Litcius/Paper detail

Neural network-supported study on erosive wear performance analysis of Y2O3/WC-10Co4Cr HVOF coating

Jashanpreet Singh, Simranjit Singh

2021Journal of King Saud University - Engineering Sciences35 citationsDOIOpen Access PDF

Abstract

In this work, a study was carried out by modifying the conventional Tungsten Carbide Cobalt Chrome (WC–10Co4Cr) powder with a small addition of yttrium-oxide (Y 2 O 3 ). Reinforcement was done by adding yttria (Y 2 O 3 ) ceramics in WC–10Co4Cr powder by using a jar ball mill process. The surface microstructure, chemical composition, and phase compositions of coating powder and coatings were examined by using scanning electron microscopy, energy dispersive spectroscopy, and X-ray diffractometry. Silt erosion was evaluated through a pot tester by preparing equi- and multi-sized slurries at different velocities, impact angles, concentrations, and rates. Results show that the WC–10Co4Cr powder coating reinforced by Y 2 O 3 ceramics possesses low porosity, providing higher erosive performance as compared to conventional WC–10Co4Cr coating. The present study reveals that the deposition of conventional WC–10Co4Cr coating helps improve the wear resistance of AISI 316L stainless steel (UNS S31600) by 9.98% for the variation in rotational speed . However, the erosive wear performance of conventional WC–10Co4Cr coating was improved by 45.9% by blending it with the Y 2 O 3 ceramics.

Topics & Concepts

Materials scienceCoatingThermal sprayingTungsten carbideMicrostructureScanning electron microscopeCeramicYttria-stabilized zirconiaMetallurgyPorositySlurryComposite materialYttriumEnergy-dispersive X-ray spectroscopyBall millOxideCubic zirconiaAdvanced materials and compositesHigh-Temperature Coating BehaviorsTunneling and Rock Mechanics