The multi-dentate Schiff base ligand (H2L), where H2L=2,2'-(((1,3,5,6)-1-(3-((l1-oxidaneyl)-l5-methyl)-4-hydroxyphenyl)-7-(4-hydroxy-3-methoxyphenyl)hepta-1,6-di ene-3,5-diylidene)bis(azaneylylidene))bis(3-(4-hydroxyphenyl)propanoic acid), has been prepared from curcumin and L- Tyrosine amino acid. The synthesized Schiff base ligand (H2L) and the second ligand 1,10-phenanthroline (phen) are used to prepare the new complexes [Al(L)(phen)]Cl, K[Ag(L)(phen)] and [Pb(L)(phen)]. The synthesized compounds are characterized by magnetic susceptibility measurements, micro elemental analysis (C.H.N), mass spectrometry, molar conductance, FT-infrared, UV-visible, atomic absorption (AA), 13C-NMR, and 1H-NMR spectral studies. The characterization of the synthesized complexes shows that the environment surrounding the central metal ion in the complexes adopted a distorted octahedral configuration. Moreover, the conductivity measurements show a non-electrolytic character for the [Pb(L)(phen)] complex and an electrolytic character for the [Al(L)(phen)]Cl and K[Ag(L)(phen)] complexes. The experimental infrared data are supported by density functional theory (DFT) calculations using the B3LYP level of theory and LANL2DZ basis set. The vibrational frequencies of the molecules are computed using the optimized geometry obtained from the DFT calculations. The calculated vibrational frequencies have been compared with obtained experimental values. 1H and 13C-NMR chemical shifts were computed for the H2L ligand using the DFT/GIAO method. Additionally, the molecular electronic structures of the complexes have been investigated by DFT calculations.
The synthesis, characterization and liquid crystalline properties of N4,N40 -bis((1 H-benzo[d]imidazol-2- yl)methyl)-3,30 -dimethyl-[1,10 -biphenyl]-4,40 -diamine and of their corresponding Mn(II), Fe(II), Ni (II), Cu(II), and Zn(II) complexes are described. The ligand and complexes have been characterized by elemental analysis, magnetic susceptibility measurements (meff), conductometric measurements and Fourier Transform Infrared (FTIR), Nuclear Magnetic Resonance (1 H NMR), (13C-NMR) and UV–Vis spectroscopy. Spectral investigations suggested octahedral coordination geometrical arrangement for M(II) complexes. The phase transition temperatures were detected by differential scanning calorimetry (DSC) analysis and the phases are confirmed
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CuO nanoparticles were synthesized in two different ways, firstly by precipitation method using copper acetate monohydrate Cu(CO2CH13)2·H2O, glacial acetic acid (CH3COOH) and sodium hydroxide(NaOH), and secondly by sol-gel method using copper chloride(CuCl2), sodium hydroxide (NaOH) and ethanol (C2H6O). Results of scanning electron microscopy (SEM) showed that different CuO nanostructures (spherical and Reef) can be formed using precipitation and sol- gel process, respectively, at which the particle size was found to be less than 2 µm. X-ray diffraction (XRD)manifested that the pure synthesized powder has no inclusions that may exist during preparations. XRD result
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The Catharanthus roseus plant was extracted and converted to nanoparticles in this work. The Soxhlet method was used to extract alkaloid compounds from the Catharanthus roseus plant and converted them to the nanoscale. Chitosan polymer was used as a linking material and converted to Chitosan nanoparticles (CSNPs). The extracted alkaloids were linked with Chitosan nanoparticles by maleic anhydride to get the final product (CSNPs-Linker-alkaloids). The pure Chitosan, Chitosan nanoparticles, and CSNPs-Linker-alkaloids were characterized by X-ray diffractometer, and Fourier Transform Infrared spectroscopy. X-ray results show that all samples have an orthorhombic structure with crystallite size in nanodimensions. FTIR spectra prove that
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In this article the conventional "solid-state reaction" method was used to synthesize perovskite Li0.4Cd0.6Ba2Ca2Cu3O10+δ. Four main types of compounds were obtained by physically replacing calcium oxide with cadmium in proportions 0, 0.03, 0.06 and 0.09, the pure Li0.4Cd0.6Ba2Ca2Cu3O10+δ phase, and the phases Li0.4Cd0.6Ba2Ca1.97Cd0.03Cu3O10+δ
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The influence of process speed (PS) and tillage depth (TD) , on growth of corn (Zea mays L) yield, for Maha cultivar, were tested at two ranges of PS of 2.483 and 4.011 km.hr-1, and three ranges of TD of 15,20 and 25cm. The experiments were conducted in a factorial experiment under complete randomized design with three replications. The results showed that the PS of 2.483 km.hr-1 was significantly better than the PS of 4.011km.hr-1 in all studied conditions. The , slippage ratio (SR) and the machine efficiency (ME), the physical soil characteristics represented by the soil density and porosity (SBD and TSP), and the plant characteristics represented the roots dry weight, PVI and the crop productivity (CP), except adjective of the fu
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This investigation reports application of a mesoporous nanomaterial based on dicationic ionic liquid bonded to amorphous silica, namely nano-N,N,N′,N′-tetramethyl-N-(silican-propyl)-N′-sulfo-ethane-1,2-diaminium chloride (nano-[TSPSED][Cl]2), as an extremely effectual and recoverable catalyst for the generation of bis(pyrazolyl)methanes and pyrazolopyranopyrimidines in solvent-free conditions. In both synthetic protocols, the performance of this catalyst was very useful and general and presented attractive features including short reaction times with high yields, reasonable turnover frequency and turnover number values, easy workup, high performance under mild conditions, recoverability and reusability in 5 consecutive runs without lo
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The high cost of chemical analysis of water has necessitated various researches into finding alternative method of determining portable water quality. This paper is aimed at modelling the turbidity value as a water quality parameter. Mathematical models for turbidity removal were developed based on the relationships between water turbidity and other water criteria. Results showed that the turbidity of water is the cumulative effect of the individual parameters/factors affecting the system. A model equation for the evaluation and prediction of a clarifier’s performance was developed:
Model: T = T0(-1.36729 + 0.037101∙10λpH + 0.048928t + 0.00741387∙alk)
The developed model will aid the predictiv
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