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Finite Element Modeling Of Finned Double-Pass Solar Air Heaters
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Publication Date
Sun Jun 30 2019
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Micro-Bubble Flotation for Removing Cadmium Ions from Aqueous Solution: Artificial Neural Network Modeling and Kinetic of Flotation
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In this work, microbubble dispersed air flotation technique was applied for cadmium ions removal from wastewater aqueous solution. Experiments parameters such as pH (3, 4, 5, and 6), initial Cd(II) ions concentration (40, 80, and 120 mg/l)  contact time( 2, 5, 10 , 15, and 20min), and surfactant (10, 20and 40mg/l) were studied in order to optimize the best conditions .The experimental results indicate that microbubbles were quite effective in removing cadmium ions and the anionic surfactant SDS was found to be more efficient than cationic CTAB in flotation process. 92.3% maximum removal efficiency achieved through 15min at pH 5, SDS surfactant concentration 20mg/l, flow rate250 cm3/min and at 40mg/l Cd(II) ions initial co

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Publication Date
Tue Aug 19 2025
Journal Name
Scientific Reports
Predictive modeling of asthma drug properties using machine learning and topological indices in a MATLAB based QSPR study
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Publication Date
Sun Aug 31 2014
Journal Name
Arabian Journal Of Geosciences
Petroleum system modeling and risk assessments of Ad’daimah oil field: a case study from Mesan Governorate, south Iraq
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Publication Date
Fri Jul 01 2022
Journal Name
Advanced Powder Technology
Modification of FAU zeolite as an active heterogeneous catalyst for biodiesel production and theoretical considerations for kinetic modeling
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Publication Date
Sat Jan 01 2022
Journal Name
The 2nd Universitas Lampung International Conference On Science, Technology, And Environment (ulicoste) 2021
Organic-inorganic ITO/CuPc/CdS/CuPc/Al solar cell prepared via pulsed laser deposition
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Publication Date
Wed Jan 25 2023
Journal Name
Molecular Simulation
Engineering promising A-π-D type molecules for efficient organic-based material solar cells
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Within this work, to promote the efficiency of organic-based solar cells, a series of novel A-π-D type small molecules were scrutinised. The acceptors which we designed had a moiety of N, N-dimethylaniline as the donor and catechol moiety as the acceptor linked through various conjugated π-linkers. We performed DFT (B3LYP) as well as TD-DFT (CAM-B3LYP) computations using 6-31G (d,p) for scrutinising the impact of various π-linkers upon optoelectronic characteristics, stability, and rate of charge transport. In comparison with the reference molecule, various π-linkers led to a smaller HOMO–LUMO energy gap. Compared to the reference molecule, there was a considerable red shift in the molecules under study (A1–A4). Therefore, based on

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Publication Date
Wed Sep 02 2020
Journal Name
Iraqi Journal Of Applied Physics
Heterojunction Solar Cell Based on Highly-Pure Nanopowders Prepared by DC Reactive Magnetron Sputtering
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In this work, a novel design for the NiO/TiO2 heterojunction solar cells is presented. Highly-pure nanopowders prepared by dc reactive magnetron sputtering technique were used to form the heterojunctions. The electrical characteristics of the proposed design were compared to those of a conventional thin film heterojunction design prepared by the same technique. A higher efficiency of 300% was achieved by the proposed design. This attempt can be considered as the first to fabricate solar cells from highly-pure nanopowders of two different semiconductors.

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Publication Date
Wed Jan 28 2026
Journal Name
F1000research
Enhancing Solar Power Forecasting Accuracy Using HMPCS and Machine Learning Techniques: An Applied Study
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Background Solar irradiance is a nonlinear and intermittent function, which makes accurate forecasting of solar power generation a challenge. The high variability of meteorological conditions is not well represented by conventional atmospheric models, thus hampering forecasting skill and model robustness. In this work, an advanced hybridization of multi-population cuckoo search (HMPCS) algorithm with machine learning (ML) methods is developed to enhance the prediction performance of photovoltaic (PV) power forecasting with more reliability. Methods In this study, a hybrid modeling framework is proposed, called HMPCS–ML framework which captures the global search capacity of HMPCS and predictive power of sophisti

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Publication Date
Sat Jan 01 2022
Journal Name
Communications In Mathematical Biology And Neuroscience
A careful study of the effect of the infectious diseases and refuge on the dynamical behavior of prey-scavenger modeling
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In this paper, the dynamics of scavenger species predation of both susceptible and infected prey at different rates with prey refuge is mathematically proposed and studied. It is supposed that the disease was spread by direct contact between susceptible prey with infected prey described by Holling type-II infection function. The existence, uniqueness, and boundedness of the solution are investigated. The stability constraints of all equilibrium points are determined. In addition to establishing some sufficient conditions for global stability of them by using suitable Lyapunov functions. Finally, these theoretical results are shown and verified with numerical simulations.

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Publication Date
Thu Jul 01 2021
Journal Name
Energy
Experimental investigations of the performance of a flat-plate solar collector using carbon and metal oxides based nanofluids
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