Image-based analysis of uniaxial ring test for mechanical characterization of soft materials and biological tissues
| Autor: | Mark C. van Turnhout, Nicholas A. Kurniawan, Eline E. van Haaften |
|---|---|
| Přispěvatelé: | Cell-Matrix Interact. Cardiov. Tissue Reg., Soft Tissue Biomech. & Tissue Eng., Institute for Complex Molecular Systems |
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
Materials science
Mechanical Phenomena Finite Element Analysis 02 engineering and technology Bending Stress 010402 general chemistry 01 natural sciences Stress (mechanics) Materials Testing Animals Materials Testing/methods Aorta Ring (mathematics) Stress–strain curve General Chemistry Mechanical 021001 nanoscience & nanotechnology Condensed Matter Physics Finite element method 0104 chemical sciences Characterization (materials science) Biomechanical Phenomena Molecular Imaging Rats Aorta/diagnostic imaging Stress Mechanical Deformation (engineering) 0210 nano-technology Biological system |
| Zdroj: | Soft Matter, 15(16), 3353-3361. Royal Society of Chemistry |
| ISSN: | 1744-683X |
| Popis: | Uniaxial ring test is a widely used mechanical characterization method for a variety of materials, from industrial elastomers to biological materials. Here we show that the combination of local material compression, bending, and stretching during uniaxial ring test results in a geometry-dependent deformation profile that can introduce systematic errors in the extraction of mechanical parameters. We identify the stress and strain regimes under which stretching dominates and develop a simple image-based analysis approach that eliminates these systematic errors. We rigorously test this approach computationally and experimentally, and demonstrate that we can accurately estimate the sample mechanical properties for a wide range of ring geometries. As a proof of concept for its application, we use the approach to analyze explanted rat vascular tissues and find a clear temporal change in the mechanical properties of these explants after graft implantation. The image-based approach can therefore offer a straightforward, versatile, and accurate method for mechanically characterizing new classes of soft and biological materials. |
| Databáze: | OpenAIRE |
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