67 research outputs found

    A Darcy-Cahn-Hilliard model of multiphase fluid-driven fracture

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    A Darcy-Cahn-Hilliard model coupled with damage is developed to describe multiphase-flow and fluid-driven fracturing in porous media. The model is motivated by recent experimental observations in Hele-Shaw cells of the fluid-driven fracturing of a synthetic porous medium with tunable fracture resistance. The model is derived from continuum thermodynamics and employs several simplifying assumptions, such as linear poroelasticity and viscous-dominated flow. Two distinct phase fields are used to regularize the interface between an invading and a defending fluid, as well as the ensuing damage. The damage model is a cohesive version of a phase-field model for fracture, in which model parameters allow for control over both nucleation and crack growth. Model-based simulations with finite elements are then performed to calibrate the model against recent experimental results. In particular, an experimentally-inferred phase diagram differentiating two flow regimes of porous invasion and fracturing is recovered. Finally, the model is employed to explore the parameter space beyond experimental capabilities, giving rise to the construction of an expanded phase diagram that suggests a new flow regime

    Combining metal nanoparticles and nanobodies to boost the biomedical imaging in neurodegenerative diseases

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    Introduction: In the study of neurodegenerative diseases, the possibility to follow the fate of specific cells or molecules within the whole body would be a milestone to better understand the complex evolution of disease mechanisms and to monitor the effects of therapies. The techniques available today do not allow the visualization of disease-relevant cells within the whole tridimensional biological context at high spatial resolution.Methods: Here we show the results from the first validation steps of a novel approach: by combining the conjugate nanobodies anti-glial fibrillary acidic protein (GFAP) and metal-nanoparticles (i.e. 2 nm gold NP) with X-ray phase contrast tomography (XPCT) we would be able to obtain a tridimensional visualization and identification of cells of interest together with the surrounding tissue and the vascular and neuronal networks.Results: By exploiting the X-ray attenuation properties of metal nanoparticles and the specific targeting capabilities of nanobodies, we could give XPCT the specificity it presently lacks, making it no longer a pure morphological but a molecular and targeted imaging technique. In our case, we synthesized and characterized Gold-NP/GFAP nanobody to target the astrocytes of mouse brain.Discussion: The results of the first tests presented in this paper have provided us with information on the feasibility of the approach, encouraging us to carry out further experiments in order to achieve the ultimate goal of setting up this new imaging technique

    Morphometric description of strength and degradation in porous media

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    The influence of the microstructural geometry on the behavior of porous media is widely recognized, particularly in geomaterials, but also in biomaterials and engineered materials. Recent advances in imaging techniques, such as X-ray microcomputed tomography, and in modeling make it possible to capture the exact morphometry of the microstructure with high precision. However, most existing continuum theories only partially account for the morphometry. We propose here a unifying approach to link the strength of porous materials with the necessary and sufficient microstructural information, using Minkowski functionals, as per Hadwiger’s theorem. A morphometric strength law is inferred from synthetic microstructures with a wide range of porosities and heterogeneities, through qualitative 2D phase-field simulations. Namely, damage is modeled at the microstructural level by tracking the solid-pore interfaces under mechanical loading. The strength is found to be best described by an exponential function of the morphometers, thus generalizing early works on metals and ceramics. We then show that the predictiveness of this relationship may extend to real porous media, including rocks, bones, and ceramics
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