ERC FUNDED PROJECTS

Cavitation is the formation of vapor cavities inside a liquid due to low pressure. Cavitation is an ubiquitous and destructive phenomenon common to most engineering applications that deal with flowing water. At the same time, the extreme conditions realized in cavitation are increasingly exploited in medicine, chemistry, and biology. What makes cavitation unpredictable is its multiscale nature: nucleation of vapor bubbles heavily depends on micro- and nanoscale details; mesoscale phenomena, as bubble collapse, determine relevant macroscopic effects, e.g., cavitation damage. In addition, macroscopic flow conditions, such as turbulence, have a major impact on it. The objective of the BIC project is to develop the lacking multiscale description of cavitation, by proposing new integrated numerical methods capable to perform quantitative predictions. The detailed and physically sound understanding of the multifaceted phenomena involved in cavitation (nucleation, bubble growth, transport, and collapse in turbulent flows) fostered by BIC project will result in new methods for designing fluid machinery, but also therapies in ultrasound medicine and chemical reactors. The BIC project builds upon the exceptionally broad experience of the PI and of his research group in numerical simulations of flows at different scales that include advanced atomistic simulations of nanoscale wetting phenomena, mesoscale models for multiphase flows, and particle-laden turbulent flows. The envisaged numerical methodologies (free-energy atomistic simulations, phase-field models, and Direct Numerical Simulation of bubble-laden flows) will be supported by targeted experimental activities, designed to validate models and characterize realistic conditions.

2 491 200 €

Start date: 2014-02-01, End date: 2019-01-31

"The eruption of volcanoes appears one of the most unpredictable phenomena on Earth. Yet the situation is rapidly changing. Quantification of the eruptive record constrains what is possible in a given volcanic system. Timing is the hardest part to quantify. The main process triggering an eruption is the refilling of a sub-volcanic magma chamber by a new magma coming from depth. This process results in magma mixing and provokes a time-dependent diffusion of chemical elements. Understanding the time elapsed from mixing to eruption is fundamental to discerning pre-eruptive behaviour of volcanoes to mitigate the huge impact of volcanic eruptions on society and the environment. The CHRONOS project proposes a new method that will cut the Gordian knot of the presently intractable problem of volcanic eruption timing using a surgical approach integrating textural, geochemical and experimental data on magma mixing. I will use the compositional heterogeneity frozen in time in the rocks the same way a broken clock at a crime scene is used to determine the time of the incident. CHRONOS will aim to: 1) be the first study to reproduce magma mixing, by performing unique experiments constrained by natural data and using natural melts, under controlled rheological and fluid-dynamics conditions; 2) obtain unprecedented high-quality data on the time dependence of chemical exchanges during magma mixing; 3) derive empirical relationships linking the extent of chemical exchanges and the mixing timescales; 4) determine timescales of volcanic eruptions combining natural and experimental data. CHRONOS will open a new window on the physico-chemical processes occurring in the days preceding volcanic eruptions providing unprecedented information to build the first inventory of eruption timescales for planet Earth. If these timescales can be linked with geophysical signals occurring prior to eruptions, this inventory will have an immense value, enabling precise prediction of volcanic eruptions."

1 993 813 €

Start date: 2014-05-01, End date: 2019-04-30

Self-assembly is the key construction principle that nature uses so successfully to fabricate its molecular machinery and highly elaborate structures. In this project we will follow nature’s strategies and make a concerted experimental and theoretical effort to study, understand and control self-assembly for a new generation of colloidal building blocks. Starting point will be recent advances in colloid synthesis strategies that have led to a spectacular array of colloids of different shapes, compositions, patterns and functionalities. These allow us to investigate the influence of anisotropy in shape and interactions on aggregation and self-assembly in colloidal suspensions and mixtures. Using responsive particles we will implement colloidal lock-and-key mechanisms and then assemble a library of “colloidal molecules” with well-defined and externally tunable binding sites using microfluidics-based and externally controlled fabrication and sorting principles. We will use them to explore the equilibrium phase behavior of particle systems interacting through a finite number of binding sites. In parallel, we will exploit them and investigate colloid self-assembly into well-defined nanostructures. Here we aim at achieving much more refined control than currently possible by implementing a protein-inspired approach to controlled self-assembly. We combine molecule-like colloidal building blocks that possess directional interactions and externally triggerable specific recognition sites with directed self-assembly where external fields not only facilitate assembly, but also allow fabricating novel structures. We will use the tunable combination of different contributions to the interaction potential between the colloidal building blocks and the ability to create chirality in the assembly to establish the requirements for the controlled formation of tubular shells and thus create a colloid-based minimal model of synthetic virus capsid proteins.

