RESUMO
Porous γ-alumina is widely used as a catalyst carrier due to its chemical properties. These properties are strongly correlated with the physical properties of the material, such as porosity, density, shrinkage, and surface area. This study presents a technique that is less time consuming than other techniques to predict the values of the above-mentioned physical properties of porous γ-alumina via an artificial neural network (ANN) numerical model. The experimental data that was implemented was determined based on 30 samples that varied in terms of sintering temperature, yeast concentration, and socking time. Of the 30 experimental samples, 25 samples were used for training purposes, while the other five samples were used for the execution of the experimental procedure. The results showed that the prediction and experimental data were in good agreement, and it was concluded that the proposed model is proficient at providing high accuracy estimation data derived from any complex analytical equation.
RESUMO
The influence of Ta additions on the microstructure and properties of Cu-Al-Ni shape memory alloys was investigated in this paper. The addition of Ta significantly affects the green and porosity densities; the minimum percentage of porosity was observed with the modified prealloyed Cu-Al-Ni-2.0 wt.% Ta. The phase transformation temperatures were shifted towards the highest values after Ta was added. Based on the damping capacity results, the alloy of Cu-Al-Ni-3.0 wt.% Ta has very high internal friction with the maximum equivalent internal friction value twice as high as that of the prealloyed Cu-Al-Ni SMA. Moreover, the prealloyed Cu-Al-Ni SMAs with the addition of 2.0 wt.% Ta exhibited the highest shape recovery ratio in the first cycle (i.e., 100% recovery), and when the number of cycles is increased, this ratio tends to decrease. On the other hand, the modified alloys with 1.0 and 3.0 wt.% Ta implied a linear increment in the shape recovery ratio with increasing number of cycles. Polarization tests in NaCl solution showed that the corrosion resistance of Cu-Al-Ni-Ta SMA improved with escalating Ta concentration as shown by lower corrosion current densities, higher corrosion potential, and formation of stable passive film.
RESUMO
In the present work, the microstructure, corrosion, and bioactivity of graphene oxide (GO) coating on the laser-modified and -unmodified surfaces of TiNb shape memory alloys (SMAs) were investigated. The surface morphology and chemical composition was examined using field emission scanning electron microscopy (FE-SEM) and X-ray diffraction (XRD). The surface modification was carried out via a femtosecond laser with the aim to increase the surface roughness, and thus increase the adhesion property. FE-SEM analysis of the laser-treated Ti-30at.% Nb revealed the increase in surface roughness and oxygen/nitrogen containing groups on the Ti-30at.% Nb surface after being surface modified via a femtosecond laser. Furthermore, the thickness of GO was increased from 35µm to 45µm after the surface was modified. Potentiodynamic polarisation and electrochemical impedance spectroscopy studies revealed that both the GO and laser/GO-coated samples exhibited higher corrosion resistance than that of the uncoated TiNb SMA sample. However, the laser/GO-coated sample presented the highest corrosion resistance in SBF at 37°C. In addition, during soaking in the simulated body fluid (SBF), both the GO and laser/GO coating improved the formation of apatite layer. Based on the bioactivity results, the GO coating exhibited a remarkable antibacterial activity against gram-negative bacteria compared with the uncoated. In conclusion, the present results indicate that Ti-30at.% Nb SMAs may be promising alternatives to NiTi for certain biomedical applications.