ERC FUNDED PROJECTS

Optical, electron and probe microscopes are enabling tools for discoveries and knowledge generation in nanoscale sicence and technology. High resolution –nanoscale or molecular-, noninvasive and label-free imaging of three-dimensional soft matter-liquid interfaces has not been achieved by any microscopy method. Force microscopy (AFM) is considered the second most relevant advance in materials science since 1960. Despite its impressive range of applications, the technique has some key limitations. Force microscopy has not three dimensional depth. What lies above or in the subsurface is not readily characterized. 3DNanoMech proposes to design, build and operate a high speed force-based method for the three-dimensional characterization soft matter-liquid interfaces (3D AFM). The microscope will combine a detection method based on force perturbations, adaptive algorithms, high speed piezo actuators and quantitative-oriented multifrequency approaches. The development of the microscope cannot be separated from its applications: imaging the error-free DNA repair and to understand the relationship existing between the nanomechanical properties and the malignancy of cancer cells. Those problems encompass the different spatial –molecular-nano-mesoscopic- and time –milli to seconds- scales of the instrument. In short, 3DNanoMech aims to image, map and measure with picoNewton, millisecond and angstrom resolution soft matter surfaces and interfaces in liquid. The long-term vision of 3DNanoMech is to replace models or computer animations of bimolecular-liquid interfaces by real time, molecular resolution maps of properties and processes.

2 499 928 €

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

Although we have extensive knowledge of many important processes in cell biology, including information on many of the molecules involved and the physical interactions among them, we still do not understand most of the dynamical features that are the essence of living systems. This is particularly true for the actin cytoskeleton, a major component of the internal architecture of eukaryotic cells. In living cells, actin networks constantly assemble and disassemble filaments while maintaining an apparent stable structure, suggesting a perfect balance between the two processes. Such behaviors are called “dynamic steady states”. They confer upon actin networks a high degree of plasticity allowing them to adapt in response to external changes and enable cells to adjust to their environments. Despite their fundamental importance in the regulation of cell physiology, the basic mechanisms that control the coordinated dynamics of co-existing actin networks are poorly understood. In the AAA project, first, we will characterize the parameters that allow the coupling among co-existing actin networks at steady state. In vitro reconstituted systems will be used to control the actin nucleation patterns, the closed volume of the reaction chamber and the physical interaction of the networks. We hope to unravel the mechanism allowing the global coherence of a dynamic actin cytoskeleton. Second, we will use our unique capacity to perform dynamic micropatterning, to add or remove actin nucleation sites in real time, in order to investigate the ability of dynamic networks to adapt to changes and the role of coupled network dynamics in this emergent property. In this part, in vitro experiments will be complemented by the analysis of actin network remodeling in living cells. In the end, our project will provide a comprehensive understanding of how the adaptive response of the cytoskeleton derives from the complex interplay between its biochemical, structural and mechanical properties.

2 349 898 €

Start date: 2017-09-01, End date: 2022-08-31

Computer models based on known physical laws are our primary tool for predicting climate change. Yet the state-of-the-art models exhibit a disturbingly wide range of predictions of future climate change, especially when examined at the regional scale, which has not decreased as the models have become more comprehensive. The reasons for this are not understood. This represents a basic challenge to our fundamental understanding of climate. The divergence of model projections is presumably related to systematic model errors in the large-scale fluxes of heat, moisture and momentum that control regional aspects of climate. That these errors stubbornly persist in spite of increases in the spatial resolution of the models suggests that they are associated with errors in the representation of unresolved processes, whose effects must be parameterised. Most attention in climate science has hitherto focused on the thermodynamic aspects of climate. Dynamical aspects, which involve the atmospheric circulation, have received much less attention. However regional climate, including persistent climate regimes and extremes, is strongly controlled by atmospheric circulation patterns, which exhibit chaotic variability and whose representation in climate models depends sensitively on parameterised processes. Moreover the dynamical aspects of model projections are much less robust than the thermodynamic ones. There are good reasons to believe that model bias, the divergence of model projections, and chaotic variability are somehow related, although the relationships are not well understood. This calls for studying them together. My proposed research will focus on this problem, addressing these three aspects of the atmospheric circulation response to climate change in parallel: (i) diagnosing the sources of model error; (ii) elucidating the relationship between model error and the spread in model projections; (iii) understanding the physical mechanisms of atmospheric variability.

2 489 151 €

Start date: 2014-03-01, End date: 2020-02-29

The numerical simulation of complex compressible flow problem is still a challenge nowaday even for simple models. In our opinion, the most important hard points that need currently to be tackled and solved is how to obtain stable, scalable, very accurate, easy to code and to maintain schemes on complex geometries. The method should easily handle mesh refinement, even near the boundary where the most interesting engineering quantities have to be evaluated. Unsteady uncertainties in the model, for example in the geometry or the boundary conditions should represented efficiently.This proposal goal is to design, develop and evaluate solutions to each of the above problems. Our work program will lead to significant breakthroughs for flow simulations. More specifically, we propose to work on 3 connected problems: 1-A class of very high order numerical schemes able to easily deal with the geometry of boundaries and still can solve steep problems. The geometry is generally defined by CAD tools. The output is used to generate a mesh which is then used by the scheme. Hence, any mesh refinement process is disconnected from the CAD, a situation that prevents the spread of mesh adaptation techniques in industry! 2-A class of very high order numerical schemes which can utilize possibly solution dependant basis functions in order to lower the number of degrees of freedom, for example to compute accurately boundary layers with low resolutions. 3-A general non intrusive technique for handling uncertainties in order to deal with irregular probability density functions (pdf) and also to handle pdf that may evolve in time, for example thanks to an optimisation loop. The curse of dimensionality will be dealt thanks Harten's multiresolution method combined with sparse grid methods. Currently, and up to our knowledge, no scheme has each of these properties. This research program will have an impact on numerical schemes and industrial applications.

1 432 769 €

Start date: 2008-12-01, End date: 2013-11-30