The current work concerns preparing cobalt manganese ferrite (Co0.2Mn0.8Fe2O4) and decorating it with polyaniline (PAni) for supercapacitor applications. The X-ray diffraction findings (XRD) manifested a broad peak of PAni and a cubic structure of cobalt manganese ferrite with crystal sizes between 21 nm. The pictures were taken with a field emission scanning electron microscope (FE-SEM), which evidenced that the PAni has nanofibers (NFs) structures, grain size 33 – 55 nm, according to the method of preparation, where the hydrothermal method was used. The magnetic measurements (VSM) that were conducted at room temperature showed that the samples had definite magnetic properties. Additionally, it was noted that the saturation magnetization value of PAni/Co0.2Mn0.8Fe2O4 nanocomposite and Co0.2Mn0.8Fe2O4 nanoparticles are maximum saturation magnetization values of (4.7) and (9) emu g−1 respectively. Studying properties of electrochemical which were tested in 1 M of H2SO4 by using the CV cyclic voltammetry analysis, galvanostatic charge-discharge (GCD), and electrochemical impedance spectroscopy (EIS), found the highest capacitance is 596 F/g.
In this research, a group of gray texture images of the Brodatz database was studied by building the features database of the images using the gray level co-occurrence matrix (GLCM), where the distance between the pixels was one unit and for four angles (0, 45, 90, 135). The k-means classifier was used to classify the images into a group of classes, starting from two to eight classes, and for all angles used in the co-occurrence matrix. The distribution of the images on the classes was compared by comparing every two methods (projection of one class onto another where the distribution of images was uneven, with one category being the dominant one. The classification results were studied for all cases using the confusion matrix between ev
... Show MoreIn this research, a group of gray texture images of the Brodatz database was studied by building the features database of the images using the gray level co-occurrence matrix (GLCM), where the distance between the pixels was one unit and for four angles (0, 45, 90, 135). The k-means classifier was used to classify the images into a group of classes, starting from two to eight classes, and for all angles used in the co-occurrence matrix. The distribution of the images on the classes was compared by comparing every two methods (projection of one class onto another where the distribution of images was uneven, with one category being the dominant one. The classification results were studied for all cases using the confusion matrix between every
... Show MorePolyimides are widely used in high-temperature plastics, adhesives, dielectrics, photoresists, nonlinear optical materials, separation membrane materials, and Langmuir-Blodgett (LB) films. They are commonly regarded as the most heat-resistant polymers. This work involved the synthesis of a new bismaleimide homopolymer and copolymer by performing many steps. The synthesis of compound (1) (bis [4-(amino phenyl) Schiff base] tolidine) via condensation of o-tolidine with two moles of 4-aminoacetophenone. Secondly, compound (1) was combined with maleic anhydride to form compound (2) (4, 4ˉ-bis[4-(N-maleamic acid) phenyl Schiff base] toluidine). Thirdly, a dehydration reaction was carried out affording compound (3) (4,4ˉ-bis [4-(N-maleimidyl
... Show MoreThe brain's magnetic resonance imaging (MRI) is tasked with finding the pixels or voxels that establish where the brain is in a medical image The Convolutional Neural Network (CNN) can process curved baselines that frequently occur in scanned documents. Next, the lines are separated into characters. In the Convolutional Neural Network (CNN) can process curved baselines that frequently occur in scanned documents case of fonts with a fixed MRI width, the gaps are analyzed and split. Otherwise, a limited region above the baseline is analyzed, separated, and classified. The words with the lowest recognition score are split into further characters x until the result improves. If this does not improve the recognition s
... Show MorePorous silicon (PS) layers are prepared by anodization for
different etching current densities. The samples are then
characterized the nanocrystalline porous silicon layer by X-Ray
Diffraction (XRD), Atomic Force Microscopy (AFM), Fourier
Transform Infrared (FTIR). PS layers were formed on n-type Si
wafer. Anodized electrically with a 20, 30, 40, 50 and 60 mA/cm2
current density for fixed 10 min etching times. XRD confirms the
formation of porous silicon, the crystal size is reduced toward
nanometric scale of the face centered cubic structure, and peak
becomes a broader with increasing the current density. The AFM
investigation shows the sponge like structure of PS at the lower
current density porous begi
The new Schiff base, namely (2-Amino-phenylimino)-acetic acid (L) was prepared
from condensation of glyoxylic acid with o-phenylene diamine. The structure (L) was
characterized by, IR,
1
H,
13
C-NMR and CHN analysis. Metal complexes of the ligand (L)
were synthesized and their structures were characterized by Atomic absorption, IR and UV-Visible spectra, molar conductivity, magnetic moment and molar ratio determination (Co
+2
,
Cd
+2
) complexes. All complexes showed octahedral geometries.
Expanded use of antibiotics may increase the ability of pathogenic bacteria to develop antimicrobial resistance. Greater attention must be paid to applying more sustainable techniques for treating wastewater contaminated with antibiotics. Semiconductor photocatalytic processes have proven to be the most effective methods for the degradation of antibiotics. Thus, constructing durable and highly active photocatalytic hybrid materials for the photodegradation of antibiotic pollutants is challenging. Herein, FeTiO3/Fe-doped g-C3N4 (FTO/FCN) heterojunctions were designed with different FTO to FCN ratios by matching the energy level of semiconductors, thereby developing effective direct Z-type heterojunctions. The photodegradation behaviors of th
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