Formation of Au–Ag–Cu ternary alloy nanoparticles (NPs) is of particular interest because this trimetallic system have miscible (Au–Ag and Au–Cu) and immiscible (Ag– Cu) system. So there is a possibility of phase segregation in this ternary system. At this challenge it was present attempts synthetic technique to generate such trimetallic alloy nanoparticles by exploding wire technique. The importance of preparing nanoparticles alloys in distilled water and in this technique makes the possibility of obtaining nanoparticles free of any additional chemical substance and makes it possible to be used in the treatment of cancer or diseases resulting from bacterial or virus with least toxic. In this work, three metals alloys Au-Ag-Cu

In this work, the effect of annealing temperature on the electrical properties are studied of p-Se/ n-Si solar cell, which p-Se are deposit by DC planar magnetron sputtering technique on crystal silicon. The chamber was pumped down to 2×10−5 mbar before admitting the gas in. The gas was Ar. The sputtering pressure varied within the range of 4x10-1 - 8x10-2mbar by adjusting the pumping speed through the opening control of throttle valve. The electrical properties are included the C-V and I-V measurements. From C-V measurements, the Vbi are calculated while from I-V measurements, the efficiency of solar cell is calculated.

The effect of different Ti additions on the microstructure of Al-Ti alloy prepared by powder metallurgy was investigated. A certain amount of Ti (10wt%, 15wt%, and 20wt%) were added to aluminium and the tests like microhardness, density, scanning electron microscope (SEM), optical microscope (OM) and X-Ray Diffraction (XRD) were conducted to determine the influence of different Ti additives on the Al-Ti alloy properties and microstructure. The results show that the grains of α-Al changed from large grains to roughly spherical and then to small rounded grains with increasing Ti content, the micro-hardness of the alloy increases with increasing Ti, and XRD results confirm the formation of TiAl₃ intermetallic co

Iron oxide (Fe3O4) nanoparticles were synthesized via an eco-friendly green approach by adding Phoenix dactylifera extract to the aqueous solution of ferric chloride. The effect of annealing temperature (Ta) (100-150) °C on particle size was studied. X-ray diffraction (XRD), UV-visible spectroscopy, atomic force microscopy (AFM), and field emission scanning electron microscopy (FESEM) were used to evaluate the produced nanoparticles. According to XRD spectra, the crystallite size of the samples was determined using the Scherrer formula. AFM and FE-SEM were used to determine surface morphology. A UV-Vis optical spectroscopic examination was carried out to determine the band gap energy of the iron oxide nanoparticles. It was found th

Nuclear structure of ^29-34Mg isotopes toward neutron dripline have been investigated using shell model with Skyrme-Hartree–Fock calculations. In particular nuclear densities for proton, neutron, mass and charge densities with their corresponding rms radii, neutron skin thicknesses and inelastic electron scattering form factors are calculated for positive low-lying states. The deduced results are discussed for the transverse form factor and compared with the available experimental data. It has been confirmed that the combining shell model with Hartree-Fock mean field method with Skyrme interaction can accommodate very well the nuclear excitation properties and can reach a highly descriptive and predictive power when investiga

This study proposes a hybrid predictive maintenance framework that integrates the Kolmogorov-Arnold Network (KAN) with Short-Time Fourier Transform (STFT) for intelligent fault diagnosis in industrial rotating machinery. The method is designed to address challenges posed by non-linear and non-stationary vibration signals under varying operational conditions. Experimental validation using the FALEX multispecimen test bench demonstrated a high classification accuracy of 97.5%, outperforming traditional models such as SVM, Random Forest, and XGBoost. The approach maintained robust performance across dynamic load scenarios and noisy environments, with precision and recall exceeding 95%. Key contributions include a hardware-accelerated K

SUMMARY. – Nanocrystalline thin fi lms of CdS are deposited on glass substrate by chemical bath deposited technique using polyvinyl alcohol (PVA) matrix solution. Crystallite size of the nanocrystalline films are determining from broading of X-ray diffraction lines and are found to vary from 0.33-0.52 nm, an increase of molarity the grain size decreases which turns increases the band gap. The band gap of nanocrystalline material is determined from the UV spectrograph. The absorption edge and absorption coefficient increases when the molarity increases and shifted towards the lower wavelength.

A substantial percentage of the world’s energy consumption (almost 40%) and carbon dioxide (CO2) emissions (around 37%) come from the construction industry, especially schools. This work presents a new hybrid artificial intelligence (AI) engineering model that aims to maximize energy performance on campuses in a holistic way. Modules for data-driven forecasting, metaheuristic optimization, and real-time adaptive control are all part of the concept. A thorough energy simulation of a university campus building is used in conjunction with the AI model to assess its performance through a co-simulation framework. Findings show that yearly peak electricity demand may be reduced by 18.7% and total site energy consumption by 22.4% when co