Papers
Topics
Authors
Recent
Assistant
AI Research Assistant
Well-researched responses based on relevant abstracts and paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses.
Gemini 2.5 Flash
Gemini 2.5 Flash 70 tok/s
Gemini 2.5 Pro 48 tok/s Pro
GPT-5 Medium 27 tok/s Pro
GPT-5 High 24 tok/s Pro
GPT-4o 75 tok/s Pro
Kimi K2 175 tok/s Pro
GPT OSS 120B 447 tok/s Pro
Claude Sonnet 4 36 tok/s Pro
2000 character limit reached

Se Nano-Powder Conversion into Lubricious 2D Selenide Layers by Tribochemical Reactions (2304.14311v1)

Published 27 Apr 2023 in cond-mat.mtrl-sci and physics.chem-ph

Abstract: Transition metal dichalcogenide (TMD) coatings have attracted enormous scientific and industrial interest due to their outstanding tribological behavior. The paradigmatic example is MoS2, even though selenides and tellurides have demonstrated superior tribological properties. Here, we describe an innovative in-operando conversion of Se nano-powders into lubricious 2D selenides by sprinkling them onto sliding metallic surfaces coated with Mo and W thin films. Advanced material characterization confirms the tribochemical formation of a thin tribofilm containing selenides, reducing the coefficient of friction down to below 0.1 in ambient air, levels typically reached using fully formulated oils. Ab initio molecular dynamics simulations under tribological conditions reveal the atomistic mechanisms that result in shear-induced synthesis of selenide monolayers from nano-powders. The use of Se nano-powder provides thermal stability and prevents outgassing in vacuum environments. Additionally, the high reactivity of the Se nano-powder with the transition metal coating in the conditions prevailing in the contact interface yields highly reproducible results, making it particularly suitable for the replenishment of sliding components with solid lubricants, avoiding the long-lasting problem of TMD-lubricity degradation caused by environmental molecules. The suggested straightforward approach demonstrates an unconventional and smart way to synthesize TMDs in-operando and exploit their friction- and wear reducing impact.

Summary

We haven't generated a summary for this paper yet.

Lightbulb Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.

Don't miss out on important new AI/ML research

See which papers are being discussed right now on X, Reddit, and more:

“Emergent Mind helps me see which AI papers have caught fire online.”

Philip

Philip

Creator, AI Explained on YouTube