercapacitors should display extremely high power, long lifetime and – for the first time – energy densities competing or even exceeding that of micro-batteries. As a key achievement, prototypes will be designed using a new concept based on a self-adaptative micro-supercapacitors matrix, which arranges itself according to the global amount of energy stored.
Summary
The realization of high-performance micro-supercapacitors is currently a big challenge but the ineluctable applications requiring such miniaturized energy storage devices are continuously emerging, from wearable electronic gadgets to wireless sensor networks. Although they store less energy than micro-batteries, micro-supercapacitors can be charged and discharged very rapidly and exhibit a quasi-unlimited lifetime. The global scientific research is consequently largely focused on the improvement of their capacitance and energetic performances. However, to date, they are still far from being able to power sensors or electronic components.
Here I propose a 3D paradigm shift of micro-supercapacitor design to ensure increased energy storage capacities. Hydrous ruthenium dioxide (RuO2) is a pseudocapacitive material for supercapacitor electrode well-known for its high capacitance. A thin-film of ruthenium will be deposited by atomic layer deposition (ALD), followed by an electrochemical oxidation process, onto a high-surface-area 3D current collector prepared via an ingenious dynamic template built with hydrogen bubbles. The structural features of these 3D architectures will be controllably tailored by the processing methodologies. These electrodes will be combined with an innovative electrolyte in solid form (a protic ionogel) able to operate over an extended cell voltage. In a parallel investigation, we will develop a fundamental understanding of electrochemical reactions occurring at the nanoscale with a FIB-patterned (Focused Ion Beam) RuO2 nano-supercapacitor. The resulting 3D micro-supercapacitors should display extremely high power, long lifetime and – for the first time – energy densities competing or even exceeding that of micro-batteries. As a key achievement, prototypes will be designed using a new concept based on a self-adaptative micro-supercapacitors matrix, which arranges itself according to the global amount of energy stored.
Max ERC Funding
1 673 438 €
Duration
Start date: 2018-04-01, End date: 2023-03-31
Project acronym 3DPROTEINPUZZLES
Project Shape-directed protein assembly design
Researcher (PI) Lars Ingemar ANDRe
Host Institution (HI) MAX IV Laboratory, Lund University
Country Sweden
Call Details Consolidator Grant (CoG), LS9, ERC-2017-COG
Summary Large protein complexes carry out some of the most complex functions in biology. Such structures are often assembled spontaneously from individual components through the process of self-assembly. If self-assembled protein complexes could be engineered from first principle it would enable a wide range of applications in biomedicine, nanotechnology and materials science. Recently, approaches to rationally design proteins to self-assembly into predefined structures have emerged. The highlight of this work is the design of protein cages that may be engineered into protein containers. However, current approaches for self-assembly design does not result in the assemblies with the required structural complexity to encode many of the sophisticated functions found in nature. To move forward, we have to learn how to engineer protein subunits with more than one designed interface that can assemble into tightly interacting complexes. In this proposal we propose a new protein design paradigm, shape directed protein design, in order to address shortcomings of the current methodology. The proposed method combines geometric shape matching and computational protein design. Using this approach we will de novo design assemblies with a wide variety of structural states, including protein complexes with cyclic and dihedral symmetry as well as icosahedral protein capsids built from novel protein building blocks. To enable these two design challenges we also develop a high-throughput assay to measure assembly stability in vivo that builds on a three-color fluorescent assay. This method will not only facilitate the screening of orders of magnitude more design constructs, but also enable the application of directed evolution to experimentally improve stable and assembly properties of designed containers as well as other designed assemblies.