2 498 040 €

Start date: 2014-02-01, End date: 2019-01-31

Today, many industrial products are defined by software and therefore customizable: their functionalities implemented by software can be modified and extended by dynamic software updates on demand. This trend towards customizable products is rapidly expanding into all domains of IT, including Embedded Real-Time Systems (ERTS) deployed in Cyber-Physical Systems such as cars, medical devices etc. However, the current state-of-practice in safety-critical systems allows hardly any modifications once they are put in operation. The lack of techniques to preserve crucial safety conditions for customizable systems severely restricts the benefits of advances in software-defined systems engineering. CUSTOMER is to provide the missing paradigm and technology for building and updating ERTS after deployment – subject to stringent timing constraints, dynamic workloads, and limited resources on complex platforms. CUSTOMER explores research areas crossing two fields: Real-Time Computing and Formal Verification to develop the key techniques enabling (1) dynamic updates of ERTS in the field, (2) incremental updates over the products life time and (3) safe updates by verification to avoid updates that may compromise system safety. CUSTOMER will develop a unified model-based framework supported with tools for the design, modelling, verification, deployment and update of ERTS, aiming at advancing the research fields by establishing the missing scientific foundation for multiprocessor real-time computing and providing the next generation of design tools with significantly enhanced capability and scalability increased by orders of magnitude compared with state-of-the-art tools e.g. UPPAAL.

2 499 894 €

Start date: 2019-10-01, End date: 2024-09-30

Traditionally, program semantics is centered around the notion of program identity, that is to say of program equivalence: a program is identified with its meaning, and programs are considered as equal only if their meanings are the same. This view has been extremely fruitful in the past, allowing for a deep understanding of highly interactive forms of computation as embodied by higher-order or concurrent programs. The byproducts of all this lie everywhere in computer science, from programming language design to verification methodologies. The emphasis on equality — as opposed to differences — is not however in line with the way programs are written and structured in modern complex software systems. Subtasks are delegated to pieces of code which behave as expected only up to a certain probability of error, and only if the environment in which they operate makes this possible deviation irrelevant. These aspects have been almost neglected by the program semantics community until recently, and still have a marginal role. DIAPASON's goal is to study differences between programs as a constitutive and informative concept, rather than by way of relations between them. This will be accomplished by generalizing four major frameworks of program semantics, traditionally used for giving semantics to programs, comparing them, proving properties of them, and controlling their usage of resources: logical relations, bisimulation, game semantics, and linear logic.

959 562 €

Start date: 2019-03-01, End date: 2024-02-29

Achieving zero net carbon emissions by the end of the century is the challenge for capping global warming. The largest share of carbon emissions belongs to the production of electric energy from fossil fuels, which renewable energies are progressively replacing. Sunlight is an ideal renewable energy source since it is most abundant and available worldwide. Photovoltaic solar cells can directly convert the sunlight into electric energy by making use of the photovoltaic effect in semiconductors. Halide perovskites are emerging crystalline semiconducting materials with among the strongest light absorption and the most effective electric charge generation needed to design the highest efficient photovoltaic solar cells. The PI has the ambition to reinvent halide perovskites as environmentally friendly photovoltaic material, aiming at: (i) Removing lead: state-of-the-art perovskite solar cells are based on lead, which is in the list of hazardous substances of the European Union. The PI will prepare new tin-based perovskites and prove them in the highest efficient solar cells. (ii) Solvent-free crystallisation: organic solvents drive the crystallisation of the perovskite in the most efficient solar cells. However, crystallising the perovskite without using solvents is more environmentally friendly. The PI will establish physical vapour deposition as a solvent-free method for preparing the perovskite and the other materials comprising the solar cell. (iii) Durable power output: the long-term power output defines the solar energy yield and thus the return on investment. The PI aims to make stable tin-based perovskites addressing the oxidative instability of tin directly. The quantified target of FREENERGY is demonstrating a tin-based perovskite solar cell with power conversion efficiency over 20% and stability for 25 years. The research strategy to enable this disruptive outcome comprises innovative perovskites formulations and unconventional supramolecular interactions

