Project acronym AROMA-CFD
Project Advanced Reduced Order Methods with Applications in Computational Fluid Dynamics
Researcher (PI) Gianluigi Rozza
Host Institution (HI) SCUOLA INTERNAZIONALE SUPERIORE DI STUDI AVANZATI DI TRIESTE
Call Details Consolidator Grant (CoG), PE1, ERC-2015-CoG
Summary The aim of AROMA-CFD is to create a team of scientists at SISSA for the development of Advanced Reduced Order Modelling techniques with a focus in Computational Fluid Dynamics (CFD), in order to face and overcome many current limitations of the state of the art and improve the capabilities of reduced order methodologies for more demanding applications in industrial, medical and applied sciences contexts. AROMA-CFD deals with strong methodological developments in numerical analysis, with a special emphasis on mathematical modelling and extensive exploitation of computational science and engineering. Several tasks have been identified to tackle important problems and open questions in reduced order modelling: study of bifurcations and instabilities in flows, increasing Reynolds number and guaranteeing stability, moving towards turbulent flows, considering complex geometrical parametrizations of shapes as computational domains into extended networks. A reduced computational and geometrical framework will be developed for nonlinear inverse problems, focusing on optimal flow control, shape optimization and uncertainty quantification. Further, all the advanced developments in reduced order modelling for CFD will be delivered for applications in multiphysics, such as fluid-structure interaction problems and general coupled phenomena involving inviscid, viscous and thermal flows, solids and porous media. The advanced developed framework within AROMA-CFD will provide attractive capabilities for several industrial and medical applications (e.g. aeronautical, mechanical, naval, off-shore, wind, sport, biomedical engineering, and cardiovascular surgery as well), combining high performance computing (in dedicated supercomputing centers) and advanced reduced order modelling (in common devices) to guarantee real time computing and visualization. A new open source software library for AROMA-CFD will be created: ITHACA, In real Time Highly Advanced Computational Applications.
Summary
The aim of AROMA-CFD is to create a team of scientists at SISSA for the development of Advanced Reduced Order Modelling techniques with a focus in Computational Fluid Dynamics (CFD), in order to face and overcome many current limitations of the state of the art and improve the capabilities of reduced order methodologies for more demanding applications in industrial, medical and applied sciences contexts. AROMA-CFD deals with strong methodological developments in numerical analysis, with a special emphasis on mathematical modelling and extensive exploitation of computational science and engineering. Several tasks have been identified to tackle important problems and open questions in reduced order modelling: study of bifurcations and instabilities in flows, increasing Reynolds number and guaranteeing stability, moving towards turbulent flows, considering complex geometrical parametrizations of shapes as computational domains into extended networks. A reduced computational and geometrical framework will be developed for nonlinear inverse problems, focusing on optimal flow control, shape optimization and uncertainty quantification. Further, all the advanced developments in reduced order modelling for CFD will be delivered for applications in multiphysics, such as fluid-structure interaction problems and general coupled phenomena involving inviscid, viscous and thermal flows, solids and porous media. The advanced developed framework within AROMA-CFD will provide attractive capabilities for several industrial and medical applications (e.g. aeronautical, mechanical, naval, off-shore, wind, sport, biomedical engineering, and cardiovascular surgery as well), combining high performance computing (in dedicated supercomputing centers) and advanced reduced order modelling (in common devices) to guarantee real time computing and visualization. A new open source software library for AROMA-CFD will be created: ITHACA, In real Time Highly Advanced Computational Applications.
Max ERC Funding
1 656 579 €
Duration
Start date: 2016-05-01, End date: 2021-04-30
Project acronym BioMNP
Project Understanding the interaction between metal nanoparticles and biological membranes
Researcher (PI) Giulia Rossi
Host Institution (HI) UNIVERSITA DEGLI STUDI DI GENOVA
Call Details Starting Grant (StG), PE3, ERC-2015-STG
Summary The BioMNP objective is the molecular-level understanding of the interactions between surface functionalized metal nanoparticles and biological membranes, by means of cutting-edge computational techniques and new molecular models.
