Polymers and their composites have been widely applied in different industrial sectors as alternatives to conventional metal-based materials, for the better performance of the system, increasing efficiency and cutting down operational costs. In those applications polymeric materials are sometime subjected to tribological loading conditions where external lubricants are not permissible and polymers’ self-lubricating ability is desirable in such tribo-contacts. In particular, high temperature is often the key factor determining the working conditions of polymers. Hence, high performance polymers (HPPs) have received increasing attention in last decades.
In view of above-mentioned facts, the present research investigated the tribological performance of some important engineering polymers and their nanocomposites such as epoxy, PEEK, PPP and PBI. For example, nano-silica (SiO2), nano-rubber (CBTN) and titanium dioxide (TiO2) nano-particles have been incorporated in thermosetting epoxy resin and PEEK, respectively, to improve their tribological properties. To explore the effect of harsh environments during sliding wear, pin-on-disk tests of above-mentioned materials were carried out in dry, wet and elevated temperature regimes.
Finally, attempts have been made to establish correlations between the basic mechanical properties of HPPs and their sliding wear behaviour. Various wear models to correlate the tribological aspects of HPPs and polymer nanocomposites with associated mechanical properties were examined along with experimental validation. In addition to that, underlying wear mechanisms were taken into account towards model developments. To develop a quantitative solution for wear prediction, the new computer techniques such as artificial neural network (ANN) may be helpful in the area. Accordingly, the ANN was employed to find the general wear trend of materials.