journal article·2021-07

Applications of carbon quantum dots in lubricant additives: a review

Weiwei Tang, Zhe Zhang, Yufeng Li

Journal of Materials Science· Volume 56· Issue 21
Publisher page

Abstract

Advances in lubricants are vital to the pursuit of energy efficiency and sustainable development. It is well known that the essence of lubricating oil is lubricant additives, especially the friction-reducing and anti-wear additives. Carbon quantum dots (CQDs), a novel zero-dimensional carbon-based nanomaterial, have attained growing expectations in material and chemical sciences because of their extraordinary properties such as low toxicity and environmentally friendly, high chemical and thermal stability, and good designability. Since their discovery, CQDs have shown great potential in many applications including sensors, medicine, photovoltaic devices, biology, and tribology. The latest application of CQDs as the high-performance friction-reducing and anti-wear additives has garnered increasing attention. With the in-depth study, CQDs have gradually exhibited their excellent tribological properties, especially acted as additives in lubricating base oils. This paper has reviewed the progress in the research and development of CQDs-based lubricant additives by introducing lots of successful applications of CQDs-based additives in the present work and then highlighted the friction-reducing and anti-wear property, superiority, as well as the lubrication mechanism of CQDs as an additive, along with some discussion on challenges and perspectives in this significant and promising field. Finally, we offered a series of suggestions for developing the next-generation high-performance CQDs-based lubricant additives. This work presented the carbon quantum dots as the lubricant additives of lubricating base oils.
Source: openaire · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Carbon and Quantum Dots Applications · Lubricants and Their Additives · Electrochemical sensors and biosensors

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

References (100+)

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