Waterborne polyurethane (WBPU) coatings represent eco-friendly alternatives to solvent-based systems due to their low volatile organic compounds (VOCs) emissions and reduced toxicity. However, their inherent hydrophilicity limits water repellence, thereby restricting their use in demanding environments. In this research, pristine calcium carbonate (CaCO3), sodium stearate-modified CaCO3 (SS-CaCO3), and a mixture of SS-CaCO3 with silica nanoparticles (SiO2NPs) improved the hydrophobicity of WBPU. Four formulations, namely, pristine WBPU (P1), WBPU+CaCO3 (P2), WBPU + SS-CaCO3 (P3), and P3 + SiO2NPs (P4), were prepared and applied onto mild steel substrates. The composite formation was confirmed using Fourier-transform infrared (FTIR) spectroscopy, with the intensity of the O-H band in P4 being lower. According to the X-ray diffraction (XRD) study, the dispersion of the SiO2NPs in P4 was improved, which reduced the crystallite size to 22.38 nm. The scanning electron microscope (SEM) images indicated that the surface roughness of P4 increased with the enrichment of SiO2NPs on the surface of the coating. The spectroscopic evidence of the energy-dispersive X-ray (EDX) spectroscopy revealed the corresponding elemental distribution and a higher proportion of oxygen. The measurements of water contact angle (WCA) showed that P4 had the best hydrophobicity (105.08 ± 0.74°), which can be explained by the fact that P4 possessed the best surface roughness produced by the nanoparticles. These results indicate that the presence of SS-CaCO3 and SiO2NPs enhances the performance and water repellence of WBPU, which further improves its prospects as an environmentally friendly coating.
We report the green synthesis of mixed-phase indium sulfide nano powder via a cost-effective wet chemical route at a temperature of 100 °C, employing minimal reagents. X-ray diffraction analysis reveals the coexistence of tetragonal In₂S₃ and monoclinic In₆S₇ phases, with an average crystallite size of 70.98 nm. Scanning electron microscopy confirms the microcrystalline morphology, while X-ray photoelectron spectroscopy excludes the presence of In–O bonds associated with In(OH)₃ impurities. Brunauer–Emmett–Teller analysis demonstrates meso-porosity with a pore size of 3.39 nm and a specific surface area of 45.59 m2/g. The mesoporous architecture and optimal band gap render mixed-phase indium sulfide nano powder highly effective for photocatalytic degradation of structurally related organic dyes, Rhodamine B and Sulforhodamine B. Comparative studies with single-phase indium sulfide samples synthesized at lower bath temperatures (30 0C and 70 0C) yielded degradation efficiencies of 14.3
Perovskite types of photovoltaic sources have become the primary candidates for next-generation photovoltaic sources thanks to their high-quality optoelectronic characteristics and their fast-enhancing power-conversion parameters. Nonetheless, the computational space of perovskites is quite large and first-principles is expensive, and this makes systematic optimization of materials a challenging problem. This paper presents a unified multiscale system that entails the implementation of density functional theory (DFT), machine learning (ML), and device-level simulation to hasten the search and development of high-performance perovskite solar cell materials. Physically significant descriptors are generated through DFT calculations such as structural parameters, electronic bandgaps, formation energies, and properties of defect-related characteristics. The descriptors are utilized to train the supervised ML models that can predict the important material and photovoltaic performance indicators with high accuracy at a rapid rate. Predictions of the ML are then combined with practicing simulations of the device to assess open-circuit voltage, short-circuit current density, fill factor, and power conversion efficiency. The findings show that there are good correlations among defect tolerance, bandgap optimization, and photovoltaic performance with defect suppression being a leading channel of increasing the efficiency. The current DFT-ML scheme consumes much less computational power; however, still has physical interpretability, and can offer efficient and predictive solution to perovskite material screening as well as solar cell design scaling.
Multi-spherical shaped of silver nanoparticles AgNPs were successfully synthesized using laser ablation method with three different laser energy (150 mJ, 300 mJ and 450 mJ). The XRD diffraction analysis are confirm of prepared of Ag and AgO particles with a face-centered cubic structure, the Average crystalline size are equal to 12.946 nm, 11.338 nm and 10.060 nm for AgNPs samples exposed with laser energy 150 mJ, 300 mJ and 450 mJ respectively. The EDX analysis are demonstrating to the crystalline Silver and Silver oxides nano particle. The SEM analysis showed that silver nanoparticle exhibits various clusters of spherical nanoparticles shapes with different nano-diameter .The Pseudomonos auruginosa and Klebsiella pneumoniae are used to investigated the AgNPs antibacterial activity. The results show that zone of inhibition (ZOI) diameter to both bacteria’s are varying when the bacteria’s are exposed with sample AgNPs prepared by laser energy 150 mJ, 300 mJ and 450 mJ. The varying range are between (18 to 15 nm) and between (23 to 15 nm) for Pseudomonos auruginosa, and Klebsiella pneumoniae bacteria respectively.