Metal nanoparticles (NP) play more and more important roles in pharmaceutical and medical technology as diagnostic or therapeutic devices. Metal NPs can nowadays be engineered in a multitude of shapes, sizes and compositions, and they can be decorated with an almost infinite variety of functionalities. Despite such technological advances, there is still poor understanding of the molecular processes that drive the interactions of metal NPs with cells. Cell membranes are the first barrier encountered by NPs entering living organisms. The understanding and control of the interaction of nanoparticles with biological membranes is therefore of paramount importance to understand the molecular basis of the NP biological effects.
BioMNP will go beyond the state of the art by rationalizing the complex interplay of NP size, composition, functionalization and aggregation state during the interaction with model biomembranes. Membranes, in turn, will be modelled at an increasing level of complexity in terms of lipid composition and phase. BioMNP will rely on cutting-edge simulation techniques and facilities, and develop new coarse-grained models grounded on finer-level atomistic simulations, to study the NP-membrane interactions on an extremely large range of length and time scales.
BioMNP will benefit from important and complementary experimental collaborations, will propose interpretations of the available experimental data and make predictions to guide the design of functional, non-toxic metal nanoparticles for biomedical applications. BioMNP aims at answering fundamental questions at the crossroads of physics, biology and chemistry. Its results will have an impact on nanomedicine, toxicology, nanotechnology and material sciences.
Summary
The BioMNP objective is the molecular-level understanding of the interactions between surface functionalized metal nanoparticles and biological membranes, by means of cutting-edge computational techniques and new molecular models.
Metal nanoparticles (NP) play more and more important roles in pharmaceutical and medical technology as diagnostic or therapeutic devices. Metal NPs can nowadays be engineered in a multitude of shapes, sizes and compositions, and they can be decorated with an almost infinite variety of functionalities. Despite such technological advances, there is still poor understanding of the molecular processes that drive the interactions of metal NPs with cells. Cell membranes are the first barrier encountered by NPs entering living organisms. The understanding and control of the interaction of nanoparticles with biological membranes is therefore of paramount importance to understand the molecular basis of the NP biological effects.
BioMNP will go beyond the state of the art by rationalizing the complex interplay of NP size, composition, functionalization and aggregation state during the interaction with model biomembranes. Membranes, in turn, will be modelled at an increasing level of complexity in terms of lipid composition and phase. BioMNP will rely on cutting-edge simulation techniques and facilities, and develop new coarse-grained models grounded on finer-level atomistic simulations, to study the NP-membrane interactions on an extremely large range of length and time scales.
BioMNP will benefit from important and complementary experimental collaborations, will propose interpretations of the available experimental data and make predictions to guide the design of functional, non-toxic metal nanoparticles for biomedical applications. BioMNP aims at answering fundamental questions at the crossroads of physics, biology and chemistry. Its results will have an impact on nanomedicine, toxicology, nanotechnology and material sciences.
