Project acronym BeStMo
Project Beyond Static Molecules: Modeling Quantum Fluctuations in Complex Molecular Environments
Researcher (PI) Alexandre TKATCHENKO
Host Institution (HI) UNIVERSITE DU LUXEMBOURG
Country Luxembourg
Call Details Consolidator Grant (CoG), PE4, ERC-2016-COG
Summary We propose focused theory developments and applications, which aim to substantially advance our ability to model and understand the behavior of molecules in complex environments. From a large repertoire of possible environments, we have chosen to concentrate on experimentally-relevant situations, including molecular fluctuations in electric and optical fields, disordered molecular crystals, solvated (bio)molecules, and molecular interactions at/through low-dimensional nanostructures. A challenging aspect of modeling such realistic environments is that both molecular electronic and nuclear fluctuations have to be treated efficiently at a robust quantum-mechanical level of theory for systems with 1000s of atoms. In contrast, the current state of the art in the modeling of complex molecular systems typically consists of Newtonian molecular dynamics employing classical force fields. We will develop radically new approaches for electronic and nuclear fluctuations that unify concepts and merge techniques from quantum-mechanical many-body Hamiltonians, statistical mechanics, density-functional theory, and machine learning. Our developments will be benchmarked using experimental measurements with terahertz (THz) spectroscopy, atomic-force and scanning tunneling microscopy (AFM/STM), time-of-flight (TOF) measurements, and molecular interferometry.
Our final goal is to bridge the accuracy of quantum mechanics with the efficiency of force fields, enabling large-scale predictive quantum molecular dynamics simulations for complex systems containing 1000s of atoms, and leading to novel conceptual insights into quantum-mechanical fluctuations in large molecular systems. The project goes well beyond the presently possible applications and once successful will pave the road towards having a suite of first-principles-based modeling tools for a wide range of realistic materials, such as biomolecules, nanostructures, disordered solids, and organic/inorganic interfaces.
Summary
We propose focused theory developments and applications, which aim to substantially advance our ability to model and understand the behavior of molecules in complex environments. From a large repertoire of possible environments, we have chosen to concentrate on experimentally-relevant situations, including molecular fluctuations in electric and optical fields, disordered molecular crystals, solvated (bio)molecules, and molecular interactions at/through low-dimensional nanostructures. A challenging aspect of modeling such realistic environments is that both molecular electronic and nuclear fluctuations have to be treated efficiently at a robust quantum-mechanical level of theory for systems with 1000s of atoms. In contrast, the current state of the art in the modeling of complex molecular systems typically consists of Newtonian molecular dynamics employing classical force fields. We will develop radically new approaches for electronic and nuclear fluctuations that unify concepts and merge techniques from quantum-mechanical many-body Hamiltonians, statistical mechanics, density-functional theory, and machine learning. Our developments will be benchmarked using experimental measurements with terahertz (THz) spectroscopy, atomic-force and scanning tunneling microscopy (AFM/STM), time-of-flight (TOF) measurements, and molecular interferometry.
Our final goal is to bridge the accuracy of quantum mechanics with the efficiency of force fields, enabling large-scale predictive quantum molecular dynamics simulations for complex systems containing 1000s of atoms, and leading to novel conceptual insights into quantum-mechanical fluctuations in large molecular systems. The project goes well beyond the presently possible applications and once successful will pave the road towards having a suite of first-principles-based modeling tools for a wide range of realistic materials, such as biomolecules, nanostructures, disordered solids, and organic/inorganic interfaces.