Summary
Large protein complexes carry out some of the most complex functions in biology. Such structures are often assembled spontaneously from individual components through the process of self-assembly. If self-assembled protein complexes could be engineered from first principle it would enable a wide range of applications in biomedicine, nanotechnology and materials science. Recently, approaches to rationally design proteins to self-assembly into predefined structures have emerged. The highlight of this work is the design of protein cages that may be engineered into protein containers. However, current approaches for self-assembly design does not result in the assemblies with the required structural complexity to encode many of the sophisticated functions found in nature. To move forward, we have to learn how to engineer protein subunits with more than one designed interface that can assemble into tightly interacting complexes. In this proposal we propose a new protein design paradigm, shape directed protein design, in order to address shortcomings of the current methodology. The proposed method combines geometric shape matching and computational protein design. Using this approach we will de novo design assemblies with a wide variety of structural states, including protein complexes with cyclic and dihedral symmetry as well as icosahedral protein capsids built from novel protein building blocks. To enable these two design challenges we also develop a high-throughput assay to measure assembly stability in vivo that builds on a three-color fluorescent assay. This method will not only facilitate the screening of orders of magnitude more design constructs, but also enable the application of directed evolution to experimentally improve stable and assembly properties of designed containers as well as other designed assemblies.
Max ERC Funding
2 325 292 €
Duration
Start date: 2018-06-01, End date: 2023-05-31
Project acronym 4DRepLy
Project Closing the 4D Real World Reconstruction Loop
Researcher (PI) Christian THEOBALT
Host Institution (HI) MAX-PLANCK-GESELLSCHAFT ZUR FORDERUNG DER WISSENSCHAFTEN EV
Country Germany
Call Details Consolidator Grant (CoG), PE6, ERC-2017-COG
Summary 4D reconstruction, the camera-based dense dynamic scene reconstruction, is a grand challenge in computer graphics and computer vision. Despite great progress, 4D capturing the complex, diverse real world outside a studio is still far from feasible. 4DRepLy builds a new generation of high-fidelity 4D reconstruction (4DRecon) methods. They will be the first to efficiently capture all types of deformable objects (humans and other types) in crowded real world scenes with a single color or depth camera. They capture space-time coherent deforming geometry, motion, high-frequency reflectance and illumination at unprecedented detail, and will be the first to handle difficult occlusions, topology changes and large groups of interacting objects. They automatically adapt to new scene types, yet deliver models with meaningful, interpretable parameters. This requires far reaching contributions: First, we develop groundbreaking new plasticity-enhanced model-based 4D reconstruction methods that automatically adapt to new scenes. Second, we develop radically new machine learning-based dense 4D reconstruction methods. Third, these model- and learning-based methods are combined in two revolutionary new classes of 4DRecon methods: 1) advanced fusion-based methods and 2) methods with deep architectural integration. Both, 1) and 2), are automatically designed in the 4D Real World Reconstruction Loop, a revolutionary new design paradigm in which 4DRecon methods refine and adapt themselves while continuously processing unlabeled real world input. This overcomes the previously unbreakable scalability barrier to real world scene diversity, complexity and generality. This paradigm shift opens up a new research direction in graphics and vision and has far reaching relevance across many scientific fields. It enables new applications of profound social pervasion and significant economic impact, e.g., for visual media and virtual/augmented reality, and for future autonomous and robotic systems.
Summary
4D reconstruction, the camera-based dense dynamic scene reconstruction, is a grand challenge in computer graphics and computer vision. Despite great progress, 4D capturing the complex, diverse real world outside a studio is still far from feasible. 4DRepLy builds a new generation of high-fidelity 4D reconstruction (4DRecon) methods. They will be the first to efficiently capture all types of deformable objects (humans and other types) in crowded real world scenes with a single color or depth camera. They capture space-time coherent deforming geometry, motion, high-frequency reflectance and illumination at unprecedented detail, and will be the first to handle difficult occlusions, topology changes and large groups of interacting objects. They automatically adapt to new scene types, yet deliver models with meaningful, interpretable parameters. This requires far reaching contributions: First, we develop groundbreaking new plasticity-enhanced model-based 4D reconstruction methods that automatically adapt to new scenes. Second, we develop radically new machine learning-based dense 4D reconstruction methods. Third, these model- and learning-based methods are combined in two revolutionary new classes of 4DRecon methods: 1) advanced fusion-based methods and 2) methods with deep architectural integration. Both, 1) and 2), are automatically designed in the 4D Real World Reconstruction Loop, a revolutionary new design paradigm in which 4DRecon methods refine and adapt themselves while continuously processing unlabeled real world input. This overcomes the previously unbreakable scalability barrier to real world scene diversity, complexity and generality. This paradigm shift opens up a new research direction in graphics and vision and has far reaching relevance across many scientific fields. It enables new applications of profound social pervasion and significant economic impact, e.g., for visual media and virtual/augmented reality, and for future autonomous and robotic systems.