Max ERC Funding
1 131 250 €
Duration
Start date: 2016-04-01, End date: 2021-03-31
Project acronym BOOST
Project Biomimetic trick to re-balance Osteblast-Osteoclast loop in osteoporoSis treatment: a Topological and materials driven approach
Researcher (PI) Chiara Silvia Vitale Brovarone
Host Institution (HI) POLITECNICO DI TORINO
Call Details Consolidator Grant (CoG), PE8, ERC-2015-CoG
Summary One out of 5 people in their fifties will experience a bone fracture due to osteoporosis (OP)-induced fragility in their lifetime. The OP socio-economic burden is dramatic and involves tens of millions of people in the EU, with a steadily increasing number due to population ageing. Current treatments entail drug-therapy coupled with a healthy lifestyle but OP fractures need mechanical fixation to rapidly achieve union: the contribution of biomaterial scientists in this field is still far from taking its expected leading role in cutting-edge research. Bone remodelling is a well-coordinated process of bone resorption by osteoclasts followed by the production of new bone by osteoblasts. This process occurs continuously throughout life in a coupling with a positive balance during growth and negative with ageing, which can result in OP. We believe that an architecture driven stimulation of the osteoclast/osteoblast coupling, with an avant-garde focus on osteoclasts activity, is the key to success in treating unbalanced bone remodelling. We aim to manufacture a scaffold that mimics healthy bone features which will establish a new microenvironment favoring a properly stimulated and active population of osteoclasts and osteoblasts, i.e. a well-balanced bone cooperation. After 5 years we will be able to prove the efficacy of this approach. A benchmark will be set up for OP fracture treatment and for the realization of smart bone substitutes that will be able to locally “trick” aged bone cells stimulating them to act as healthy ones. BOOST results will have an unprecedented impact on the scientific research community, opening a new approach to set up smart, biomimetic strategies to treat aged, unbalanced bone tissues and to reduce OP-associated disabilities and financial burdens.
Summary
One out of 5 people in their fifties will experience a bone fracture due to osteoporosis (OP)-induced fragility in their lifetime. The OP socio-economic burden is dramatic and involves tens of millions of people in the EU, with a steadily increasing number due to population ageing. Current treatments entail drug-therapy coupled with a healthy lifestyle but OP fractures need mechanical fixation to rapidly achieve union: the contribution of biomaterial scientists in this field is still far from taking its expected leading role in cutting-edge research. Bone remodelling is a well-coordinated process of bone resorption by osteoclasts followed by the production of new bone by osteoblasts. This process occurs continuously throughout life in a coupling with a positive balance during growth and negative with ageing, which can result in OP. We believe that an architecture driven stimulation of the osteoclast/osteoblast coupling, with an avant-garde focus on osteoclasts activity, is the key to success in treating unbalanced bone remodelling. We aim to manufacture a scaffold that mimics healthy bone features which will establish a new microenvironment favoring a properly stimulated and active population of osteoclasts and osteoblasts, i.e. a well-balanced bone cooperation. After 5 years we will be able to prove the efficacy of this approach. A benchmark will be set up for OP fracture treatment and for the realization of smart bone substitutes that will be able to locally “trick” aged bone cells stimulating them to act as healthy ones. BOOST results will have an unprecedented impact on the scientific research community, opening a new approach to set up smart, biomimetic strategies to treat aged, unbalanced bone tissues and to reduce OP-associated disabilities and financial burdens.
Max ERC Funding
1 977 500 €
Duration
Start date: 2016-05-01, End date: 2021-12-31
Project acronym CAVE
Project Challenges and Advancements in Virtual Elements
Researcher (PI) Lourenco Beirao da veiga
Host Institution (HI) UNIVERSITA' DEGLI STUDI DI MILANO-BICOCCA
Call Details Consolidator Grant (CoG), PE1, ERC-2015-CoG
Summary The Virtual Element Method (VEM) is a novel technology for the discretization of partial differential equations (PDEs), that shares the same variational background as the Finite Element Method. First but not only, the VEM responds to the strongly increasing interest in using general polyhedral and polygonal meshes in the approximation of PDEs without the limit of using tetrahedral or hexahedral grids. By avoiding the explicit integration of the shape functions that span the discrete space and introducing an innovative construction of the stiffness matrixes, the VEM acquires very interesting properties and advantages with respect to more standard Galerkin methods, yet still keeping the same coding complexity. For instance, the VEM easily allows for polygonal/polyhedral meshes (even non-conforming) with non-convex elements and possibly with curved faces; it allows for discrete spaces of arbitrary C^k regularity on unstructured meshes.
