Manganese sulfate and Punica granatum plant extract were used to create MnO2 nanoparticles, which were then characterized using techniques like Fourier transform infrared spectroscopy, ultraviolet-visible spectroscopy, atomic force microscopy, X-ray diffraction, transmission electron microscopy, scanning electron microscopy, and energy-dispersive X-ray spectroscopy. The crystal's size was calculated to be 30.94nm by employing the Debye Scherrer equation in X-ray diffraction. MnO2 NPs were shown to be effective in adsorbing M(II) = Co, Ni, and Cu ions, proving that all three metal ions may be removed from water in one go. Ni(II) has a higher adsorption rate throughout the board. Co, Ni, and Cu ion removal efficiencies were 32.79%, 75

This study includes using green or biosynthesis-friendly technology, which is effective in terms of low cost and low time and energy to prepare V₂O₅NPs nanoparticles from vanadium sulfate VSO₄.H₂O using aqueous extract of Punica Granatum at a concentration of 0.1M and with a basic medium PH= 8-12. The V₂O₅NPs nanoparticles were diagnosed using several techniques, such as FT-IR, UV-visible with energy gap Eg = 3.734eV, and the X-Ray diffraction XRD was calculated using the Debye Scherrer equation. It was discovered to be 34.39nm, Scanning Electron Microscope (SEM), Transmission Electron Microscopy TEM. The size, structure, and composition of synthetic V₂O₅

In this study, two types of mixes were adopted by using two grading of coarse aggregate. The practical side of this study was to produce no-fine aggregate concrete by using crushed clay brick aggregates. The durability of the produced concrete and internal sulfate attack was studied.      For durability assessment, it is found that the no-fine concrete made with crushed brick aggregate lost about (15-25) % of its compressive strength after being subjected to 60 cycles of wetting and drying with age 120 days. The curing condition showed that the water curing improved the compressive strength with a rate higher than that when sealed or air dry curing were used. The crushed brick no-fine concrete de

تصف هذه الدراسة تطوير تقنية سهلة ورخيصة ودقيقة وسريعة لقياس 4-اثيل فينول وتنطوي الطريقة الأولية على تحويل -3 نيترو انيلين إلى ملح ديازونيوم ثم التفاعل مع 4 - إثيل فينول في وسط قلوي.المعقد المتكون هو أصفر اللون وله امتصاص عند اعلى طول موجي عند 426 nm. ويتبع قانون بير في مدى خطي قدره 5-12 μg mL-1 مع معامل ارتباط قدره 0.994 وامتصاص مولاري 6.0024x10^3  L.mol-1.cm-1  وتم استُخدِام تقنية نقطة السحابة لقياس كميات قليلة جدا من الفينول باس

In this work, porous silicon (PS) are fabricated using electrochemical etching (ECE) process for p-type crystalline silicon (c-Si) wafers of (100) orientation. The structural, morphological and electrical properties of PS synthesized at etching current density of (10, 20, 30) mA/cm2 at constant etching time 10 min are studied. From X-ray diffraction (XRD) measurement, the value of FWHM is in general decreases with increasing current density for p-type porous silicon (p-PS). Atomic force microscope (AFM) showed that for p-PS the average pore diameter decreases at 20 mA. Porous silicon which formed on silicon will be a junction so I-V characteristics have been studied in the dark to calculate ideality factor (n), and saturation current (Is

This study includes adding chemicals to gypseous soil to improve its collapse characteristics. The collapse behavior of gypseous soil brought from the north of Iraq (Salah El-Deen governorate) with a gypsum content of 59% was investigated using five types of additions (cement dust, powder sodium meta-silicate, powder activated carbon, sodium silicate solution, and granular activated carbon). The soil was mixed by weight with cement dust (10, 20, and 30%), powder sodium meta-silicate (6%), powder activated carbon (10%), sodium silicate solution (3, 6, and 9%), and granular activated carbon (5, 10, and 15%). The collapse potential is reduced by 86, 71, 43, 37, and 35% when 30% cement dust, 6% powder sodium meta-silicate, 10% powder activated

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