Hybrid architecture of ZnO nanorods/graphene oxide ZnO-NRs@GO synthesized by electrostatic self-assembly methods. The morphological, optical and luminescence characteristics of ZnO-NRs@GO and ZnO-NRs thin films have been described by FESEM, TEM, HRTEM, and AFM, which refers to graphene oxide have been coated ZnO-NRs with five layers. Here we synthesis ZnO-NRs@GO by simple, cheap and environmentally friendly method, which made it favorable for huge -scale preparation in many applications such as photocatalyst. ZnO-NRs@GO was applied as a photocatalyst Rodamin 6 G (R6G) dye from water using 532 nm diode laser-induced photocatalytic process. Overall degradation of R6G/ ZnO-NRs@GO was achieved after 90 minutes of laser irradiation while it needs more time for R6G alone. The reaction rate constant fit pseudo first order for R6G / ZnO-NRs@GO degradation was 0.41 min−1 compared to 0.015 min-1 using blank sample. The ZnO-NRs@GO thin film was considered as an excellent candidate to enhance the photocatalytic system.
Density functional theory calculations are employed to investigate the impact of edifenphos molecule on the reactivity and electronic sensitivity of pure calcium oxide (CaO) nanocluster. The strong adsorption of edifenphos molecule on CaO nanocluster occurs by the sulfur head of the adsorbate, and the amount of the energy of this adsorption is around − 84.40 kcal/mol. The adsorption of edifenphos molecules results in a decrease in the values of Eg of CaO from 4.67 to 3.56 eV, as well as an increase in the electrical conductance. Moreover, the work function of CaO nanocluster is significantly affected, which changes the current of the field emission electron. Eventually, the recovery time is calculated around 99 ms at ambient temperature f
... Show MoreHuman serum albumin (HSA) nanoparticles have been widely used as versatile drug delivery systems for improving the efficiency and pharmaceutical properties of drugs. The present study aimed to design HSA nanoparticle encapsulated with the hydrophobic anticancer pyridine derivative (2-((2-([1,1'-biphenyl]-4-yl)imidazo[1,2-a]pyrimidin-3-yl)methylene)hydrazine-1-carbothioamide (BIPHC)). The synthesis of HSA-BIPHC nanoparticles was achieved using a desolvation process. Atomic force microscopy (AFM) analysis showed the average size of HSA-BIPHC nanoparticles was 80.21 nm. The percentages of entrapment efficacy, loading capacity and production yield were 98.11%, 9.77% and 91.29%, respectively. An In vitro release study revealed that HSA-BIPHC nan
... Show MoreObjective: The aim of this study was to develop a bioadhesive gel of gatifloxacin for the treatment of periodontal diseases.Methods: Periodontal gels of gatifloxacin were prepared using different hydrophilic polymers such as carbopol 940 (CP 940), carboxymethyl cellulose (CMC) and hydroxypropylmethyl cellulose (HPMC) in varied concentrations, either alone or as a combination. The prepared gels were evaluated for their physical appearance, pH, drug content, viscosity, bioadhesiveness and in vitro drug release profile. The influence of the type and the concentration of polymer on the drug release as well as on viscosity and mucoadhesiveness of prepared gels were investigated.Results: The prepared gels showed acceptable physical proper
... Show MoreNine new compounds of 2-amino-5-chlorobenzothiazole derivatives were synthesized. These new compounds were formed through the reaction of 2-amino-5-chlorobenzothiazole 1 with ethyl chloroacetate and KOH, which gave an ester derivative 2, followed by refluxing compound 2 with hydrazine hydrate to afford hydrazide derivative 3. The reaction of compound 3 with CS2 and KOH gave 1,3,4-oxadiazole-2-thiol derivative 4, and then the reaction of compound 2 with thiosemicarbazide to produce compound 5 then treated it with 4%NaOH led to ring closure to provide 1,2,4-triazole-3-thiol derivative
... Show MoreThe synthesis and bioactivity of zinc oxide nanoparticles has been extensively studied. The antibacterial activity of different antibiotics individually (ceftriaxone (C), chloramphenicol (CRO), penicillin (P) and amoxicillin (Ax)) and Zinc oxide nanoparticles (60μg/ml) in combination with the previously mentioned antibiotics has been demonstrated in the present study by using the disk diffusion assay method. The results showed a synergistic effect between Zinc oxide nanoparticles (ZnO NPs) and both Ax and P for most of the studied Gram-positive isolates (Staphylococcus aureus1, Staphylococcus aureus2, Staphylococcus epidermidis1, Staphylococcus epidermidis2, Enterococcus faecalis1, Enterococcus faecalis2 ) and between ZnO NPs and both C
... Show MoreExperimental measurements of viscosity and thermal conductivity of single layer of graphene . based DI-water nanofluid are performed as a function of concentrations (0.1-1wt%) and temperatures between (5 to 35ºC). The result reveals that the thermal conductivity of GNPs nanofluids was increased with increasing the nanoparticle weight fraction concentration and temperature, while the maximum enhancement was about 22% for concentration of 1 wt.% at
35ºC. These experimental results were compared with some theoretical models and a good agreement between Nan’s model and the experimental results was observed. The viscosity of the graphene nanofluid displays Newtonian and Non-Newtonian behaviors with respect to nanoparticles concen
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
... Show MoreImage 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
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