Deep Insight into Surface Flatness Based on AFM Images Illustrated by Ni-Based Alloy

Coated conductor based on epitaxial growth of thin films usually demands highly clean, smooth and flat Ni-based metal tape as the substrate. The surface quality of Ni-based alloy is typically assessed by atomic force microscopy (AFM). However, many complex local surface features can not be reflected adequately by conventional statistic parameters such as overall root mean square (RMS) roughness. Here, we developed a numerical analysis method for AFM images based on height histogram or gray histogram to gain more insight into surface features by evaluating the degree of surface flatness. Compared to conventional statistical RMS roughness, binary image with the flat area fraction gives more information on surface flatness. The degree and distribution of surface flatness can be reflected vividly by binary image with the percentage of flat area. This numerical analysis for surface flatness based on height histogram or gray histogram was demonstrated using Ni-based alloy as a paradigmatic example, which can also be applied to AFM images of other solid materials.