439 research outputs found

    Solid-State Supercritical CO2 Foaming of PCL and PCL-HA Nano-Composite: Effect of Composition, Thermal History and Foaming Process on Foam Pore Structure

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    In this work we investigated the solid-state supercritical CO2 (scCO2) foaming of poly(e-caprolactone) (PCL), a semi-crystalline, biodegradable polyester, and PCL loaded with 5 wt% of hydroxyapatite (HA) nano-particles. In order to investigate the effect of the thermal history and eventual residue of the crystalline phase on the pore structure of the foams, samples were subjected to three different cooling protocols from the melt, and subsequently foamed by using scCO2 as blowing agent. The foaming process was performed in the 37–40◦C temperature range, melting point of PCL being 60◦C. The saturation pressure, in the range from 10 to 20 MPa, and the foaming time, from 2 to 900 s, were modulated in order to control the final morphology, porosity and pore structure of the foams and, possibly, to amplify the original differences among the different samples. The results of this study demonstrated that by the scCO2 foaming it was possible to produce PCL and PCL-HA foams with homogeneous morphologies at relatively low temperatures. Furthermore, by the appropriate combination of materials properties and foaming parameters, we prepared foams with porosities in the 55–85% range, mean pore size from 40 to 250um and pore density from 105 to 108 pore/cm3. Finally, we also proposed a two-step depressurization foaming process for the design of bi-modal and highly interconnected foams suitable as scaffolds for tissue engineering

    Mechanical strength of cold plasma treated PET fibers

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    In this work, the effects of cold plasma treatment on the mechanical strength of polyethyleneterephthalate (PET) fibers has been verified. Single fibers were treated with oxygen and a mixture of oxygen and tetrafluoroethylene in a cold plasma reactor for 30, 100 and 200 s. The single fibers were then tested in tensile mode and the mechanical strength was analyzed by using the Weibull distribution function. © 1999 Kluwer Academic Publishers
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