Max ERC Funding
1 811 650 €
Duration
Start date: 2017-03-01, End date: 2022-08-31
Project acronym CLEANH2
Project Chemical Engineering of Fused MetalloPorphyrins Thin Films for the Clean Production of Hydrogen
Researcher (PI) Nicolas BOSCHER
Host Institution (HI) LUXEMBOURG INSTITUTE OF SCIENCE AND TECHNOLOGY
Country Luxembourg
Call Details Consolidator Grant (CoG), PE8, ERC-2019-COG
Summary This project stands in the general context of the current worldwide energy and environmental crisis. It aims to engineer a new generation of conjugated microporous polymers based on fused metalloporphyrins for the low-cost, clean and efficient production of hydrogen from solar water splitting. The CLEANH2 concept relies on the gas phase reaction of metalloporphyrins to engineer new heterogeneous catalysts with remarkable hydrogen production yields. Metalloporphyrins, selected by Nature to fulfil the main catalytic phenomena allowing life, are attractive molecules for water splitting owing to their highly conjugated structure and central metal ion, which can readily interconvert between different oxidation states to accomplish oxidation and reduction reactions. For efficiency and sustainability considerations, it is highly desirable to employ metalloporphyrins in conductive assemblies for heterogeneous catalysis. Nevertheless, due to the lack of synthetic approach, the design and application of conjugated porphyrin assemblies is a largely unexplored topic in view of the plethora of available porphyrin patterns.
The central idea of CLEANH2 builds upon our recent advance in the gas phase synthesis and deposition of directly fused metalloporphyrins coatings. Progress in our approach is expected to open the way for the construction of powerful catalytic and photocatalytic materials. To achieve this, the key challenging goals of this project are: 1) the engineering of the microstructure and electronic structure of directly fused metalloporphyrins thin films; 2) the use of the full potential of directly fused metalloporphyrins thin films for the unmet, clean and high quantum yield overall water splitting for hydrogen production. The outcomes of CLEANH2 will be foundational for the engineering of directly fused metalloporphyrins systems and their implementation in advanced technological applications related to catalysis and solar energy.
Summary
This project stands in the general context of the current worldwide energy and environmental crisis. It aims to engineer a new generation of conjugated microporous polymers based on fused metalloporphyrins for the low-cost, clean and efficient production of hydrogen from solar water splitting. The CLEANH2 concept relies on the gas phase reaction of metalloporphyrins to engineer new heterogeneous catalysts with remarkable hydrogen production yields. Metalloporphyrins, selected by Nature to fulfil the main catalytic phenomena allowing life, are attractive molecules for water splitting owing to their highly conjugated structure and central metal ion, which can readily interconvert between different oxidation states to accomplish oxidation and reduction reactions. For efficiency and sustainability considerations, it is highly desirable to employ metalloporphyrins in conductive assemblies for heterogeneous catalysis. Nevertheless, due to the lack of synthetic approach, the design and application of conjugated porphyrin assemblies is a largely unexplored topic in view of the plethora of available porphyrin patterns.
The central idea of CLEANH2 builds upon our recent advance in the gas phase synthesis and deposition of directly fused metalloporphyrins coatings. Progress in our approach is expected to open the way for the construction of powerful catalytic and photocatalytic materials. To achieve this, the key challenging goals of this project are: 1) the engineering of the microstructure and electronic structure of directly fused metalloporphyrins thin films; 2) the use of the full potential of directly fused metalloporphyrins thin films for the unmet, clean and high quantum yield overall water splitting for hydrogen production. The outcomes of CLEANH2 will be foundational for the engineering of directly fused metalloporphyrins systems and their implementation in advanced technological applications related to catalysis and solar energy.
