An understanding of the mechanical properties of soft hydrogel materials over multiple length scales is important for their application in many fields. Typical measurement methods provide either bulk mechanical properties (compression, tensile, rheology) or probing of nano or microscale properties and heterogeneity (nanoindentation, AFM). In this work we demonstrate the complementarity of instrumented microindentation to these techniques, as it provides representative Young's moduli for soft materials with minimal influence of the experimental parameters chosen, and allows mechanical property mapping across macroscopic areas. To enable automated analysis of the large quantities of data required for these measurements, we develop a new fitting algorithm to process indentation data. This method allows for the determination of Young's moduli from imperfect data by automatic selection of a region of the indentation curve which does not display inelastic deformation or substrate effects. We demonstrate the applicability of our approach with a range of hydrogels, including materials with patterns and gradients in stiffness, and expect the techniques described here to be useful developments for the mechanical analysis of a wide range of soft and biological systems.

Automated analysis of soft material microindentation

Agostino Galanti;Pierangelo Gobbo
2022-01-01

Abstract

An understanding of the mechanical properties of soft hydrogel materials over multiple length scales is important for their application in many fields. Typical measurement methods provide either bulk mechanical properties (compression, tensile, rheology) or probing of nano or microscale properties and heterogeneity (nanoindentation, AFM). In this work we demonstrate the complementarity of instrumented microindentation to these techniques, as it provides representative Young's moduli for soft materials with minimal influence of the experimental parameters chosen, and allows mechanical property mapping across macroscopic areas. To enable automated analysis of the large quantities of data required for these measurements, we develop a new fitting algorithm to process indentation data. This method allows for the determination of Young's moduli from imperfect data by automatic selection of a region of the indentation curve which does not display inelastic deformation or substrate effects. We demonstrate the applicability of our approach with a range of hydrogels, including materials with patterns and gradients in stiffness, and expect the techniques described here to be useful developments for the mechanical analysis of a wide range of soft and biological systems.
2022
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https://pubs.rsc.org/en/content/articlelanding/2022/sm/d2sm00857b
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11368/3034181
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