The study involved preparing a new compound by combining Schiff bases generated from compounds for antipyrine, including lanthanide ions (lanthanum, neodymium, erbium, gadolinium, and dysprosium). The preparation of the ligand from condensation reactions (4-antipyrinecarboxaldehyde with ethylene di-amine) at room temperature, and was characterization using spectroscopic and analytical studies ( FT-IR, UV-visible spectra, ¹H-NMR, mass spectrometry, (C.H.N.O), thermogravimetric analysis (TGA), in addition to the magnetic susceptibility and conductivity measurement of the synthesis complexes, among the results we obtained from the tests, we showed that the ligand behaves with the (triple Valence) lanthanide ions, the multidentate

An environmentally friendly technique was used to prepare titanium dioxide@ silver (core shell) (TiO₂@Ag NPs) using chard leaf extract, a natural stabilizer and reductant. A nanocomposite (NCs) of TiO₂@Ag supported by halloysite nanotubes (HNTs), TiO2@Ag/HNT NCs, was prepared under microwave irradiation. The microwave technique is used to accelerate the reaction and enhance the homogeneity of nanoparticle distribution. Spectroscopic and structural analyses were performed on the resulting nanocomposite. X-ray diffraction (XRD) revealed a clear crystalline structure with grain sizes ranging from 7 to 15 nm, with an average of ~11 nm, the transmission electron microscope (TEM) revealed that the size of nanoparticles in the TiO₂@Ag/HNT N

In this article, new Schiff base ligand LH-prepared Mn(II), Co(II), Ni(II), Cu(II), Zn(II), Cd(II), Hg(II), Pd(II), and Pt(II) materials were analyzed using spectroscopy (1 Metal: 2 LH). The ligand was identified using techniques such as FTIR, UV-vis, 1H-13C-NMR, and mass spectra, and their complexes were identified using CHN microanalysis, UV-vis and FTIR spectral studies, atomic absorption, chloride content, molar conductivity measurements, and magnetic susceptibility. According to the measurements, the ligand was bound to the divalent metal ions as a bidentate through oxygen and nitrogen atoms. The complexes that were created had microbicide activity against two different bacterial species and one type of fungus. DPPH techniques were bei

In this study, cloud point extraction combined with molecular spectrometry as an eco-friendly method is used for extraction, enrichment and determination of bendiocarb (BC) insecticide in different complex matrices. The method involved an alkaline hydrolysis of BC followed Emerson reaction in which the resultant phenol is reacted with 4-aminoantipyrene(4-AAP) in the presence of an alkaline oxidant of potassium ferric cyanide to form red colored product which then extracted into micelles of Triton X-114 as a mediated extractant at room temperature. The extracted product in cloud point layer is separated from the aqueous layer by centrifugation for 20 min and dissolved in a minimum amount of a mixture ethanol: water (1:1) followed

Corrosion resistance of metals is one of the most important topics for researchers. In this work, epoxy-TiO2 nanocomposite has been developed for protection of 6061AL alloy. The dip-coating technique used to deposit the coating on 6061 Al alloy substrate. Different concentrations of TiO2 NPs (1,3,5 )Wt% have been used to study the corrosion behavior in 3.5% NaCl medium. Also, 200,150 and 100 mm/min dipping speeds have been employed for 1%wt TiO2 to show their effects on coating layer and corrosion rate. Characterization of coated surfaces were investigated by AFM, FESEM andEDS,while theelectrochemical measurementswas using to evaluate protective nature of the coating. The results have shown that the corrosion rate has decreased with

Analyzing sentiment and emotions in Arabic texts on social networking sites has gained wide interest from researchers. It has been an active research topic in recent years due to its importance in analyzing reviewers' opinions. The Iraqi dialect is one of the Arabic dialects used in social networking sites, characterized by its complexity and, therefore, the difficulty of analyzing sentiment. This work presents a hybrid deep learning model consisting of a Convolution Neural Network (CNN) and the Gated Recurrent Units (GRU) to analyze sentiment and emotions in Iraqi texts. Three Iraqi datasets (Iraqi Arab Emotions Data Set (IAEDS), Annotated Corpus of Mesopotamian-Iraqi Dialect (ACMID), and Iraqi Arabic Dataset (IAD)) col