Characterization of Metallic Gold Nanoparticles in a Colloidal State by Artificial Vision

Abstract

Gold nanoparticles in their colloidal state have different colors, and the equipment for their characterization, such as UV-Vis spectrophotometers, scanning electron microscopy (SEM), and transmission electron microscopy (TEM), has high costs. The research aimed to characterize metallic gold nanoparticles by artificial vision based on the color of the samples in the colloidal state. The sensor used for the sampling was a 50 MP triple-lens camera with the optical image stabilization (OIS) of a smartphone. The Vision Acquisition and Vision Assistant blocks in the NI LabVIEW platform were used to implement an artificial vision device. The camera interface was used to identify the color of each of the 10 samples of colloidal gold nanoparticles produced by the YAG laser and chemical reduction in 15 ml of deionized water. The characterization consisted of the determination of the size and concentration of the gold nanoparticles based on their color, which ranged from pink to red wine. As a result, the artificial vision device adequately identified the color of the metallic gold nanoparticles in a colloidal state with a certainty of more than 95%, allowing the nanoparticles to be adequately characterized. Therefore, it is concluded that artificial vision adequately characterized gold nanoparticles' wavelength, absorbance, diameter, and concentration.