Max ERC Funding
1 900 711 €
Duration
Start date: 2020-05-01, End date: 2025-04-30
Project acronym ExpoBiome
Project Deciphering the impact of exposures from the gut microbiome-derived molecular complex in human health and disease
Researcher (PI) Paul WILMES
Host Institution (HI) UNIVERSITE DU LUXEMBOURG
Country Luxembourg
Call Details Consolidator Grant (CoG), LS2, ERC-2019-COG
Summary The human gut microbiome is a complex ecosystem, which contributes essential functions to human physiology. Changes to the microbiome are associated with several chronic diseases characterised by inflammation, including neurodegenerative and autoimmune diseases. Microbiome-derived effector molecules comprising nucleic acids, (poly)peptides and metabolites are present at high levels in the gut but have so far eluded systematic study. This gap in knowledge is limiting mechanistic understanding of the microbiome’s functional impact on chronic diseases such as Parkinson’s disease (PD) and rheumatoid arthritis (RA). Here, I will for the first time integrate a combination of advanced high-resolution methodologies to comprehensively identify the constituents of this molecular complex and their impact on the human immune system. First, I will perform a quantitative, integrated multi-omic analysis on microbiome samples collected from healthy individuals and patients with newly diagnosed PD or RA. I will integrate and analyse the data using a newly developed knowledge base. Using contextualised prior knowledge (ExpoBiome Map) and machine learning methods, I will identify microbial molecules associated with condition-specific immunophenotypes. Second, I will validate and track the biomarker signature during a model clinical intervention (therapeutic fasting) to predict treatment outcomes. Third, microbes and molecules will be screened in personalised HuMiX gut-on-chip models to identify novel anti-inflammatory compounds. By providing mechanistic insights into the molecular basis of human-microbiome interactions, the project will generate essential new knowledge about causal relationships between the gut microbiome and the immune system in health and disease. By facilitating the elucidation of currently unknown microbiome-derived molecules, it will identify new genes, proteins, metabolites and host pathways for the development of future diagnostic and therapeutic applications.
Summary
The human gut microbiome is a complex ecosystem, which contributes essential functions to human physiology. Changes to the microbiome are associated with several chronic diseases characterised by inflammation, including neurodegenerative and autoimmune diseases. Microbiome-derived effector molecules comprising nucleic acids, (poly)peptides and metabolites are present at high levels in the gut but have so far eluded systematic study. This gap in knowledge is limiting mechanistic understanding of the microbiome’s functional impact on chronic diseases such as Parkinson’s disease (PD) and rheumatoid arthritis (RA). Here, I will for the first time integrate a combination of advanced high-resolution methodologies to comprehensively identify the constituents of this molecular complex and their impact on the human immune system. First, I will perform a quantitative, integrated multi-omic analysis on microbiome samples collected from healthy individuals and patients with newly diagnosed PD or RA. I will integrate and analyse the data using a newly developed knowledge base. Using contextualised prior knowledge (ExpoBiome Map) and machine learning methods, I will identify microbial molecules associated with condition-specific immunophenotypes. Second, I will validate and track the biomarker signature during a model clinical intervention (therapeutic fasting) to predict treatment outcomes. Third, microbes and molecules will be screened in personalised HuMiX gut-on-chip models to identify novel anti-inflammatory compounds. By providing mechanistic insights into the molecular basis of human-microbiome interactions, the project will generate essential new knowledge about causal relationships between the gut microbiome and the immune system in health and disease. By facilitating the elucidation of currently unknown microbiome-derived molecules, it will identify new genes, proteins, metabolites and host pathways for the development of future diagnostic and therapeutic applications.
Max ERC Funding
1 998 620 €
Duration
Start date: 2020-11-01, End date: 2025-10-31
Project acronym INTERACT
Project Intelligent Non-woven Textiles and Elastomeric Responsive materials by Advancing liquid Crystal Technology
Researcher (PI) Jan Peter Felix Lagerwall
Host Institution (HI) UNIVERSITE DU LUXEMBOURG
Country Luxembourg
Call Details Consolidator Grant (CoG), PE8, ERC-2014-CoG
Summary A grand challenge in today’s materials research is the realization of flexible materials that are also intelligent and functional. They will be the enablers of true breakthroughs in the hot trends of soft robotics and wearable technology. The standard approach to the latter is to decorate rubber sheets with electronic components, yielding two serious flaws: rubber is uncomfortable as it does not breath and solid state electronics will eventually fail as a garment is flexed and stretched when worn. While the softness of rubber is ideal it must be used in the form of textile fibers to provide breathability, and for long-term failure resistance we need intelligent components that are soft. A solution to this conundrum was recently presented by the PI with the concept of liquid crystal (LC) electrospinning. The extreme responsiveness of LCs is transferred to a non-woven textile by incorporating the LC in the fiber core, yielding a smart flexible mat with sensory function. Moreover, it consumes no power, providing a further advantage over electronics-based approaches. In a second research line he uses microfluidics to make LC rubber microshells, functioning as autonomous actuators which may serve as innovative components for soft robotics, and photonic crystal shells. This interdisciplinary project presents an ambitious agenda to advance these new concepts to the realization of soft, stretchable intelligent materials of revolutionary character. Five specific objectives are in focus: 1) develop understanding of the dynamic response of LCs in these unconventional configurations; 2) establish interaction dynamics during polymerisation of an LC precursor; 3) elucidate LC response to gas exposure; 4) establish correlation between actuation response and internal order of curved LCE rubbers; and 5) assess usefulness of LC-functionalized fibers and polymerized LC shells, tubes and Janus particles in wearable sensors, soft robotic actuators and high-security identification tags.
