Project acronym 3D Reloaded
Project 3D Reloaded: Novel Algorithms for 3D Shape Inference and Analysis
Researcher (PI) Daniel Cremers
Host Institution (HI) TECHNISCHE UNIVERSITAET MUENCHEN
Call Details Consolidator Grant (CoG), PE6, ERC-2014-CoG
Summary Despite their amazing success, we believe that computer vision algorithms have only scratched the surface of what can be done in terms of modeling and understanding our world from images. We believe that novel image analysis techniques will be a major enabler and driving force behind next-generation technologies, enhancing everyday life and opening up radically new possibilities. And we believe that the key to achieving this is to develop algorithms for reconstructing and analyzing the 3D structure of our world.
In this project, we will focus on three lines of research:
A) We will develop algorithms for 3D reconstruction from standard color cameras and from RGB-D cameras. In particular, we will promote real-time-capable direct and dense methods. In contrast to the classical two-stage approach of sparse feature-point based motion estimation and subsequent dense reconstruction, these methods optimally exploit all color information to jointly estimate dense geometry and camera motion.
B) We will develop algorithms for 3D shape analysis, including rigid and non-rigid matching, decomposition and interpretation of 3D shapes. We will focus on algorithms which are optimal or near-optimal. One of the major computational challenges lies in generalizing existing 2D shape analysis techniques to shapes in 3D and 4D (temporal evolutions of 3D shape).
C) We will develop shape priors for 3D reconstruction. These can be learned from sample shapes or acquired during the reconstruction process. For example, when reconstructing a larger office algorithms may exploit the geometric self-similarity of the scene, storing a model of a chair and its multiple instances only once rather than multiple times.
Advancing the state of the art in geometric reconstruction and geometric analysis will have a profound impact well beyond computer vision. We strongly believe that we have the necessary competence to pursue this project. Preliminary results have been well received by the community.
Summary
Despite their amazing success, we believe that computer vision algorithms have only scratched the surface of what can be done in terms of modeling and understanding our world from images. We believe that novel image analysis techniques will be a major enabler and driving force behind next-generation technologies, enhancing everyday life and opening up radically new possibilities. And we believe that the key to achieving this is to develop algorithms for reconstructing and analyzing the 3D structure of our world.
In this project, we will focus on three lines of research:
A) We will develop algorithms for 3D reconstruction from standard color cameras and from RGB-D cameras. In particular, we will promote real-time-capable direct and dense methods. In contrast to the classical two-stage approach of sparse feature-point based motion estimation and subsequent dense reconstruction, these methods optimally exploit all color information to jointly estimate dense geometry and camera motion.
B) We will develop algorithms for 3D shape analysis, including rigid and non-rigid matching, decomposition and interpretation of 3D shapes. We will focus on algorithms which are optimal or near-optimal. One of the major computational challenges lies in generalizing existing 2D shape analysis techniques to shapes in 3D and 4D (temporal evolutions of 3D shape).
C) We will develop shape priors for 3D reconstruction. These can be learned from sample shapes or acquired during the reconstruction process. For example, when reconstructing a larger office algorithms may exploit the geometric self-similarity of the scene, storing a model of a chair and its multiple instances only once rather than multiple times.
Advancing the state of the art in geometric reconstruction and geometric analysis will have a profound impact well beyond computer vision. We strongly believe that we have the necessary competence to pursue this project. Preliminary results have been well received by the community.
Max ERC Funding
2 000 000 €
Duration
Start date: 2015-09-01, End date: 2020-08-31
Project acronym 3MC
Project 3D Model Catalysts to explore new routes to sustainable fuels
Researcher (PI) Petra Elisabeth De jongh
Host Institution (HI) UNIVERSITEIT UTRECHT
Call Details Consolidator Grant (CoG), PE4, ERC-2014-CoG
Summary Currently fuels, plastics, and drugs are predominantly manufactured from oil. A transition towards renewable resources critically depends on new catalysts, for instance to convert small molecules (such as solar or biomass derived hydrogen, carbon monoxide, water and carbon dioxide) into more complex ones (such as oxygenates, containing oxygen atoms in their structure). Catalyst development now often depends on trial and error rather than rational design, as the heterogeneity of these composite systems hampers detailed understanding of the role of each of the components.