The main scope of the project is to address the recent theoretical challenges posed by VEM and to assess whether this promising technology can achieve a breakthrough in applications. First, the theoretical and computational foundations of VEM will be made stronger. A deeper theoretical insight, supported by a wider numerical experience on benchmark problems, will be developed to gain a better understanding of the method's potentials and set the foundations for more applicative purposes. Second, we will focus our attention on two tough and up-to-date problems of practical interest: large deformation elasticity (where VEM can yield a dramatically more efficient handling of material inclusions, meshing of the domain and grid adaptivity, plus a much stronger robustness with respect to large grid distortions) and the cardiac bidomain model (where VEM can lead to a more accurate domain approximation through MRI data, a flexible refinement/de-refinement procedure along the propagation front, to an exact satisfaction of conservation laws).
Summary
The Virtual Element Method (VEM) is a novel technology for the discretization of partial differential equations (PDEs), that shares the same variational background as the Finite Element Method. First but not only, the VEM responds to the strongly increasing interest in using general polyhedral and polygonal meshes in the approximation of PDEs without the limit of using tetrahedral or hexahedral grids. By avoiding the explicit integration of the shape functions that span the discrete space and introducing an innovative construction of the stiffness matrixes, the VEM acquires very interesting properties and advantages with respect to more standard Galerkin methods, yet still keeping the same coding complexity. For instance, the VEM easily allows for polygonal/polyhedral meshes (even non-conforming) with non-convex elements and possibly with curved faces; it allows for discrete spaces of arbitrary C^k regularity on unstructured meshes.
The main scope of the project is to address the recent theoretical challenges posed by VEM and to assess whether this promising technology can achieve a breakthrough in applications. First, the theoretical and computational foundations of VEM will be made stronger. A deeper theoretical insight, supported by a wider numerical experience on benchmark problems, will be developed to gain a better understanding of the method's potentials and set the foundations for more applicative purposes. Second, we will focus our attention on two tough and up-to-date problems of practical interest: large deformation elasticity (where VEM can yield a dramatically more efficient handling of material inclusions, meshing of the domain and grid adaptivity, plus a much stronger robustness with respect to large grid distortions) and the cardiac bidomain model (where VEM can lead to a more accurate domain approximation through MRI data, a flexible refinement/de-refinement procedure along the propagation front, to an exact satisfaction of conservation laws).
Max ERC Funding
980 634 €
Duration
Start date: 2016-07-01, End date: 2021-06-30
Project acronym COMPASS
Project Control for Orbit Manoeuvring through Perturbations for Application to Space Systems
Researcher (PI) Camilla Colombo
Host Institution (HI) POLITECNICO DI MILANO
Call Details Starting Grant (StG), PE8, ERC-2015-STG
Summary Space benefits mankind through the services it provides to Earth. Future space activities progress thanks to space transfer and are safeguarded by space situation awareness. Natural orbit perturbations are responsible for the trajectory divergence from the nominal two-body problem, increasing the requirements for orbit control; whereas, in space situation awareness, they influence the orbit evolution of space debris that could cause hazard to operational spacecraft and near Earth objects that may intersect the Earth. However, this project proposes to leverage the dynamics of natural orbit perturbations to significantly reduce current extreme high mission cost and create new opportunities for space exploration and exploitation.
The COMPASS project will bridge over the disciplines of orbital dynamics, dynamical systems theory, optimisation and space mission design by developing novel techniques for orbit manoeuvring by “surfing” through orbit perturbations. The use of semi-analytical techniques and tools of dynamical systems theory will lay the foundation for a new understanding of the dynamics of orbit perturbations. We will develop an optimiser that progressively explores the phase space and, though spacecraft parameters and propulsion manoeuvres, governs the effect of perturbations to reach the desired orbit. It is the ambition of COMPASS to radically change the current space mission design philosophy: from counteracting disturbances, to exploiting natural and artificial perturbations.
COMPASS will benefit from the extensive international network of the PI, including the ESA, NASA, JAXA, CNES, and the UK space agency. Indeed, the proposed idea of optimal navigation through orbit perturbations will address various major engineering challenges in space situation awareness, for application to space debris evolution and mitigation, missions to asteroids for their detection, exploration and deflection, and in space transfers, for perturbation-enhanced trajectory design.
