(564a) Chemical Vapor Deposition Applications in Thin Film Coatings for High-Temperature Lubrication

In the design of high-speed engines whose operating temperatures often exceed 400 degree celsius, the choice of a lubricant and lubrication technique is of considerable concern. The method chosen to lubricate the contact surfaces must be effective in reducing friction and increasing the usable life of these components. Liquid lubricants provide excellent protection at low temperatures, but at temperatures above 250 degree celsius, traditional liquid lubricants break down and cannot be used. A number of high-temperature lubrication mechanisms exist, including solid, powder, catalytic lubrication and tribo-polymerization. Work at the Advanced Manufacturing Center at Cleveland State University and research performed at Wright-Patterson Air Force Base have produced novel techniques for forming lubricating films on ceramics using a vapor delivered lubricant. This paper focuses on the formulation of a deposition model to study the chemical vapor deposition (CVD) mechanism on cast-iron as the most promising new technology for high temperature lubrication. Vapor phase deposition produces a protective film that is stable at temperatures above 300 degree celsius. This film provides a lubricating environment that has the ability to significantly reduce the coefficient of friction. At these high temperatures, no other method of lubrication is capable of providing such low values of coefficient of friction and enabling wear control. Wear and friction studies have indicated that the initial formation of iron phosphate film catalyzes the formation of a protective lubricating film. Protective films were grown by CVD in the TGA setting. Kinetic analysis of the TGA data indicates that the film deposition model can be used for the estimation of both kinetic and transport parameters. Statistical analysis of the experimental data yields transport and kinetic parameters that complement the proposed model. Results have shown that the model can be reliably used as a predictive and scale-up tool.