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Effect of reduced graphene oxide hybridization on ZnO nanoparticles sensitivity to NO2 gas: A DFT study
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In the present work, a density functional theory (DFT) calculation to simulate reduced graphene oxide (rGO) hybrid with zinc oxide (ZnO) nanoparticle's sensitivity to NO2 gas is performed. In comparison with the experiment, DFT calculations give acceptable results to available bond lengths, lattice parameters, X-ray photoelectron spectroscopy (XPS), energy gaps, Gibbs free energy, enthalpy, entropy, etc. to ZnO, rGO, and ZnO/rGO hybrid. ZnO and rGO show n-type and p-type semiconductor behavior, respectively. The formed p-n heterojunction between rGO and ZnO is of the staggering gap type. Results show that rGO increases the sensitivity of ZnO to NO2 gas as they form a hybrid. ZnO/rGO hybrid has a higher number of vacancies that can be used to attract oxygen atoms from NO2 and change the resistivity of the hybrid. The combined reduction of oxygen from NO2 and NO can give a very high value of the Gibbs free energy of reaction that explains the ppb level sensitivity of the ZnO/rGO hybrid. The dissociation of NO2 in the air reduces the sensitivity of the ZnO/rGO hybrid at temperatures higher than 300 ̊C.

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Publication Date
Sun Jan 01 2023
Journal Name
International Journal Of Nonlinear Analysis And Applications
The use of ARIMA, LSTM and GRU models in time series hybridization with practical application
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The importance of forecasting has emerged in the economic field in order to achieve economic growth, as forecasting is one of the important topics in the analysis of time series, and accurate forecasting of time series is one of the most important challenges in which we seek to make the best decision. The aim of the research is to suggest the use of hybrid models for forecasting the daily crude oil prices as the hybrid model consists of integrating the linear component, which represents Box Jenkins models and the non-linear component, which represents one of the methods of artificial intelligence, which is long short term memory (LSTM) and the gated recurrent unit (GRU) which represents deep learning models. It was found that the proposed h

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Publication Date
Wed Mar 01 2023
Journal Name
International Journal Of Nonlinear Analysis And Applications
The use of ARIMA, ANN and SVR models in time series hybridization with practical application
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Forecasting is one of the important topics in the analysis of time series, as the importance of forecasting in the economic field has emerged in order to achieve economic growth. Therefore, accurate forecasting of time series is one of the most important challenges that we seek to make the best decision, the aim of the research is to suggest employing hybrid models to predict daily crude oil prices. The hybrid model consists of integrating the linear component, which represents Box Jenkins models, and the non-linear component, which represents one of the methods of artificial intelligence, which is the artificial neural network (ANN), support vector regression (SVR) algorithm and it was shown that the proposed hybrid models in the predicti

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Publication Date
Thu Oct 31 2013
Journal Name
Al-khwarizmi Engineering Journal
Simulation of a Wet Sulfuric Acid Process (WSA) for Utilization of Acid Gas Separated from Omani Natural Gas
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In this study, a proposed process for the utilization of hydrogen sulphide separated with other gases from omani natural gas for the production of sulphuric acid by wet sulphuric acid process (WSA) was studied. The processwas simulated at an acid gas feed flow of   5000 m3/hr using Aspen ONE- V7.1-HYSYS software. A sensitivity analysis was conducted to determine the optimum conditions for the operation of plant. This included primarily the threepacked bed reactors connected in series for the production of sulphur trioxidewhich represented the bottleneck of the process. The optimum feed temperature  and catalyst bed volume for each reactor were estimated and then used in the simulation of the whole process for tw

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Publication Date
Sun Jun 21 2026
Journal Name
Journal Of Petroleum Research And Studies
Possibility to Apply Gas Lift Method for Low Production Wells with High Water Cut in (A) Oil Field
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Gas lift is one of the oldest methods used to produce hydrocarbon fluids from wells experiencing declining production. It works by aerating the mixture inside production tubing and forcing it to the surface. One of the reasons for declining production in oil wells is an increase in water cut or a drop in reservoir pressure, which requires one of the artificial lift methods to restore production. (A) oil field suffers from an increase in water cut, which has affected well productivity. The wells under study have a water cut of up to 66%, resulting in very low production rates. In this research, Pipesim software was used to build a physical and fluid model, then design an optimal gas lift system that achieves the highest possible prod

