Automated quantification of one-dimensional nanostructure alignment on surfaces
This provides researchers in nanoscience and nanotechnology with a rigorous tool for analyzing nanostructure alignment, which is incremental as it builds on existing metrics but improves accuracy for highly aligned domains.
The paper tackles the problem of quantifying the alignment of one-dimensional nanostructures on surfaces from microscopy images, presenting a method that uses multiple parameter metrics to enable automated analysis and rigorous comparison of different samples, overcoming limitations of past single-parameter approaches.
A method for automated quantification of the alignment of one-dimensional nanostructures from microscopy imaging is presented. Nanostructure alignment metrics are formulated and shown to able to rigorously quantify the orientational order of nanostructures within a two-dimensional domain (surface). A complementary image processing method is also presented which enables robust processing of microscopy images where overlapping nanostructures might be present. Scanning electron microscopy (SEM) images of nanowire-covered surfaces are analyzed using the presented methods and it is shown that past single parameter alignment metrics are insufficient for highly aligned domains. Through the use of multiple parameter alignment metrics, automated quantitative analysis of SEM images is shown to be possible and the alignment characteristics of different samples are able to be rigorously compared using a similarity metric. The results of this work provide researchers in nanoscience and nanotechnology with a rigorous method for the determination of structure/property relationships where alignment of one-dimensional nanostructures is significant.