I propose 3D model catalysts as a novel enabling tool to overcome this problem. Their well-defined nature allows unprecedented precision in the variation of structural parameters (morphology, spatial distribution) of the individual components, while at the same time they mimic real catalysts closely enough to allow testing under industrially relevant conditions. Using this approach I will address fundamental questions, such as:
* What are the mechanisms (structural, electronic, chemical) by which non-metal promoters influence the functionality of copper-based catalysts?
* Which nanoalloys can be formed, how does their composition influence the surface active sites and catalytic functionality under reaction conditions?
* Which size and interface effects occur, and how can we use them to tune the actitivity and selectivity towards desired products?
Our 3D model catalysts will be assembled from ordered mesoporous silica and carbon support materials and Cu-based promoted and bimetallic nanoparticles. The combination with high resolution characterization and testing under realistic conditions allows detailed insight into the role of the different components; critical for the rational design of novel catalysts for a future more sustainable production of chemicals and fuels from renewable resources.
Summary
Currently fuels, plastics, and drugs are predominantly manufactured from oil. A transition towards renewable resources critically depends on new catalysts, for instance to convert small molecules (such as solar or biomass derived hydrogen, carbon monoxide, water and carbon dioxide) into more complex ones (such as oxygenates, containing oxygen atoms in their structure). Catalyst development now often depends on trial and error rather than rational design, as the heterogeneity of these composite systems hampers detailed understanding of the role of each of the components.
I propose 3D model catalysts as a novel enabling tool to overcome this problem. Their well-defined nature allows unprecedented precision in the variation of structural parameters (morphology, spatial distribution) of the individual components, while at the same time they mimic real catalysts closely enough to allow testing under industrially relevant conditions. Using this approach I will address fundamental questions, such as:
* What are the mechanisms (structural, electronic, chemical) by which non-metal promoters influence the functionality of copper-based catalysts?
* Which nanoalloys can be formed, how does their composition influence the surface active sites and catalytic functionality under reaction conditions?
* Which size and interface effects occur, and how can we use them to tune the actitivity and selectivity towards desired products?
Our 3D model catalysts will be assembled from ordered mesoporous silica and carbon support materials and Cu-based promoted and bimetallic nanoparticles. The combination with high resolution characterization and testing under realistic conditions allows detailed insight into the role of the different components; critical for the rational design of novel catalysts for a future more sustainable production of chemicals and fuels from renewable resources.
Max ERC Funding
1 999 625 €
Duration
Start date: 2015-09-01, End date: 2020-08-31
Project acronym AEDMOS
Project Attosecond Electron Dynamics in MOlecular Systems
Researcher (PI) Reinhard Kienberger
Host Institution (HI) TECHNISCHE UNIVERSITAET MUENCHEN
Call Details Consolidator Grant (CoG), PE2, ERC-2014-CoG
Summary Advanced insight into ever smaller structures of matter and their ever faster dynamics hold promise for pushing the frontiers of many fields in science and technology. Time-domain investigations of ultrafast microscopic processes are most successfully carried out by pump/probe experiments. Intense waveform-controlled few-cycle near-infrared laser pulses combined with isolated sub-femtosecond XUV (extreme UV) pulses have made possible direct access to electron motion on the atomic scale. These tools along with the techniques of laser-field-controlled XUV photoemission (“attosecond streaking”) and ultrafast UV-pump/XUV-probe spectroscopy have permitted real-time observation of electronic motion in experiments performed on atoms in the gas phase and of electronic transport processes in solids.
The purpose of this project is to to get insight into intra- and inter-molecular electron dynamics by extending attosecond spectroscopy to these processes. AEDMOS will allow control and real-time observation of a wide range of hyperfast fundamental processes directly on their natural, i.e. attosecond (1 as = EXP-18 s) time scale in molecules and molecular structures. In previous work we have successfully developed attosecond tools and techniques. By combining them with our experience in UHV technology and target preparation in a new beamline to be created in the framework of this project, we aim at investigating charge migration and transport in supramolecular assemblies, ultrafast electron dynamics in photocatalysis and dynamics of electron correlation in high-TC superconductors. These dynamics – of electronic excitation, exciton formation, relaxation, electron correlation and wave packet motion – are of broad scientific interest reaching from biomedicine to chemistry and physics and are pertinent to the development of many modern technologies including molecular electronics, optoelectronics, photovoltaics, light-to-chemical energy conversion and lossless energy transfer.
