Sistema Regional de Información
en línea para Revistas Científicas de América Latina,
el Caribe, España y Portugal

Cadmium selenide nanoparticles (NPs-CdSe) were synthesized by colloidal route at room temperature and atmospheric pressure using cadmium chloride (CdCl2·2.5 hydrate) and elemental selenium (Se) as precursors. Sodium borohydride (NaBH4) was used as reducing agent to obtain Se2- ions and an aqueous solution with a NaOH and Penta sodium tripolyphosphate (STPP) was used to protect Cd2+ ions. To remove the by-products generated during the chemical reaction and to promote the precipitation of NPs-CdSe, a cleaning process with an aqueous solution of HCl was performed. The HCl volume was varied from 0.2 to 1.2 ml during the cleaning process to study its effects on CdSe synthesis. The crystalline structure was analyzed by inspection of the high-resolution transmission electron microscope (HR-TEM) and X-ray diffraction (XRD). This analysis showed that crystals of CdSe exhibit a face-centered cubic structure (FCC). The calculated crystallite size is 3.5 nm and increases to 4.5 nm as the HCl volume increases. The morphologies of the products were observed by SEM and TEM techniques. HRTEM images showed that NPs-CdSe synthetized to 0.8 ml are composed of a great number of homogeneous and smooth nanospheres which are not appreciable in SEM but are observable in TEM. By contrast, 0.2 and 1.2 ml HCl samples are comprised of a great deal of rods of compounds of Se mixed with CdSe spheres nanostructures. This work, which did not require the use of surfactants complexes or specials environment, is considered to have advantages over other works.

Analysis of the seabed composition over a large spatial scale is an interesting yet very challenging task. Apart from the field work involved, hours of video footage captured by cameras mounted on Remote Operated Vehicles (ROVs) have to be reviewed by an expert in order to classify the seabed topology and to identify potential anthropogenic impacts on sensitive benthic assemblages. Apart from being time consuming, such work is highly subjective and through visual inspection alone, a quantitative analysis is highly unlikely to be made. This study investigates the applicability of various Machine Learning techniques for the automatic classification of the seabed into maerl and sand regions from recorded ROV footage. ROV data collected from depths ranging between 50 m and 140 m and at 9.5 km from the northeast coastline of the Maltese Islands, is processed. Through the application of the presented technique, 5.23 GB of data corresponding to 2 h and 24 min of footage which was collected during June 2013, was initially cleaned and classified. An estimate for the percentage cover of the two benthic habitats (sandy seabed and maerl) was also computed by using artifacts encountered during the ROV survey and of known dimensions as a reference. Unlike other automatic seabed mapping techniques, the presented prototype processes video footage captured by a down-facing camera and not through acoustic backscatter. Image data is easier and much cheaper to capture. Promising results that indicate a very good degree of agreement between the true and predicted habitat type distribution values, were obtained.

The main purpose of this work is to produce low cost activated carbons from date stones wastes for the adsorption of l-phenylalanine. The activated carbons were prepared by chemical activation with KOH (ACK) and ZnCl2 (ACZ) and characterized by scanning electron microscopy, N2 adsorption–desorption isotherms and FT-IR spectroscopy. Both The activated carbons ACK and ACZ have high specific surface areas and large pore volumes, favorable for the adsorption. Batch experiments were conducted to determine the adsorption capacities. A Strong dependence of the adsorption capacity on pH was observed, the capacity decreases with increasing pH up to optimal value of 5.7. The adsorption follows a pseudo-second order kinetic model. Additionally, the equilibrium adsorption data were well fitted to the Langmuir isotherm, and the maximum adsorption capacities of l-phenylalanine onto ACK and ACZ were 188.3 and 133.3 mg g−1 at pH 5.7, respectively. The thermodynamic study revealed that the adsorption of l-phenylalanine onto activated carbons was exothermic in nature. The proposed adsorption mechanisms take into account the hydrophobic and electrostatic interactions which played the critical roles in the l phenylalanineadsorption.

The present paper reports the heating ability and hemolysis test of magnetite nanoparticles (MNPs) for biomedical applications, obtained bya novel and easy co-precipitation method, in which it is not necessary the use of controlled atmospheres and high stirring rates. Different molarproportions of FeCl2:FeCl3 (2:1 and 3:2 respectively) were used and the obtained MNPs were analyzed by X-ray diffraction, vibrating samplemagnetometry and transmission electron microscopy. The heating ability was evaluated under a magnetic field using a solid state induction heatingequipment at two different frequencies (362 and 200 kHz). Additionally, a hemolysis test was performed according to the ASTM method. Theobtained ferrites showed a particle size in the range of 8–12 nm and superparamagnetic behavior. The MNPs increased the temperature up to43.1◦C in 5 min under a low magnetic field and showed non hemolytic effect up to 3 mg/ml. The MNPs obtained are highly potential materials forhyperthermia cancer treatment.

