20 resultados para Constant Loading Rate


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The thermal and mechanical behaviour of isotactic polypropylene (iPP) nanocomposites reinforced with different loadings of inorganic fullerene-like tungsten disulfide (IF-WS2) nanoparticles was investigated. The IF-WS2 noticeably enhanced the polymer stiffness and strength, ascribed to their uniform dispersion, the formation of a large nanoparticle?matrix interface combined with a nucleating effect on iPP crystallization. Their reinforcement effect was more pronounced at high temperatures. However, a drop in ductility and toughness was found at higher IF-WS2 concentrations. The tensile behaviour of the nanocomposites was extremely sensitive to the strain rate and temperature, and their yield strength was properly described by the Eyring s equation. The activation energy increased while the activation volume decreased with increasing nanoparticle loading, indicating a reduction in polymer chain motion. The nanoparticles improved the thermomechanical properties of iPP: raised the glass transition and heat deflection temperatures while decreased the coefficient of thermal expansion. The nanocomposites also displayed superior flame retardancy with longer ignition time and reduced peak heat release rate. Further, a gradual rise in thermal conductivity was found with increasing IF-WS2 loading both in the glassy and rubbery states. The results presented herein highlight the benefits and high potential of using IF-nanoparticles for enhancing the thermomechanical properties of thermoplastic polymers compared to other nanoscale fillers.

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With the growing body of research on traumatic brain injury and spinal cord injury, computational neuroscience has recently focused its modeling efforts on neuronal functional deficits following mechanical loading. However, in most of these efforts, cell damage is generally only characterized by purely mechanistic criteria, function of quantities such as stress, strain or their corresponding rates. The modeling of functional deficits in neurites as a consequence of macroscopic mechanical insults has been rarely explored. In particular, a quantitative mechanically based model of electrophysiological impairment in neuronal cells has only very recently been proposed (Jerusalem et al., 2013). In this paper, we present the implementation details of Neurite: the finite difference parallel program used in this reference. Following the application of a macroscopic strain at a given strain rate produced by a mechanical insult, Neurite is able to simulate the resulting neuronal electrical signal propagation, and thus the corresponding functional deficits. The simulation of the coupled mechanical and electrophysiological behaviors requires computational expensive calculations that increase in complexity as the network of the simulated cells grows. The solvers implemented in Neurite-explicit and implicit-were therefore parallelized using graphics processing units in order to reduce the burden of the simulation costs of large scale scenarios. Cable Theory and Hodgkin-Huxley models were implemented to account for the electrophysiological passive and active regions of a neurite, respectively, whereas a coupled mechanical model accounting for the neurite mechanical behavior within its surrounding medium was adopted as a link between lectrophysiology and mechanics (Jerusalem et al., 2013). This paper provides the details of the parallel implementation of Neurite, along with three different application examples: a long myelinated axon, a segmented dendritic tree, and a damaged axon. The capabilities of the program to deal with large scale scenarios, segmented neuronal structures, and functional deficits under mechanical loading are specifically highlighted.

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The mechanical behavior and the deformation and failure micromechanisms of a thermally-bonded polypropylene nonwoven fabric were studied as a function of temperature and strain rate. Mechanical tests were carried out from 248 K (below the glass transition temperature) up to 383 K at strain rates in the range ≈10−3 s−1 to 10−1 s−1. In addition, individual fibers extracted from the nonwoven fabric were tested under the same conditions. Micromechanisms of deformation and failure at the fiber level were ascertained by means of mechanical tests within the scanning electron microscope while the strain distribution at the macroscopic level upon loading was determined by means of digital image correlation. It was found that the nonwoven behavior was mainly controlled by the properties of the fibers and of the interfiber bonds. Fiber properties determined the nonlinear behavior before the peak load while the interfiber bonds controlled the localization of damage after the peak load. The influence of these properties on the strength, ductility and energy absorbed during deformation is discussed from the experimental observations.

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We report on an experimental study on the spin-waves relaxation rate in two series of nanodisks of diameter ϕ=300 , 500, and 700 nm, patterned out of two systems: a 20 nm thick yttrium iron garnet (YIG) film grown by pulsed laser deposition either bare or covered by 13 nm of Pt. Using a magnetic resonance force microscope, we measure precisely the ferromagnetic resonance linewidth of each individual YIG and YIG|Pt nanodisks. We find that the linewidth in the nanostructure is sensibly smaller than the one measured in the extended film. Analysis of the frequency dependence of the spectral linewidth indicates that the improvement is principally due to the suppression of the inhomogeneous part of the broadening due to geometrical confinement, suggesting that only the homogeneous broadening contributes to the linewidth of the nanostructure. For the bare YIG nano-disks, the broadening is associated to a damping constant α=4 × 10−4 . A threefold increase of the linewidth is observed for the series with Pt cap layer, attributed to the spin pumping effect. The measured enhancement allows to extract the spin mixing conductance found to be G↑↓=1.55 × 1014 Ω−1 m−2 for our YIG(20nm)|Pt interface, thus opening large opportunities for the design of YIG based nanostructures with optimized magnetic losses.

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Poly(L‐lactide) is a widely studied biomaterial, currently approved for use in a range of medical devices. Its mechanical properties can be tailored giving the material different crystallinity degrees. PLLA presents a complex non‐linear behaviour that depends not only on structural parameters such as crystallinity degree but also on external parameters such as strain rate and temperature. Failure of polymeric implants is attributed to their intrinsic time‐dependent performance under static loading conditions.