1 500 000 €

Start date: 2019-02-01, End date: 2024-01-31

Recently, there has been a paradigmatic shift in experimental molecular spectroscopy, with new methods focusing on the study of molecules embedded within complex supramolecular/nanostructured aggregates. In the past, molecular spectroscopy has benefitted from the synergistic developments of accurate and cost-effective computational protocols for the simulation of a wide variety of spectroscopies. These methods, however, have been limited to isolated molecules or systems in solution, therefore are inadequate to describe the spectroscopy of complex nanostructured systems. The aim of GEMS is to bridge this gap, and to provide a coherent theoretical description and cost-effective computational tools for the simulation of spectra of molecules interacting with metal nano-particles, metal nanoaggregates and graphene sheets. To this end, I will develop a novel frequency-dependent multilayer Quantum Mechanical (QM)/Molecular Mechanics (MM) embedding approach, general enough to be extendable to spectroscopic signals by using the machinery of quantum chemistry and able to treat any kind of plasmonic external environment by resorting to the same theoretical framework, but introducing its specificities through an accurate modelling and parametrization of the classical portion. The model will be interfaced with widely used computational chemistry software packages, so to maximize its use by the scientific community, and especially by non-specialists. As pilot applications, GEMS will study the Surface-Enhanced Raman (SERS) spectra of systems that have found applications in the biosensor field, SERS of organic molecules in subnanometre junctions, enhanced infrared (IR) spectra of oligopeptides adsorbed on graphene, Graphene Enhanced Raman Scattering (GERS) of organic dyes, and the transmission of stereochemical response from a chiral analyte to an achiral molecule in the vicinity of a plasmon resonance of an achiral metallic nanostructure, as measured by Raman Optical Activity-ROA

1 609 500 €

Start date: 2019-06-01, End date: 2024-05-31

"Partial Differential Equations (PDEs) are widely used in science and engineering simulations, often in tight connection with Computer Aided Design (CAD). The Finite Element Method (FEM) is one of the most popular technique for the discretization of PDEs. The IsoGeometric Method (IGM), proposed in 2005 by T.J.R. Hughes et al., aims at improving the interoperability between CAD and FEMs. This is achieved by adopting the CAD mathematical primitives, i.e. Splines and Non-Uniform Rational B-Splines (NURBS), both for geometry and unknown fields representation. The IGM has gained an incredible momentum especially in the engineering community. The use of high-degree, highly smooth NURBS is extremely successful and the IGM outperforms the FEM in most academic benchmarks. However, we are far from having a satisfactory mathematical understanding of the IGM and, even more importantly, from exploiting its full potential. Until now, the IGM theory and practice have been deeply influenced by finite element analysis. For example, the IGM is implemented resorting to a FEM code design, which is very inefficient for high-degree and high-smoothness NURBS. This has made possible a fast spreading of the IGM, but also limited it to quadratic or cubic NURBS in complex simulations. The use of higher degree IGM for real-world applications asks for new tools allowing for the efficient construction and solution of the linear system, time integration, flexible local mesh refinement, and so on. These questions need to be approached beyond the FEM framework. This is possible only on solid mathematical grounds, on a new theory of splines and NURBS able to comply with the needs of the IGM. This project will provide the crucial knowledge and will re-design the IGM to make it a superior, highly accurate and stable methodology, having a significant impact in the field of numerical simulation of PDEs, particularly when accuracy is essential both in geometry and fields representation."

928 188 €

Start date: 2014-06-01, End date: 2019-05-31

In spite of their small areal extent, inland waters play a vital role in the carbon cycle of the continents, as they emit significant amounts of the greenhouse gases (GHG) carbon dioxide (CO2) and methane (CH4) to the atmosphere, and simultaneously bury more organic carbon (OC) in their sediments than the entire ocean. Particularly in tropical hydropower reservoirs, GHG emissions can be large, mainly owing to high CH4 emission. Moreover, the number of tropical hydropower reservoirs will continue to increase dramatically, due to an urgent need for economic growth and a vast unused hydropower potential in many tropical countries. However, the current understanding of the magnitude of GHG emission, and of the processes regulating it, is insufficient. Here I propose a research program on tropical reservoirs in Brazil that takes advantage of recent developments in both concepts and methodologies to provide unique evaluations of GHG emission and OC burial in tropical reservoirs. In particular, I will test the following hypotheses: 1) Current estimates of reservoir CH4 emission are at least one order of magnitude too low, since they have completely missed the recently discovered existence of gas bubble emission hot spots; 2) The burial of land-derived OC in reservoir sediments offsets a significant share of the GHG emissions; and 3) The sustained, long-term CH4 emission from reservoirs is to a large degree fuelled by primary production of new OC within the reservoir, and may therefore be reduced by management of nutrient supply. The new understanding and the cross-disciplinary methodological approach will constitute a major advance to aquatic science in general, and have strong impacts on the understanding of other aquatic systems at other latitudes as well. In addition, the results will be merged into an existing reservoir GHG risk assessment tool to improve planning, design, management and judgment of hydropower reservoirs.