Successful synthesis of metal–, semiconductor–, and metal/semiconductor–mordenite nanocomposites, using geothermal solid waste as precursoris reported. Powders of nanostructured composites, consisting of metal and/or semiconductor nanoparticles grown on a mordenite-type zeoliticmatrix surface, were synthesized by a one-step solvent-free and organic template-free process. The developed methodology is capable of controllingand tuning the final properties of composites from their synthesis and is also reproducible and repeatable. For comparison and demonstration of theapplication of the final products, dye photocatalysis degradation tests were done using commercial TiO2 as reference (degradation reached ∼75%in 215 min, k = 0.004 min−1), [M]–S–MOR samples revealed better performance (≥95% in 100 min, k = 0.009 min−1).

The chemometric method based on the EDS analysis has been utilized to classify archeological ceramic fragments from Arpakkam site (eight samples) in Kanchipuram district. EDS was used to determine their elemental composition and the results were treated statistically using two methods: factor analysis (FA) and cluster analysis (CA). This treatment revealed two main groups; the first one encompasses only the two samples (ARMP4 and ARMP8) and the second one comprises the remaining samples (ARMP1–ARMP7) (except ARMP4). Grouping of selected artifacts was carried out using the ratios of SiO2 to Al2O3 concentrations because of their non-volatile nature. The mineralogical compositions of the potteries were determined by means of X-ray powder diffraction and FT-IR spectroscopy. The firing temperature and the methods were assessedby SEM, FT-IR and XRD spectroscopic analysis. The present studies evaluate the mineralogical, chemical and microstructural characteristics and the grouping of potteries. These techniques might be useful methods for the material analysis of ceramics.

In this era of flexible manufacturing systems, a real-time structural health monitoring (SHM) is paramount for machining processes which are of great relevance today, when there is a constant call for better productivity with high quality at low price. During machining, vibrations are always brought forth because of mechanical disturbances from various sources such as an engine, a sound, and noise, among others. A SHM system provides significant economic benefits when applied to machine tools and machining processes. This study demonstrates a non contact SHM system for machine tools based on the vibration signal collected through a low-cost, microcontroller based data acquisition system. The examination tests of this developed system have been carried out on a vibration rig. The readings have also been calibrated with the accelerometer to validate the proposed system. The developed system results in quick measurement, enables reliable monitoring, and is cost effective with no need to alter the structure of the machine tool. It is expected that the system can forewarn the operator for timely based maintenance actions in addition to reducing the costs of machine downtime and acquiring equipments with reduction in complexity of machine tools.

Aluminum/carbon nanotube composite is a promising candidate material for aerospace applications owing to its high strength-to-weight ratio.Because of the low density of carbon nanotubes (CNTs), their dispersion is difficult in molten metal. We investigated induction melting, a fairlydistinct approach to facilitate the dispersion of CNTs in molten aluminum. The nanocomposites were characterized using scanning electronmicroscopy, X-ray diffraction, transmission electron microscopy and mechanical testing. Refinement in crystallite size (∼320 nm) and increase inlattice strain (∼3.24 × 10−3) were observed in the composites. A simultaneous increase in yield strength (∼77%), tensile strength (∼52%), ductility(∼44%) and hardness (∼45%) was observed. Induction melting appeared to be a potential method to fabricate aluminum–CNTs composites.

Magneto-rheological (MR) dampers are effective solutions in improving vehicle stability and passenger comfort. However, handling these dampers implies a strong effort in modeling and control. This research proposes an H2 controller, based on a Takagi–Sugeno (T–S) fuzzy model, for a two-degrees-of-freedom (2-DOF) one-quarter vehicle semi-active suspension with an MR damper; a system with important applications in automotive industry. Regarding performance criteria (in frequency domain) handled herein, the developed controller considerably improves the passive suspension’s efficiency. Moreover, nonlinear actuator dynamics usually avoided in reported work, is included in controller’s synthesis; improving the relevance of research outcomes because the controller is synthesized from a closer-to-reality suspension model. Going further, outcomes of this research are compared (based on frequency domain performance criteria and a common time domain test) with reported work to highlight the outstanding results. H2 controller is given in terms of quadratic Lyapunov stability theory and carried out by means of Linear Matrix Inequalities (LMI), and the command signal is applied via the Parallel Distributed Compensation (PDC) approach. A case of study, with real data, is developed and simulation work supports the results. The methodology applied herein can be extended to include other vehicle suspension’s dynamics towards a general chassis control.

The construction, characterization and control of an electric oven dedicated to the study of thermoresistive polymer nanocomposites is presented. The oven is designed with a heating plate capable of reaching 300◦C with a resolution of 0.3◦C and an area of uniform temperature of3.8 cm × 2.5 cm. The temperature is regulated by means of a discrete proportional–integral–derivative controller. A heat transfer model comprisingthree coupled non-linear differential equations is proposed to predict the thermal profiles of the oven during heating and cooling, which are experimentally verified. The oven is used for thermoresistive characterization of polymer nanocomposites manufactured from a polysulfone polymerand multiwall  carbon nanotubes.