生物材料
选择(遗传算法)
计算机科学
材料选择
生物材料
生化工程
工程类
纳米技术
作者
Arun Arjunan,Ahmad Baroutaji,Ayyappan Susila Praveen,John Robinson,Chang Wang
出处
期刊:Elsevier eBooks
[Elsevier]
日期:2020-10-22
被引量:5
标识
DOI:10.1016/b978-0-12-815732-9.00027-9
摘要
The rapid evolution in biomaterial performance over the last decade calls for an ever-increasing need in the classification of their functionalities. In many cases, emerging biomaterials are expected to be multifunctional, customizable, and biologically active. It is also likely that the future of biomaterials will assume even greater roles in terms of their bioactive capabilities making it all the more difficult to be regulated. As such a functional classification of biomaterials allows to consider both the safety, performance, and application while facilitating the selection of the best candidate material. Although every biomaterial undergoes rigorous experimental evaluation, they are often classified similarly to conventional materials based on their composition. This contributes to the challenges in biomaterials selection, evaluation, and use, which can subsequently lead to convoluted regulations, and inherent biases. The paper, therefore, provides a general introduction into the classification of biomaterials based on their functionalities. In this regard, the biomaterial qualifiers are introduced and summarized into an overall framework in a way that allows for meaningful classification. Furthermore, the framework that is presented can accommodate both traditional and emerging biomaterials based on their existing biomechanical performance and evolving functionalities.
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