New Schiff-base ligands bearing tetrazole moiety and their polymeric metal complexes with Co(II), Ni(II) and Cd(II) ions are reported. Ligands were prepared in a multiple-step reaction. The reaction of sodium 2,6- diformylphenolate and cyclohexane-1,3-dione with 5-amino-2-fluorobenzonitrile resulted in the isolation of two precursors sodium 2,6-bis((E)-(3-cyano-4-fluorophenylimino)methyl)-4-methylphenolate 1 and 5,5'- (1E,1'E)-cyclohexane-1,3-diylidenebis- (azan-1-yl-1-ylidene)bis(2-fluorobenzonitrile) 2, respectively. The reaction of precursors with azide gave the required ligands; sodium 2,6-bis((E)-(4-fluoro-3-(1H-tetrazol-5- yl)phenylimino)methyl)-4-methylphenolate (NaL) and (N, N'E, N, N'E)-N, N'-(cyclohexane-1,3-diylidene)bis(4- fluoro-3-(1H-tetrazol-5-yl)aniline) (L1). The reaction of these ligands with the appropriate metal ions gave polymeric metal complexes of the formulae {[M2(L)]Cl}n and [M(L1)Cl2]n (where M = Co(II), Ni(II) and Cd(II)). A range of techniques were used to confirm the entity of ligands and their complexes. The formation of ligands and mode of complexation and geometrical structure of the title polymeric complexes were verified using FTIR, electronic spectra, NMR, ESMS, magnetic susceptibility, micro-elemental analysis, metal content, chloride content and conductance. The analytical and spectroscopic data indicated the formation of four-coordinate complexes, with a tetrahedral geometry for Co(II) and Cd(II), and square planer for Ni(II) in L- and L1 complexes. Biological evaluation of ligands and their polymeric complexes against gram-positive bacteria (G+), Bacillus stubtili, Staphylococcus aureus, and gram-negative bacteria (G-), Escherichia coli and Pseudomonas aeruginosa, showed ligands and their polymeric metal complexes have a good effect on the screened bacteria.
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Organic permeable‐base transistors (OPBTs) show potential for high‐speed, flexible electronics. Scaling laws of OPBTs are discussed and it is shown that OPBT performance can be increased by reducing their effective device area. Comparing the performance of optimized OPBTs with state‐of‐the‐art organic field‐effect transistors (OFETs), it is shown that OPBTs have a higher potential for an increased transit frequency. Not only do OPBTs reach higher transconductance values without the need for sophisticated structuring techniques, but they are also less sensitive to parasitic contact resistances. With the help of a 2D numerical model, the reduced contact resistances of OPBTs are explained by a homogeneous injection of current acros
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At atmospheric pressure and at a frequency of 9.1 kHz, a constructed magnetically stabilized tornado gliding arc discharge (MSGAD) system was utilized in this study to generate a non-thermal plasma with an alternating voltage source from 2,4,6,8 to 10 kV. Argon gas was used to generate the arc plasma with an adjustable flow rate using a flow meter regulator to stabilize the gas flow rate to 2 L/min. A gliding plasma discharge is achieved by a magnetic field for the purpose of a planned investigation. The influence of the magnetically stabilized tornado gliding arc discharge parameters such as magnetic field and applied voltage on microscopic tornado plasma parameters was studied. The electron temperature1was measured using a Boltzmann plot
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The lowest layer of the atmosphere is called the atmospheric mixed layer, characterized by small-scale, irregular air motions defined by winds that change in speed and direction. Aerosol radiative effects impact the atmospheric boundary layer (ABL), which holds most aerosols in the lower atmosphere. Aerosol absorption and scattering both lower the quantity of solar energy that reaches the ground, which has an impact on the spectral signature of the land coverings. In this study, 51 locations in downtown Baghdad were chosen for four different types of land cover (water bodies, farms, open areas, and residential areas) for Sentinel 2 satellite imagery, and the time the pictures were taken was 8:00 am ( 22 March, 22 June, 20 September,
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In this paper, a construction microwave induced plasma jet(MIPJ) system was used to produce a non-thermal plasma jet at atmospheric pressure, at standard frequency of 2.45 GHz and microwave power of 800 W. The working gas Argon (Ar) was supplied to flow through the torch with adjustable flow rate using flow meter regulator. The influence of the MIPJ parameters such as applied voltage and argon gas flow rate on macroscopic microwave plasma parameters were studied. The macroscopic parameters results show increasing of microwave plasma jet length with increasing of applied voltage, argon gas flow rate where the plasma jet length exceed 12 cm as maximum value. While the increasing of argon gas flow rate will cause increasing into the ar
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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
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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
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Fullerene nanotube was synthesized in this research by pyrolysis of plastic waste Polypropylene (PP) at 1000 ° C for two hours in a closed reactor made from stainless steel using molybdenum oxide (MoO3) as a catalyst and nitrogen gas. The resultant carbon was purified and characterized by energy dispersive X-ray spectroscopy (EDX), X-ray powder diffraction (XRD). The surface characteristics of C60 nanotubes were observed with the Field emission scanning electron microscopy (FESEM). The carbon is evenly spread and has the highest concentration from SEM-EDX characterization. The result of XRD and FESEM shows that C60 nanotubes are present in Nano figures, synthesized at 1000 ° C and with pyrolysis tempera
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