Max ERC Funding
1 977 000 €
Duration
Start date: 2018-09-01, End date: 2023-08-31
Project acronym Acclimatize
Project Hypothalamic mechanisms of thermal homeostasis and adaptation
Researcher (PI) Jan SIEMENS
Host Institution (HI) UNIVERSITATSKLINIKUM HEIDELBERG
Country Germany
Call Details Consolidator Grant (CoG), LS5, ERC-2017-COG
Summary Mammalian organisms possess the remarkable ability to maintain internal body temperature (Tcore) within a narrow range close to 37°C despite wide environmental temperature variations. The brain’s neural “thermostat” is made up by central circuits in the hypothalamic preoptic area (POA), which orchestrate peripheral thermoregulatory responses to maintain Tcore. Thermogenesis requires metabolic fuel, suggesting intricate connections between the thermoregulatory centre and hypothalamic circuits controlling energy balance. How the POA detects and integrates temperature and metabolic information to achieve thermal balance is largely unknown. A major question is whether this circuitry could be harnessed therapeutically to treat obesity.
We have recently identified the first known molecular temperature sensor in thermoregulatory neurons of the POA, transient receptor potential melastatin 2 (TRPM2), a thermo-sensitive ion channel. I aim to use TRPM2 as a molecular marker to gain access to and probe the function of thermoregulatory neurons in vivo. I propose a multidisciplinary approach, combining local, in vivo POA temperature stimulation with optogenetic circuit-mapping to uncover the molecular and cellular logic of the hypothalamic thermoregulatory centre and to assess its medical potential to counteract metabolic syndrome.
Acclimation is a beneficial adaptive process that fortifies thermal responses upon environmental temperature challenges. Thermoregulatory neuron plasticity is thought to mediate acclimation. Conversely, maladaptive thermoregulatory changes affect obesity. The cell-type-specific neuronal plasticity mechanisms underlying these changes within the POA, however, are unknown.
Using ex-vivo slice electrophysiology and in vivo imaging, I propose to characterize acclimation- and obesity-induced plasticity of thermoregulatory neurons. Ultimately, I aim to manipulate thermoregulatory neuron plasticity to test its potential counter-balancing effect on obesity.
Summary
Mammalian organisms possess the remarkable ability to maintain internal body temperature (Tcore) within a narrow range close to 37°C despite wide environmental temperature variations. The brain’s neural “thermostat” is made up by central circuits in the hypothalamic preoptic area (POA), which orchestrate peripheral thermoregulatory responses to maintain Tcore. Thermogenesis requires metabolic fuel, suggesting intricate connections between the thermoregulatory centre and hypothalamic circuits controlling energy balance. How the POA detects and integrates temperature and metabolic information to achieve thermal balance is largely unknown. A major question is whether this circuitry could be harnessed therapeutically to treat obesity.
We have recently identified the first known molecular temperature sensor in thermoregulatory neurons of the POA, transient receptor potential melastatin 2 (TRPM2), a thermo-sensitive ion channel. I aim to use TRPM2 as a molecular marker to gain access to and probe the function of thermoregulatory neurons in vivo. I propose a multidisciplinary approach, combining local, in vivo POA temperature stimulation with optogenetic circuit-mapping to uncover the molecular and cellular logic of the hypothalamic thermoregulatory centre and to assess its medical potential to counteract metabolic syndrome.
