Copper oxide (CuO) nanoparticles were synthesized through the thermal decomposition of a copper(II) Schiff-base complex. The complex was formed by reacting cupric acetate with a Schiff base in a 2:1 metal-to-ligand ratio. The Schiff base itself was synthesized via the condensation of benzidine and 2-hydroxybenzaldehyde in the presence of glacial acetic acid. This newly synthesized symmetric Schiff base served as the ligand for the Cu(II) metal ion complex. The ligand and its complex were characterized using several spectroscopic methods, including FTIR, UV-vis, 1H-NMR, 13C-NMR, CHNS, and AAS, along with TGA, molar conductivity and magnetic susceptibility measurements. The CuO nanoparticles were produced by thermally decomposing the

The present study aimed to synthesize selenium nanoparticles (SeNPs) using aqueous extract of black currant as a reducing agent. The green synthesized black currant selenium nanoparticles (BCSeNPs) were identified by color change. The characterization of SeNPs was achieved by Ultraviolet-visible (UV–VIS) spectroscopy, scanning electron microscopy (SEM), X–ray diffraction analysis (XRD), and Fourier transform infrared spectroscopy (FTIR). These tests were used to detect: stability, morphology, size, crystalline nature, and functional groups present on the surface of BCSeNPs. The results revealed appearance of the brick-red color indicating the specific color of selenium nanoparticles, and UV-Vis spectroscopy showed band absorbanc

Binuclear copper, nickel, cobalt, manganese and mercury complexes of the Schiff base H2L (C40H28N2O4) obtained by condensation of 2-benzoyl benzoic acid with benzidine.  The Schiff base and their complexes have been subjected to[ FT-IR, elemental analysis ,UV-Vis, 1H and 13C NMR ] spectral studies, molar conductivity, magnetic moment and HPLC measurements. All the complexes showed tetrahedral geometries with the general structure [M2(L)2].  Generality of the synthesized components offer antibacterial efficiency to (Staphylococcu saureus), (Escherichia coli),(Bacillus subtilis) and(Pseudomonas aeruginosa).
 

RKASFH Ghanim, Ibn Al -Haitham Journal for pure and applied science, 2017

Myrtle plant was washed, dried, and powdered after harvesting to produce a fine powder that was used in water treatment. created an alcoholic extract from the myrtle plant using ethanol, which was then analyzed using GC-Mass, Fourier Transform Infrared spectroscopy, and ultraviolet-visible spectroscopy to identify the active components. Zinc nanoparticles were created using alcoholic extract. We used FTIR, UV-Vis, SEM, EDX, and TEM to characterize zinc nanoparticles. Using a continuous processing procedure, zinc nanoparticles with myrtle extract and powder were employed to clean polluted water containing heavy metals.

Firstly used 2g with 20ml polluted water and the result was ( Fe 96.20%, Cr 84%, Pb 100%, Sb 93.70, Cd 100%, andCu

In recent years, infectious diseases are increasingly being encountered in clinical settings. Due to the development of antibiotic resistance and the outbreak of these diseases caused by resistant pathogenic bacteria, the pharmaceutical companies and the researchers are now searching for new unconventional antibacterial agents. Recently, in this field, the application of nanoparticles is an emerging area of nanoscience and nanotechnology. For this reason, nanotechnology has a great deal of attention from the scientific community and may provide solutions to technological and environmental challenges. A common feature that these nanoparticles exhibit their antimicrobial behavior against pathogenic bacteria. In this report, we evaluate

The alfalfa plant, after harvesting, was washed, dried, and grinded to get fine powder used in water treatment. We used the alfalfa plant with ethanol to make the alcoholic extract characterized by using (GC-Mass, FTIR, and UV) spectroscopy to determine active compounds. Alcoholic extract was used to prepare zinc nanoparticles. We characterized Zinc nanoparticles using (FTIR, UV, SEM, EDX Zeta potential, XRD, AFM). Zinc nanoparticle with Alfalfa extract and alfalfa powder were used in the treatment of water polluted with inorganic elements such as Cr, Mn, Fe, Cu, Cd, Ag by (Batch processing). The batch process with using alfalfa powder gets treated with Pb (51.45%), which is the highest percentage of treatment. Mn (13.18%), which is the

Some maps of the chaotic firefly algorithm were selected to select variables for data on blood diseases and blood vessels obtained from Nasiriyah General Hospital where the data were tested and tracking the distribution of Gamma and it was concluded that a Chebyshevmap method is more efficient than a Sinusoidal map method through mean square error criterion.

This paper includes an experimental study of hydrogen mass flow rate and inlet hydrogen pressure effect on the fuel cell performance. Depending on the experimental results, a model of fuel cell based on artificial neural networks is proposed. A back propagation learning rule with the log-sigmoid activation function is adopted to construct neural networks model. Experimental data resulting from 36 fuel cell tests are used as a learning data. The hydrogen mass flow rate, applied load and inlet hydrogen pressure are inputs to fuel cell model, while the current and voltage are outputs. Proposed model could successfully predict the fuel cell performance in good agreement with actual data. This work is extended to developed fuel cell feedback