1 798 227 €

Start date: 2013-09-01, End date: 2019-08-31

"Failure in ductile materials results from a multiscale interaction of discrete microstructures hierarchically emerging through subsequent material instabilities and self-organizing into regular patterns (shear band clusters, for instance). The targets of the project are: (i.) to disclose the failure mechanisms of materials through analysis of material instabilities and (ii.) to develop innovative microstructures to be embedded in solids, in order to open new possibilities in the design of ultra-resistant materials and structures. The link between the two targets is that micromechanisms developing during failure inspire the way of enhancing the mechanical properties of materials by embedding microstructures. The aim is to provide design tools to obtain groundbreaking and unchallenged mechanical properties employing discrete microstructures, for instance to design a microstructure defining a material working under flutter condition. The design of these microstructures will permit the achievement of innovative dynamical properties, defining elastic metamaterials, for instance, permitting the fabrication of flat lenses for elastic waves, evidencing negative refraction and superlensing effects. The objective is the discovery of these effects in mechanics, thus disclosing new horizons in the dynamics of materials. Microstructures introduce length scales and nonlocal effects in the mechanical modelling, which involve the use of higher-order theories. The analysis of these effects, usually developed within a phenomenological approach, will be attacked from the fundamental and almost unexplored point of view: the explicit evaluation of nonlocality, related to the microstructure via homogenisation theory."

2 379 359 €

Start date: 2014-03-01, End date: 2019-02-28

Generation of toxic oligomers during aggregation of amyloid beta peptide (Abeta42) into amyloid fibrils is a central event in Alzheimer disease. Understanding the aggregation process is therefore one important step towards therapy and diagnosis of the disease. We propose a physical chemistry approach with the goal of finding the molecular mechanisms behind the process in terms of the underlying microscopic steps and the molecular driving forces governing each step. We will use methodology developed recently in our laboratory yielding unprecedented reproducibility in the kinetic data. The methodology relies on optimization of every step from production and purification to isolation of highly pure monomeric peptide, and inertness and minimized area of all surfaces. We will use cell viability studies to detect toxic oligomeric species, and selective radio-labeling experiments to pinpoint the origin of those species. In order to obtain insight into the molecular determinants and the relative role of different kinds of intermolecular interactions for each microscopic step, we will study the concentration dependent aggregation kinetics as a function of extrinsic and intrinsic parameters. Extrinsic parameters include temperature, salt, pH, biological membranes, other proteins, and low and high Mw inhibitors. Intrinsic parameters include point mutations and sequence extension/truncation. We will perform detailed kinetic studies for each inhibitor to learn which step in the process is inhibited coupled to cell toxicity assays to learn whether the generation of toxic oligomers is limited. We will use spectroscopic techniques, dynamic light scattering, cryogenic transmission electron microscopy and mass spectrometry coupled to HD exchange to learn about structural transitions as a function of process progression under different conditions to favor different microscopic steps. The results may lead to improved diagnostics and therapeutics of Alzheimer disease.

2 499 920 €

Start date: 2014-02-01, End date: 2019-01-31

I propose to realize the first shapeshifting optical metasurface that changes its functionality on-demand and adapts to changing external conditions. The metasurface may work as a chemically selective lens that allows transmission only of the spectral fingerprint of a specific molecule in the mid-IR wavelength range. The same metasurface can later be turned into an adaptive lens for focusing and detection under the skin. For such ambitious goal, a radically new approach is needed. I will realize shapeshifting metasurfaces made of a polymer containing photo-switchable molecules. The surface of such polymers undergoes a morphology re-organization (surface structuring) when illuminated by an external visible light pattern. The polymer will be structured with visible light and the resulting metasurfaces will work in the mid-IR. I will use state-of-the-art optical nano-imaging techniques to investigate the surface structuring phenomenon at the nanoscale in order to achieve full control of the mechanism. Since the polymer surface can continuously be adjusted with the illuminating visible light, it will be possible to shift from one encoded optical functionality to a completely different one. Once optimized, this completely out-of-the-box approach will be completed by developing a feedback mechanism that allows for self- adjustment of the polymeric metasurface to changing external conditions. This will open endless possibilities in many fields, from medical imaging to security and quality control. The proposed approach is unprecedented but it is perfectly in line with my research activities, resulting in fact from merging different techniques that I master into a new research field. My approach is also inexpensive relative to the usual nano-fabrication techniques and immediately compatible with high-volume production, providing a viable technology platform for lightweight, eyewear technology, that reflects the views of key industrial players in the field.

