The present work is devoted to investigate the performance of a homemade Y-shape catalytic microreactor for degradation of dibenzothiophene (DBT), as a model of sulphur compounds including in gas oil, utilizing solar incident energy. The microchannel was coated with TiO2 nanoparticles which were used as a photocatalyst. Performance of the microreactor was investigated using different conditions (e.g., DBT concentration, LHSV, operating temperature, and (H2O2/DBT) ratio). Our experiments show that, in the absence of UV light, no reaction takes place. The results revealed that outlet concentration of DBT decreases as the mean residence time in the microreactor increases. Also, it was noted that operating temperature showed a positive impact on the degradation rate of DBT while LHSV showed a different image. The results reported an optimum (H2O2/DBT) ratio which gave maximum conversion of DBT which vary with initial concentration. Kinetic study was carried out which confirmed that desulfurization of DBT followed a pseudo-first order reaction at 30 and 50oC, respectively. However deviation from linearity was observed at 60oC. Comparison between microreactor´s performance and performance of batch reactors from published literature were illustrated. The Comparison confirmed the unique characteristics of the microreactor.
This study focuses on synthesizing Niobium pentoxide (Nb2O5) thin films on silicon wafers and quartz substrates using DC reactive magnetron sputtering for NO2 gas sensors. The films undergo annealing in ambient air at 800 °C for 1 hr. Various characterization techniques, including X-ray diffraction (XRD), atomic force microscopy (AFM), energy-dispersive X-ray spectroscopy (EDS), Hall effect measurements, and sensitivity measurements, are employed to evaluate the structural, morphological, electrical, and sensing properties of the Nb2O5 thin films. XRD analysis confirms the polycrystalline nature and hexagonal crystal structure of Nb2O5. The optical band gap val
... Show More
(3)
In subterranean coal seam gas (CSG) reservoirs, massive amounts of small-sized coal fines are released during the production and development stages, especially during hydraulic fracturing stimulation. These coal fines inevitably cause mechanical pump failure and permeability damage due to aggregation and subsequent pore-throat blockage. This aggregation behavior is thus of key importance in CSG production and needs to be minimized. Consequently, such coal fines dispersions need to be stabilized, which can be achieved by the formulation of improved fracturing fluids. Here, we thus systematically investigated the effectiveness of two additives (ethanol, 0.5 wt % and SDBS, 0.001 and 0.01 wt %) on dispersion stability for a wide range of condit
... Show More
(88)
(83)
Thin films ZrO2: MgO nanostructure have been synthesized by a radio frequency magnetron plasma sputtering technique at different ratios of MgO (0,6, 8 and 10)% percentage to be used as the gas sensor for nitrogen dioxide NO2. The samples were investigated by X-ray diffraction (XRD), atomic force microscopy (AFM), scanning electron microscopy (SEM), energy-dispersive X-ray (EDX) and sensing properties were also investigated. The average particle size of all prepared samples was found lower than 33.22nm and the structure was a monoclinic phase. The distribution of grain size was found lower than36.3 nm and uninformed particles on the surface. Finally, the data of sensing properties have been discussed, where the
... Show More
(9)
(1)
(1)
(2)
(6)
(6)
The field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. In recent years, the processing of Arabian image databases by deep learning architectures has experienced a remarkable development. However, this remains insufficient to satisfy the enormous wealth of Arabic manuscripts. In this research, a deep learning architecture is used to address the issue of classifying Arabic letters written by hand. The method based on a convolutional neural network (CNN) architecture as a self-extractor and classifier. Considering the nature of the dataset images (binary images), the contours of the alphabet
... Show More
(1)
(1)
Solar energy usage in Iraq is facing many issues; one of those is the accumulation “of the dust on the surface of the solar module which” would highly lower its efficiency. The present work study the effect of dust accumulation” on installing fixed solar modules with different inclined angles 15o, 33o, 45o, 60o. Evaluation of the solar modules performance under different circumstance conditions such as rain, wind and humidity are considered in study of dust effect on solar module performance. The results show that the lowest output average efficiencies of solar modules occurs at 15o horizontally inclined angle are 7.4% , 6.7% , 8.0% , 8.1%, and 8.4% for the cor
... Show MoreIn this paper, the goal of proposed method is to protect data against different types of attacks by unauthorized parties. The basic idea of proposed method is generating a private key from a specific features of digital color image such as color (Red, Green and Blue); the generating process of private key from colors of digital color image performed via the computing process of color frequencies for blue color of an image then computing the maximum frequency of blue color, multiplying it by its number and adding process will performed to produce a generated key. After that the private key is generated, must be converting it into the binary representation form. The generated key is extracted from blue color of keyed image then we selects a c
... Show More