Acclimation is a beneficial adaptive process that fortifies thermal responses upon environmental temperature challenges. Thermoregulatory neuron plasticity is thought to mediate acclimation. Conversely, maladaptive thermoregulatory changes affect obesity. The cell-type-specific neuronal plasticity mechanisms underlying these changes within the POA, however, are unknown.
Using ex-vivo slice electrophysiology and in vivo imaging, I propose to characterize acclimation- and obesity-induced plasticity of thermoregulatory neurons. Ultimately, I aim to manipulate thermoregulatory neuron plasticity to test its potential counter-balancing effect on obesity.
Max ERC Funding
1 902 500 €
Duration
Start date: 2018-09-01, End date: 2023-08-31
Project acronym Active-DNA
Project Computationally Active DNA Nanostructures
Researcher (PI) Damien WOODS
Host Institution (HI) NATIONAL UNIVERSITY OF IRELAND MAYNOOTH
Country Ireland
Call Details Consolidator Grant (CoG), PE6, ERC-2017-COG
Summary During the 20th century computer technology evolved from bulky, slow, special purpose mechanical engines to the now ubiquitous silicon chips and software that are one of the pinnacles of human ingenuity. The goal of the field of molecular programming is to take the next leap and build a new generation of matter-based computers using DNA, RNA and proteins. This will be accomplished by computer scientists, physicists and chemists designing molecules to execute ``wet'' nanoscale programs in test tubes. The workflow includes proposing theoretical models, mathematically proving their computational properties, physical modelling and implementation in the wet-lab.
The past decade has seen remarkable progress at building static 2D and 3D DNA nanostructures. However, unlike biological macromolecules and complexes that are built via specified self-assembly pathways, that execute robotic-like movements, and that undergo evolution, the activity of human-engineered nanostructures is severely limited. We will need sophisticated algorithmic ideas to build structures that rival active living systems. Active-DNA, aims to address this challenge by achieving a number of objectives on computation, DNA-based self-assembly and molecular robotics. Active-DNA research work will range from defining models and proving theorems that characterise the computational and expressive capabilities of such active programmable materials to experimental work implementing active DNA nanostructures in the wet-lab.
Summary
During the 20th century computer technology evolved from bulky, slow, special purpose mechanical engines to the now ubiquitous silicon chips and software that are one of the pinnacles of human ingenuity. The goal of the field of molecular programming is to take the next leap and build a new generation of matter-based computers using DNA, RNA and proteins. This will be accomplished by computer scientists, physicists and chemists designing molecules to execute ``wet'' nanoscale programs in test tubes. The workflow includes proposing theoretical models, mathematically proving their computational properties, physical modelling and implementation in the wet-lab.
The past decade has seen remarkable progress at building static 2D and 3D DNA nanostructures. However, unlike biological macromolecules and complexes that are built via specified self-assembly pathways, that execute robotic-like movements, and that undergo evolution, the activity of human-engineered nanostructures is severely limited. We will need sophisticated algorithmic ideas to build structures that rival active living systems. Active-DNA, aims to address this challenge by achieving a number of objectives on computation, DNA-based self-assembly and molecular robotics. Active-DNA research work will range from defining models and proving theorems that characterise the computational and expressive capabilities of such active programmable materials to experimental work implementing active DNA nanostructures in the wet-lab.
Max ERC Funding
2 349 603 €
Duration
Start date: 2018-11-01, End date: 2023-10-31
Project acronym AFIRMATIVE
Project Acoustic-Flow Interaction Models for Advancing Thermoacoustic Instability prediction in Very low Emission combustors
Researcher (PI) Aimee MORGANS
Host Institution (HI) IMPERIAL COLLEGE OF SCIENCE TECHNOLOGY AND MEDICINE
Country United Kingdom
Call Details Consolidator Grant (CoG), PE8, ERC-2017-COG
Summary Gas turbines are an essential ingredient in the long-term energy and aviation mix. They are flexible, offer fast start-up and the ability to burn renewable-generated fuels. However, they generate NOx emissions, which cause air pollution and damage human health, and reducing these is an air quality imperative. A major hurdle to this is that lean premixed combustion, essential for further NOx emission reductions, is highly susceptible to thermoacoustic instability. This is caused by a two-way coupling between unsteady combustion and acoustic waves, and the resulting large pressure oscillations can cause severe mechanical damage. Computational methods for predicting thermoacoustic instability, fast and accurate enough to be used as part of the industrial design process, are urgently needed.