2 745 000 €

Start date: 2019-10-01, End date: 2024-09-30

Consider a population of individuals belonging to different species with unknown proportions. Given an initial (observable) random sample from the population, how do we estimate the number of species in the population, or the probability of discovering a new species in one additional sample, or the number of hitherto unseen species that would be observed in additional unobservable samples? These are archetypal examples of a broad class of statistical problems referred to as species sampling problems (SSP), namely: statistical problems in which the objects of inference are functionals involving the unknown species proportions and/or the species frequency counts induced by observable and unobservable samples from the population. SSPs first appeared in ecology, and their importance has grown considerably in the recent years driven by challenging applications in a wide range of leading scientific disciplines, e.g., biosciences and physical sciences, engineering sciences, machine learning, theoretical computer science and information theory, etc. The objective of this project is the introduction and a thorough investigation of new nonparametric Bayes and empirical Bayes methods for SSPs. The proposed advances will include: i) addressing challenging methodological open problems in classical SSPs under the nonparametric empirical Bayes framework, which is arguably the most developed (currently most implemented by practitioners) framework do deal with classical SSPs; fully exploiting and developing the potential of tools from mathematical analysis, combinatorial probability and Bayesian nonparametric statistics to set forth a coherent modern approach to classical SSPs, and then investigating the interplay between this approach and its empirical counterpart; extending the scope of the above studies to more challenging SSPs, and classes of generalized SSPs, that have emerged recently in the fields of biosciences and physical sciences, machine learning and information theory.

982 930 €

Start date: 2019-03-01, End date: 2024-02-29

Research neuronal signaling is the subject of a very large community, but progresses face a dense multi-scale dynamics involving signaling at the molecular, cellular and large neuronal network levels. Whereas the brain capabilities are most likely emerging from large neuronal networks, available electrophysiological methods limit our access to single cells and typically provides only a fragmented observation, on limited spatial/temporal scales. Therefore, broadening the spectrum of scales for observing neuronal signaling within large neuronal networks is a major challenge that can revolutionize our capability of studying the brain and its physio-pathological functions, as well as of deriving bio-inspired concepts to implement artificial system based on neuronal circuits. We propose the development of an innovative electro-plasmonic multifunctional platform that by combining different methodologies emerging from distant fields of Science and Technology will provide a radically new path for real time neurointerfacing at different scale levels: 1. The molecular scale: 3D plasmonic nanoantennas will give access to information at molecular level by means of enhanced spectroscopies with particular regard of time resolved Raman scattering. 2. The single-neuron scale within neuronal networks: by both in-cell and extra-cell couplings with 3D nanostructures which work at the same time as plasmonic antennas and CMOS 3D nanoelectrodes. 3. The scale of large neuronal networks: by CMOS high-density electrode arrays for spatially and temporally resolving neuronal signaling form thousands of measuring sites. This is achieved by exploiting an innovative nanofabrication method able to realize 3D nanostructures which can work at the same time as plasmonic nanoantennas and as nanoelectrodes. These structures will be integrated on CMOS multi-electrode arrays designed to manage multiscale measurements from the molecular level up to network level on several thousand of measurement sites.

1 388 000 €

Start date: 2014-04-01, End date: 2018-03-31

Advances in transportation, energy harvesting, chemical processing, climatology, atmospheric and marine pollution are obstructed by the lack of understanding of turbulence. The turbulent energy transfer toward small-scales is characterized by highly non-Gaussian and out-of-equilibrium fluctuations that cannot be described by mean-field theories or traditional closure approximations. State-of-the-art computers and algorithms do not allow to perform brute-force direct numerical simulations of any realistic turbulent configuration: modelling is mandatory. On the other hand, turbulence models are often strongly limited by our lack of understanding of fundamental mechanisms. As a result, we have a deadlock: turbulence is thought of as ‘unsolvable’ theoretically and computationally ‘intensive’. Indeed, progress by using conventional methods has been slow. Last year, however, something new happened. Two unconventional conceptual and numerical methodologies to study Navier-Stokes equations appeared based on: (i) a surgery of nonlinear interactions with different Energy and Helicity contents, (ii) a fractal-Fourier decimation. These unexplored tools are potential breakthroughs to unravel the basic mechanisms governing the turbulent transfer in isotropic, anisotropic and bounded flows, e.g. the mechanism behind the growth of small-scales vorticity and formation/stability of coherent structures, a challenge that has defeated all numerical and theoretical attempts, up to now. The ultimate goal of NewTURB is to integrate the fresh knowledge achieved by using these novel numerical instruments to push forward the frontiers of turbulence modelling, exploiting the possibility to reduce the number-of-degrees-of-freedom in an innovative way to deliver alternative frontier ‘multiscale eddy-simulations’ methodologies for both unbounded and bounded flows with smooth walls or with heterogeneous landscapes, e.g. flows over a rough surface.