Summary
A grand challenge in today’s materials research is the realization of flexible materials that are also intelligent and functional. They will be the enablers of true breakthroughs in the hot trends of soft robotics and wearable technology. The standard approach to the latter is to decorate rubber sheets with electronic components, yielding two serious flaws: rubber is uncomfortable as it does not breath and solid state electronics will eventually fail as a garment is flexed and stretched when worn. While the softness of rubber is ideal it must be used in the form of textile fibers to provide breathability, and for long-term failure resistance we need intelligent components that are soft. A solution to this conundrum was recently presented by the PI with the concept of liquid crystal (LC) electrospinning. The extreme responsiveness of LCs is transferred to a non-woven textile by incorporating the LC in the fiber core, yielding a smart flexible mat with sensory function. Moreover, it consumes no power, providing a further advantage over electronics-based approaches. In a second research line he uses microfluidics to make LC rubber microshells, functioning as autonomous actuators which may serve as innovative components for soft robotics, and photonic crystal shells. This interdisciplinary project presents an ambitious agenda to advance these new concepts to the realization of soft, stretchable intelligent materials of revolutionary character. Five specific objectives are in focus: 1) develop understanding of the dynamic response of LCs in these unconventional configurations; 2) establish interaction dynamics during polymerisation of an LC precursor; 3) elucidate LC response to gas exposure; 4) establish correlation between actuation response and internal order of curved LCE rubbers; and 5) assess usefulness of LC-functionalized fibers and polymerized LC shells, tubes and Janus particles in wearable sensors, soft robotic actuators and high-security identification tags.
Max ERC Funding
1 929 976 €
Duration
Start date: 2015-04-01, End date: 2020-03-31
Project acronym NanoThermo
Project Energy Conversion and Information Processing at Small Scales
Researcher (PI) Massimiliano Gennaro Esposito
Host Institution (HI) UNIVERSITE DU LUXEMBOURG
Country Luxembourg
Call Details Consolidator Grant (CoG), PE3, ERC-2015-CoG
Summary Thermodynamics provided mankind with the intellectual tools to master energy transfers and energy conversion in macroscopic systems operating close to equilibrium. It is now one of the most fundamental theories in physics. My goal is to establish a thermodynamic theory describing energy conversion and information processing in small synthetic or biological systems operating far from equilibrium. Significant progress has been achieved in this direction over the last decade. The new theory is called stochastic thermodynamics (ST). It allows us to describe and understand energy conversion in systems as diverse as quantum junctions and molecular motors, and also to predict the energetic cost of information processing operations such as erasing bits of information or feedback controlling a small device. It was validated in single molecule pulling experiments, electronic circuits, NMR and colloidal particles in optical tweezers. Nevertheless, ST still suffers from serious limitations which prevent its application in more complex systems. Therefore, I propose to expand the theoretical foundations of ST far beyond its current realm of validity and to broaden the scope of its applications in various new directions. I want to answer questions such as: Can one design devices made of many small energy converters (e.g. thermoelectric junctions) arranged in such a way as to generate collective behaviors (e.g. synchronization) prompting higher powers and efficiencies? Can one do the same by engineer quantum effects? How can one reduce the dissipation occurring when computing very quickly with small devices? Why are metabolic networks so efficient in converting energy, transmitting information, and preventing errors (e.g. toxic byproducts)? I will do so in close contact with leading experimental groups in the field. My conviction is that ST will become as important for nanotechnologies and molecular biology as thermodynamics has been for the industrial revolution.
