A MULTISCALE MODELING APPROACH TO UNDERSTAND MECHANISM OF DEPOSIT CONTROL BY LUBRICANT DETERGENTS AND DISPERSANTS

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2022-7-29

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Kan, Esra

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With the recent developments in high performance computing power, molecular modeling calculations to design and improve new generation additives for engine oils have reached a level that can support and guide experimental results. Control of insoluble nanoparticle aggregations in oil and on the engine pistons is the most important key performance parameter for lubricant oil additives. General consensus about the mechanism of deposit build-up is the self-aggregation of nanosized insoluble structures. Detergents and dispersants are the major additives to prevent aggregation in lubricant formulations provided by Lubrizol Corporation. Together with the base oil, they play a significant role to disperse and stabilize insoluble particles to control deposit formation. In this study, multiscale modeling methods were used to elucidate molecular mechanism of deposit control via detergents and dispersants by using density functional theory, molecular dynamics simulations of cells constructed by statistical sampling of large number of molecular configurations and coarse-grained simulations. The aim of this study is to understand the role of different groups such as bis-succinimide amine center and two polyisobutylene tails in dispersants as well as anionic sulfonate head group and alkyl tails in detergents. It was demonstrated that the mechanism of deposit control can be explained by the interactions between constituents such as hydrogen bonding and hydrophobic-hydrophilic forces. We showed that nanoparticle aggregation is mitigated by intercalation of dispersant and detergent polar groups between the insoluble nanoparticles followed by the extension of hydrophobic tails into the oil phase that decreases coalesce further by forming a repulsive layer against the other nanoparticles.

Subject Keywords

Dispersant, Detergent, Multiscale Modeling, Molecular Dynamics Simulation, Coarse-Grained Simulation

URI

https://hdl.handle.net/11511/98615

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Graduate School of Natural and Applied Sciences, Thesis

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Citation Formats

E. Kan, “A MULTISCALE MODELING APPROACH TO UNDERSTAND MECHANISM OF DEPOSIT CONTROL BY LUBRICANT DETERGENTS AND DISPERSANTS,” M.S. - Master of Science, Middle East Technical University, 2022.