Summary
Advanced insight into ever smaller structures of matter and their ever faster dynamics hold promise for pushing the frontiers of many fields in science and technology. Time-domain investigations of ultrafast microscopic processes are most successfully carried out by pump/probe experiments. Intense waveform-controlled few-cycle near-infrared laser pulses combined with isolated sub-femtosecond XUV (extreme UV) pulses have made possible direct access to electron motion on the atomic scale. These tools along with the techniques of laser-field-controlled XUV photoemission (“attosecond streaking”) and ultrafast UV-pump/XUV-probe spectroscopy have permitted real-time observation of electronic motion in experiments performed on atoms in the gas phase and of electronic transport processes in solids.
The purpose of this project is to to get insight into intra- and inter-molecular electron dynamics by extending attosecond spectroscopy to these processes. AEDMOS will allow control and real-time observation of a wide range of hyperfast fundamental processes directly on their natural, i.e. attosecond (1 as = EXP-18 s) time scale in molecules and molecular structures. In previous work we have successfully developed attosecond tools and techniques. By combining them with our experience in UHV technology and target preparation in a new beamline to be created in the framework of this project, we aim at investigating charge migration and transport in supramolecular assemblies, ultrafast electron dynamics in photocatalysis and dynamics of electron correlation in high-TC superconductors. These dynamics – of electronic excitation, exciton formation, relaxation, electron correlation and wave packet motion – are of broad scientific interest reaching from biomedicine to chemistry and physics and are pertinent to the development of many modern technologies including molecular electronics, optoelectronics, photovoltaics, light-to-chemical energy conversion and lossless energy transfer.
Max ERC Funding
1 999 375 €
Duration
Start date: 2015-05-01, End date: 2020-04-30
Project acronym ALDof 2DTMDs
Project Atomic layer deposition of two-dimensional transition metal dichalcogenide nanolayers
Researcher (PI) Ageeth Bol
Host Institution (HI) TECHNISCHE UNIVERSITEIT EINDHOVEN
Call Details Consolidator Grant (CoG), PE5, ERC-2014-CoG
Summary Two-dimensional transition metal dichalcogenides (2D-TMDs) are an exciting class of new materials. Their ultrathin body, optical band gap and unusual spin and valley polarization physics make them very promising candidates for a vast new range of (opto-)electronic applications. So far, most experimental work on 2D-TMDs has been performed on exfoliated flakes made by the ‘Scotch tape’ technique. The major next challenge is the large-area synthesis of 2D-TMDs by a technique that ultimately can be used for commercial device fabrication.
Building upon pure 2D-TMDs, even more functionalities can be gained from 2D-TMD alloys and heterostructures. Theoretical work on these derivates reveals exciting new phenomena, but experimentally this field is largely unexplored due to synthesis technique limitations.
The goal of this proposal is to combine atomic layer deposition with plasma chemistry to create a novel surface-controlled, industry-compatible synthesis technique that will make large area 2D-TMDs, 2D-TMD alloys and 2D-TMD heterostructures a reality. This innovative approach will enable systematic layer dependent studies, likely revealing exciting new properties, and provide integration pathways for a multitude of applications.
Atomistic simulations will guide the process development and, together with in- and ex-situ analysis, increase the understanding of the surface chemistry involved. State-of-the-art high resolution transmission electron microscopy will be used to study the alloying process and the formation of heterostructures. Luminescence spectroscopy and electrical characterization will reveal the potential of the synthesized materials for (opto)-electronic applications.
The synergy between the excellent background of the PI in 2D materials for nanoelectronics and the group’s leading expertise in ALD and plasma science is unique and provides an ideal stepping stone to develop the synthesis of large-area 2D-TMDs and derivatives.
Summary
Two-dimensional transition metal dichalcogenides (2D-TMDs) are an exciting class of new materials. Their ultrathin body, optical band gap and unusual spin and valley polarization physics make them very promising candidates for a vast new range of (opto-)electronic applications. So far, most experimental work on 2D-TMDs has been performed on exfoliated flakes made by the ‘Scotch tape’ technique. The major next challenge is the large-area synthesis of 2D-TMDs by a technique that ultimately can be used for commercial device fabrication.
