The present work reports an approach of hydrothermal growth of ZnO nanorods, which simplifies the production of low cost films with controlled morphology for H2S gas sensor application. The prepared ZnO nanorods exhibit a hexagonal wurtzite phase analyzed by the X-ray diffraction analysis. The FTIR spectra provide information that the band located between 465-570 cm-1 corresponds to the stretching bond of Zn-O, which confirms the creation of ZnO. PL spectroscopic studies showed that the doping of Ag NPs and f-MWCNT in the ZnO matrix leads to the tuning of the bandgap. The SEM analysis showed the morphology of ZnO was the nanorods. The nanocomposites Ag/ZnO and F-MWCNT/ZnO which prepared, separately were tested for H2S gas at low (2 ppm) and high (50 ppm) concentrations. ZnO nanorods films showed a sensitivity of 14.71% for pure ZnO with a fast response time of 25.2 sec and recovery time of 33.3 sec towards 2 ppm H2S. For Ag NPs/ZnO and f-MWCNTs/ZnO, sensors showed a significant sensitivity of 27.95 and 42.39 % at ~150 °C with a response time and recovery time less than pure ZnO. The ZnO sensor showed a higher sensitivity at ~150 °C for both Ag NPs and F-MWCNTs at high gas concentration, where it was 35.085 and 58.89% respectively.
Lithium-rich layered oxide cathodes have attracted considerable attention due to their high energy density, but have suffered from voltage drop, structural instability, and limited electrical conductivity. In this study, the electrochemical performance of the lithium-rich cathode material Li[Li0.20Mn0.54Ni0.13Co0.13]O2 was evaluated after modification by zinc doping and composition with graphene oxide or graphene. The zinc-doped powders were synthesized by the sol-gel method, while the graphene-based composites were prepared by the hydrothermal route. The structural, morphological and electrochemical characteristics of the modified materials were examined using X-ray diffraction, Fourier transform infrared spectroscopy, field emission scann
... Show MoreThe addition of organic-inorganic hybrid nanoparticles presents a promising avenue for enhancing both the ionic conductivity at room temperature and the mechanical resilience of solid polymer electrolytes (SPEs). In this study, a novel nanocomposite solid polymer electrolytes (NSPEs) based on poly(ethylene oxide)-lithium difluoro(oxalato)borate (PEO20-LiDFOB) incorporating polyhedral oligomeric silsesquioxane-poly(ethylene glycol) (POSS-PEG(13.3)) hybrid nanoparticles were developed. And also reported the effect of POSS-PEG(13.3) hybrid nanoparticles on the structural, thermal, electrical, mechanical, and electrochemical properties of the (PEO20-LiDFOB) SPE. X-ray diffraction (XRD), differential scanning calorimetry analysis (DSC) and polar
... Show MoreIn this work the interaction of plasma jet with water and hydrogen peroxide liquids used for assisted teeth bleaching by plasma jet had been study. A homemade plasma jet system was used. The plasma jet supply by 15 W electrical power generated by high voltage power supply of 9.6 kV peak to peak and frequency of 33 kHz .this power supply generate high electric field on electrodes that would be enough to ionize the argon gas. Some important agents were study such as the effect of the Ar gas flow rates on the length of the plasma jet, the influence of plasma jet on some properties of water and two hydrogen peroxide concentrations 25 % and 30 % like pH, conductivity and liquid temperature for different exposure time. The liquids temperature
... Show MoreIn this study, an improved process was proposed for the synthesis of structure-controlled Cu2O nanoparticles, using a simplified wet chemical method at room temperature. A chemical solution route was established to synthesize Cu2O crystals with various sizes and morphologies. The structure, morphology, and optical properties of Cu2O nanoparticles were analyzed by X-ray diffraction, SEM (scanning electron microscope), and UV-Vis spectroscopy. By adjusting the aqueous mixture solutions of NaOH and NH2OH•HCl, the synthesis of Cu2O crystals with different morphology and size could be realized. Strangely, it was found that the change in the ratio of de-ionized water and NaOH aqueous solution led to the synthesis of Cu2O crystals of differen
... Show MoreDetection of early clinical keratoconus (KCN) is a challenging task, even for expert clinicians. In this study, we propose a deep learning (DL) model to address this challenge. We first used Xception and InceptionResNetV2 DL architectures to extract features from three different corneal maps collected from 1371 eyes examined in an eye clinic in Egypt. We then fused features using Xception and InceptionResNetV2 to detect subclinical forms of KCN more accurately and robustly. We obtained an area under the receiver operating characteristic curves (AUC) of 0.99 and an accuracy range of 97–100% to distinguish normal eyes from eyes with subclinical and established KCN. We further validated the model based on an independent dataset with
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