Summary
Space benefits mankind through the services it provides to Earth. Future space activities progress thanks to space transfer and are safeguarded by space situation awareness. Natural orbit perturbations are responsible for the trajectory divergence from the nominal two-body problem, increasing the requirements for orbit control; whereas, in space situation awareness, they influence the orbit evolution of space debris that could cause hazard to operational spacecraft and near Earth objects that may intersect the Earth. However, this project proposes to leverage the dynamics of natural orbit perturbations to significantly reduce current extreme high mission cost and create new opportunities for space exploration and exploitation.
The COMPASS project will bridge over the disciplines of orbital dynamics, dynamical systems theory, optimisation and space mission design by developing novel techniques for orbit manoeuvring by “surfing” through orbit perturbations. The use of semi-analytical techniques and tools of dynamical systems theory will lay the foundation for a new understanding of the dynamics of orbit perturbations. We will develop an optimiser that progressively explores the phase space and, though spacecraft parameters and propulsion manoeuvres, governs the effect of perturbations to reach the desired orbit. It is the ambition of COMPASS to radically change the current space mission design philosophy: from counteracting disturbances, to exploiting natural and artificial perturbations.
COMPASS will benefit from the extensive international network of the PI, including the ESA, NASA, JAXA, CNES, and the UK space agency. Indeed, the proposed idea of optimal navigation through orbit perturbations will address various major engineering challenges in space situation awareness, for application to space debris evolution and mitigation, missions to asteroids for their detection, exploration and deflection, and in space transfers, for perturbation-enhanced trajectory design.
Max ERC Funding
1 499 021 €
Duration
Start date: 2016-08-01, End date: 2021-07-31
Project acronym DMAP
Project Data Mining Algorithms in Practice
Researcher (PI) Flavio Chierichetti
Host Institution (HI) UNIVERSITA DEGLI STUDI DI ROMA LA SAPIENZA
Call Details Starting Grant (StG), PE6, ERC-2015-STG
Summary Data Mining algorithms are a cornerstone of today's Internet-related services and products. We aim to tackle some of the most important problems in Data Mining --- our goal is to develop a systematic theoretical understanding of certain simple algorithms that, in spite of being at the core of today's web industry, are not yet well understood in terms of their properties and performances, and to develop new simple algorithms for fundamental problems in this domain that have so far escaped a satisfactory solution.
Summary
Data Mining algorithms are a cornerstone of today's Internet-related services and products. We aim to tackle some of the most important problems in Data Mining --- our goal is to develop a systematic theoretical understanding of certain simple algorithms that, in spite of being at the core of today's web industry, are not yet well understood in terms of their properties and performances, and to develop new simple algorithms for fundamental problems in this domain that have so far escaped a satisfactory solution.
Max ERC Funding
1 137 500 €
Duration
Start date: 2016-02-01, End date: 2021-01-31
Project acronym FIRSTORM
Project Modeling first-order Mott transitions
Researcher (PI) Michele FABRIZIO
Host Institution (HI) SCUOLA INTERNAZIONALE SUPERIORE DI STUDI AVANZATI DI TRIESTE
Call Details Advanced Grant (AdG), PE3, ERC-2015-AdG
Summary Mott insulators are “unsuccessful metals”, where conduction is impeded by strong Coulomb repulsion. Their use in microelectronics started to be seriously considered in the 1990s, when first reports of field-effect switches appeared. These attempts were motivated by the expectation that the dielectric breakdown in Mott insulators could suddenly release all formerly localized carriers, a significant potential for nanometer scaling. Over the very last years striking experimental data on narrow-gap Mott insulators have finally materialized that expectation disclosing an unprecedented scenario where the metal phase actually stabilized was only metastable at equilibrium, which foreshadows exciting potential applications. These new data call for an urgent theoretical understanding so far missing. In fact, the conventional portrait of Mott insulators has overlooked that Mott transitions are mostly 1st order, implying an extended insulator-metal coexistence. As a result, bias or light may nucleate long-lived metastable metal droplets within the stable insulator, as indeed seen in experiments. The unexpected 1st order nature of dielectric breakdown in Mott insulators and its poorly explored but important conceptual and practical consequences are the scope of my theoretical project. I will model known Mott insulators identifying the variety of mechanisms (Coulomb, lattice distortions) that support and boost the 1st order character of the Mott transition. I will model and study insulator-metal coexistence and associated novel phenomena such as those related to nucleation and wetting at the interface, including possible unexplored role of quantum fluctuations. I will then simulate in model calculations the spatially inhomogeneous dynamics and non-equilibrium pathways across the 1st order Mott transition, relating the results to ongoing experiments in top groups. The outcome of this project is expected to yield immediate conceptual as well as later technological consequences.