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Publication Date
Wed Oct 01 2025
Journal Name
Assiut Veterinary Medical Journal
MOLECULAR INVESTIGATION AND COMPARATIVE STUDIES OF THE BACTERICIDAL ACTION BETWEEN SILICA AND ZINC OXIDE NANOPARTICLES AGAINST KLEBSIELLA PNEUMONIAE
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Publication Date
Fri Nov 03 2023
Journal Name
Karbala International Journal Of Modern Science
Synthesis and characterization of zirconium oxide nanoparticles using Z. officinale and S. aromaticum plant extracts for antibacterial application
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Publication Date
Wed Apr 15 2026
Journal Name
Experimental And Theoretical Nanotechnology
Antibacterial and antioxidant activity of gamma star-like MnO2 nanostructure with and without coating with iron oxide nanoparticles
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Bacterial resistance caused by antibiotic misuse has garnered substantial attention, prompting numerous researchers to develop materials that can combat these resistant pathogens. The hydrothermal method is employed to produce γ-MnO2 nanostars and to coat them with Fe2O3 nanoparticles. The materials are characterized using XRD, FE-SEM, EDX, and UV-vis spectrophotometry, as well as antioxidant and antibacterial activities. The nano γ-MnO2 star shapes are coated with tiny spherical Fe2O3 nanoparticles with diameters of 35-47 nm. The peaks located at the crystal planes (120), (031), (131), (230), (300), (160), (421), and (003) are represented by the values of 2θ = 22.36º, 34.36º, 37.22º, 38.78º, 42.56º, 56.14º, 65.48º and 68.

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Publication Date
Wed May 29 2019
Journal Name
Iraqi Journal Of Physics
Effect of current intensity on structural properties of cupper iodine nanoparticles produced by exploding Cu wire
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Exploding wire Technique is a way for production metal and its compound nanoparticle that is capable of production of bulk amount at low cost semiconductor. In this work a copper iodine nanoparticles were fabricate by exploding copper wires with different currents in iodine solution. The produced samples were examined by XRD, FTIR, SEM and TEM to characterize their properties. The XRD proved the Nano-size for producer. The crystalline size increases with increasing current. FTIR measurements show a peaks located at 638.92 for Cu-I stretch bond indicate on formation of copper iodide compound and the peaks intensities increase with increasing current. The SEM and TEM measurements show that the thin films have nanostructures.

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Publication Date
Fri Mar 15 2019
Journal Name
Al-khwarizmi Engineering Journal
Studying the effect of Different wt % AL2O3 Nanoparticles of 2024Al Alloy / AL2O3 Composites on Mechanical Properties
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The nanocompsite of alumina (Al2O3) produced a number of beneficial effects in alloys. There is increasing in resistance of materials to surface related failures , such as the mechanical properties , fatigue and stress corrosion cracking .The experimental results observed that the adding of reinforced  nanomaterials  type Al2O3  enhanced the   HB hardness, UTS, 0.2 YS and ductility of 2014 Al/Al2O3 nano composites . the analysis of experiments, indicated that The maximum enhancement was observed at 0.4 wt.% Al2O3. The ultimate improvement percentage were 15.78% HB hardness, 18.1% (UTS), 12.86% (

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Publication Date
Mon Jun 04 2018
Journal Name
Baghdad Science Journal
Structural Analysis of Chemical and Green Synthesis of CuO Nanoparticles and their Effect on Biofilm Formation
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Copper oxide nanoparticles (CuO NPs) were synthesized by two methods. The first was chemical method by using copper nitrate Cu (NO3)2 and NaOH, while the second was green method by using Eucalyptus camaldulensis leaves extract and Cu (NO3)2. These methods easily give a large scale production of CuO nanoparticles. X-ray diffraction pattern (XRD) reveals single phase monoclinic structure. The average crystalline size of CuO NPs was measured and used by Scherrer equation which found 44.06nm from chemical method, while the average crystalline size was found from green method was 27.2nm. The morphology analysis using atomic force microscopy showed that the grain size for CuO NPs was synthesized by chemical and green methods were 77.70 an

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