Building upon pure 2D-TMDs, even more functionalities can be gained from 2D-TMD alloys and heterostructures. Theoretical work on these derivates reveals exciting new phenomena, but experimentally this field is largely unexplored due to synthesis technique limitations.
The goal of this proposal is to combine atomic layer deposition with plasma chemistry to create a novel surface-controlled, industry-compatible synthesis technique that will make large area 2D-TMDs, 2D-TMD alloys and 2D-TMD heterostructures a reality. This innovative approach will enable systematic layer dependent studies, likely revealing exciting new properties, and provide integration pathways for a multitude of applications.
Atomistic simulations will guide the process development and, together with in- and ex-situ analysis, increase the understanding of the surface chemistry involved. State-of-the-art high resolution transmission electron microscopy will be used to study the alloying process and the formation of heterostructures. Luminescence spectroscopy and electrical characterization will reveal the potential of the synthesized materials for (opto)-electronic applications.
The synergy between the excellent background of the PI in 2D materials for nanoelectronics and the group’s leading expertise in ALD and plasma science is unique and provides an ideal stepping stone to develop the synthesis of large-area 2D-TMDs and derivatives.
Max ERC Funding
1 968 709 €
Duration
Start date: 2015-08-01, End date: 2020-07-31
Project acronym ALLEGRO
Project unrAvelLing sLow modE travelinG and tRaffic: with innOvative data to a new transportation and traffic theory for pedestrians and bicycles
Researcher (PI) Serge Hoogendoorn
Host Institution (HI) TECHNISCHE UNIVERSITEIT DELFT
Call Details Advanced Grant (AdG), SH3, ERC-2014-ADG
Summary A major challenge in contemporary traffic and transportation theory is having a comprehensive understanding of pedestrians and cyclists behaviour. This is notoriously hard to observe, since sensors providing abundant and detailed information about key variables characterising this behaviour have not been available until very recently. The behaviour is also far more complex than that of the much better understood fast mode. This is due to the many degrees of freedom in decision-making, the interactions among slow traffic participants that are more involved and far less guided by traffic rules and regulations than those between car-drivers, and the many fascinating but complex phenomena in slow traffic flows (self-organised patterns, turbulence, spontaneous phase transitions, herding, etc.) that are very hard to predict accurately.
With slow traffic modes gaining ground in terms of mode share in many cities, lack of empirical insights, behavioural theories, predictively valid analytical and simulation models, and tools to support planning, design, management and control is posing a major societal problem as well: examples of major accidents due to bad planning, organisation and management of events are manifold, as are locations where safety of slow modes is a serious issue due to interactions with fast modes.
This programme is geared towards establishing a comprehensive theory of slow mode traffic behaviour, considering the different behavioural levels relevant for understanding, reproducing and predicting slow mode traffic flows in cities. The levels deal with walking and cycling operations, activity scheduling and travel behaviour, and knowledge representation and learning. Major scientific breakthroughs are expected at each of these levels, in terms of theory and modelling, by using innovative (big) data collection and experimentation, analysis and fusion techniques, including social media data analytics, using augmented reality, and remote and crowd sensing.
Summary
A major challenge in contemporary traffic and transportation theory is having a comprehensive understanding of pedestrians and cyclists behaviour. This is notoriously hard to observe, since sensors providing abundant and detailed information about key variables characterising this behaviour have not been available until very recently. The behaviour is also far more complex than that of the much better understood fast mode. This is due to the many degrees of freedom in decision-making, the interactions among slow traffic participants that are more involved and far less guided by traffic rules and regulations than those between car-drivers, and the many fascinating but complex phenomena in slow traffic flows (self-organised patterns, turbulence, spontaneous phase transitions, herding, etc.) that are very hard to predict accurately.
With slow traffic modes gaining ground in terms of mode share in many cities, lack of empirical insights, behavioural theories, predictively valid analytical and simulation models, and tools to support planning, design, management and control is posing a major societal problem as well: examples of major accidents due to bad planning, organisation and management of events are manifold, as are locations where safety of slow modes is a serious issue due to interactions with fast modes.
