The objective of the work was to evaluate the influence of gold nanoparticles, obtained by laser ablation, on the photocatalytic action of titanium dioxide in the improvement of the physical-chemical parameters of domestic greywater, with visualization by means of a PLC. The YAG laser equipment was used for the production of spherical gold nanoparticles, whereas the Raman spectroscope allowed characterizing the different particles contained in aqueous solutions. The solar photoreactor programmable and viewable from PLC with connection to sensors allowed determining the variations of the pH, EC, DO and FCL parameters. The work consisted of a control group (greywater + titanium dioxide) and an experimental group (greywater + titanium dioxide + gold nanoparticles). The titanium dioxide doses for both groups were 0.5 mg/L and the gold nanoparticles were 0.20 ml per liter of greywater only for the control group. The experiments were carried out on sunny days with the exposure periods of 30 and 60 minutes around solar noon with an average UV index of 13.35. Once the experiments were carried out, it was determined that the pH improved by 5.30%, EC by 3.03%, DO by 29.3% and FCL by 43.71%, so that the gold nanoparticles dissolved in the aqueous solution of titanium dioxide with greywater positively influenced the improvement of the photocatalytic action of titanium dioxide in the physical-chemical parameters of greywater.
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.
The Phthorimaea operculella Zeller moth is a pest that affects potato crops and is found mainly in the inter-Andean valleys of the highlands of Peru (Huancavelica). The objective of the research was to use the phenomenon of light generated by light-emitting diodes (LEDs) to attract the potato moth in storage. Every day at seven o’clock in the morning, the number of moths falling dead in the light trap on the water contained in the container was counted. Five LED lights with different light densities per square centimeter were tested for five nights with different frequencies: 3.125 Hz, 12.5 Hz, 50 Hz, 200 Hz and 400 Hz. Every five nights the operating current of the LEDs was changed: 5 mA, 10 mA and 15 mA. Every fifteen nights the color of the LEDs was changed, according to the following sequence: white, blue, green, yellow and red; the color that attracted the most was white light, while the one with the least attraction was red light. The white light trap using the 64 LED array attracted 38.73% of moths and consumed a total of 43 W of energy in seven days, so it is considered low energy consumption.
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