A pioneering idea for increasing the thermal performance of heat transfer fluids was to use ultrafine solid particles suspended in the base fluid. Nanofluids, synthesized by mixing solid nanometer sized particles at low concentrations with the base fluid, were used as a new heat transfer fluid and developed a remarkable effect on the thermophysical properties and heat transfer coefficient. For any nanofluid to be usable in heat transfer applications, the main concern is its long-term stability. The aim of this research is to investigate the effect of using four different surfactants (sodium dodecyl benzene sulfonate (SDBS), sodium dodecyl sulfate (SDS), cetyl trimethylammonium bromide (CTAB), and gum Arabic (GA)), each with three different concentrations, and five ultrasonication times (15, 30, 60, 90, and 120 min) on the stability of water-based graphene nanoplatelets (GNPs) nanofluids. In addition, the viscosity and thermal conductivity of the highest stability samples were measured at different temperatures. For this aim, nineteen different nanofluids with 0.1 wt% concentration of GNPs were prepared via the two-step method. An ultrasonication probe was utilized to disperse the GNPs in distilled water. UV–vis spectrometry, zeta potential, average particle size, and Transmission Electron Microscopy (TEM) were helpful in evaluating the stability and characterizing the prepared nanofluids. TEM and zeta potential results were in agreement with the UV–vis measurements. The highest nanofluid stability was obtained at 60-min ultrasonication time. The prepared water-based pristine GNPs nanofluids were not stable, and the stability was improved with the addition of surfactants. The presence of SDBS, SDS, and CTAB surfactants in the nanofluids resulted in excessive foam. The best water-based GNPs nanofluid was selected in terms of better stability, higher thermal conductivity, and lower viscosity. From all the samples that were prepared in this research, the (1–1) SDBS–GNPs sample with 60-min ultrasonication showed the highest stability (82% relative concentration after 60 days), the second better enhancement in the thermal conductivity of the base fluid (8.36%), and nearly the lowest viscosity (7.4% higher than distilled water).
The research includes the study of the scientific miracle in the verse: (It is the one who made you the earth humiliation and walked in their positions and eat from the living and to the publication of the human body and in the Qur'an) And mental and spiritual. The research also pointed to the tight link between the miracle of the precedent in the Holy Quran and the miracle of the divine power in the book of the Infinite Universe to give each miracle testimony of delivery and ratification of the other. The research included after the introduction, the first topic included four demands, which included basic concepts: - Definition of scientific miracle and its importance in the Koran, and the significance of the universal verses in the Kor
... Show MoreA new four series of 2,2′-([1,1′- phenyl or biphenyl]-4,4′-diylbis(azanediyl)) bis(N′-((E)-1-(4-alkoxyphenyl) ethylidene) acetohydrazide) [V-XI]a,b and 1,1′-(2,2′-([1,1′- phenyl or biphenyl]-4,4′-diyl bis(azanediyl)) bis- (acetyl)) bis(3-(4-ethoxyphenyl)-1H-pyrazole-4-carbalde hyde) [XII-XVIII]a,b have been synthesized by varying terminal lateral alkoxy chain length (n = 1–3, 5–8), central linkage group (phenyl or biphenyl) and induced pyrazole heterocyclic ring in the main chain. The last two series were synthesized by the cyclization of substituted acetophenone hydrazones with Vilsmeier–Haack reagent (DMF/POCl3) to produce 4-formylpyrazole derivatives. The chemical structures of the synthesized compounds were examine
... Show MoreThe current research's problem includes the impact of cognitive reappraisal and reformulate on self-experience of emotional response and its negative feelings and the activity of cognitive reappraisal in changing response. The aim of this research is to detect the relation between adaptive response and cognitive reappraisal upon students of secondary school, and to find differences in gender and stage. The sample contained male and female student for the year(2022-2023) and consists of (480) students (240) male and (240) female in the karkh education/ 1 To achieve this aims researcher used descriptive method and to measure the two variables researcher built a scale for adaptive response according to theory of compound emotion (Barrett,20
... Show MoreIn this paper, three approximate methods namely the Bernoulli, the Bernstein, and the shifted Legendre polynomials operational matrices are presented to solve two important nonlinear ordinary differential equations that appeared in engineering and applied science. The Riccati and the Darcy-Brinkman-Forchheimer moment equations are solved and the approximate solutions are obtained. The methods are summarized by converting the nonlinear differential equations into a nonlinear system of algebraic equations that is solved using Mathematica®12. The efficiency of these methods was investigated by calculating the root mean square error (RMS) and the maximum error remainder (𝑀𝐸𝑅n) and it was found that the accuracy increases with increasi
... Show MoreThis article comprehensively examines the history, diagnosis, genetics, diversity, and treatment of SARS-CoV-2. It details the emergence of coronaviruses over the past 50 years, including the coronavirus from 2019 and its subsequent mutations, along with updated information about this virus. This review explains the development and nomenclature of coronaviruses, their cellular invasion through glycoprotein spikes binding to ACE-2 receptors, and the mechanism of cell entry via endocytosis. Diagnosis methods for COVID-19, including nucleic acid amplification, serology, and imaging techniques like chest X-ray and CT scan tests, are discussed. Treatment approaches for COVID-19 are outlined, emphasizing healthcare, antiviral medications like Rem
... Show MoreThis work implements an Electroencephalogram (EEG) signal classifier. The implemented method uses Orthogonal Polynomials (OP) to convert the EEG signal samples to moments. A Sparse Filter (SF) reduces the number of converted moments to increase the classification accuracy. A Support Vector Machine (SVM) is used to classify the reduced moments between two classes. The proposed method’s performance is tested and compared with two methods by using two datasets. The datasets are divided into 80% for training and 20% for testing, with 5 -fold used for cross-validation. The results show that this method overcomes the accuracy of other methods. The proposed method’s best accuracy is 95.6% and 99.5%, respectively. Finally, from the results, it
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