18 resultados para GLASS-INFILTRATED ALUMINA COMPOSITE


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A severe shortage of good quality donor cornea is now an international crisis in public health. Alternatives for donor tissue need to be urgently developed to meet the increasing demand for corneal transplantation. Hydrogels have been widely used as scaffolds for corneal tissue regeneration due to their large water content, similar to that of native tissue. However, these hydrogel scaffolds lack the fibrous structure that functions as a load-bearing component in the native tissue, resulting in poor mechanical performance. This work shows that mechanical properties of compliant hydrogels can be substantially enhanced with electrospun nanofiber reinforcement. Electrospun gelatin nanofibers were infiltrated with alginate hydrogels, yielding transparent fiber-reinforced hydrogels. Without prior crosslinking, electrospun gelatin nanofibers improved the tensile elastic modulus of the hydrogels from 78±19. kPa to 450±100. kPa. Stiffer hydrogels, with elastic modulus of 820±210. kPa, were obtained by crosslinking the gelatin fibers with carbodiimide hydrochloride in ethanol before the infiltration process, but at the expense of transparency. The developed fiber-reinforced hydrogels show great promise as mechanically robust scaffolds for corneal tissue engineering applications. © 2013 Elsevier Ltd.

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The residual strength of glass fibre reinforced vinyl-ester laminates with multiple holes was investigated through an experimental programme. Different types of structured hole patterns and hole densities were investigated and analysed using digital image correlation strain measuring technique. Three different failure modes could be observed when the hole patterns and the hole densities were a altered. These three failure modes were used as the foundation for a simple yet effective analytical model in order to predict the residual strength of damaged composite specimens. Finally, a number of laminates with randomly distributed holes were tested experimentally. The analytical model can predict the failure mode and failure strength of the experiments with sufficiently good fidelity. © 2010 Elsevier Ltd.