1 986 000 €

Start date: 2014-03-01, End date: 2019-02-28

The expansion of a dilute gas through a gasdynamics convergent-divergent nozzle can occur in three different regimes, depending on the inlet and discharge conditions and on the gas: via a fully subsonic expansion, via a subsonic-supersonic or via a subsonic-supersonic-subsonic expansion embedding a compression shock wave within the divergent portion of the nozzle. I devised an exact solution procedure for computing nozzle flows of real gases, which allowed me to discover that in molecularly complex fluids eighteen additional different flow configurations are possible, each including multiple compression classical shocks as well as non classical rarefaction ones. Modern thermodynamic models indicate that these exotic regimes can possibly occur in nozzle flows of molecularly complex fluids such as hydrocarbons, siloxanes or perfluorocarbons operating close to the liquid-vapour saturation curve and critical point. The experimental observation of one only of these eighteen flow configurations would be sufficient to prove for the first time that non classical gasdynamics phenomena are indeed possible in the vapour region of a fluid with high molecular complexity To this purpose, a modification to the blow-down wind tunnel for dense gases at Politecnico di Milano is proposed to use mixtures of siloxane fluids. Measurements are complemented by numerical simulations of the expected flow field and by state-of-the-art uncertainty quantification techniques. The distinctive feature of the proposed experiment is the adoption of mixture of siloxanes as working fluids. Mixtures of siloxanes are well known to exhibit an higher stability limit than their pure components, due to the redistribution process occurring at high temperature. The increased understanding of real-gas dynamics will enable to improve the design of Organic Rankine Cycle Engines, to be used in small scale energy production from biomasses, binary geothermal systems and concentrating solar thermal power plants.

1 485 600 €

Start date: 2014-03-01, End date: 2019-02-28

The outflows of young and old stars play a crucial role in the cycle of matter in galaxies. Stars and planetary systems are formed through complex physical processes during the collapse of gas clouds with outflows a required ingredient. At the end of a stars life, stellar outflows are the main source of heavy elements that are essential for the formation of stars, planets and life. Magnetic fields are one of the key factors governing the in particular the often observed collimated outflow. They might also be a key ingredient in driving stellar mass loss and are potentially essential for stabilizing accretion disks of, in particular, massive proto-stars. Only polarization observations at different spatial scales are able to measure the strength and structure of magnetic fields during the launching of outflows from young and old stars. Because stars in these evolutionary phases are highly obscured by dusty envelopes, their magnetic fields are best probed through observations of molecules and dust at submillimeter and radio wavelengths. In addition to its role, the origin of the magnetic field in these stellar phases is also still unknown and to determine it multi-wavelength observations are essential. The proposed research group will use state of the art submillimeter and radio instruments, integrated with self-consistent radiative transfer and magneto-hydrodynamic models, to examine the role and origin of magnetic fields during star formation and in the outflows from evolved stars. The group will search for planets around evolved stars to answer the elusive question on the origin of their magnetic field and determine the connection between the galactic magnetic field and that responsible for the formation of jets and potentially disks around young proto-stars. This fundamental new work, for which a dedicated research group is essential, will reveal the importance of magnetism during star formation as well as in driving and shaping the mass loss of evolved stars.

2 000 000 €

Start date: 2014-05-01, End date: 2019-04-30

Despite significant advances in chemotherapy, the effective treatment of malignant masses via systemically injectable agents are still limited by insufficient accumulation at the biological target (<< 10% injected dose per gram tumor) and non-specific sequestration by the reticulo-endothelial system (tumor/liver < 0.1). The goal of this proposal is to engineer Discoidal Polymeric Nanoconstructs (DPNs) to preferentially target the malignant neovasculature for the delivery of imaging agents, controlled release of therapeutic molecules and thermal energy. The central hypothesis is that the size, shape, surface properties and stiffness (4S parameters) of the DPNs can be controlled during synthesis, and that therapeutic molecules (Temozolomide), Gd(DOTA) complexes and ultra-small Super-Paramagnetic Iron Oxide nanoparticles (USPIOs) can be efficiently incorporated within the DPN polymeric matrix. This will be achieved by pursuing 3 specific aims: i) synthesis and physico-chemical characterization of poly(lactic-co-glycolic acid)/poly(ethylene glycol) DPNs with multiple 4S combinations; ii) in-silico and in vitro rational selection of DPN configurations with preferential tumor deposition, low macrophage uptake and high loading; and iii) in-vivo testing of the DPN imaging and therapeutic performance in mice bearing Glioblastoma Multiforme (GBM). The innovation stays in i) using synergistically three different targeting strategies (rational selection of the 4S parameters; magnetic guidance via external magnets acting on the USPIOs; specific ligand-receptor recognition of the tumor neovasculature); ii) combining therapeutic and imaging molecules within the same nanoconstruct; and iii) employing synergistically different therapeutic approaches (molecular and thermal ablation therapies). This would allow us to support minimally invasive screening via clinical imaging and enhance therapeutic efficacy in GBM patients.

