Automated quantification of one-dimensional nanostructure alignment on surfaces

TL;DR

This paper introduces an automated method for quantifying the alignment of one-dimensional nanostructures on surfaces using microscopy images, enabling rigorous comparison of nanostructure orientation in nanoscience research.

Contribution

It presents new alignment metrics and an image processing approach that together allow for robust, automated analysis of nanostructure orientation in microscopy images.

Findings

Multiple parameter metrics outperform single parameter metrics in alignment analysis.

Automated analysis enables comparison of nanostructure alignment across different samples.

The method is applicable to SEM images of nanowire-covered surfaces.

Abstract

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.