In this research, nanofibers have been prepared by using an electrospinning method. Three types of polymer (PVA, VC, PMMA) have been used with different concentration. The applied voltage and the gap length were changed. It was observed that VC is the best polymer than the other types of polymers.

Hydrogen sulfide removal catalyst was prepared chemically by precipitation of zinc bicarbonate at a controlled pH. The physical and chemical catalyst characterization properties were investigated. The catalyst was tested for its activity in adsorption of H₂S using a plant that generates the H₂S from naphtha hydrodesulphurization and a unit for the adsorption of H₂S. The results comparison between the prepared and commercial catalysts revealed that the chemical method can be used to prepare the catalyst with a very good activity.

It has observed that the hydrogen sulfide removal over zinc oxide catalyst follows first order reaction kinetics with activation energy of 19.26 kJ/mole and enthalpy and e

Hybrid architecture of ZnO nanorods/graphene oxide ZnO-NRs@GO synthesized by electrostatic self-assembly methods. The morphological, optical and luminescence characteristics of ZnO-NRs@GO and ZnO-NRs thin films have been described by FESEM, TEM, HRTEM, and AFM, which refers to graphene oxide have been coated ZnO-NRs with five layers. Here we synthesis ZnO-NRs@GO by simple, cheap and environmentally friendly method, which made it favorable for huge -scale preparation in many applications such as photocatalyst. ZnO-NRs@GO was applied as a photocatalyst Rodamin 6 G (R6G) dye from water using 532 nm diode laser-induced photocatalytic process. Overall degradation of R6G/ ZnO-NRs@GO was achieved after 90 minutes of laser irradiation while it ne

This work includes preparation of Az, Qz, and Tz derivatives from the reaction of Schiff base (Sb) derivative with anthranilic acid, chloroacetyl chloride, and sodium azide, as well as, the characterization via FT-IR, 1H-NMR, and 13CNMR. The anticorrosion inhibition of these compounds was studied and the measurements of carbon steel (CS) corrosion in sodium chloride solution 3.5% (blank) and inhibitor in solutions were calculated at a temperature range of 293-323 K by the technique of electrochemical polarization. In addition, some thermodynamic and kinetic activation parameters for inhibitor and blank solutions (Ea⋇, ΔH⋇, ΔS⋇, and ΔG⋇) were determined. The results showed high inhibition efficacy for all the prepared compounds,

The increasing use of antiseptic compounds creates selective pressure cause emergence of antiseptic resistance among Staphylococcus aureus .Resistance mechanism of antiseptic is driven mainly by multi drug resistant (MDR) efflux protein.Sixty five isolates of S.aureuswere collected from different clinical sources and subjected to 11 antibiotics most of them are recognized by efflux systems as extruded substrates. Range of efflux activity was estimated using cartwheel method. Simultaneous discrimination of antiseptic coding genes (qacA/B, smr and norA)as well as nuc and mecA genes among multidrug resistantS.aureus(MRSA) isolates was preformed using multiplex PCR assay

In this research, a group of complexes were prepared which were derived from Schiff base ligands, which is called (1E,1'E)-1,1'-(1,2-phenylene)bis(N-(2,4-dichlorophenyl) methanimine) (L) with ortho-phenanthroline (o-phen).The prepared complexes areM(II) [Co(II),Ni(II),Cu(II), Zn(II), Cd(II),and Hg(II)].A range of spectroscopic and technical techniques have been used to characterizethese materials, including:The FTIR, 1H-NMR, LC-Mass Spectrum, UV-Visbale, molar conductance, and magnaticmoment, atomic absorbtion, chlorid contents. Spectral results obtainedare showen that (ortho-phen) and (L) behave as neutral coordinating to the central metal ion by the donatingatoms(N2)of the both compounds. The geometry sha

The aim of this research is to prepare a set of complexes with the general formula [M(HMB)n] , where M=VO (II) , Cr(III) and Cu(II) while  n=2,3,2 respectively resulting from the reaction of anew ligand [N'-(2-hydroxy-3-methoxybenzyl)-4-methylbenzohydrazide] (HMB) derived from the reaction of the tow substances (4-methylbenzohydrazide  and 2-hydroxy-3-methoxy benzaldehyde) with metal ions. The prepared compounds were identified by several spectroscopic methods such as Infrared, Nuclear Magnetic Resonance and Electronic Spectra. From the results of the measurements, it was suggested that the prepared complexes have different geometries such as square planar (Cu), square pyramidal (VO) and octahedral (Cr). DFT simulations backed up

This research involved synthesis of new β-Lactam derivative from Azo compound[4-amino-N-(pyrimidine-2-yl)-3-(pyrimidine-2-yldiazenyl) benzene sulfonamide] (S1) record previously by many steps. Starting conversion the free amino group in an azo comp. to chloro acetamide derivative(S2), then reacted it with urea to give the oxazole ring  derivative (S3) that which containing free amino group. The condensation reaction between the amino group and P-bromobenzaldehyde to produce Shiff base (B14). Finally staudinger's cyclo addition reaction go run between the Shiff base derivative (B14) and chloro acetyl chloride in the presence of tri ethyl amine (Et₃N) as Base catalyst and dioxane a

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de