An automated algorithm for the determination of oil absorption strategy of magnetic nanoparticles from SEM images

Abstract

In recent years, the magnetic iron oxide nanoparticles (MNPs) are employed as efficient absorbents for oil removal from water. In this research, the particle size (diameter) obtained from Scanning Electron Microscopy (SEM) images of MNPs, before and after oil-absorption, are utilized to determine the oil-absorption capacity. However, the manual evaluation of the particle size and particle size distribution (PSD) are highly time-consuming and needs expertised people for accurate analysis. Hence, an image processing algorithm is employed for the determination of particle size and PSD from the Scanning Electron Microscopy (SEM) images. The key objective revolves with the preparation of the Maleic Anhydride Grafted Polypropylene anchored Magnetic Nanoparticles (MAPP-a-MNPs) to absorb crude oil from the marine water. The shape, size, and size distribution of MAPP-a-MNPs were assessed by both manual and automated analysis. For this purpose, expertise people help with the manual analysis and Threshold Adaptive-Canny Edge Detection (TA-CED) and Accumulator Updated-Circular Hough Transform (AU-CHT) method is employed for automated analysis. All the automated process were conducted in MATLAB and the measurements were taken for both before and after the oil absorption images. These measurements aid us to determine the quantity of oil absorbed by MAPP-a-MNPs. The results demonstrates excellent oil removal capacity of MAPP-a-MNPs.

Keywords: Accumulator updated-circular hough transform; Magnetic nanoparticles; Oil absorption; Scanning electron microscopy; Threshold adaptive-canny edge detection.