This programme is geared towards establishing a comprehensive theory of slow mode traffic behaviour, considering the different behavioural levels relevant for understanding, reproducing and predicting slow mode traffic flows in cities. The levels deal with walking and cycling operations, activity scheduling and travel behaviour, and knowledge representation and learning. Major scientific breakthroughs are expected at each of these levels, in terms of theory and modelling, by using innovative (big) data collection and experimentation, analysis and fusion techniques, including social media data analytics, using augmented reality, and remote and crowd sensing.
Max ERC Funding
2 458 700 €
Duration
Start date: 2015-11-01, End date: 2020-10-31
Project acronym AMPLify
Project Allocation Made PracticaL
Researcher (PI) Toby Walsh
Host Institution (HI) TECHNISCHE UNIVERSITAT BERLIN
Call Details Advanced Grant (AdG), PE6, ERC-2014-ADG
Summary Allocation Made PracticaL
The AMPLify project will lay the foundations of a new field, computational behavioural game theory that brings a computational perspective, computational implementation, and behavioural insights to game theory. These foundations will be laid by tackling a pressing problem facing society today: the efficient and fair allocation of resources and costs. Research in allocation has previously considered simple, abstract models like cake cutting. We propose to develop richer models that capture important new features like asynchronicity which occur in many markets being developed in our highly connected and online world. The mechanisms currently used to allocate resources and costs are limited to these simple, abstract models and also do not take into account how people actually behave in practice. We will therefore design new mechanisms for these richer allocation problems that exploit insights gained from behavioural game theory like loss aversion. We will also tackle the complexity of these rich models and mechanisms with computational tools. Finally, we will use computation to increase both the efficiency and fairness of allocations. As a result, we will be able to do more with fewer resources and greater fairness. Our initial case studies in resource and cost allocation demonstrate that we can improve efficiency greatly, offering one company alone savings of up to 10% (which is worth tens of millions of dollars every year). We predict even greater impact with the more sophisticated mechanisms to be developed during the course of this project.
Summary
Allocation Made PracticaL
The AMPLify project will lay the foundations of a new field, computational behavioural game theory that brings a computational perspective, computational implementation, and behavioural insights to game theory. These foundations will be laid by tackling a pressing problem facing society today: the efficient and fair allocation of resources and costs. Research in allocation has previously considered simple, abstract models like cake cutting. We propose to develop richer models that capture important new features like asynchronicity which occur in many markets being developed in our highly connected and online world. The mechanisms currently used to allocate resources and costs are limited to these simple, abstract models and also do not take into account how people actually behave in practice. We will therefore design new mechanisms for these richer allocation problems that exploit insights gained from behavioural game theory like loss aversion. We will also tackle the complexity of these rich models and mechanisms with computational tools. Finally, we will use computation to increase both the efficiency and fairness of allocations. As a result, we will be able to do more with fewer resources and greater fairness. Our initial case studies in resource and cost allocation demonstrate that we can improve efficiency greatly, offering one company alone savings of up to 10% (which is worth tens of millions of dollars every year). We predict even greater impact with the more sophisticated mechanisms to be developed during the course of this project.
Max ERC Funding
2 499 681 €
Duration
Start date: 2016-06-01, End date: 2021-05-31
Project acronym ANISOGEL
Project Injectable anisotropic microgel-in-hydrogel matrices for spinal cord repair
Researcher (PI) Laura De Laporte
Host Institution (HI) DWI LEIBNIZ-INSTITUT FUR INTERAKTIVE MATERIALIEN EV
Call Details Starting Grant (StG), PE8, ERC-2014-STG
Summary This project will engineer an injectable biomaterial that forms an anisotropic microheterogeneous structure in vivo. Injectable hydrogels enable a minimal invasive in situ generation of matrices for the regeneration of tissues and organs, but currently lack structural organization and unidirectional orientation. The anisotropic, injectable hydrogels to be developed will mimic local extracellular matrix architectures that cells encounter in complex tissues (e.g. nerves, muscles). This project aims for the development of a biomimetic scaffold for spinal cord regeneration.
