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Sensitivity of SnO2 nanoparticles/reduced graphene oxide hybrid to NO2 gas: A DFT study
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Abstract<p>The sensitivity of SnO<sub>2</sub> nanoparticles/reduced graphene oxide hybrid to NO<sub>2</sub> gas is discussed in the present work using density functional theory (DFT). The SnO<sub>2</sub> nanoparticles shapes are taken as pyramids, as proved by experiments. The reduced graphene oxide (rGO) edges have oxygen or oxygen-containing functional groups. However, the upper and lower surfaces of rGO are clean, as expected from the oxide reduction procedure. Results show that SnO<sub>2</sub> particles are connected at the edges of rGO, making a p-n heterojunction with a reduced agglomeration of SnO2 particles and high gas sensitivity. The DFT results are in good agreement with the experimental characterization of both SnO<sub>2</sub> and rGO using energy gap and XPS values. Gibbs free energy, enthalpy, and entropy of the various considered reactions are calculated. Results show that the sensitivity of the rGO/SnO<sub>2 </sub>hybrid to NO<sub>2</sub> gas is the result of the interplay of the dissociation and oxidation reactions of NO<sub>2</sub> gas.</p>
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Publication Date
Tue Dec 30 2025
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Optimum design and performance analysis of a gas lift system in the carbonate reservoir of Ahdab oil field
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   Gas lift is one of the most important artificial lift methods for increasing oil production, as wells often require this method after the reservoir's energy has decreased. In this research, an optimal gas lift system is designed for five horizontal wells in the Ahdab oil field, which suffers from low production. At the same time, water cut in some of these wells reaches 66%, while the productivity index is low in others, which makes the challenges clear, and a deep analysis is needed to find an optimal system. The Pipesim program is used to design the optimal gas lift system, which contains features that facilitate the implementation of the appropriate design and provide the ability to analyze and determine the optimal design v

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Publication Date
Wed Jun 01 2022
Journal Name
Journal Of The College Of Languages (jcl)
Innovative approaches to the development of the lexical composition of the oil and gas industry : Инновационные подходы развития лексического состава нефтегазовой промышленности
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 The present study discusses one of the most relevant and required topics in the recent period during globalization, the modern Russian system of terms for the oil and gas industry as a whole acquired a complete form in the second half of the twentieth century. The period of the late XX - early XXI centuries. marked by cardinal transformations in all areas of the political, economic, social and cultural life of Russia. These changes could not but affect industrial production. Transition to a new vector of development of the Russian economy based on the development of commercial trade, on the change and improvement of the development of industrial enterprises in the context of the implementation of national projects and the introduction

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Publication Date
Fri Mar 31 2017
Journal Name
Journal Of Engineering
Experimental Measurements of Viscosity and Thermal Conductivity of Single Layer Graphene Based DI-water Nanofluid
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Experimental measurements of viscosity and thermal conductivity of single layer of graphene . based DI-water nanofluid are performed as a function of  concentrations (0.1-1wt%) and temperatures between (5 to 35ºC). The result reveals that the thermal conductivity of GNPs nanofluids was increased with increasing the nanoparticle weight fraction concentration and temperature, while the maximum enhancement was about 22% for concentration of 1 wt.% at
35ºC. These experimental results were compared with some theoretical models and a good agreement between Nan’s model and the experimental results was observed. The viscosity of the graphene nanofluid displays Newtonian and Non-Newtonian behaviors with respect to nanoparticles concen

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Publication Date
Wed Jan 01 2020
Journal Name
Annals Of Tropical Medicine And Public Health
Role of high sensitivity C - Reactive protein and some of heavy metals in patients with rheumatoid arthritis
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Publication Date
Thu Jun 02 2016
Journal Name
Ashrae Transactions
Melting of PCM with nanoparticles in a triplex-tube thermal energy storage system
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Publication Date
Thu Sep 01 2016
Journal Name
Applied Thermal Engineering
Solidification of a PCM with nanoparticles in triplex-tube thermal energy storage system
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Publication Date
Thu Sep 01 2016
Journal Name
Applied Thermal Engineering
Solidification of a PCM with nanoparticles in triplex-tube thermal energy storage system
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Publication Date
Fri Apr 15 2016
Journal Name
International Journal Of Computer Applications
Hybrid Techniques based Speech Recognition
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Information processing has an important application which is speech recognition. In this paper, a two hybrid techniques have been presented. The first one is a 3-level hybrid of Stationary Wavelet Transform (S) and Discrete Wavelet Transform (W) and the second one is a 3-level hybrid of Discrete Wavelet Transform (W) and Multi-wavelet Transforms (M). To choose the best 3-level hybrid in each technique, a comparison according to five factors has been implemented and the best results are WWS, WWW, and MWM. Speech recognition is performed on WWS, WWW, and MWM using Euclidean distance (Ecl) and Dynamic Time Warping (DTW). The match performance is (98%) using DTW in MWM, while in the WWS and WWW are (74%) and (78%) respectively, but when using (

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Hybrid CNN-based Recommendation System
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Recommendation systems are now being used to address the problem of excess information in several sectors such as entertainment, social networking, and e-commerce. Although conventional methods to recommendation systems have achieved significant success in providing item suggestions, they still face many challenges, including the cold start problem and data sparsity. Numerous recommendation models have been created in order to address these difficulties. Nevertheless, including user or item-specific information has the potential to enhance the performance of recommendations. The ConvFM model is a novel convolutional neural network architecture that combines the capabilities of deep learning for feature extraction with the effectiveness o

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Publication Date
Thu May 07 2026
Journal Name
Frontiers In Sustainability
Using ethical artificial intelligence (EAI) to achieve sustainable development, Iraq as a case study
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Introduction

Iraq faces persistent challenges in achieving sustainable development due to decades of conflict, political instability, and infrastructural degradation. These challenges are particularly evident in critical sectors such as energy, water, healthcare, education, and governance, which significantly influence human well-being, social equity, and quality of life. This study proposes an AI-driven, ethically guided, and human-centric sustainability framework to support resilient urban transformation in Iraq.

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