Strain-induced damage analysis of hyperelastic material through scanning electron microscopy: A statistical approach using digital image processing

In order to acquire topographic/morphological images with superior resolution and depth of focus than an ordinary optical microscope, scanning electron microscopy (SEM) is used to take photographs of a surface of materials or specimens at a desired point. In the context of polymer and rubber materials science, SEM investigations frequently try to visualize phase morphology, surface and cross-sectional topography, and surface molecular order, and clarify damage mechanisms. In the case of rubber vulcanizates, test specimens are frequently put through a variety of mechanical property assessment procedures, including tensile, flexing, fatigue, abrasion, and tear tests, in order to finalize compounding parameters for required levels of quality. The damaged surface of the test specimens exhibits distinctive topographical characteristics, which are captured as an SEM picture and associated with relevant strength properties. However, the majority of the time, the relationship between strength attributes and the type of surface topography is qualitative. Surface roughness measurement metrics such as root mean square (r.m.s) roughness, average roughness, and peak-to-valley distance are frequently determined for quantitative research using standard software accessible in an SEM. The primary goal of this research is to use a statistical/spectral-based technique for quantitatively measuring surface topography using SEM. The Mullins stress-softening phenomenon of an isotropic, incompressible, hyperelastic rubberlike material is predicted using a phenomenological model. A simple exponential damage function characterizes the model, which represents deformation-induced microstructural degradation of rubberlike material.