Summary
Mott insulators are “unsuccessful metals”, where conduction is impeded by strong Coulomb repulsion. Their use in microelectronics started to be seriously considered in the 1990s, when first reports of field-effect switches appeared. These attempts were motivated by the expectation that the dielectric breakdown in Mott insulators could suddenly release all formerly localized carriers, a significant potential for nanometer scaling. Over the very last years striking experimental data on narrow-gap Mott insulators have finally materialized that expectation disclosing an unprecedented scenario where the metal phase actually stabilized was only metastable at equilibrium, which foreshadows exciting potential applications. These new data call for an urgent theoretical understanding so far missing. In fact, the conventional portrait of Mott insulators has overlooked that Mott transitions are mostly 1st order, implying an extended insulator-metal coexistence. As a result, bias or light may nucleate long-lived metastable metal droplets within the stable insulator, as indeed seen in experiments. The unexpected 1st order nature of dielectric breakdown in Mott insulators and its poorly explored but important conceptual and practical consequences are the scope of my theoretical project. I will model known Mott insulators identifying the variety of mechanisms (Coulomb, lattice distortions) that support and boost the 1st order character of the Mott transition. I will model and study insulator-metal coexistence and associated novel phenomena such as those related to nucleation and wetting at the interface, including possible unexplored role of quantum fluctuations. I will then simulate in model calculations the spatially inhomogeneous dynamics and non-equilibrium pathways across the 1st order Mott transition, relating the results to ongoing experiments in top groups. The outcome of this project is expected to yield immediate conceptual as well as later technological consequences.
Max ERC Funding
1 422 684 €
Duration
Start date: 2016-09-01, End date: 2021-08-31
Project acronym Fornax
Project Galaxy evolution in dense environments
Researcher (PI) Paolo Serra
Host Institution (HI) ISTITUTO NAZIONALE DI ASTROFISICA
Call Details Starting Grant (StG), PE9, ERC-2015-STG
Summary The Universe around us is populated with galaxies, each containing from millions to tens of billions of individual stars. Far from being immutable, galaxies undergo profound changes as they age. Their evolution depends on their position in the cosmic web, a network of sheets and filaments of matter that stretches across the entire Universe. The goal of FORNAX is to study the evolution of galaxies in the densest regions of the cosmic web, galaxy clusters. In these regions, a number of physical processes are thought to make galaxies lose their cold gas – the material from which new stars are born – and change their appearance dramatically. I will study these processes in action by observing the flow of cold gas in and out of galaxies living inside an important, nearby cluster of galaxies: Fornax.
I will observe Fornax for 2,450 hours with MeerKAT, a new, state-of-the-art radio telescope precursor of the Square Kilometre Array. Thanks to the unprecedented combination of sensitivity, resolution and sky-coverage of my survey, I will reveal the most subtle signs of the removal of gas from galaxies, I will detect the smallest gas-bearing galaxies in the cluster, and I will hunt the elusive cold gas which, according to cosmological theories, floats in the space between galaxies along the filaments of the cosmic web.
