In this study, multi-objective optimization of nanofluid aluminum oxide in a mixture of water and ethylene glycol (40:60) is studied. In order to reduce viscosity and increase thermal conductivity of nanofluids, NSGA-II algorithm is used to alter the temperature and volume fraction of nanoparticles. Neural network modeling of experimental data is used to obtain the values of viscosity and thermal conductivity on temperature and volume fraction of nanoparticles. In order to evaluate the optimization objective functions, neural network optimization is connected to NSGA-II algorithm and at any time assessment of the fitness function, the neural network model is called. Finally, Pareto Front and the corresponding optimum points are provided and introduced. Optimal results showed that the optimum viscosity and thermal conductivity occurs at maximum temperature.
Thermal conductivity for epoxy composites filled with Al2O3 and Fe2O3 are
calculated, it found that increasing the weight ratio of Al2O3 and Fe2O3 lead to
increase in the values of thermal conductivity, but the epoxy composite filled with
Fe2O3, have values of thermal conductivity less than for epoxy composite filled with
Al2O3, for the same weight ratio. Also thermal conductivity calculated for epoxy
composites by contact to every two specimens (like sandwich) content same weight
ratio of alumina-oxide and ferrite-oxide, its found that the value of thermal
conductivity lays between the values of epoxy filled Al2O3 and of epoxy filled Fe2O3
A Schiff base ligand 1,2-[Bis-(1-phenyl-2-hydroxy-2-phenyl)-amino] benzene [H2L] and its complexes with (Cu(II), Zn(II), Cd(II) and Hg(II)) ions are reported. The ligand was prepared by condensation reaction of ortho-phenylenediamine in methanol under reflux with benzoin to give the mentioned ligand. Then the complexes were synthesized by adding corresponding metal salts to the solution of the ligand in methanol under reflux with 1:1 metal to ligand ratio. On the basis of molar conductance I.R., U.V-Vis, HPLC, chloride content and atomic absorption the complexes may be formulated as K2[M(L)Cl2][MII = Cu, Zn, Cd and Hg]. The data of these measurements suggest a tetrahedral geometry to complexes Cu, Zn, Cd and Hg.
The research included preparation of new Schiff base (L) by two steps: preparation of precursor [bis(2-formyl-6-methoxyphenyl) succinate] (P) by reacting (3-methoxy salicyl aldehyde) with (succinoyl dichloride) as first step then react the prepared precursor (P) with (ethanethioamide) to have the new Schiff base [bis(2-((ethane thioyl imino) methyl)-6-methoxy phenyl) succinate] (L) as second step. Characterized compounds based on Mass spectra, 1 H, 13CNMR (for ligand (L)), FT-IR and UV spectrum, melting point, molar conduct, %C, %H, and %N, the percentage of the metal in complexes %M, magnetic susceptibility, while study corrosion inhibition (mild steel) in acid solution by weight loss. These measurements proved that by (Oxygen, Nitrogen, a
... Show MoreIn this paper, a comparison between horizontal and vertical OFET of Poly (3-Hexylthiophene) (P3HT) as an active semiconductor layer (p-type) was studied by using two different gate insulators (ZrO2 and PVA). The electrical performance output (Id-Vd) and transfer (Id-Vg) characteristics were investigated using the gradual-channel approximation model. The device shows a typical output curve of a field-effect transistor (FET). The analysis of electrical characterization was performed in order to investigate the source-drain voltage (Vd) dependent current and the effects of gate dielectric on the electrical performance of the OFET. This work also considered the effects of the capacitance semiconductor on the performance OFETs. The value
... Show MoreChurning of employees from organizations is a serious problem. Turnover or churn of employees within an organization needs to be solved since it has negative impact on the organization. Manual detection of employee churn is quite difficult, so machine learning (ML) algorithms have been frequently used for employee churn detection as well as employee categorization according to turnover. Using Machine learning, only one study looks into the categorization of employees up to date. A novel multi-criterion decision-making approach (MCDM) coupled with DE-PARETO principle has been proposed to categorize employees. This is referred to as SNEC scheme. An AHP-TOPSIS DE-PARETO PRINCIPLE model (AHPTOPDE) has been designed that uses 2-stage MCDM s
... Show MoreThe main problem established by a discovery of a thyroid nodule is to discriminate between a benign and malignant lesion. Differential diagnosis between follicular thyroid cancer (FTC) and benign follicular thyroid adenoma (FTA) is a great challenge for even an experienced pathologist and requires special effort. A developing number of some encouraging IHC markers for the differential diagnosis of thyroid lesions have emerged, including, Hector Battifora mesothelial (HBME-1) and galectin-3 (Gal-3). There was significant positive correlation between Galectin-3 and HBME-1 in follicular carcinoma and follicular variant of papillary carcinoma (r= 0.380, P= 0.041) and (r= 0.315, P=0.047) respectively. There was no significant correlation between
... Show MoreNew binuclear Mn(II), Co(II), Ni(II), Cu(II), Zn(II), and Hg(II) Complexes of N2S2 tetradentate or N4S2 hexadentate symmetric Schiff base were prepared by the condensation of butane-1,4-diylbis(2-amino ethylcarbamodithioate) with 3-acetyl pyridine. The complexes having the general formula [M2LCl4] (where L=butane-1,4-diyl bis (2-(z)-1-(pyridine-3-ylethylidene amino))ethyl carbamodithioate, M= Mn(II), Co(II), Ni(II), Cu(II), Zn(II), and Hg(II)), were prepared by the reaction of the mentioned metal salts and the ligand. The resulting binuclear complexes were characterized by molar conductance, magnetic susceptibility ,infrared and electronic spectral measurements. This study indicated that Mn(II), Ni(II) and Cu(II) complexes have octahedral g
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