The only computational methods with the prospect of being fast enough are those based on coupled treatment of the acoustic waves and unsteady combustion. These exploit the amenity of the acoustic waves to analytical modelling, allowing costly simulations to be directed only at the more complex flame. They show real promise: my group recently demonstrated the first accurate coupled predictions for lab-scale combustors. The method does not yet extend to industrial combustors, the more complex flow-fields in these rendering current acoustic models overly-simplistic. I propose to comprehensively overhaul acoustic models across the entirety of the combustor, accounting for real and important acoustic-flow interactions. These new models will offer the breakthrough prospect of extending efficient, accurate predictive capability to industrial combustors, which has a real chance of facilitating future, instability free, very low NOx gas turbines.
Summary
Gas turbines are an essential ingredient in the long-term energy and aviation mix. They are flexible, offer fast start-up and the ability to burn renewable-generated fuels. However, they generate NOx emissions, which cause air pollution and damage human health, and reducing these is an air quality imperative. A major hurdle to this is that lean premixed combustion, essential for further NOx emission reductions, is highly susceptible to thermoacoustic instability. This is caused by a two-way coupling between unsteady combustion and acoustic waves, and the resulting large pressure oscillations can cause severe mechanical damage. Computational methods for predicting thermoacoustic instability, fast and accurate enough to be used as part of the industrial design process, are urgently needed.
The only computational methods with the prospect of being fast enough are those based on coupled treatment of the acoustic waves and unsteady combustion. These exploit the amenity of the acoustic waves to analytical modelling, allowing costly simulations to be directed only at the more complex flame. They show real promise: my group recently demonstrated the first accurate coupled predictions for lab-scale combustors. The method does not yet extend to industrial combustors, the more complex flow-fields in these rendering current acoustic models overly-simplistic. I propose to comprehensively overhaul acoustic models across the entirety of the combustor, accounting for real and important acoustic-flow interactions. These new models will offer the breakthrough prospect of extending efficient, accurate predictive capability to industrial combustors, which has a real chance of facilitating future, instability free, very low NOx gas turbines.
Max ERC Funding
1 985 288 €
Duration
Start date: 2018-06-01, End date: 2023-05-31
Project acronym Amitochondriates
Project Life without mitochondrion
Researcher (PI) Vladimir HAMPL
Host Institution (HI) UNIVERZITA KARLOVA
Country Czechia
Call Details Consolidator Grant (CoG), LS8, ERC-2017-COG
Summary Mitochondria are often referred to as the “power houses” of eukaryotic cells. All eukaryotes were thought to have mitochondria of some form until 2016, when the first eukaryote thriving without mitochondria was discovered by our laboratory – a flagellate Monocercomonoides. Understanding cellular functions of these cells, which represent a new functional type of eukaryotes, and understanding the circumstances of the unique event of mitochondrial loss are motivations for this proposal. The first objective focuses on the cell physiology. We will perform a metabolomic study revealing major metabolic pathways and concentrate further on elucidating its unique system of iron-sulphur cluster assembly. In the second objective, we will investigate in details the unique case of mitochondrial loss. We will examine two additional potentially amitochondriate lineages by means of genomics and transcriptomics, conduct experiments simulating the moments of mitochondrial loss and try to induce the mitochondrial loss in vitro by knocking out or down genes for mitochondrial biogenesis. We have chosen Giardia intestinalis and Entamoeba histolytica as models for the latter experiments, because their mitochondria are already reduced to minimalistic “mitosomes” and because some genetic tools are already available for them. Successful mitochondrial knock-outs would enable us to study mitochondrial loss in ‘real time’ and in vivo. In the third objective, we will focus on transforming Monocercomonoides into a tractable laboratory model by developing methods of axenic cultivation and genetic manipulation. This will open new possibilities in the studies of this organism and create a cell culture representing an amitochondriate model for cell biological studies enabling the dissection of mitochondrial effects from those of other compartments. The team is composed of the laboratory of PI and eight invited experts and we hope it has the ability to address these challenging questions.
