Corncob is an agricultural biomass waste that was widely investigated as an adsorbent of contaminants after transforming it into activated carbon. In this research carbonization and chemical activation processes were achieved to synthesize corncob-activated carbon (CAC). Many pretreatment steps including crushing, grinding, and drying to obtain corncob powder were performed before the carbonization step. The carbonization of corncob powder has occurred in the absence of air at a temperature of 500 °C. The chemical activation was accomplished by using HCl as an acidic activation agent. Fourier transform infrared spectroscopy (FT-IR), scanning electron microscopy (SEM), X-ray diffraction (XRD), and Brunauer–Emmett–Teller (BET) facilitate

Traditional volumetric asphalt mix design methods do not directly evaluate cracking and rutting resistance, which may result in mixtures with inadequate field performance despite satisfying conventional volumetric requirements. Balanced Mix Design (BMD) has been introduced to address this limitation by incorporating performance testing. However, it remains unclear whether additive modification alone can recover mixtures that do not satisfy BMD criteria, or whether volumetric redesign (binder content optimization) is necessary. Therefore, this study investigated the effectiveness of additive modification before and after BMD redesign using IDEAL-CT and IDEAL-RT performance indices. Three additive systems were evaluated: SBS polymer,

This research is presenting a study of optical and structural properties of (Fe2O3)1-x(MgO)x composites synthesized as thin film that can be used as a gas sensor. Pulsed laser deposition technique was used to prepare thin films of (Fe2O3)1-x(MgO)x. The pattern of X-ray diffraction of the composites powder showed the consistency of iron oxide (α-Fe2O3) hematite phase along with the planes (104) and (110) as preferred planes for crystal growth where the intensities of which varied with MgO content. The crystal size of the thin film material was varied in between (26.8-35.1) nm. The diffraction pattern of the pulsed laser deposited thin films was absent from any diffraction peaks. The maximum transparency obtained of hematite

Blend solid polymer electrolytes (BSPEs) comprising PVA/HPMC/CuSO4 were prepared using a solution casting approach. BSPEs were synthesized with varying weight percentages of CuSO4 (0, 10, 20, and 30 wt.%). A variety of experimental methods, including X-ray diffraction (XRD), Fourier transform infrared (FTIR) spectroscopy, scanning electron microscopy (SEM), electrochemical impedance spectroscopy (EIS), cyclic voltammetry (CV), and linear sweep voltammetry (LSV), were used to characterize these BSPE systems. The polymer blend matrix underwent structural alterations, according to the XRD data. The standard data from JCPDS card numbers for copper sulfate matches well with the observed strong peaks of PVA/HPMC+20 wt.% of CuSO4 BSPE. The complex

This research aims to removes dyes from waste water by adsorption using banana peels. The conduct experiment done by banana powder and banana gel to compare between them and find out which one is the most efficient in adsorption. Studying the effects different factors on adsorption material and calculate the best removal efficiency to get rid of the methylene blue dye (MB).

Background: Frovatriptan succinate (FVT) is an effective medication used to treat migraines; however, available oral formulations suffer from low permeability; accordingly, several formulations of FVT were prepared. Objective: Prepare, optimize, and evaluate FVT-BE formulation to develop enhanced intranasal binary nano-ethosome gel. Methods: Binary ethosomes were prepared using different concentrations of phospholipid PLH90, ethanol, propylene glycol, and cholesterol by thin film hydration and characterized by particle size, zeta potential, and entrapment efficiency. Furthermore, in-vitro, in-vivo, ex-vivo, pharmacokinetics, and histopathological studies were done. Results: Regarding FVT-loaded BE, formula (F9) demonstrated the best paramet

Feature selection (FS) constitutes a series of processes used to decide which relevant features/attributes to include and which irrelevant features to exclude for predictive modeling. It is a crucial task that aids machine learning classifiers in reducing error rates, computation time, overfitting, and improving classification accuracy. It has demonstrated its efficacy in myriads of domains, ranging from its use for text classification (TC), text mining, and image recognition. While there are many traditional FS methods, recent research efforts have been devoted to applying metaheuristic algorithms as FS techniques for the TC task. However, there are few literature reviews concerning TC. Therefore, a comprehensive overview was systematicall

A Ligand (ECA) methyl 2-((1-cyano-2-ethoxy-2-oxoethyl)diazenyl)benzoate with metals of (Co²⁺, Ni²⁺, Cu²⁺) were prepared and characterization using H-NMR, atomic absorption spectroscopy, ultra violet (UV) visible, magnetic moments measurements, bioactivity, and Molar conductivity measurements in soluble ethanol. Complexes have been prepared using a general formula which was suggested as [M (ECA)₂] Cl₂, where M = (Cobalt(II), Nickel(II) and Copper(II), the geometry shape of the complexes is octahedral.