The effect of microwave radiation on the hydrothermal synthesis of the double perovskite Sr₂FeMoO₆ has been studied based on a comparison of the particle size and structural characteristics of products from both methods. A temperature, pressure, and pH condition screening was performed, and the most representative results of these are herein presented and discussed. Radiation of microwaves in the hydrothermal synthesis method led to a decrease in crystallite size, which is an effect from the reaction temperature. The particle size ranged from 378 to 318 nm when pH was 4.5 and pressure was kept under 40 bars. According to X-ray diffraction (XRD) results coupled with the size-strain plot method, the product obtained by both synthesis methods (with and without microwave radiation) have similar crystal purity. The Scanning Electron Microscopy (SEM) and Energy Dispersive X-ray Spectroscopy (EDS) techniques showed that the morphology and the distribution of metal ions are uniform. The Curie temperature obtained by thermogravimetric analysis indicates that, in the presence of microwaves, the value was higher with respect to traditional synthesis from 335 K to 342.5 K. Consequently, microwave radiation enhances the diffusion and nucleation process of ionic precursors during the synthesis, which promotes a uniform heating in the reaction mixture leading to a reduction in the particle size, but keeping good crystallinity of the double perovskite. Precursor phases and the final purity of the Sr₂FeMoO₆ powder can be controlled via hydrothermal microwave heating on the first stages of the Sol-Gel method.

A simple ultrasonic radiation method was employed for the preparation of zinc and cadmium sulfide solid solution (Zn_xCd_1−xS; x = 0–0.25 wt.%) with the aim to investigate its efficiency for H₂ production via a visible light-driven water-splitting reaction. The catalyst characterization by X-ray diffraction confirmed the formation of solid solution (Zn_xCd_1−xS) between CdS and ZnS phases. All catalysts exhibited hierarchical morphology (from SEM and TEM) formed by aggregated nanoparticles of Zn_xCd_1−xS solid solution with crystals showing mainly (111) planes of cubic CdS phase. The crystal size linearly decreased with an increase in Zn incorporation in the crystal lattice (from 4.37 nm to 3.72 nm). The Zn_xCd_1−xS photocatalysts showed a gradual increase in the H₂ evolution, with an increase in the Zn concentration up to 0.2 wt.% making the most effective Zn_0.2Cd_0.8S catalyst toward H₂ production. From the catalyst activity–structure correlation, it has been concluded that the twin-like CdS structure, the (111) plane and specific morphology are the main factors influencing the catalyst effectivity toward H₂ production. All those factors compensated for the negative effect of an increase in band gap energy (E_bg) after ZnS incorporation into solid solution (from 2.21 eV to 2.34 eV). The effect of the catalyst morphology is discussed by comparing H₂ evolution over unsupported and supported Zn_0.2Cd_0.8S solid solutions.

The symptoms of multiple sclerosis (MS) are determined by the location of demyelinating lesions in the white matter of the brain and spinal cord. Currently, magnetic resonance imaging (MRI) is the most common tool used for diagnosing MS, understanding the course of the disease, and analyzing the effects of treatments. However, undesirable components may appear during the generation of MRI scans, such as noise or intensity variations. Mathematical morphology (MM) is a powerful image analysis technique that helps to filter the image and extract relevant structures. Granulometry is an image measurement tool for measuring MM that determines the size distribution of objects in an image without explicitly segmenting each object. While several methods have been proposed for the automatic segmentation of MS lesions in MRI scans, in some cases, only simple data preprocessing, such as image resizing to standardize the input dimensions, has been performed before the algorithm training. Therefore, this paper proposes an MRI preprocessing algorithm capable of performing elementary morphological transformations in brain images of MS patients and healthy individuals in order to delete undesirable components and extract the relevant structures such as MS lesions. Also, the algorithm computes the granulometry in MRI scans to describe the size qualities of lesions. Using this algorithm, we trained two artificial neural networks (ANNs) to predict MS diagnoses. By computing the differences in granulometry measurements between an image with MS lesions and a reference image (without lesions), we determined the size characterization of the lesions. Then, the ANNs were evaluated with the validation set, and the performance results (test accuracy = 0.9753; cross-entropy loss = 0.0247) show that the proposed algorithm can support specialists in making decisions to diagnose MS and estimating the disease progress based on granulometry values.

This study focuses on the use of Au nanoparticles supported on the SrTiO_3−δ perovskite doped with Fe ions as a photocatalyst for CO₂ reduction and methanol production using water as the hydrogen supplier. The photocatalytic evaluation of the synthesized materials shows that Au nanoparticles supported on the SrTi_(1−x)Fe_xO_3−δ perovskites can enhance photocatalytic CO₂ reduction. The sample with the doping level x = 0.125 has the highest methanol production, 9.5 times more than the undoped sample and 3.5 times more than its counterpart without Au nanoparticles. The results of the DFT + U calculations show that the contributions from the iron atoms states reduce the energy gap in the perovskite composite, SrTi_(1−x)Fe_xO_3−δ. Additionally, Fe incorporation endows the system with the capacity to create electron–hole pairs via direct band transitions at the high‐symmetry point R with the doping levels of x = 0.125 and x = 0.250.

In this article, we describe a prototype photoreactor of which the geometrical configuration was obtained by Genetic Algorithms to maximize the residence time of the reactant gases. A gas reaction mixture of CO₂:H₂O (1:2 molar ratio) was studied from the fluid dynamic point of view. The two main features of this prototype reactor are the conical shape, which enhances the residence time as compared to a cylindrical shape reference reactor, and the inlet heights and position around the main chamber that enables turbulence and mass transfer control. Turbulence intensity, mixing capability, and residence time attributes for the optimized prototype reactor were calculated with Computational Fluid Dynamics (CFD) software and compared with those from a reference reactor. Turbulence intensity near the envisioned catalytic bed was one percentage point higher in the reference than in the optimized prototype reactor. Finally, the homogeneity of the mixture was guaranteed since both types of reactors had a turbulent regime, but for the prototype the CO₂ mass fraction was found to be better distributed.

Solid solutions Zn_xCd_1−xS were compared by coprecipitation and sonochemistry methods, where . This rate is the one that presents the best photocatalytic activity and the best performance for the production of hydrogen from a water source, according to our previous results. The influence of the synthesis method on the morphology and its electronic properties of the CdS and Zn_0.2Cd_0.8S systems was investigated, as well as the effect of the incorporation of Zn in the crystal lattice and its effect on the production of hydrogen from the division of water. X-ray diffraction characterization confirmed the formation of a solid solution corresponding to a face-centered cubic crystalline phase with preferential growth of (111), (220), and (311) planes and hierarchical morphology according to SEM and TEM microscopy, formed by aggregated nanoparticles of Zn_xCd_1−xS compound. The crystallite size decreased with the Zn incorporation in the crystal lattice from 8.61 nm by a coprecipitation method to 4.37 nm when the synthesis was assisted with sonochemistry, and the crystallite sizes range from 7.92 nm to 3.80 nm for the case of CdS pure. Other characterization techniques were also used, such as photoluminescence (PL), Raman microscopy, and N₂ adsorption and desorption. The PL results show tunability of band edge emission as a function of zinc concentration in the Zn_0.2Cd_0.8S nanoparticles. For the water splitting to hydrogen production, the separation of the charge carriers promoted by the incorporation of Zn in addition to the shallow trap emissions generated defects in the catalyst structure; such processes are important factors found which increased with the sonochemical method, as well as the potential matched positions.