To realize such a major breakthrough, my group will focus on three research objectives. i) Poly(ethylene glycol) microgel-in-hydrogel matrices will be fabricated with the ability to create macroscopic order due to microgel shape anisotropy and magnetic alignment. Barrel-like microgels will be prepared using an in-mold polymerization technique. Their ability to self-assemble will be investigated in function of their dimensions, aspect ratio, crosslinking density, and volume fraction. Superparamagnetic nanoparticles will be included into the microgels to enable unidirectional orientation by means of a magnetic field. Subsequently, the oriented microgels will be interlocked within a master hydrogel. ii) The microgel-in-hydrogel matrices will be equipped with (bio)functional properties for spinal cord regeneration, i.e., to control and optimize mechanical anisotropy and biological signaling by in vitro cell growth experiments. iii) Selected hydrogel composites will be injected after rat spinal cord injury and directional tissue growth and animal functional behavior will be analyzed.
Succesful fabrication of the proposed microgel-in-hydrogel matrix will provide a new type of biomaterial, which enables investigating the effect of an anisotropic structure on physiological and pathological processes in vivo. This is a decisive step towards creating a clinical healing matrix for anisotropic tissue repair.
Summary
This project will engineer an injectable biomaterial that forms an anisotropic microheterogeneous structure in vivo. Injectable hydrogels enable a minimal invasive in situ generation of matrices for the regeneration of tissues and organs, but currently lack structural organization and unidirectional orientation. The anisotropic, injectable hydrogels to be developed will mimic local extracellular matrix architectures that cells encounter in complex tissues (e.g. nerves, muscles). This project aims for the development of a biomimetic scaffold for spinal cord regeneration.
To realize such a major breakthrough, my group will focus on three research objectives. i) Poly(ethylene glycol) microgel-in-hydrogel matrices will be fabricated with the ability to create macroscopic order due to microgel shape anisotropy and magnetic alignment. Barrel-like microgels will be prepared using an in-mold polymerization technique. Their ability to self-assemble will be investigated in function of their dimensions, aspect ratio, crosslinking density, and volume fraction. Superparamagnetic nanoparticles will be included into the microgels to enable unidirectional orientation by means of a magnetic field. Subsequently, the oriented microgels will be interlocked within a master hydrogel. ii) The microgel-in-hydrogel matrices will be equipped with (bio)functional properties for spinal cord regeneration, i.e., to control and optimize mechanical anisotropy and biological signaling by in vitro cell growth experiments. iii) Selected hydrogel composites will be injected after rat spinal cord injury and directional tissue growth and animal functional behavior will be analyzed.
Succesful fabrication of the proposed microgel-in-hydrogel matrix will provide a new type of biomaterial, which enables investigating the effect of an anisotropic structure on physiological and pathological processes in vivo. This is a decisive step towards creating a clinical healing matrix for anisotropic tissue repair.
Max ERC Funding
1 435 396 €
Duration
Start date: 2015-03-01, End date: 2020-02-29
Project acronym ASICA
Project New constraints on the Amazonian carbon balance from airborne observations of the stable isotopes of CO2
Researcher (PI) Wouter Peters
Host Institution (HI) WAGENINGEN UNIVERSITY
Call Details Consolidator Grant (CoG), PE10, ERC-2014-CoG
Summary Severe droughts in Amazonia in 2005 and 2010 caused widespread loss of carbon from the terrestrial biosphere. This loss, almost twice the annual fossil fuel CO2 emissions in the EU, suggests a large sensitivity of the Amazonian carbon balance to a predicted more intense drought regime in the next decades. This is a dangerous inference though, as there is no scientific consensus on the most basic metrics of Amazonian carbon exchange: the gross primary production (GPP) and its response to moisture deficits in the soil and atmosphere. Measuring them on scales that span the whole Amazon forest was thus far impossible, but in this project I aim to deliver the first observation-based estimate of pan-Amazonian GPP and its drought induced variations.
My program builds on two recent breakthroughs in our use of stable isotopes (13C, 17O, 18O) in atmospheric CO2: (1) Our discovery that observed δ¹³C in CO2 in the atmosphere is a quantitative measure for vegetation water-use efficiency over millions of square kilometers, integrating the drought response of individual plants. (2) The possibility to precisely measure the relative ratios of 18O/16O and 17O/16O in CO2, called Δ17O. Anomalous Δ17O values are present in air coming down from the stratosphere, but this anomaly is removed upon contact of CO2 with leaf water inside plant stomata. Hence, observed Δ17O values depend directly on the magnitude of GPP. Both δ¹³C and Δ17O measurements are scarce over the Amazon-basin, and I propose more than 7000 new measurements leveraging an established aircraft monitoring program in Brazil. Quantitative interpretation of these observations will break new ground in our use of stable isotopes to understand climate variations, and is facilitated by our renowned numerical modeling system “CarbonTracker”. My program will answer two burning question in carbon cycle science today: (a) What is the magnitude of GPP in Amazonia? And (b) How does it vary over different intensities of drought?