Summary
Mitochondria are often referred to as the “power houses” of eukaryotic cells. All eukaryotes were thought to have mitochondria of some form until 2016, when the first eukaryote thriving without mitochondria was discovered by our laboratory – a flagellate Monocercomonoides. Understanding cellular functions of these cells, which represent a new functional type of eukaryotes, and understanding the circumstances of the unique event of mitochondrial loss are motivations for this proposal. The first objective focuses on the cell physiology. We will perform a metabolomic study revealing major metabolic pathways and concentrate further on elucidating its unique system of iron-sulphur cluster assembly. In the second objective, we will investigate in details the unique case of mitochondrial loss. We will examine two additional potentially amitochondriate lineages by means of genomics and transcriptomics, conduct experiments simulating the moments of mitochondrial loss and try to induce the mitochondrial loss in vitro by knocking out or down genes for mitochondrial biogenesis. We have chosen Giardia intestinalis and Entamoeba histolytica as models for the latter experiments, because their mitochondria are already reduced to minimalistic “mitosomes” and because some genetic tools are already available for them. Successful mitochondrial knock-outs would enable us to study mitochondrial loss in ‘real time’ and in vivo. In the third objective, we will focus on transforming Monocercomonoides into a tractable laboratory model by developing methods of axenic cultivation and genetic manipulation. This will open new possibilities in the studies of this organism and create a cell culture representing an amitochondriate model for cell biological studies enabling the dissection of mitochondrial effects from those of other compartments. The team is composed of the laboratory of PI and eight invited experts and we hope it has the ability to address these challenging questions.
Max ERC Funding
1 935 500 €
Duration
Start date: 2018-05-01, End date: 2023-04-30
Project acronym AMPERE
Project Accounting for Metallicity, Polarization of the Electrolyte, and Redox reactions in computational Electrochemistry
Researcher (PI) Mathieu Eric Salanne
Host Institution (HI) SORBONNE UNIVERSITE
Country France
Call Details Consolidator Grant (CoG), PE4, ERC-2017-COG
Summary Applied electrochemistry plays a key role in many technologies, such as batteries, fuel cells, supercapacitors or solar cells. It is therefore at the core of many research programs all over the world. Yet, fundamental electrochemical investigations remain scarce. In particular, electrochemistry is among the fields for which the gap between theory and experiment is the largest. From the computational point of view, there is no molecular dynamics (MD) software devoted to the simulation of electrochemical systems while other fields such as biochemistry (GROMACS) or material science (LAMMPS) have dedicated tools. This is due to the difficulty of accounting for complex effects arising from (i) the degree of metallicity of the electrode (i.e. from semimetals to perfect conductors), (ii) the mutual polarization occurring at the electrode/electrolyte interface and (iii) the redox reactivity through explicit electron transfers. Current understanding therefore relies on standard theories that derive from an inaccurate molecular-scale picture. My objective is to fill this gap by introducing a whole set of new methods for simulating electrochemical systems. They will be provided to the computational electrochemistry community as a cutting-edge MD software adapted to supercomputers. First applications will aim at the discovery of new electrolytes for energy storage. Here I will focus on (1) ‘‘water-in-salts’’ to understand why these revolutionary liquids enable much higher voltage than conventional solutions (2) redox reactions inside a nanoporous electrode to support the development of future capacitive energy storage devices. These selected applications are timely and rely on collaborations with leading experimental partners. The results are expected to shed an unprecedented light on the importance of polarization effects on the structure and the reactivity of electrode/electrolyte interfaces, establishing MD as a prominent tool for solving complex electrochemistry problems.
