journal article·2007-08-28

Insights into whole bone and tooth function using optical metrology

Ron Shahar, Steve Weiner

Journal of Materials Science· Volume 42· Issue 21
Publisher page

Abstract

Understanding the relations between the mechanical responses of whole entities, their materials properties and their structures, is a challenge. This challenge is greatly enhanced when the material itself is complex, and when the entity it forms has a convoluted shape. It is for these reasons that it is still beyond the state-of-the-art to predict and fully understand the mechanical functions of whole biological entities such as bones and teeth. Recent advances in optical metrology open up new opportunities as they enable the precise and accurate mapping of the manner in which the entire surface of a whole stiff mineralized tissue deforms. Furthermore these data can be obtained non-destructively and without contact with the sample. Data of this kind create the exciting possibility of relating the complex distribution of mechanical properties of loaded biological materials such as bone and teeth and their microstructures to deformations and strains. Such studies could improve our understanding of normal physiological processes such as skeletal aging, as well as disease processes such as osteoporosis. They also provide opportunities for engineers designing bio-inspired materials to study the principles, advantages, and characteristics of the behavior of hierarchical and multifunctional materials. In this manuscript we review optical metrology methods, highlight studies of whole body function for bones and teeth, and in particular those studies that provide insights into structure-function relations. We also outline the potential for future studies.
Source: openaire · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Bone Tissue Engineering Materials · Calcium Carbonate Crystallization and Inhibition · Endodontics and Root Canal Treatments

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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