Summary
Severe droughts in Amazonia in 2005 and 2010 caused widespread loss of carbon from the terrestrial biosphere. This loss, almost twice the annual fossil fuel CO2 emissions in the EU, suggests a large sensitivity of the Amazonian carbon balance to a predicted more intense drought regime in the next decades. This is a dangerous inference though, as there is no scientific consensus on the most basic metrics of Amazonian carbon exchange: the gross primary production (GPP) and its response to moisture deficits in the soil and atmosphere. Measuring them on scales that span the whole Amazon forest was thus far impossible, but in this project I aim to deliver the first observation-based estimate of pan-Amazonian GPP and its drought induced variations.
My program builds on two recent breakthroughs in our use of stable isotopes (13C, 17O, 18O) in atmospheric CO2: (1) Our discovery that observed δ¹³C in CO2 in the atmosphere is a quantitative measure for vegetation water-use efficiency over millions of square kilometers, integrating the drought response of individual plants. (2) The possibility to precisely measure the relative ratios of 18O/16O and 17O/16O in CO2, called Δ17O. Anomalous Δ17O values are present in air coming down from the stratosphere, but this anomaly is removed upon contact of CO2 with leaf water inside plant stomata. Hence, observed Δ17O values depend directly on the magnitude of GPP. Both δ¹³C and Δ17O measurements are scarce over the Amazon-basin, and I propose more than 7000 new measurements leveraging an established aircraft monitoring program in Brazil. Quantitative interpretation of these observations will break new ground in our use of stable isotopes to understand climate variations, and is facilitated by our renowned numerical modeling system “CarbonTracker”. My program will answer two burning question in carbon cycle science today: (a) What is the magnitude of GPP in Amazonia? And (b) How does it vary over different intensities of drought?
Max ERC Funding
2 269 689 €
Duration
Start date: 2015-09-01, End date: 2020-08-31
Project acronym ASTROROT
Project Unraveling interstellar chemistry with broadband microwave spectroscopy and next-generation telescope arrays
Researcher (PI) Melanie Schnell-Küpper
Host Institution (HI) STIFTUNG DEUTSCHES ELEKTRONEN-SYNCHROTRON DESY
Call Details Starting Grant (StG), PE4, ERC-2014-STG
Summary The goal of the research program, ASTROROT, is to significantly advance the knowledge of astrochemistry by exploring its molecular complexity and by discovering new molecule classes and key chemical processes in space. So far, mostly physical reasons were investigated for the observed variations in molecular abundances. We here propose to study the influence of chemistry on the molecular composition of the universe by combining unprecedentedly high-quality laboratory spectroscopy and pioneering telescope observations. Array telescopes provide new observations of rotational molecular emission, leading to an urgent need for microwave spectroscopic data of exotic molecules. We will use newly developed, unique broadband microwave spectrometers with the cold conditions of a molecular jet and the higher temperatures of a waveguide to mimic different interstellar conditions. Their key advantages are accurate transition intensities, tremendously reduced measurement times, and unique mixture compatibility.
Our laboratory experiments will motivate and guide astronomic observations, and enable their interpretation. The expected results are
• the exploration of molecular complexity by discovering new classes of molecules in space,
• the detection of isotopologues that provide information about the stage of chemical evolution,
• the generation of abundance maps of highly excited molecules to learn about their environment,
• the identification of key intermediates in astrochemical reactions.
The results will significantly foster and likely revolutionize our understanding of astrochemistry. The proposed research will go far beyond the state-of-the-art: We will use cutting-edge techniques both in the laboratory and at the telescope to greatly improve and speed the process of identifying molecular fingerprints. These techniques now enable studies at this important frontier of physics and chemistry that previously would have been prohibitively time-consuming or even impossible.
