## Abstract Within this study, chemically modified polymer surfaces were to be developed, which should enhance the subsequent immobilization of various bioactive substances. To improve the hemocompatibility and endothelialization of poly(ε‐caprolactone) (PCL) intended as scaffold material for bioar
Material model measurements and predictions for a random pore poly(ϵ-caprolactone) scaffold
✍ Scribed by T. P. Quinn; T. L. Oreskovic; F. A. Landis; N. R. Washburn
- Publisher
- John Wiley and Sons
- Year
- 2007
- Tongue
- English
- Weight
- 291 KB
- Volume
- 82B
- Category
- Article
- ISSN
- 1552-4973
No coin nor oath required. For personal study only.
✦ Synopsis
Abstract
We investigated material models for a polymeric scaffold used for bone. The material was made by co‐extruding poly(ε‐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 with the coefficients of the hyperbolic model, and it is therefore easier to compare differences in material processing and ensure quality of the scaffold. A prediction of the small–strain 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 with Hooke's law for a linear‐elastic isotropic material. The model was able to predict the small–strain elastic 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. © 2006 Wiley Periodicals, Inc. J Biomed Mater Res Part B: Appl Biomater, 2006
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