Lithium-rich layered oxide cathodes have attracted considerable attention due to their high energy density, but have suffered from voltage drop, structural instability, and limited electrical conductivity. In this study, the electrochemical performance of the lithium-rich cathode material Li[Li0.20Mn0.54Ni0.13Co0.13]O2 was evaluated after modification by zinc doping and composition with graphene oxide or graphene. The zinc-doped powders were synthesized by the sol-gel method, while the graphene-based composites were prepared by the hydrothermal route. The structural, morphological and electrochemical characteristics of the modified materials were examined using X-ray diffraction, Fourier transform infrared spectroscopy, field emission scanning electron microscopy, cyclic voltammetry, electrochemical impedance spectroscopy and charge-discharge testing. The co-modified samples exhibited improved lithium-ion diffusion, reduced charge transfer resistance, and increased structural stability. The graphene-zinc oxide composite provided the highest discharge capacity of 302 at 0.1 C, compared to 249 for the unmodified material, and showed a Coulombic efficiency of 89.7%. The synergistic effect of zinc incorporation and graphene-based composition significantly improved rate capability and minimized polarization. These findings demonstrated that combined structural and conductive modifications effectively improved the overall performance of lithium-rich cathodes and offered a promising path to improving next-generation lithium-ion battery systems.
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.
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).
Introduction: Cutaneous leishmaniasis (CL) is a common protozoan disease in Iraq characterized by localized ulcers, primarily on exposed skin. This study aimed to investigate the hematological parameters of infected patients using a complete blood count (CBC) in the endemic area of Diyala Governorate, northeast of Baghdad. This has been studied in newly diagnosed, untreated individuals and patients receiving sodium antimony gluconate. Methodology: Hematological screening was performed on blood samples from 161 patients with microscopically diagnosed cutaneous leishmaniasis before and after treatment. Anti-Leishmania IgG was also assessed by ELISA in seropositive and seronegative subjects. Results: The newly diagnosed, untreated pati
... Show MoreThe current research dealt with a vital subject contributing In success Iraqi Industrial Companies general and Iraqi Cement state company A market knowledge, It is one of the most important industrial companies that Which serve to fill the local market need Of cement without resorting to import, The problem of research was limited understanding of the importance of the role played market knowledge of the tendencies and desires of competitors, This in turn affects the company's ability to achieve competitive advantages,The research aims to know the extent of adoption Iraqi Cement state company Concept market knowledge And employment achieving Competitive advantage By removing them (Cost, and quality, and del
... Show MoreFeature 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
... Show MoreGenome sequencing has significantly improved the understanding of HIV and AIDS through accurate data on viral transmission, evolution and anti-therapeutic processes. Deep learning algorithms, like the Fined-Tuned Gradient Descent Fused Multi-Kernal Convolutional Neural Network (FGD-MCNN), can predict strain behaviour and evaluate complex patterns. Using genotypic-phenotypic data obtained from the Stanford University HIV Drug Resistance Database, the FGD-MCNN created three files covering various antiretroviral medications for HIV predictions and drug resistance. These files include PIs, NRTIs and NNRTIs. FGD-MCNNs classify genetic sequences as vulnerable or resistant to antiretroviral drugs by analyzing chromosomal information and id
... Show MoreTwo nanocomposite corrosion inhibitors were synthesized from Aloe vera extract: one incorporating sodium thiosulfate and the other silver nitrate. Both nanocomposites were subjected to structural characterization using atomic force microscopy (AFM), which revealed distinct morphological features. The sodium thiosulfate-based nanocomposite exhibited uniform and well-dispersed nanoparticles with an average size of 47.51 nm, suggesting a stable and homogeneous distribution. In contrast, the silver nitrate-based nanocomposite displayed slightly larger particles with an average diameter of 58.34 nm, indicating a tendency toward moderate aggregation. The corrosion inhibition performance of these nanocomposites for carbon steel (CS1137) was invest
... Show MoreThis article showcases the development and utilization of a side-polished fiber optic sensor that can identify altered refractive index levels within a glucose solution through the investigation of the surface Plasmon resonance (SPR) effect. The aim was to enhance efficiency by means of the placement of a 50 nm-thick layer of gold at the D-shape fiber sensing area. The detector was fabricated by utilizing a silica optical fiber (SOF), which underwent a cladding stripping process that resulted in three distinct lengths, followed by a polishing method to remove a portion of the fiber diameter and produce a cross-sectional D-shape. During experimentation with glucose solution, the side-polished fiber optic sensor revealed an adept detection
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