Related Experiment Video
Updated: May 12, 2026

07:29
Comprehensive Characterization of Tissue Mineralization in an Ex Vivo Model
Published on: September 27, 2024
Multiscale modelling and diffraction-based characterization of elastic behaviour of human dentine
Tan Sui1, Michael A Sandholzer, Nikolaos Baimpas
1Department of Engineering Science, University of Oxford, Parks Road, Oxford OX1 3PJ, UK. tan.sui@eng.ox.ac.uk
Acta Biomaterialia
|April 23, 2013
Summary
Human dentine
Area of Science:
- Biomaterials Science
- Nanomechanics
- Dental Tissues
Background:
- Human dentine exhibits a complex two-level hierarchical structure influencing mechanical properties.
- Microscale tubules and nanoscale hydroxyapatite (HAp) crystallites are key structural features.
- Understanding dentine's mechanical response requires considering both micro and nanoscale structural elements.
Purpose of the Study:
- To investigate the in situ elastic strain evolution within HAp crystallites in human dentine under uniaxial compression.
- To develop and validate a multiscale model that incorporates dentine's hierarchical structure.
- To enhance the understanding of mechanical behavior in hierarchical biomaterials.
Main Methods:
- Simultaneous in situ small-angle X-ray scattering (SAXS) and wide-angle X-ray scattering (WAXS) under uniaxial compression.
- Characterization of HAp crystallite strain (WAXS) and nanoscale HAp distribution (SAXS).
- Development and validation of an improved multiscale Eshelby inclusion model.
Main Results:
- WAXS quantified the apparent modulus relating external load to internal HAp strain.
- SAXS provided insights into the nanoscale HAp distribution and arrangement.
- The validated multiscale model accurately reflected dentine's structural arrangement and mechanical response.
Conclusions:
- The developed multiscale hierarchical model effectively captures the mechanical behavior of human dentine.
- This study advances the understanding of hierarchical biomaterials' mechanical properties.
- Knowledge of structure-property relationships is crucial for predicting effects of diseases or treatments on dental tissues.