Summary
Applied electrochemistry plays a key role in many technologies, such as batteries, fuel cells, supercapacitors or solar cells. It is therefore at the core of many research programs all over the world. Yet, fundamental electrochemical investigations remain scarce. In particular, electrochemistry is among the fields for which the gap between theory and experiment is the largest. From the computational point of view, there is no molecular dynamics (MD) software devoted to the simulation of electrochemical systems while other fields such as biochemistry (GROMACS) or material science (LAMMPS) have dedicated tools. This is due to the difficulty of accounting for complex effects arising from (i) the degree of metallicity of the electrode (i.e. from semimetals to perfect conductors), (ii) the mutual polarization occurring at the electrode/electrolyte interface and (iii) the redox reactivity through explicit electron transfers. Current understanding therefore relies on standard theories that derive from an inaccurate molecular-scale picture. My objective is to fill this gap by introducing a whole set of new methods for simulating electrochemical systems. They will be provided to the computational electrochemistry community as a cutting-edge MD software adapted to supercomputers. First applications will aim at the discovery of new electrolytes for energy storage. Here I will focus on (1) ‘‘water-in-salts’’ to understand why these revolutionary liquids enable much higher voltage than conventional solutions (2) redox reactions inside a nanoporous electrode to support the development of future capacitive energy storage devices. These selected applications are timely and rely on collaborations with leading experimental partners. The results are expected to shed an unprecedented light on the importance of polarization effects on the structure and the reactivity of electrode/electrolyte interfaces, establishing MD as a prominent tool for solving complex electrochemistry problems.
Max ERC Funding
1 588 769 €
Duration
Start date: 2018-04-01, End date: 2023-03-31
Project acronym ANTILEAK
Project Development of antagonists of vascular leakage
Researcher (PI) Pipsa SAHARINEN
Host Institution (HI) HELSINGIN YLIOPISTO
Country Finland
Call Details Consolidator Grant (CoG), LS4, ERC-2017-COG
Summary Dysregulation of capillary permeability is a severe problem in critically ill patients, but the mechanisms involved are poorly understood. Further, there are no targeted therapies to stabilize leaky vessels in various common, potentially fatal diseases, such as systemic inflammation and sepsis, which affect millions of people annually. Although a multitude of signals that stimulate opening of endothelial cell-cell junctions leading to permeability have been characterized using cellular and in vivo models, approaches to reverse the harmful process of capillary leakage in disease conditions are yet to be identified. I propose to explore a novel autocrine endothelial permeability regulatory system as a potentially universal mechanism that antagonizes vascular stabilizing ques and sustains vascular leakage in inflammation. My group has identified inflammation-induced mechanisms that switch vascular stabilizing factors into molecules that destabilize vascular barriers, and identified tools to prevent the barrier disruption. Building on these discoveries, my group will use mouse genetics, structural biology and innovative, systematic antibody development coupled with gene editing and gene silencing technology, in order to elucidate mechanisms of vascular barrier breakdown and repair in systemic inflammation. The expected outcomes include insights into endothelial cell signaling and permeability regulation, and preclinical proof-of-concept antibodies to control endothelial activation and vascular leakage in systemic inflammation and sepsis models. Ultimately, the new knowledge and preclinical tools developed in this project may facilitate future development of targeted approaches against vascular leakage.
Summary
Dysregulation of capillary permeability is a severe problem in critically ill patients, but the mechanisms involved are poorly understood. Further, there are no targeted therapies to stabilize leaky vessels in various common, potentially fatal diseases, such as systemic inflammation and sepsis, which affect millions of people annually. Although a multitude of signals that stimulate opening of endothelial cell-cell junctions leading to permeability have been characterized using cellular and in vivo models, approaches to reverse the harmful process of capillary leakage in disease conditions are yet to be identified. I propose to explore a novel autocrine endothelial permeability regulatory system as a potentially universal mechanism that antagonizes vascular stabilizing ques and sustains vascular leakage in inflammation. My group has identified inflammation-induced mechanisms that switch vascular stabilizing factors into molecules that destabilize vascular barriers, and identified tools to prevent the barrier disruption. Building on these discoveries, my group will use mouse genetics, structural biology and innovative, systematic antibody development coupled with gene editing and gene silencing technology, in order to elucidate mechanisms of vascular barrier breakdown and repair in systemic inflammation. The expected outcomes include insights into endothelial cell signaling and permeability regulation, and preclinical proof-of-concept antibodies to control endothelial activation and vascular leakage in systemic inflammation and sepsis models. Ultimately, the new knowledge and preclinical tools developed in this project may facilitate future development of targeted approaches against vascular leakage.
