Abstract
Polyphenylene sulfide (PPS) composites filled with short carbon fibers (SCFs) (up to 15 vol.%) and sub-micro-scale TiO 2 particles (up to 7 vol.%) were prepared by extrusion and subsequently injection-molding. Based on the results of sliding wear tests, the tribological behavior of these materials was investigated using an artificial neural network (ANN) approach. A synergistic effect of the incorporated short carbon fibers and sub-micro TiO 2 particles is reported. The lowest specific wear rate was obtained for the composition of PPS with 15 vol.% SCF and 5 vol.% TiO 2. A more optimal composition of PPS with 15 vol.% SCF and 6 vol.% TiO 2 was estimated according to ANN prediction. The scanning electron microscopy (SEM) observation revealed that this hybrid reinforcement could be interpreted in terms of a positive rolling effect of the particles between the two sliding surfaces, which protected the short carbon fibers from being pulled-out of the PPS matrix.
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