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A low-cost and open-source measurement system to determine the Young’s and shear moduli and Poisson's ratio of soft materials using a Raspberry Pi camera module and 3D printed parts
Advances in biomedical and engineering fields have greatly increased the need for understanding of soft structures. Soft materials such as gelatin and gelatin-based hydrogels have grown in popularity for use in a wide variety of applications including tissue engineering, biofabrication, and organ tr...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9793308/ https://www.ncbi.nlm.nih.gov/pubmed/36582477 http://dx.doi.org/10.1016/j.ohx.2022.e00386 |
Sumario: | Advances in biomedical and engineering fields have greatly increased the need for understanding of soft structures. Soft materials such as gelatin and gelatin-based hydrogels have grown in popularity for use in a wide variety of applications including tissue engineering, biofabrication, and organ transplantation. With hydrogel structures being used in such demanding applications, it is crucial to properly characterize the dynamic behavior of these soft structures. Although there have been major improvements in measurement technology for determining the mechanical properties of soft, translucent materials, it remains quite challenging to reliably measure the Young’s and shear moduli of these materials in a way that remains straightforward, low-cost, and non-contact. This research aims to address the weaknesses in modern measurement methods and develop a system suitable for characterizing the elastic moduli of soft materials that requires only four, inexpensive, off-the-shelf components. Utilizing a Raspberry Pi, stepping motor, and an inexpensive camera, the Young’s and shear moduli of a gelatin column is measured five times. The standard deviation between measurement was observed to be less than 0.15% with high accuracy having an error of less than 4.6% when compared to relatively expensive, conventional measurement techniques. |
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