ERC FUNDED PROJECTS

Rupture of Aortic Aneurysms (AA), which kills more than 30 000 persons every year in Europe and the USA, is a complex phenomenon that occurs when the wall stress exceeds the local strength of the aorta due to degraded properties of the tissue. The state of the art in AA biomechanics and mechanobiology reveals that major scientific challenges still have to be addressed to permit patient-specific computational predictions of AA rupture and enable localized repair of the structure with targeted pharmacologic treatment. A first challenge relates to ensuring an objective prediction of localized mechanisms preceding rupture. A second challenge relates to modelling the patient-specific evolutions of material properties leading to the localized mechanisms preceding rupture. Addressing these challenges is the aim of the BIOLOCHANICS proposal. We will take into account internal length-scales controlling localization mechanisms preceding AA rupture by implementing an enriched, also named nonlocal, continuum damage theory in the computational models of AA biomechanics and mechanobiology. We will also develop very advanced experiments, based on full-field optical measurements, aimed at characterizing localization mechanisms occurring in aortic tissues and at identifying local distributions of material properties at different stages of AA progression. A first in vivo application will be performed on genetic and pharmacological models of mice and rat AA. Eventually, a retrospective clinical study involving more than 100 patients at the Saint-Etienne University hospital will permit calibrating estimations of AA rupture risk thanks to our novel approaches and infuse them into future clinical practice. Through the achievements of BIOLOCHANICS, nonlocal mechanics will be possibly extended to other soft tissues for applications in orthopaedics, oncology, sport biomechanics, interventional surgery, human safety, cell biology, etc.

1 999 396 €

Start date: 2015-05-01, End date: 2020-04-30

Why do ethnic differences matter in some cases and not in others? What determines the strength of ethnic self-identification? This question is central to understanding the consequences of ethnic divisions for conflict and economic development and their policy implications but it was neglected by economic research until now. This project aims at filling this gap by endogenizing ethnic identity. We study how the salience of ethnic differences depends on economic and social context and policies of nation building. Our research program is organized around 3 pillars focusing on social, economic, and political determinants of ethnic tensions, respectively. The first pillar tests social psychology theories of ethnic identity using natural experiments, generated by forced mass movements of ethnic groups in Eastern Europe and from Eastern Europe to Central Asia as a result of WWII. The second pillar studies how market interactions between representatives of different ethnic groups and, in particular, ethnic occupational segregation affects ethnic tensions in the context of historical anti-Jewish violence following agro-climatic income shocks in the 19th and 20th century Eastern Europe. The third pillar focuses on the effects of political manipulation on ethnic conflict in the context of the historical experiment of nation building in Central Asia. It studies how political empowerment of a certain ethnic elite in a multi-ethnic traditional society coupled with a set of nation-building policies affects ethnic conflicts depending on the pre-existing ethnic mix and the distribution of political power among ethnic elites. This research will shed light on factors that make ethnic diversity important for conflict and economic development.

1 598 308 €

Start date: 2015-11-01, End date: 2020-10-31

Icing of surfaces is common in nature and technology, affecting everyday life and often causing catastrophic events. Despite progress in recent years in the area of hydrophobicity, engineered surfaces that can be employed in applications based on their intrinsic icephobicity, going beyond classical additional chemical coatings or heating treatments, are not a reality. Understanding and counteracting surface icing brings with it significant scientific challenges, which form an intersection of nucleation thermodynamics, interfacial thermofluidics and surface nanoengineering/science. This project will investigate important mesoscale phenomena (a term used here to summarily describe phenomena manifesting themselves in the spatial range from the order of a nanometer to a hundred microns), which affect the behavior of water on surfaces with respect to icing. With the resulting, unifying knowledge base, the aim is to identify pathways for the design and fabrication of a new class of intrinsically icephobic surfaces, based on their a-priori engineered composition and texture. Our aim is to identify anti-nucleation and anti-wetting phenomena, leading to surfaces having long ice nucleation time scales, low water contact and retention, and low ice adhesion. The effects of surface texture curvature on ice nucleation, local liquid confinement on freezing point depression, and mesoscale texture features on interfacial thermofluidics, have intertwined and sometimes counteracting impacts on surface icing behavior, which we aim at unraveling, to determine pathways to high performance surfaces. Connected to all this is the employment of advanced surface texture fabrication and methods to perform the necessary experiments, lending consideration to the development of such surfaces for future applications. Beyond icephobicity, this research has clear implications to the characterization of mesoscale phase change phenomena, for multiphase heat and mass transfer processes and devices.

2 498 043 €

Start date: 2015-11-01, End date: 2020-10-31

It is now possible to make an enormous spectrum of different, novel nanoporous materials simply by changing the building blocks in the synthesis of Metal Organic Frameworks (MOF) or related materials. This unique chemical tunability allows us to tailor-make materials that are optimal for a given application. The promise of finding just the right material seems remote however: because of practical limitations we can only ever synthesize, characterize, and test a tiny fraction of all possible materials. To take full advantage of this development, therefore, we need to develop alternative techniques, collectively referred to as Materials Genomics, to rapidly screen large numbers of materials and obtain fundamental insights into the chemical nature of the ideal material for a given application. The PI will tackle the challenge and promise posed by this unprecedented chemical tunability through the development of a multi-scale computational approach, which aims to reliably predict the performance of novel materials before synthesis. We will develop methodologies to generate libraries of representative sets of synthesizable hypothetical materials and perform large-scale screening of these libraries. These studies should give us fundamental insights into the common molecular features of the top-performing materials. The methods developed will be combined into an open access infrastructure in which our hypothetical materials are publicly accessible for data mining and big-data analysis. The project is organized in three Work Packages, each centered around finding better materials for carbon capture: (1) screen materials for gas separations and develop the tools to predict the best materials for carbon capture; (2) gain insights into and develop a computational methodology for screening the mechanical properties of nanoporous materials; (3) achieve an understanding of the amine-CO2 chemistry in diamine-appended MOFs and use this to predict their performance.

2 486 720 €

Start date: 2015-11-01, End date: 2020-10-31