Quasi-static and dynamic depth-sensing indentation measurements to characterize wear and mar resistance of coating–polymer systems

Abstract

Different layers of different thicknesses were coated on the same polymethyl methacrylate (PMMA) substrate. For each of these bilayered systems, quasi-static and dynamic instrumented indentations using continuous stiffness measurement have been made. We verified if data from indentation tests performed on a given sample obey a power law relationship. The aim was to calculate the viscoplasticity index n with sufficient accuracy (by taking into account the viscoelastoplastic properties of the studied samples), since this value is characteristic of the viscoplastic properties of a material and, therefore, allows evaluating the plastic scratch resistance of the surface. Thanks to both indentation methods the viscoplasticity index could be calculated and its value compared to the different bilayered systems one. As n is supposed to be intrinsic to a material, its value should not depend on the characterization technique.

Artificial Intelligence for Mechanical Properties Prediction of Polyethylene-Carbon Nanotube Composites

“…Specifically, carbon nanotubes (CNTs) have attracted considerable interest as a potentially optimal nanofiller for polyethylene due to their exceptional electrical and mechanical characteristics [15,16]. In this context, depth-sensing indentation emerges as the method of choice for evaluating the mechanical factors of polyethylene materials, thanks to its higher signal accuracy and examination of reduced material volumes [17][18][19]. However, to further optimize its utility, it is essential to emphasize the need for a smoother transition in the narrative, especially when transitioning from the discussion of DSI to exploring the potential of carbon nanotubes in polyethylene composites [20].…”