2 390 000 €

Start date: 2014-07-01, End date: 2019-06-30

Modern society is critically dependent on large-scale networks for services such as energy supply, transportation and communications. The design and control of such networks is becoming increasingly complex, due to their growing size, heterogeneity and autonomy. A systematic theory and methodology for control of large-scale interconnected systems is therefore needed. In an ambitious effort towards this goal, this project will develop rigorous tools for control synthesis, adaptation and verification. Many large-scale systems exhibit properties that have not yet been systematically exploited by the control community. One such property is positive (or monotone) system dynamics. This correspond to the property that all states of a network respond in the same direction when the demand or supply is perturbed in some node. Scalable methods for control of positive systems are starting to be developed, but several fundamental questions remain: How can existing results be extended to scalable synthesis of dynamic controllers? Can results for linear positive systems be extended to nonlinear monotone ones? How about systems with resonances? The second focus area, adaptation, takes advantage of recent progress in machine learning, such as statistical concentration bounds and approximate dynamic programming. Adaptation is of fundamental importance for scalability, since high-fidelity models are very expensive to generate manually and hard to maintain. Thirdly, since systematic procedures for control synthesis generally rely on simplified models and idealized assumptions, we will also develop scalable methods to bound the effect of imperfections, such as nonlinearities, time-variations and parameter uncertainty that are not taken into account in the original design. The research will be carried out in interaction with industry studying a new concept for district heating networks. This collaboration will give access to experimental data from a full scale demonstration plant.

2 500 000 €

Start date: 2019-09-01, End date: 2024-08-31

"Cutting went through a revolution in the 1990s when high-speed milling (HSM) was introduced: the sculpture-like workpieces produced with high precision and efficiency resulted in one order of magnitude less parts in cars/aircrafts, which kept this traditional technology competitive at the turn of the century. This has been followed by an incremental development when not just the cutting speeds, but depths of cut and feed rates are pushed to limits, too. The limits are where harmful vibrations occur. Cutting is subject to a special one called chatter, which is originated in a time delay: the cutting edge interferes with its own past oscillation recorded on the wavy surface cut of the workpiece. In 1907, the 3rd president of ASME, Taylor wrote: “Chatter is the most obscure and delicate of all problems facing the machinist”. In spite of the development of the theory of delay-differential equations and nonlinear dynamics, Taylor’s statement remained valid 100 years later when HSM appeared together with a new kind of chatter. The applicant has been among those leading researchers who predicted these phenomena; the experimental/numerical techniques developed in his group are widely used to find parameters, e.g. where milling tools with serrated edges and/or with varying helix angles are advantageous. The SIREN project aims to find isolated parameter islands with 3-5 times increased cutting efficiency. The work-packages correspond to points of high risk: (1) validated, delay-based nonlinear modelling of the dynamic contact problem between chip and tool; (2) fixation of the tool that is compatible with a dynamically reliable mathematical model of the contact between tool and tool-holder; (3) up-to-date dynamic modelling of the spindle at varying speeds. High risk originates in the attempt of using distributed delay models, but high gain is expected with robust use of parameter islands where technology reaches a breakthrough in cutting efficiency for the 21st century."

2 573 000 €

Start date: 2014-03-01, End date: 2019-02-28

In a recovery problem, we are interested in recovering structure from data that contains a mix of combinatorial structure and random noise. In a robust recovery problem, the data may contain adversarial perturbations as well. A series of recent results in theoretical computer science has led to algorithms based on the convex optimization technique of Semidefinite Programming for several recovery problems motivated by unsupervised machine learning. Can those algorithms be made robust? Sparsifiers are compressed representations of graphs that speed up certain algorithms. The recent proof of the Kadison-Singer conjecture by Marcus, Spielman and Srivastava (MSS) shows that certain kinds of sparsifiers exist, but the proof does not provide an explicit construction. Dynamics and population protocols are simple models of distributed computing that were introduced to study sensor networks and other lightweight distributed systems, and have also been used to model naturally occurring networks. What can and cannot be computed in such models is largely open. We propose an ambitious unifying approach to go beyond the state of the art in these three domains, and provide: robust recovery algorithms for the problems mentioned above; a new connection between sparsifiers and the Szemeredi Regularity Lemma and explicit constructions of the sparsifiers resulting from the MSS work; and an understanding of the ability of simple distributed algorithms to solve community detection problems and to deal with noise and faults. The unification is provided by a common underpinning of spectral methods, random matrix theory, and convex optimization. Such tools are used in technically similar but conceptually very different ways in the three domains. By pursuing these goals together, we will make it more likely that an idea that is natural and simple in one context will translate to an idea that is deep and unexpected in another, increasing the chances of a breakthrough.

