The electrocoagulation process became one of the most important technologies used for water treatment processes in the last few years. It’s the preferred method to remove suspended solids and heavy metals from water for treating drinking water and wastewater from textile, diary, and electroplating factories. This research aims to study the effect of using the electrocoagulation process with aluminum electrodes on the removal efficiency of suspended solids and turbidity presented in raw water and optimizing by the response surface methodology (RSM). The most important variables studied in this research included electrode spacing, the applied voltage, and the operating time of the electrocoagulation process. The samples

This paper considers and proposes new estimators that depend on the sample and on prior information in the case that they either are equally or are not equally important in the model. The prior information is described as linear stochastic restrictions. We study the properties and the performances of these estimators compared to other common estimators using the mean squared error as a criterion for the goodness of fit. A numerical example and a simulation study are proposed to explain the performance of the estimators.

Myrtle plant was washed, dried, and powdered after harvesting to produce a fine powder that was used in water treatment. created an alcoholic extract from the myrtle plant using ethanol, which was then analyzed using GC-Mass, Fourier Transform Infrared spectroscopy, and ultraviolet-visible spectroscopy to identify the active components. Zinc nanoparticles were created using alcoholic extract. We used FTIR, UV-Vis, SEM, EDX, and TEM to characterize zinc nanoparticles. Using a continuous processing procedure, zinc nanoparticles with myrtle extract and powder were employed to clean polluted water containing heavy metals. Firstly used 2g with 20ml polluted water and the result was ( Fe 96.20%, Cr 84%, Pb 100%, Sb 93.70, Cd 100%, andCu 90.60%) S

Photovoltaic devices (PVs) were fabricated by spray-coating an ink of copper indium diselenide CuInSeR 2 R(CIS) nanocrystals as the light-absorbing layer. Without high-temperature post-deposition annealing, PVs were made on glass substrates with power conversion efficiencies of up to 1.5% and 0.9%, for Au and Mo coated respectively, under AM 1.5 illumination. UV–Vis spectrophotometer in the wavelength range 350–1500 nm. X-ray diffraction (XRD) and energy dispersive spectroscopy (EDS) analysis it is evident that CuInSeR 2 R have the chalcopyrite structure as the major phase and no secondary phase with a preferred orientation along (112) direction and The atomic ratio of Cu : In : Se in the nanocrystals is nearly 1 : 1 : 2.

The incorporation of recycled concrete aggregate (RCA) into asphalt concrete supports circular economy goals by reducing reliance on virgin materials and minimizing construction waste. However, RCA’s inherent limitations, such as high porosity, microcracking, and poor interfacial bonding, compromise the structural integrity and durability of asphalt mixtures. This study introduces sugarcane molasses (SCM), a naturally derived, carbohydrate-rich byproduct of sugarcane refining, as a novel and eco-friendly surface treatment for RCA aimed at enhancing its compatibility with asphalt binders. SCM was applied at 5-6% by weight of RCA replacing coarse aggregate at varying levels (0-100%) to assess its effect on asphalt mixture performance. A com

            In this study, pure SnO₂ Nanoparticles doped with Cu were synthesized by a chemical precipitation method. Using SnCl₂.2H₂O, CuCl₂.2H₂O as raw materials, the materials were annealed at 550°C for 3 hours in order to improve crystallization. The XRD results showed that the samples crystallized in the tetragonal rutile type SnO₂ stage. As the average SnO₂ crystal size is pure 9nm and varies with the change of Cu doping (0.5%, 1%, 1.5%, 2%, 2.5%, 3%),( 8.35, 8.36, 8.67, 9 ,7, 8.86)nm respectively an increase in crystal size to 2.5% decreases at this rate and that the crystal of SnO₂ does not change with the introduction of Cu, and S

In this study, the acid-alkaline transesterification of refined coconut seed oil (RCOSO) to fatty acid methyl ester was followed by the production of a trimethylolpropane-based thermosensitive biolubricant using potassium hydroxide, and its physicochemical characteristics were evaluated. The American Standard Test for Materials (ASTM) was employed to ascertain the biolubricant's pour point and index of viscosity, which were found to be -4 ^oC and 283.75, respectively. The opposite connection between lubricant viscosity and temperature was shown by the measured viscosities at varied transesterification to be transformed into biodiesel. Following this, a biolubricant was created by further transesterifiedtemperature. The ester gr

Nations witnessed since its existence a state of wills conflict as a result of the intersection and intertwining of interests, through which it sought to achieve its goals and objectives, and this has often led to direct military conflicts and countless wars, and witnessed the entry into global wars in which humanity lost millions of lives and losses .Despite the great changes in the international arena, especially in recent decades, the conflict of wills has not ceased, although some of its features and forms have changed, and it has become more complicated after the withdrawal of this conflict to international organizations and bodies, including the Security Council. It is mandated under the Charter of the United Nations to wor

It is well known that drilling fluid is a key parameter for optimizing drilling operations, cleaning the hole, and managing the rig hydraulics and margins of surge and swab pressures. Although the experimental works represent valid and reliable results, they are expensive and time consuming. In contrast, continuous and regular determination of the rheological fluid properties can perform its essential functions during good construction. The aim of this study is to develop empirical models to estimate the drilling mud rheological properties of water-based fluids with less need for lab measurements. This study provides two predictive techniques, multiple regression analysis and artificial neural networks, to determine the rheological