Automated quantification of one-dimensional nanostructure alignment on surfaces

03/03/2016
by   Jianjin Dong, et al.
0

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.

READ FULL TEXT

page 3

page 6

page 8

research
04/07/2017

Three-Dimensional Segmentation of Vesicular Networks of Fungal Hyphae in Macroscopic Microscopy Image Stacks

Automating the extraction and quantification of features from three-dime...
research
08/05/2019

Unsupervised Representations of Pollen in Bright-Field Microscopy

We present the first unsupervised deep learning method for pollen analys...
research
12/26/2013

A Topologically-informed Hyperstreamline Seeding Method for Alignment Tensor Fields

A topologically-informed method is presented for seeding of hyperstreaml...
research
01/28/2018

Monitoring of Wild Pseudomonas Biofilm Strain Conditions Using Statistical Characterisation of Scanning Electron Microscopy Images

The present paper proposes a novel method of quantification of the varia...
research
06/27/2023

Nano1D: An accurate Computer Vision model for segmentation and analysis of low-dimensional objects

Microscopy images are usually analyzed qualitatively or manually and the...
research
09/17/2023

CryoAlign: feature-based method for global and local 3D alignment of EM density maps

Advances on cryo-electron imaging technologies have led to a rapidly inc...

Please sign up or login with your details

Forgot password? Click here to reset