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Publication Citation: MATERIAL MODEL MEASUREMENTS AND PREDICTIONS FOR A RANDOM PORE POLY(Epsilon-CAPROLACTONE) SCAFFOLD

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Author(s): Timothy P. Quinn; Tammy L. Oreskovic; Forrest A. Landis; N. R. Washburn;
Title: MATERIAL MODEL MEASUREMENTS AND PREDICTIONS FOR A RANDOM PORE POLY(Epsilon-CAPROLACTONE) SCAFFOLD
Published: July 02, 2007
Abstract: We investigate material models for a polymeric scaffold used for bone. The material was made by co-extruding poly(¿¿-caprolactone) (PCL), a biodegradable polyester, and poly(ethylene oxide) (PEO). The water soluble PEO was removed resulting in a porous scaffold. The stress-strain curve in compression was fit with a phenomenological model in hyperbolic form. This material model will be useful for designers for quasi-static analysis as it provides a simple form that can easily be used in finite element models. The ASTM D-1621 standard recommends using a secant modulus based on 10 % strain. The resulting modulus has a smaller scatter in its value compared to the coefficients of the hyperbolic model, and it is therefore easier to compare material processing differences and ensure quality of the scaffold. A prediction of the initial elastic modulus was constructed from images of the microstructure. Each pixel of the micrographs was represented with a brick finite element and assigned the Young¿¿s modulus of bulk PCL or a value of 0 for a pore. A compressive strain was imposed on the model and the resulting stresses were calculated. The elastic constants of the scaffold were then computed using Hooke¿¿s law for a linear-elastic isotropic material. The model was able to predict the small strain Young¿¿s modulus measured in the experiments to within one standard deviation. Thus, by knowing the microstructure of the scaffold, its bulk properties can be predicted from the material properties of the constituents.
Citation: Journal of Biomedical Materials Research
Volume: 82B
Issue: 1
Pages: pp. 205 - 209
Keywords: tissue engineering, scaffold, PCL, mechanical properties, stress-strain curve, finite element model, secant modulus, hyperbolic model
Research Areas: Bioscience & Health
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