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Study the Electronic and Spectroscopic Characteristics of p-n Heterojunction Hybrid (Sn10O16/C24O6) via Density Functional Theory (DFT)
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The electronic characteristics, including the density of state and bond length, in addition to the spectroscopic properties such as IR spectrum and Raman scattering, as a function of the frequency of Sn10O16, C24O6, and hybrid junction (Sn10O16/C24O6) were studied. The methodology uses DFT for all electron levels with the hybrid function B3-LYP (Becke level, 3-parameters, Lee–Yang-Parr), with 6-311G (p,d)  basis set, and Stuttgart/Dresden (SDD) basis set, using Gaussian 09 theoretical calculations. The geometrical structures were calculated by Gaussian view 05 as a supplementary program. The band gap was calculated and compared to the measured values. The density of state of the hybrid junction (Sn10O16/C24O6) increased because of the increased number of degeneracy states. Theoretical values of bonds for C=C, C=O, and Sn-O are equal to 1.33, 1.20 and 2.27 Å respectively, these bonds values are in good agreement with experimental values of bond length of 1.34 for the C=C bond, 1.23 for the C=O bond, and 2.3 for the Sn-O bond. . The spectroscopic properties, such as IR spectra have shown a peak which is comparable to longitudinal modes of GO and tin dioxide SnO2 at  (1582 and 690) cm-1, respectively.

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Publication Date
Sun Dec 01 2019
Journal Name
Materials Science-poland
Electrical and thermal characteristics of MWCNTs modified carbon fiber/epoxy composite films
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Abstract<p>To enhance interfacial bonding between carbon fibers and epoxy matrix, the carbon fibers have been modified with multiwall carbon nanotubes (MWCNTs) using the dip- coating technique. FT-IR spectrum of the MWCNTs shows a peak at 1640 cm<sup>−1</sup> corresponding to the stretching mode of the C=C double bond which forms the framework of the carbon nanotube sidewall. The broad peak at 3430 cm<sup>−1</sup> is due to O–H stretching vibration of hydroxyl groups and the peak at 1712 cm<sup>−1</sup> corresponds to the carboxylic (C=O) group attached to the carbon fiber. The peaks at 2927 cm<sup>−1</sup> and 2862 cm<sup>−1</sup> ar</p> ... Show More
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Publication Date
Mon Dec 05 2022
Journal Name
Baghdad Science Journal
K-Nearest Neighbor Method with Principal Component Analysis for Functional Nonparametric Regression
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This paper proposed a new  method to study functional non-parametric regression data analysis with conditional expectation in the case that the covariates  are functional and the Principal Component Analysis was utilized to de-correlate the multivariate response variables. It  utilized the formula of the Nadaraya Watson estimator (K-Nearest Neighbour (KNN)) for prediction with different types of the semi-metrics, (which are based on Second Derivative and Functional Principal Component Analysis (FPCA))  for measureing the closeness between curves.  Root Mean Square Errors is used for the  implementation of this model which is then compared to the independent response method. R program is used for analysing data. Then, when  the cov

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Publication Date
Fri Jan 01 2021
Journal Name
Computers, Materials &amp; Continua
A New Hybrid Feature Selection Method Using T-test and Fitness Function
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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Hybrid Framework To Exclude Similar and Faulty Test Cases In Regression Testing
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Regression testing is a crucial phase in the software development lifecycle that makes sure that new changes/updates in the software system don’t introduce defects or don’t affect adversely the existing functionalities. However, as the software systems grow in complexity, the number of test cases in regression suite can become large which results into more testing time and resource consumption. In addition, the presence of redundant and faulty test cases may affect the efficiency of the regression testing process. Therefore, this paper presents a new Hybrid Framework to Exclude Similar & Faulty Test Cases in Regression Testing (ETCPM) that utilizes automated code analysis techniques and historical test execution data to

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Publication Date
Fri Dec 24 2021
Journal Name
Journal Of Engineering Science And Technology. Journal Of Engineering Science And Technology
Grey-Level Image Compression Using 1-D Polynomial and Hybrid Encoding Techniques
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Publication Date
Mon Feb 05 2052
Journal Name
Partial Differential Equations In Applied Mathematics
A hybrid analytical method for fractional order Klein–Gordon and Burgers equations
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Publication Date
Fri Sep 01 2017
Journal Name
International Journal Of Engineering Research And Advanced Technology
. Medical Image Compression using Hybrid Technique of Wavelet Transformation and Seed Selective Predictive Method
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Publication Date
Tue May 01 2018
Journal Name
2018 2nd Ieee Advanced Information Management,communicates,electronic And Automation Control Conference (imcec)
Hybrid Regressor and Approximation-Based Adaptive Control of Robotic Manipulators with Contact-Free Motion
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Publication Date
Sun May 05 2024
Journal Name
Review Of Clinical Pharmacology And Pharmacokinetics - International Edition
Cytotoxic effects of the Crassula ovata n-hexane fraction on human esophagus cancer KYSE-30 cells
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The current study shows the cytotoxicity effect of the Crassula ovata n-hexane extract on esophagus can¬cer. C. ovata is a perennial succulent plant belonging to the Crassulaceae family. In Africa, the leaves were used medicinally to cure epilepsy and diarrhoea by boiling them in milk. The hexane fraction, which is obtained through the maceration method, demonstrates the presence of many compounds that have an anticancer effect, which are ob¬tained by gas chromatography - mass spectroscopy. The phytosterol compound was isolated by a preparative thin layer chromato¬graph and was identified by liquid chromatography - mass spectroscopy. The hexane fraction was found to possess a strong anticancer effect against esophagus cancer. The

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Publication Date
Tue Sep 01 2020
Journal Name
Petroleum
Reversible and irreversible adsorption of bare and hybrid silica nanoparticles onto carbonate surface at reservoir condition
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Realistic implementation of nanofluids in subsurface projects including carbon geosequestration and enhanced oil recovery requires full understanding of nanoparticles (NPs) adsorption behaviour in the porous media. The physicochemical interactions between NPs and between the NP and the porous media grain surface control the adsorption behavior of NPs. This study investigates the reversible and irreversible adsorption of silica NPs onto oil-wet and water-wet carbonate surfaces at reservoir conditions. Each carbonate sample was treated with different concentrations of silica nanofluid to investigate NP adsorption in terms of nanoparticles initial size and hydrophobicity at different temperatures, and pressures. Aggregation behaviour and the

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