Metal-organic frameworks (MOFs) are a relatively new class of materials of unique porous structures and exceptional properties. Currently, more than 110,000 types of MOFs have been reported among the countless possibilities. In this study, we have synthesised a novel MOF using zirconium chloride as the metal source and 4,4'-dicarboxy-2,2'-biquinoline (bicinchoninic acid disodium salt) as the linker, which reacted in N,N-Dimethylformamide (DMF) solvent. Three preparation methods were employed to prepare five types of the MOF, and they were compared to optimize the synthesis conditions. The resulting MOFs, named Zr-BADS, were characterised using scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), microscopy, and X-ray diffraction (XRD). By incorporating methanol into the preparation solvent, the surface area was increased to 396 m2/g. Additionally, the prepared MOFs exhibited amorphous shapes, with variations in size depending on the synthesis method. This research demonstrates the significance of the preparation method in controlling resulting particles’ properties.
This work reports the synthesis and characterization of some Co(111), Ni(11), Cu(11), Zn(l 1), Cd(1 1) and Hg(11) chelates of the new benzothia-zolylazo Ligand ( 5-Me-BTAC ) . The compounds were Characterized by IR , electronic spectroscopy, magnetic susceptibility ,elemental analysis and molar conductance measurements . The elemental analysis suggest the formula [ ML2 ] x.nH2O where x=Cl , n=1 for M= Co(111) and x=o , n=o for the remaining metal ions Electronic spectra and magnetic susceptibility data has supported the proposed octahedral geometry of Co(111) Ni(11) and Cu(1 I) Complexes. Conductivity measurements refer to nonionic structure of these Complexes except of Co(111) .
A new Schiff base, 2-N( 4- N,N – dimethyl benzyliden )5 – (p- methoxy phenyl) – 1,3,4- thiodiazol ,and their metal complexes Cu (Π) ,Ni (Π), Fe (III) , Pd (Π) , Pt (IV) , Zn(Π) ,V(IV) and Co (Π) , were synthesized. The prepared complexes were identified and their structural geometries were suggested by using flam atomic absorption technique , FT-IR and Uv-Vis spectroscopy, in addition to magnetic susceptibility and conductivity measurements. The study of the nature of the complexes formed in ethanol solution , following the mole ratio method , gave results which were compared successfully with those obtained from the isolated solid state studied. Structur
... Show MoreHydrogen productions were achieved by irradiating ethanol ic aqueous solutions (20%. v/v) containing mixtures of the ligand 2,4- dimethoxybcnzylidene-2-hydroxy aniline (HL) or one of i ts complexes (ML2) wi th the following divalent ions: fVbl (II), Fc(IT), Co(II). Ni( rt ), Cu(H) and Zn (11), as photosensi1izers, methyl viol ogen (MY.:-) as electron acceptor. ethylene diamine  
... Show MoreThe ligand 2-[1-(1H-indol-3-yl)ethylimino) methyl]naphthalene-1-ol, derived from 1-hydroxy-2-naphthaldehyde and 2-(1H-indol-3-yl)ethylamine, was used to produce a new sequence of metal ions complexes. Thus ligand reactions with NiCl2.6H2O, PdCl2, FeCl3.6H2O and H2PtCl6.6H2O were sequentially made to collect mono-nuclear Ni(II), Pd(II), Fe (III), and Pt(IV). (IR or FTIR), Ultraviolet Reflective (UV–visible), Mass Spectra analysis, Bohr-magnetic (B.M.), metal content, chloride content and molar conductivity have been the defining features of the composites. The Fe(III) and Pt(IV) complexes have octahedral geometries, while the Ni(II) complex has tetra
... Show MoreA batch and flow injection (FI) spectrophotometric methods are described for the determination of barbituric acid in aqueous and urine samples. The method is based on the oxidative coupling reaction of barbituric acid with 4-aminoantipyrine and potassium iodate to form purple water soluble stable product at λ 510 nm. Good linearity for both methods was obtained ranging from 2 to 60 μg mL−1, 5–100 μg mL−1 for batch and FI techniques, respectively. The limit of detection (signal/noise = 3) of 0.45 μg mL−1 for batch method and 0.48 μg mL−1 for FI analysis was obtained. The proposed methods were applied successfully for the determination of barbituric acid in tap water, river water, and urine samples with good recoveries of 99.92
... Show MoreBackground: The immunogenetic predisposition
may be considered as an important factor for the
development of Type 1 Diabetes Mellitus (T1DM)
in association with the HLA antigens.
Objective:This study was designed to investigate
the role of HLA-class II antigens in the etiology of
type T1DM and in prediction of this disease in
siblings, and its effect on expression of glutamic
acid decarboxylase autoantibodies (GADA).
methods:Sixty children who were newly diagnosed
type 1 diabetes (diagnosed less than five months)
were selected. Their age ranged from 3-17 years.
Another 50 healthy siblings were available for this
study, their ages range from 3-16 years. Eighty
apparently healthy control subjects,
This study uses an environmentally friendly and low-cost synthesis method to manufacture zinc oxide nanoparticles (ZnO NPs) by using zinc sulfate. Eucalyptus leaf extract is an effective chelating and capping agent for synthesizing ZnO NPs. The structure, morphology, thermal behavior, chemical composition, and optical properties of ZnO nanoparticles were studied utilizing FT-IR, FE-SEM, EDAX, AFM, and Zeta potential analysis. The FE-SEM pictures confirmed that the ZnO NPs with a size range of (22-37) nm were crystalline and spherical. Two methods were used to prepare ZnO NPs. The first method involved calcining the resulting ZnO NPs, while the second method did not. The prepared ZnO NPs were used as adsorbents for removing acid black 210
... Show MoreWireless Body Area Sensor Network (WBASN) is gaining significant attention due to its applications in smart health offering cost-effective, efficient, ubiquitous, and unobtrusive telemedicine. WBASNs face challenges including interference, Quality of Service, transmit power, and resource constraints. Recognizing these challenges, this paper presents an energy and Quality of Service-aware routing algorithm. The proposed algorithm is based on each node's Collaboratively Evaluated Value (CEV) to select the most suitable cluster head (CH). The Collaborative Value (CV) is derived from three factors, the node's residual energy, the distance vector between nodes and personal device, and the sensor's density in each CH. The CEV algorithm operates i
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