Digital Image Analysis for Chemical Phase Identification and Particle Size Determination

Abstract

A methodology employing digital image analysis for chemical phase identification and particle size determination is presented. The phase of unknown iron-oxide based particulate sample was identified by analyzing its transmission electron microscope diffraction patterns and diffraction contrast images using ImageJ pattern recognition software. A standard diffraction pattern with known crystallographic spacing and a standard diffraction contrast image with known fringe spacing were used to calibrate the sample’s diffraction patterns and diffraction contrast images, respectively. The phase of unknown sample was identified as iron (III) oxide with an average particle size of 8.9 nm computed from digitized binary images through thresholding process. The particles size distribution closely resembled Poisson cumulative distribution function with 61% of the particles having diameters between 1-10 nm.

Keywords: Phase identification, ImageJ, Diffraction pattern, Digital image, Particle size determination