Morphological characterization, statistical modelling and tribological behaviour of aluminum hybrid nanocomposites reinforced with micro-nano-silicon carbide

Abstract

The wear behavior of Al-10 wt. %, SiCmicro-x wt. %, SiCnano (x = 0, 1, 3, 5 and 7) hybrid nanocomposites were investigated. The effects of nano-silicon carbide (SiC) addition, the sliding distance and the applied load were studied in factorial design (5 × 3 × 2) of experiments. The influence of SiC, the sliding distance and the applied load were found to be 42.4, 42.3 and 11.3%, respectively. The wear resistance of the nanocomposite reinforced with 5 wt. % SiC nanoparticles was the best amongst all the synthesized nanocomposites. The worn surfaces and wear debris were analyzed using both scanning electron microscopy (SEM) and electron dispersive spectroscopy (EDS). Five different regression models were also developed to estimate the tribological behavior of composites with nano-silicon carbide (SiC) reinforcement, the sliding distance and the applied load as inputs. The accuracy of these models was evaluated using the five most commonly applied statistical indicators. The models were ranked according to their suitability for prediction using the Global Performance Indicator. The predicted values and experimental data showed a high degree of association. It was determined that the developed models could be used to predict wear behavior within the range of the investigation.

Keywords

• aluminum
• composites
• wear
• anova
• regression models