Max ERC Funding
1 999 770 €
Duration
Start date: 2018-05-01, End date: 2023-04-30
Project acronym ANTSolve
Project A multi-scale perspective into collective problem solving in ants
Researcher (PI) Ofer Feinerman
Host Institution (HI) WEIZMANN INSTITUTE OF SCIENCE
Country Israel
Call Details Consolidator Grant (CoG), LS8, ERC-2017-COG
Summary Cognition improves an animal’s ability to tune its responses to environmental conditions. In group living animals, communication works to form a collective cognition that expands the group’s abilities beyond those of individuals. Despite much research, to date, there is little understanding of how collective cognition emerges within biological ensembles. A major obstacle towards such an understanding is the rarity of comprehensive multi-scale empirical data of these complex systems.
We have demonstrated cooperative load transport by ants to be an ideal system to study the emergence of cognition. Similar to other complex cognitive systems, the ants employ high levels of emergence to achieve efficient problem solving over a large range of scenarios. Unique to this system, is its extreme amenability to experimental measurement and manipulation where internal conflicts map to forces, abstract decision making is reflected in direction changes, and future planning manifested in pheromone trails. This allows for an unprecedentedly detailed, multi-scale empirical description of the moment-to-moment unfolding of sophisticated cognitive processes.
This proposal is aimed at materializing this potential to the full. We will examine the ants’ problem solving capabilities under a variety of environmental challenges. We will expose the underpinning rules on the different organizational scales, the flow of information between them, and their relative contributions to collective performance. This will allow for empirical comparisons between the ‘group’ and the ‘sum of its parts’ from which we will quantify the level of emergence in this system. Using the language of information, we will map the boundaries of this group’s collective cognition and relate them to the range of habitable environmental niches. Moreover, we will generalize these insights to formulate a new paradigm of emergence in biological groups opening new horizons in the study of cognitive processes in general.
Summary
Cognition improves an animal’s ability to tune its responses to environmental conditions. In group living animals, communication works to form a collective cognition that expands the group’s abilities beyond those of individuals. Despite much research, to date, there is little understanding of how collective cognition emerges within biological ensembles. A major obstacle towards such an understanding is the rarity of comprehensive multi-scale empirical data of these complex systems.
We have demonstrated cooperative load transport by ants to be an ideal system to study the emergence of cognition. Similar to other complex cognitive systems, the ants employ high levels of emergence to achieve efficient problem solving over a large range of scenarios. Unique to this system, is its extreme amenability to experimental measurement and manipulation where internal conflicts map to forces, abstract decision making is reflected in direction changes, and future planning manifested in pheromone trails. This allows for an unprecedentedly detailed, multi-scale empirical description of the moment-to-moment unfolding of sophisticated cognitive processes.
This proposal is aimed at materializing this potential to the full. We will examine the ants’ problem solving capabilities under a variety of environmental challenges. We will expose the underpinning rules on the different organizational scales, the flow of information between them, and their relative contributions to collective performance. This will allow for empirical comparisons between the ‘group’ and the ‘sum of its parts’ from which we will quantify the level of emergence in this system. Using the language of information, we will map the boundaries of this group’s collective cognition and relate them to the range of habitable environmental niches. Moreover, we will generalize these insights to formulate a new paradigm of emergence in biological groups opening new horizons in the study of cognitive processes in general.
Max ERC Funding
2 000 000 €
Duration
Start date: 2018-06-01, End date: 2023-05-31