Electrochemical method was used to prepare carbon quantum dots (CQDs). Size of matter was nature when evaluate via X-ray diffraction (XRD). A distinct peak at 2θ equal to 31.6° and three other small peaks at 38.28°, 56.41° and 66.12° were observed. The measures of Fourier Transform Infrared Spectroscopy (FTIR) showed the bonds in the transmittance spectrum are manufactured with carbon nanostructures in view. The first peaks are the O–H stretching vibration bands at (3417 and 2922) cm−1, (C–O–H at 1400, and 1317) cm−1, (C–H), (C=C), (C–O–H), (C=O), and (C–O) bonds at 2850, 1668, 1101, and 1026 cm−1 sequentially. The transmission electron microscopy (TEM) results presented that the spherical CQDs are in shape and on a

This work concerned on nanocrystalline NiAl2O4 and ZnAl2O4 having spinel structure prepared by Sol–gel technique. The structural and characterization properties for the obtained samples were examined using different measurements such as X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), finally, Field emission scanning electron microscope (FESEM).The Spinel-type for two prepared compound (NiAl2O4) and (ZnAl2O4) at different calcination temperature examined by XRD. Williamson-Hall Methods used to estimate crystallite size, Average distribution crystallite size of two compound were, 34.2 nm for NiAl2O4 and32.6 for ZnAl2O4, the increase in crystallite size affecting by increasing in calcination temperature for both comp

This contribution investigates the impact of adding transition metal of Ti to CeOy samples at various concentrations referring to 0, 15.84, 24.46, 34.46, 36.23, 38.46, 45.38% and pure TiOy, correspondingly. The samples were fabricated by the magnetron sputtering technique. X-ray diffraction (XRD) configurations demonstrate the presence of α-Ce2O3 and Ce2O3 phases with increased Ti contents in the systems. X-ray photoelectron spectroscopy (XPS) experimentation confirms the purity of the S1-sample (CeO2) and the purity of the S8-sample (TiO2). Further XPS analysis reveals that Ti incorporation in the doped systems functions as a reducing agent because of the existence of α-Ce2O3 and Ce2O3 phases. Moreover, based on UV–vis spectroscopy res

This contribution investigates the impact of adding transition metal of Ti to CeOy samples at various concentrations referring to 0, 15.84, 24.46, 34.46, 36.23, 38.46, 45.38% and pure TiOy, correspondingly. The samples were fabricated by the magnetron sputtering technique. X-ray diffraction (XRD) configurations demonstrate the presence of α-Ce2O3 and Ce2O3 phases with increased Ti contents in the systems. X-ray photoelectron spectroscopy (XPS) experimentation confirms the purity of the S1-sample (CeO2) and the purity of the S8-sample (TiO2). Further XPS analysis reveals that Ti incorporation in the doped systems functions as a reducing agent because of the existence of α-Ce2O3 and Ce2O3 phases. Moreover, based on UV–vis spectroscopy res

In this research the a-As flims have been prepared by thermal evaporation with thickness 250 nm and rata of deposition r_d(1.04nm/sec) as function to annealing temperature (373 and 473K), from XRD analysis we can see that the degree of crystalline increase with T_a, and I-V characteristic for dark and illumination shows that forward bias current varieties approximately exponentially with voltage bias. Also we found that the quality factor and saturation current dependence on annealing temperatures.

This 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

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class