Summary
The Universe around us is populated with galaxies, each containing from millions to tens of billions of individual stars. Far from being immutable, galaxies undergo profound changes as they age. Their evolution depends on their position in the cosmic web, a network of sheets and filaments of matter that stretches across the entire Universe. The goal of FORNAX is to study the evolution of galaxies in the densest regions of the cosmic web, galaxy clusters. In these regions, a number of physical processes are thought to make galaxies lose their cold gas – the material from which new stars are born – and change their appearance dramatically. I will study these processes in action by observing the flow of cold gas in and out of galaxies living inside an important, nearby cluster of galaxies: Fornax.
I will observe Fornax for 2,450 hours with MeerKAT, a new, state-of-the-art radio telescope precursor of the Square Kilometre Array. Thanks to the unprecedented combination of sensitivity, resolution and sky-coverage of my survey, I will reveal the most subtle signs of the removal of gas from galaxies, I will detect the smallest gas-bearing galaxies in the cluster, and I will hunt the elusive cold gas which, according to cosmological theories, floats in the space between galaxies along the filaments of the cosmic web.
Max ERC Funding
1 500 000 €
Duration
Start date: 2016-10-01, End date: 2021-09-30
Project acronym FricLess
Project A seamless multi-scale model for contact, friction, and solid lubrication
Researcher (PI) Lucia Nicola
Host Institution (HI) UNIVERSITA DEGLI STUDI DI PADOVA
Call Details Consolidator Grant (CoG), PE8, ERC-2015-CoG
Summary Friction and wear are liable for enormous losses in terms of energy and resources in modern society. Costs related to unwanted friction in industrialised countries are estimated to be about 3% of the gross domestic product. Urgency is even greater nowadays as friction between micro-components has become the bottleneck of several applications for which miniaturisation is critical.
Lubrication is a commonly adopted solution to reduce friction. Graphite is a broadly used solid lubricant for large scale applications, while the lubricating properties of a few-layers graphene hold great promise especially for smaller scale applications. At present, our knowledge of the friction and lubrication of rough surfaces is essentially phenomenological. This is because friction is only deceivingly a simple mechanisms, which instead requires understanding of physical phenomena simultaneously acting at different length scales. The change in contact size, which controls the friction stress, depends on nano-scale phenomena such as atomic de-adhesion, sliding, dislocation nucleation in metals, but also on micro- and macro-scale phenomena as (size-dependent) plastic deformation.
The objective of this proposal is to reach an unprecedented understanding of metal friction and lubrication by accounting, for the first time, for all relevant phenomena occurring from the atomic to the macro-scale, and their interplay.
To this end, a seamless concurrent multi-scale model will be developed. The power of this new model lies in its capability of describing three-dimensional bodies with realistic roughness in sliding lubricated contact, with the accuracy of an atomistic simulation.
This research builds towards a complete picture of metal friction and lubrication. The materials chosen for the proposed research are copper and multi-layer graphene. However, the model that will be developed is general and can be used to study different materials, lubricants and environmental conditions.
Summary
Friction and wear are liable for enormous losses in terms of energy and resources in modern society. Costs related to unwanted friction in industrialised countries are estimated to be about 3% of the gross domestic product. Urgency is even greater nowadays as friction between micro-components has become the bottleneck of several applications for which miniaturisation is critical.
Lubrication is a commonly adopted solution to reduce friction. Graphite is a broadly used solid lubricant for large scale applications, while the lubricating properties of a few-layers graphene hold great promise especially for smaller scale applications. At present, our knowledge of the friction and lubrication of rough surfaces is essentially phenomenological. This is because friction is only deceivingly a simple mechanisms, which instead requires understanding of physical phenomena simultaneously acting at different length scales. The change in contact size, which controls the friction stress, depends on nano-scale phenomena such as atomic de-adhesion, sliding, dislocation nucleation in metals, but also on micro- and macro-scale phenomena as (size-dependent) plastic deformation.