1 971 805 €

Start date: 2019-09-01, End date: 2024-08-31

"Models of the Thermally Pulsing Asymptotic Giant Branch (TP-AGB) stellar evolutionary phase play a critical role across astrophysics, from the chemical composition of meteorites belonging to the pre-solar nebula up to galaxy evolution in the high-redshift Universe. In spite of its importance, the modelling of TP-AGB is still affected by large uncertainties that propagate into the field of extragalactic astronomy, degrading the predicting power of current population synthesis models of galaxies. The major goal of this proposal is to remedy this persistent condition of uncertainty and controversy. The solution to the TP-AGB star conundrum will be provided by a new approach, which stands on the optimised integration of a) state-of-the-art theoretical tools to account for the complex physics of TP-AGB stars (evolution, nucleosynthesis, pulsation, winds, dust formation, etc.), and b) exceptionally high-quality observations of resolved TP-AGB stellar populations in stars clusters and nearby galaxies (Magellanic Clouds, M31, dwarf galaxies up to 4 Mpc) with reliable measurements of their star formation histories. We will adopt a global calibration method, in which TP-AGB evolution models are required to simultaneously reproduce a set of well-defined observational constraints (distributions of luminosities, colours, pulsation periods, dust mass-loss rates, expansion velocities of dusty envelopes, etc.). This project will deepen our understanding of TP-AGB physics profoundly, and provide wide-spread community benefits as well. We will publicly release well-tested and reliable ``TP-AGB products'', including stellar tracks, isochrones in all photometric systems, and chemical yields for both gas and dust. Eventually these products will be embedded in the stellar population synthesis models that are routinely used to analyse the integrated galaxy observables that probe the extragalactic Universe."

1 930 628 €

Start date: 2014-05-01, End date: 2019-04-30

Determining the origin of the elements is a fundamental quest in physics and astronomy. Most of the elements in the periodic table are believed to be produced by supernovae and kilonovae. However, this has for decades been little more than a prediction from theory. Now, with a dramatically changing observational situation and new modelling capabilities, it is within our reach to determine the nucleosynthesis production and structure in these transients. To really see what supernovae and kilonovae contain, we must study their spectra in the later so called nebular phase when the inner regions become visible. This project is aimed at establishing the first picture of the origin of elements by determining the yields from supernovae and kilonovae using such analysis. To do this, new spectral synthesis methods need to be developed considering the necessary microphysical (ejecta chemistry, r-process physics, time-dependent gas state) and macrophysical (3D radiation transport) processes to obtain sufficient accuracy. These tools will then be applied to the first 3D explosion simulations of these transients now becoming available. When applied to the growing library of data emerging from automated surveys and follow-up programs, as well to the recent first kilonova observations, this will provide a breakthrough in our understanding of these transients. This development will not only allow a determination of cosmic element production, but also allow tests of theories for stellar evolution, nucleosynthesis, and explosion processes. This will in turn have fundamental impact on several fields of astrophysics such as population synthesis, galactic chemical evolution modelling, and understanding of mass transfer in the progenitor systems. It has a strong connection to recent detections of stellar-mass black holes and merging neutron stars by gravitational waves.

1 500 000 €

Start date: 2019-10-01, End date: 2024-09-30

Earthquakes represent one of our greatest natural hazards. Even a modest improvement in the ability to forecast devastating events like the 2016 sequence that destroyed the villages of Amatrice and Norcia, Italy would save thousands of lives and billions of euros. Current efforts to forecast earthquakes are hampered by a lack of reliable lab or field observations. Moreover, even when changes in rock properties prior to failure (precursors) have been found, we have not known enough about the physics to rationally extrapolate lab results to tectonic faults and account for tectonic history, local plate motion, hydrogeology, or the local P/T/chemical environment. However, recent advances show: 1) clear and consistent precursors prior to earthquake-like failure in the lab and 2) that lab earthquakes can be predicted using machine learning (ML). These works show that stick-slip failure events –the lab equivalent of earthquakes– are preceded by a cascade of micro-failure events that radiate elastic energy in a manner that foretells catastrophic failure. Remarkably, ML predicts the failure time and in some cases the magnitude of lab earthquakes. Here, I propose to connect these results with field observations and use ML to search for earthquake precursors and build predictive models for tectonic faulting. This proposal will support acquisition and analysis of seismic and geodetic data and construction of new lab equipment to unravel earthquake physics, precursors and forecasts. I will use my background in earthquake source theory, ML, fault rheology, and geodesy to address the physics of earthquake precursors, the conditions under which they can be observed for tectonic faults and the extent to which ML can forecast the spectrum of fault slip modes. My multidisciplinary team will train the next generation of researchers in earthquake science and foster a new level of broad community collaboration.

3 459 750 €

Start date: 2020-01-01, End date: 2024-12-31