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Natural laterite can be regarded as a strong adsorbent due to its special structure and composition. In this study, the laterite was modified by manganese oxide (MnO2) to create a new good adsorbent for treating phosphate and fluoride in water environment. Under the optimized conditions of the adsorbent dose (pH 6, temperature 20°C, and the contact time 180 min), laterite, doped manganese, with diameter of grains from 0.1 to 0.5 mm has maximum adsorption capacity of 31.25 mg/g and 10.99 mg/g for phosphate and fluoride, respectively. The characteristics of the manganese doping laterite were confirmed using various techniques like SEM, BET, XRD, EDX. The adsorption process of the material was investigated by both kinetic models (pseudo-first and second orders) and isotherm models (Freundlich and Langmuir). This new material was tested for treatment of wastewater taken from the superphosphate fertilizer factory, with the results obtained showing high potential for application in reality.

Highly selective etching of silicon nitride (Si3N4) and silicon dioxide (SiO2) has received considerable attention from the semiconductor community owing to its precise patterning and cost efficiency. We investigated the etching selectivity of Si3N4 and SiO2 in an NF3/O2 radio-frequency glow discharge. The etch rate linearly depended on the source and bias powers, whereas the etch selectivity was affected by the power and ratio of the gas mixture. We found that the selectivity can be controlled by lowering the power with a suitable gas ratio, which affects the surface reaction during the etching process. X-ray photoelectron spectroscopy of the Si3N4 and QMS measurements support the effect of surface reaction on the selectivity change by surface oxidation and nitrogen reduction with the increasing flow of O2. We suggest that the creation of SiOxNy bonds on the surface by NO oxidation is the key mechanism to change the etch selectivity of Si3N4 over SiO2. [ABSTRACT FROM AUTHOR]

The last decade has witnessed an increasing interest in metamaterial absorbers (MMAs) because of their huge potential in a wide range of applications including energy harvesting, photodetectors, sensors, light modulators, infrared camouflage and wireless communication. Recently, machine learning (ML) has become one of the modern and powerful tools that can examine the design data in order to forecast the absorption behavior with much less effort and cost-effectiveness than conventional experimental and computation approaches. In this work, we utilize two ML algorithms, Polynomial Regression (PR) and Random Forest Regression (RFR), to predict the absorption strength and frequency of a symmetric disk-shape metamaterial structure operating within 10 and 16 GHz. The proposed models are trained on hundreds of simulation-generated samples. We show that fine-tuning some hyperparameters results in higher forecasting performance. The dependence of predicted results on input parameters demonstrates that PR has better performance in predicting absorption strength, while both algorithms share similar accuracy in predicting the absorption frequency. [ABSTRACT FROM AUTHOR]

Molecular and dissociative hydrogen adsorption of transition metal (TM)-doped [Mo 3 S 13 ] 2- atomic clusters were investigated using density functional theory calculations. The introduced TM dopants form stable bonds with S atoms, preserving the geometric structure. The S-TM-S bridging bond emerges as the most stable configuration. The preferred adsorption sites were found to be influenced by various factors, such as the relative electronegativity, coordination number, and charge of the TM atom. Notably, the presence of these TM atoms remarkably improved the hydrogen adsorption activity. The dissociation of a single hydrogen molecule on TM[Mo 3 S 13 ] 2- clusters (TM = Sc, Cr, Mn, Fe, Co, and Ni) is thermodynamically and kinetically favorable compared to their bare counterparts. The extent of favorability monotonically depends on the TM impurity, with a maximum activation barrier energy ranging from 0.62 to 1.58 eV, lower than that of the bare cluster (1.69 eV). Findings provide insights for experimental research on hydrogen adsorption using TM-doped molybdenum sulfide nanoclusters, with potential applications in the field of hydrogen energy., Competing Interests: The authors declare no competing financial interest., (© 2024 The Authors. Published by American Chemical Society.)