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  • Chemical Kinetics Modeling of Antioxidant Reactions in Lubricating Oils
    Mechanical and Aerospace Engineering
    Carleton University

    We are currently seeking to hire a Post-Doctoral Fellow for a term of up to 2 years, to work on a project to model the degradation of lubricants in bearing and engine lubrication environments. Our industrial partner has an interest in developing an in-line oil monitor capable of detecting the remaining useful life of a lubricating oil. This requires an accurate model of the relationship between oil operating conditions and detectable levels of antioxidant degradation by-products.

    While it is known that the consumption of antioxidant additives is a key indicator of lubricant degradation, the quantitative relationship between operating conditions, antioxidant by-product concentrations and reaction rates is not fully understood. In this project, we will develop this understanding through a combination of theoretical calculations and experiments. The end goal is an “engineering” model of the relationship between oil operating history and by-product formation, which will be validated with the help of the experimental data.

    The PDF will work on the development of the chemical kinetics modelling aspects of the project. Using a combination of the known literature, experimentally determined rate parameters and first-principles models, the PDF will test and refine databases of reaction-rate parameters and develop a model of anti-oxidant consumption for a variety of pressure and  temperature conditions.

    Interested candidates should have a PhD in Chemical Engineering, Chemistry, Mechanical Engineering, or a related discipline and experience with one or more of (1) chemical kinetics modeling, (2) experimental determination of reaction rate constants in condensed-phase (liquid) systems, (3) characterization methods such as HPLC, Raman Spectroscopy and GC-MS, and (4) computational fluid dynamics.

    Please submit a CV and the names of three references to Professor Miller to apply.


 


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