The objective of this proposal is to reach an unprecedented understanding of metal friction and lubrication by accounting, for the first time, for all relevant phenomena occurring from the atomic to the macro-scale, and their interplay.
To this end, a seamless concurrent multi-scale model will be developed. The power of this new model lies in its capability of describing three-dimensional bodies with realistic roughness in sliding lubricated contact, with the accuracy of an atomistic simulation.
This research builds towards a complete picture of metal friction and lubrication. The materials chosen for the proposed research are copper and multi-layer graphene. However, the model that will be developed is general and can be used to study different materials, lubricants and environmental conditions.
Max ERC Funding
1 999 985 €
Duration
Start date: 2016-06-01, End date: 2022-11-30
Project acronym GeCo
Project Data-Driven Genomic Computing
Researcher (PI) stefano CERI
Host Institution (HI) POLITECNICO DI MILANO
Call Details Advanced Grant (AdG), PE6, ERC-2015-AdG
Summary Next-generation sequencing technology has dramatically reduced the cost and time of reading the DNA. Huge investments are targeted to sequencing the DNA of large populations, and repositories of well-curated sequence data are being collected. Answers to fundamental biomedical problems are hidden in these data, e.g. how cancer arises, how driving mutations occur, how much cancer is dependent on environment. But genomic computing has not comparatively evolved. Bioinformatics has been driven by specific needs and distracted from a foundational approach; hundreds of methods solve individual problems, but miss the broad perspective.
The objective of GeCo is to rethink genomic computing through the lens of basic data management. We will first design the data model, using few general abstractions that guarantee interoperability between existing data formats. Next, we will design a new-generation query language inspired by classic relational algebra and extended with orthogonal, domain-specific abstractions for genomics. Query processing will trace metadata and computation steps, opening doors to the seamless integration of descriptive statistics and high-level data analysis (e.g., DNA region clustering and extraction of regulatory networks).
Genomic computing is a “big data” problem, therefore we will also achieve computational efficiency by using parallel computing on both clusters and public clouds; the choice of a suitable data model and of computational abstractions will boost performance in a principled way. The resulting technology will be applicable to individual and federated repositories, and will be exploited for providing integrated access to curated data, made available by large consortia, through user-friendly search services. Our most far-fetching vision is to move towards an Internet of Genomes exploiting data indexing and crawling. The PI’s background in distributed data, data modelling, query processing and search will drive a radical paradigm shift.
Summary
Next-generation sequencing technology has dramatically reduced the cost and time of reading the DNA. Huge investments are targeted to sequencing the DNA of large populations, and repositories of well-curated sequence data are being collected. Answers to fundamental biomedical problems are hidden in these data, e.g. how cancer arises, how driving mutations occur, how much cancer is dependent on environment. But genomic computing has not comparatively evolved. Bioinformatics has been driven by specific needs and distracted from a foundational approach; hundreds of methods solve individual problems, but miss the broad perspective.
The objective of GeCo is to rethink genomic computing through the lens of basic data management. We will first design the data model, using few general abstractions that guarantee interoperability between existing data formats. Next, we will design a new-generation query language inspired by classic relational algebra and extended with orthogonal, domain-specific abstractions for genomics. Query processing will trace metadata and computation steps, opening doors to the seamless integration of descriptive statistics and high-level data analysis (e.g., DNA region clustering and extraction of regulatory networks).
Genomic computing is a “big data” problem, therefore we will also achieve computational efficiency by using parallel computing on both clusters and public clouds; the choice of a suitable data model and of computational abstractions will boost performance in a principled way. The resulting technology will be applicable to individual and federated repositories, and will be exploited for providing integrated access to curated data, made available by large consortia, through user-friendly search services. Our most far-fetching vision is to move towards an Internet of Genomes exploiting data indexing and crawling. The PI’s background in distributed data, data modelling, query processing and search will drive a radical paradigm shift.
Max ERC Funding
2 500 000 €
Duration
Start date: 2016-09-01, End date: 2021-08-31