Considerable amounts of domestic and industrial wastewater that should be treated before reuse are discharged into the environment annually. Electrocoagulation is an electrochemical technology in which electrical current is conducted through electrodes, it is mainly used to remove several types of wastewater pollutants, such as dyes, toxic materials, oil content, chemical oxygen demand, and salinity, individually or in combination with other processes. Electrocoagulation technology used in hybrid systems along with other technologies for wastewater treatment are reviewed in this work, and the articles reviewed herein were published from 2018 to 2021. Electrocoagulation is widely employed in integrated systems with other electrochemical tech

In this work, an inventive photovoltaic evaporative cooling (PV/EC) hybrid system was constructed and experimentally investigated. The PV/EC hybrid system has the prosperous advantage of producing electrical energy and cooling the PV panel besides providing cooled-humid air. Two cooling techniques were utilized: backside evaporative cooling (case #1) and combined backside evaporative cooling with a front-side water spray technique (case #2). The water spraying on the front side of the PV panel is intermittent to minimize water and power consumption depending on the PV panel temperature. In addition, two pad thicknesses of 5 cm and 10 cm were investigated at three different water flow rates of 1, 2, and 3 lpm. In Case #1,

Infection with cryptosporidiosis endangers the lives of many people with immunodeficiency, especially HIV patients. Nitazoxanide is one of the main therapeutic drugs used to treat cryptosporidiosis. However, it is poorly soluble in water, which restricts its usefulness and efficacy in immunocompromised patients. Surfactants have an amphiphilic character which indicates their ability to improve the water solubility of the hydrophobic drugs. Our research concerns the synthesis of new cationic Gemini surfactants that have the ability to improve the solubility of the drug Nanazoxide. So, we synthesized cationic Gemini surfactants. N1,N1,N3,N3-tetramethyl-N1,N3-bis(2-octadecanamidoethyl)propane-1,3-diaminium bromide (CGSPS18) and 2,2‘-(etha

Barium–doped TiO2 / n-Si photodetector was fabricated by spray pyrolysis exhibited visible enhancement responsivity profile with peak response at 600 nm flat response between 650 and 900 nm. The quantum efficiency was 30% and specific detectivity was 5x1012 W-1Hz1/2cm at peak response. The GaAlAs laser diode was used to estimate the rise time of the detector.

Smart water flooding (low salinity water flooding) was mainly invested in a sandstone reservoir. The main reasons for using low salinity water flooding are; to improve oil recovery and to give a support for the reservoir pressure.

In this study, two core plugs of sandstone were used with different permeability from south of Iraq to explain the effect of water injection with different ions concentration on the oil recovery. Water types that have been used are formation water, seawater, modified low salinity water, and deionized water.

The effects of water salinity, the flow rate of water injected, and the permeability of core plugs have been studied in order to summarize the best conditions of low salinity

The proton-neutron interacting boson model (IBM-2) has been used to make a schematic study of the Ruthenium ( ) isotopes of mass region around with and . For each isotope of the values of the IBM-2 Hamiltonian parameters, which yield an acceptable results for excitation energies in comparison with those of experimental data, have been determined. Fixed values of the effective charges ( ) and of the proton and neutron g factors ( and ) have been chosen for all isotopes under study. The calculated electric quadrupole moments of state, transitions, the magnetic dipole moments transitions and mixing ratios are in reasonable agreement with the experimental data.

In this work, a new development of predictive voltage-tracking control algorithm for Proton Exchange Membrane Fuel Cell (PEMFCs) model, using a neural network technique based on-line auto-tuning intelligent algorithm was proposed. The aim of proposed robust feedback nonlinear neural predictive voltage controller is to find precisely and quickly the optimal hydrogen partial pressure action to control the stack terminal voltage of the (PEMFC) model for N-step ahead prediction. The Chaotic Particle Swarm Optimization (CPSO) implemented as a stable and robust on-line auto-tune algorithm to find the optimal weights for the proposed predictive neural network controller to improve system performance in terms of fast-tracking de