Summary
Thermodynamics provided mankind with the intellectual tools to master energy transfers and energy conversion in macroscopic systems operating close to equilibrium. It is now one of the most fundamental theories in physics. My goal is to establish a thermodynamic theory describing energy conversion and information processing in small synthetic or biological systems operating far from equilibrium. Significant progress has been achieved in this direction over the last decade. The new theory is called stochastic thermodynamics (ST). It allows us to describe and understand energy conversion in systems as diverse as quantum junctions and molecular motors, and also to predict the energetic cost of information processing operations such as erasing bits of information or feedback controlling a small device. It was validated in single molecule pulling experiments, electronic circuits, NMR and colloidal particles in optical tweezers. Nevertheless, ST still suffers from serious limitations which prevent its application in more complex systems. Therefore, I propose to expand the theoretical foundations of ST far beyond its current realm of validity and to broaden the scope of its applications in various new directions. I want to answer questions such as: Can one design devices made of many small energy converters (e.g. thermoelectric junctions) arranged in such a way as to generate collective behaviors (e.g. synchronization) prompting higher powers and efficiencies? Can one do the same by engineer quantum effects? How can one reduce the dissipation occurring when computing very quickly with small devices? Why are metabolic networks so efficient in converting energy, transmitting information, and preventing errors (e.g. toxic byproducts)? I will do so in close contact with leading experimental groups in the field. My conviction is that ST will become as important for nanotechnologies and molecular biology as thermodynamics has been for the industrial revolution.
Max ERC Funding
1 669 029 €
Duration
Start date: 2016-07-01, End date: 2021-12-31
Project acronym STAMFORD
Project Statistical Methods For High Dimensional Diffusions
Researcher (PI) Mark Podolskij
Host Institution (HI) UNIVERSITE DU LUXEMBOURG
Country Luxembourg
Call Details Consolidator Grant (CoG), PE1, ERC-2018-COG
Summary In the past twenty years the availability of vast dimensional data, typically referred to as big data, has given rise to exciting challenges in various fields of mathematics and computer sciences. The increasing need for getting a better understanding of such data in internet traffic, biology, genetics, and economics, has lead to a revolution in statistical and machine learning, optimisation and numerical analysis. Due to high dimensionality of modern statistical models, parameter estimation is a difficult task and statisticians typically investigate estimation methods under sparsity constraints. While an abundance of estimation algorithms is now available for high dimensional discrete models, a rigorous mathematical investigation of estimation problems for high dimensional continuous-time processes is completely undeveloped.
The aim of STAMFORD is to provide a concise statistical theory for estimation of high dimensional diffusions. Such high dimensional processes naturally appear in modelling particle interactions in physics, neural networks in biology or large portfolios in economics, just to name a few. The methodological part of the project will require development of novel
advanced techniques in mathematical statistics and probability theory. In particular, new results will be needed in parametric and non-parametric statistics, and high dimensional probability, that are reaching far beyond the state-of-the-art. Hence, a successful outcome of STAMFORD will not only have a tremendous impact on statistical inference for continuous-time models in natural and applied sciences, but also strongly influence the field of high dimensional statistics and probability.
Summary
In the past twenty years the availability of vast dimensional data, typically referred to as big data, has given rise to exciting challenges in various fields of mathematics and computer sciences. The increasing need for getting a better understanding of such data in internet traffic, biology, genetics, and economics, has lead to a revolution in statistical and machine learning, optimisation and numerical analysis. Due to high dimensionality of modern statistical models, parameter estimation is a difficult task and statisticians typically investigate estimation methods under sparsity constraints. While an abundance of estimation algorithms is now available for high dimensional discrete models, a rigorous mathematical investigation of estimation problems for high dimensional continuous-time processes is completely undeveloped.
