About this Abstract |
Meeting |
2024 TMS Annual Meeting & Exhibition
|
Symposium
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Chemistry and Physics of Interfaces
|
Presentation Title |
Tribochemical Reaction of Molybdenum Dithiocarbamate Revealed by Neural Network Potential-based Molecular Dynamics Simulations |
Author(s) |
Kento Hosono, Takuya Tozawa, Arisa Chiba, Ryutaro Kudo, Mizuho Yokoi, Masayuki Kawamura, Yixin Su, Shogo Fukushima, Yuta Asano, Yusuke Ootani, Nobuki Ozawa, Momoji Kubo |
On-Site Speaker (Planned) |
Kento Hosono |
Abstract Scope |
Molybdenum dithiocarbamate (MoDTC) has been used as an additive reducing friction generated on steel interface to improve the lubrication performance of modern engine lubricants. Indeed, MoDTC works by forming molybdenum disulfide (MoS_2) film on rubbed surfaces, which is able to offer super-low friction and prevent wear in moving parts because of its weak interlayer forces. However, engine oils contain harmful elements such as sulfur derived from MoDTC additives to environmental catalysis and development of alternative additives is required. Therefore, elucidating the mechanism of forming MoS_2 film from MoDTC can be beneficial for creating new friction reducing additives.
Neural network potential (NNP) based molecular dynamics simulations are employed to describe chemical reactions such as MoS2 formation on steel interface with low computational cost and to clarify the mechanism of the MoS2 formation. In the presentation, we will also discuss the mechanism of super-low friction due to tribo-layers. |
Proceedings Inclusion? |
Planned: |
Keywords |
Computational Materials Science & Engineering, Thin Films and Interfaces, Machine Learning |