There is currently a pressing need to create an electro-analytical approach capable of detecting and monitoring genosensors in a highly sensitive, specific, and selective way. In this work, Functionalized Multiwall Carbon Nanotubes, Graphene, Polypyrrole, and gold nanoparticles nanocomposite (f-MWCNTs-GR-PPy-AuNP) were effectively deposited on the surface of the ITO electrode using a drop-casting process to modify it. The structural, morphological, and optical analysis of the modified ITO electrodes was carried out at room temperature using X-ray diffraction (XRD), field emission scanning electron microscopy (FE-SEM) images, atomic force microscopy (AFM) and Fourier transform infrared (FTIR) spectra. Cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) were used to assess the electroanalytical performance of the electrodes after modification. The results showed that using AuNPs and PPy for modification of ITO/f-MWCNTs-GR electrode surfaces is conducive to augmenting the electrochemical performances of the electrodes. ITO/f-MWCNTs-GR showed better results in terms of higher electroactive area formation after modification with PPy and AuNPs. This work aims to figure out how to develop electrochemical biosensors for improved genosensor monitoring.
In this study, the effect of grafting with magnesium (Mg) ratios (0.1, 0.3, 0.5) on the structural and optical properties of cadmium oxide films (CdO) was studied, as these films were prepared on glass bases using the method of pulse laser deposition (PLD). The crystallization nature of the prepared membranes was examined by X-ray diffraction technique (XRD), which showed that the synthesis of the prepared membranes is polycrystalline, and (AFM) images also showed that the increased deformation with magnesium led to an increase in the grain size ratio and a decrease in surface roughness, as well as the absorption coefficient was calculated. And the optical energy gap for the prepared membranes, where it was found that the absorption coef
... Show MoreIn this study, gold nanoparticle samples were prepared by the chemical reduction method (seed-growth) with 4 ratios (10, 12, 15 and 18) ml of seed, and the growth was stationary at 40 ml. The optical and structural properties of these samples were studied. The 18 ml seed sample showed the highest absorbance. The X- ray diffraction (XRD) patterns of these samples showed clear peaks at (38.25o, 44.5o, 64.4o, and 77.95o). The UV-visible showed that the absorbance of all the samples was in the same range as the standard AuNPs. The field emission-scanning electron microscope (FE-SEM) showed the shape of AuNPs as nanorods and the particle size between 30-50 nm. Rhodamine-610 (RhB) was prepared at 10<
... Show MoreThis study discussed the effects of doping with silver (Ag) on the optical and structural properties of
CdO nanoparticles at different concentrations 0, 1, 2, 3, 4, 5 wt% prepared by the precipitation method. The
materials were annealed at 550˚C for 1 h. The structural, topographical, and optical properties were
diagnosed by X-ray diffraction analysis, atomic force instrument, and visible and ultraviolet spectrometers.
The results show that the average diameter of the grains depends on the percentage of added silver to the
material, as the diameter decreased from 88.8 to 59.7 nm, and it was found that the roughness increased from
5.56 to 26.5. When studying the optical properties, it was noted that th
The design, synthesis, and characterization of a star shaped 2,4,6-tris-(4`-carboxyphenoxy)-1,3,5-triazine liquid crystalline with columnar discotic mesophase properties establish H-bond interactions with 3,5-dialkoxypyidine were reported. The structures of the synthesized compounds were actually determined by elementary analysis, and FT-IR, ¹HNMR, ¹³CNMR, and mass spectroscopy. The mesomorphic properties of these mesogens were examined using differential scanning calorimetry (DSC) and optical polarizing microscopy (OPM). The synthesized molecules exhibited enantiotropic hexagonal columnar liquid crystal, which depends for the H- bond complex in a 1:3 ratio.
Current studies interested on the biosynthesis of zinc oxide nanoparticles (ZnO-NPs) using hot plants extracts of Allium sativum and characterization of them using: Atomic Force Microscopy (AFM), X-ray diffractions (XRD), Fourier Transform Infrared Spectroscopy (FT- IR), UV–visible spectral and Hot stage. The results found that all NPs are had nano-size. ZnO NPs was produced by four procedures using hot extract of Allium sativum. The average diameters were: 101.59 nm, 110.33 nm, 75.69 nm, 88.67 nm for first, second, third and fourth procedures respectively compared with 47.57 nm for standard NPs. The Roughness averages (Ra) were: 10.8 nm, 6.83 nm, 13.8 nm, 0.541 nm for first, second, third and fourth respectively. The Root mean square (Sq
... Show MoreNanoparticles of Pb1-xCdxS within the composition of 0≤x≤1 were prepared from the reaction of aqueous solution of cadmium acetate, lead acetate, thiourea, and NaOH by chemical co-precipitation. The prepared samples were characterized by UV-Vis spectroscopy(in the range 300-1100nm) to study the optical properties, AFM and SEM to check the surface morphology(Roughness average and shape) and the particle size. XRD technique was used to determine the crystalline structure, XRD technique was used to determine the purity of the phase and the crystalline structure, The crystalline size average of the nanoparticles have been found to be 20.7, 15.48, 11.9, 11.8, and 13.65 nm for PbS, Pb0.75Cd0.25S,
... Show MoreThis research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.