The aim of STAMFORD is to provide a concise statistical theory for estimation of high dimensional diffusions. Such high dimensional processes naturally appear in modelling particle interactions in physics, neural networks in biology or large portfolios in economics, just to name a few. The methodological part of the project will require development of novel
advanced techniques in mathematical statistics and probability theory. In particular, new results will be needed in parametric and non-parametric statistics, and high dimensional probability, that are reaching far beyond the state-of-the-art. Hence, a successful outcome of STAMFORD will not only have a tremendous impact on statistical inference for continuous-time models in natural and applied sciences, but also strongly influence the field of high dimensional statistics and probability.
Max ERC Funding
1 655 048 €
Duration
Start date: 2019-09-01, End date: 2024-08-31
Project acronym UpTEMPO
Project Ultrafast tunneling microscopy by optical field control of quantum currents
Researcher (PI) Daniele BRIDA
Host Institution (HI) UNIVERSITE DU LUXEMBOURG
Country Luxembourg
Call Details Consolidator Grant (CoG), PE2, ERC-2018-COG
Summary The project aims at imaging electronic dynamics in molecules with atomic precision and sub-femtosecond temporal resolution. This result will be achieved by establishing new experiments at the boundary of ultrafast optics and scanning probe microscopy where the electric field of single-cycle light pulses is harnessed to control currents in nanojunctions. The basic concept relies on the fact that state-of-the-art femtosecond optical wave packets exhibit only one cycle of radiation with a defined electric field maximum. These pulses need to be phase locked to a “cosine-like” electric field profile. If such radiation is focused onto a junction with a nonlinear current-voltage characteristics, a net charge flow results solely due to the bias induced by the optical field.
In detail, we want to exploit the time resolution provided by this new technique and induce electron transport at the probe tip of a scanning tunneling microscope (STM). The optical control of the current over a sub-optical-cycle interval will guarantee a temporal resolution better that one femtosecond, thus improving by several orders of magnitude what can be achieved with standard electronic bias.
The core of the experimental system will be an ultrabroadband and passively phase-locked Er:fiber laser that is designed to generate single-cycle optical pulses in the near/mid-infrared, i.e. off resonant to the transition energies of III-V and II-VI semiconductors and large molecules. This laser will operate at 80-MHz repetition rate for enhanced sensitivity and stability when coupled to an ultra-high-vacuum STM. The setup will allow for the direct combination of independent pulse trains to resonantly excite few-femtosecond dynamics and then probe the electron density via the optically driven tunneling. In this pump-probe scheme it will be possible to map with atomic resolution the coherent evolution of electronic wavefunctions that in molecules and nanosystems follows an impulsive photoexcitation.
Summary
The project aims at imaging electronic dynamics in molecules with atomic precision and sub-femtosecond temporal resolution. This result will be achieved by establishing new experiments at the boundary of ultrafast optics and scanning probe microscopy where the electric field of single-cycle light pulses is harnessed to control currents in nanojunctions. The basic concept relies on the fact that state-of-the-art femtosecond optical wave packets exhibit only one cycle of radiation with a defined electric field maximum. These pulses need to be phase locked to a “cosine-like” electric field profile. If such radiation is focused onto a junction with a nonlinear current-voltage characteristics, a net charge flow results solely due to the bias induced by the optical field.
In detail, we want to exploit the time resolution provided by this new technique and induce electron transport at the probe tip of a scanning tunneling microscope (STM). The optical control of the current over a sub-optical-cycle interval will guarantee a temporal resolution better that one femtosecond, thus improving by several orders of magnitude what can be achieved with standard electronic bias.
The core of the experimental system will be an ultrabroadband and passively phase-locked Er:fiber laser that is designed to generate single-cycle optical pulses in the near/mid-infrared, i.e. off resonant to the transition energies of III-V and II-VI semiconductors and large molecules. This laser will operate at 80-MHz repetition rate for enhanced sensitivity and stability when coupled to an ultra-high-vacuum STM. The setup will allow for the direct combination of independent pulse trains to resonantly excite few-femtosecond dynamics and then probe the electron density via the optically driven tunneling. In this pump-probe scheme it will be possible to map with atomic resolution the coherent evolution of electronic wavefunctions that in molecules and nanosystems follows an impulsive photoexcitation.
Max ERC Funding
1 999 509 €
Duration
Start date: 2019-09-01, End date: 2024-08-31