Summary
The goal of the research program, ASTROROT, is to significantly advance the knowledge of astrochemistry by exploring its molecular complexity and by discovering new molecule classes and key chemical processes in space. So far, mostly physical reasons were investigated for the observed variations in molecular abundances. We here propose to study the influence of chemistry on the molecular composition of the universe by combining unprecedentedly high-quality laboratory spectroscopy and pioneering telescope observations. Array telescopes provide new observations of rotational molecular emission, leading to an urgent need for microwave spectroscopic data of exotic molecules. We will use newly developed, unique broadband microwave spectrometers with the cold conditions of a molecular jet and the higher temperatures of a waveguide to mimic different interstellar conditions. Their key advantages are accurate transition intensities, tremendously reduced measurement times, and unique mixture compatibility.
Our laboratory experiments will motivate and guide astronomic observations, and enable their interpretation. The expected results are
• the exploration of molecular complexity by discovering new classes of molecules in space,
• the detection of isotopologues that provide information about the stage of chemical evolution,
• the generation of abundance maps of highly excited molecules to learn about their environment,
• the identification of key intermediates in astrochemical reactions.
The results will significantly foster and likely revolutionize our understanding of astrochemistry. The proposed research will go far beyond the state-of-the-art: We will use cutting-edge techniques both in the laboratory and at the telescope to greatly improve and speed the process of identifying molecular fingerprints. These techniques now enable studies at this important frontier of physics and chemistry that previously would have been prohibitively time-consuming or even impossible.
Max ERC Funding
1 499 904 €
Duration
Start date: 2015-05-01, End date: 2020-04-30
Project acronym AVS-ISS
Project Analysis, Verification, and Synthesis for Infinite-State Systems
Researcher (PI) Joel Olivier Ouaknine
Host Institution (HI) MAX-PLANCK-GESELLSCHAFT ZUR FORDERUNG DER WISSENSCHAFTEN EV
Call Details Consolidator Grant (CoG), PE6, ERC-2014-CoG
Summary The central objective of this project is to investigate key algorithmic verification questions concerning two fundamental mathematical structures used to model and analyse infinite-state systems, namely discrete linear dynamical systems and counter automata, in both ordinary and parametric form. Motivated especially by applications to software model checking (more specifically the termination of linear loops and predicate abstraction computations), as well as parametric real-time reasoning and the verification of Markov chains, we will focus on model-checking, module-checking, and synthesis problems for linear dynamical systems and one-counter automata against various fragments and extensions of Linear Temporal Logic (LTL) specifications. The key deliverables will be novel verification algorithms along with a map of the complexity landscape. A second objective is then to transfer algorithmic insights into practical verification methodologies and tools, in collaboration with colleagues in academia and industrial research laboratories.
We will build on a series of recent advances and breakthroughs in these areas (some of which from the PI’s team) to attack a range of specific algorithmic problems. We believe that this line of research will not only result in fundamental theoretical contributions and insights in their own right—potentially answering mathematical questions that have been open for years or even decades—but will also impact the practice of formal verification and lead to new and more powerful methods and tools for the use of engineers and programmers.
Summary
The central objective of this project is to investigate key algorithmic verification questions concerning two fundamental mathematical structures used to model and analyse infinite-state systems, namely discrete linear dynamical systems and counter automata, in both ordinary and parametric form. Motivated especially by applications to software model checking (more specifically the termination of linear loops and predicate abstraction computations), as well as parametric real-time reasoning and the verification of Markov chains, we will focus on model-checking, module-checking, and synthesis problems for linear dynamical systems and one-counter automata against various fragments and extensions of Linear Temporal Logic (LTL) specifications. The key deliverables will be novel verification algorithms along with a map of the complexity landscape. A second objective is then to transfer algorithmic insights into practical verification methodologies and tools, in collaboration with colleagues in academia and industrial research laboratories.
We will build on a series of recent advances and breakthroughs in these areas (some of which from the PI’s team) to attack a range of specific algorithmic problems. We believe that this line of research will not only result in fundamental theoretical contributions and insights in their own right—potentially answering mathematical questions that have been open for years or even decades—but will also impact the practice of formal verification and lead to new and more powerful methods and tools for the use of engineers and programmers.
Max ERC Funding
1 834 975 €
Duration
Start date: 2015-08-01, End date: 2020-07-31
