Reducing friction and engine vibrations with trace amounts of carbon nanotubes in the lubricating oil

Kałużny, Jarosław; Waligórski, Marek; Szymański, Grzegorz M.; Merkisz, Jerzy; Różański, Jacek; Nowicki, Marek; Karawi, Mohanad Al; Kempa, Krzysztof

doi:10.1016/j.triboint.2020.106484

Cited by 40 publications

(29 citation statements)

References 35 publications

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“…On the one hand, our expertise knowledge and experience allowed us to assess, via analysing certain functional relations, the quality of the material being tested; yet, on the other hand, the compiled results of individual studies turned out to be, simultaneously, completely unpredictable. It is worth noting that applying CNMs in lubrication is an emerging science; thus, a large part of the above-mentioned functional relations has not yet been discovered [ 27 ]. Hence, the idea of building a database using expertise knowledge, which will then be used to train selected MLAs with particular emphasis on artificial neural networks seems to be, undoubtedly, a promising solution.…”

Section: Neural Network For the Nanolubricant Designmentioning

confidence: 99%

“…In our macroscale experiments, we showed that CNTs combined with liquids can considerably decrease friction [ 25 , 26 , 27 , 28 , 29 ]. This takes place either by lubricating the nanofluid films or forming interface molecular layers, both of which yield superlubricity.…”

Section: Introductionmentioning

confidence: 99%

“…We believe that, despite purely mechanical actions such as surface coverage (graphene), CNTs may also produce the following effects: (i) transfer of energy revealed in single-asperity contacts, in particular tribo-electrons and heat; (ii) tribochemical impact, for example interactions with common oil additives such as anti-wear additives, which lead to the activation of zinc dithiophosphate (ZDDP) [ 28 , 29 ]; (iii) preventing lubricant molecules from being arranged in symmetrical superstructures, thus reducing stick–slip vibrations according to the theory of shear-induced vibrations [ 27 ]; and (iv) in situ modifications of CNMs in the friction process, for example CNTs due to mechanical stress—and hence, graphene production. It is worth noting all of the abovementioned effects, and we strongly believe that there are other specific carbon-based nanolubricant effects not yet found, which can occur simultaneously, even if only trace amounts of CNMs have been introduced into the lubricant [ 27 ]. It is therefore clear that while studying the details of the tribological roles of nanoparticles is extremely important, we must simultaneously accept that quantitative calculations of friction for machine parts will not be possible in a predictable time.…”

Section: Introductionmentioning

confidence: 99%

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Machine Learning Approach for Application-Tailored Nanolubricants’ Design

et al. 2022

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The fascinating tribological phenomenon of carbon nanotubes (CNTs) observed at the nanoscale was confirmed in our numerous macroscale experiments. We designed and employed CNT-containing nanolubricants strictly for polymer lubrication. In this paper, we present the experiment characterising how the CNT structure determines its lubricity on various types of polymers. There is a complex correlation between the microscopic and spectral properties of CNTs and the tribological parameters of the resulting lubricants. This confirms indirectly that the nature of the tribological mechanisms driven by the variety of CNT–polymer interactions might be far more complex than ever described before. We propose plasmonic interactions as an extension for existing models describing the tribological roles of nanomaterials. In the absence of quantitative microscopic calculations of tribological parameters, phenomenological strategies must be employed. One of the most powerful emerging numerical methods is machine learning (ML). Here, we propose to use this technique, in combination with molecular and supramolecular recognition, to understand the morphology and macro-assembly processing strategies for the targeted design of superlubricants.

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Section: Neural Network For the Nanolubricant Designmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Machine Learning Approach for Application-Tailored Nanolubricants’ Design

et al. 2022

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“…Plenty of nanomaterials have been used for this objective. This includes carbon and its derivatives (Gr [26], MWCNT [27], ND [28,29]), oxides of inorganic compounds (ZnO [30,31], CuO [32] MgO [33], TiO 2 [34]), and transition metal dichalcogenide (MoS 2 [35]).…”

Section: Basic Conceptsmentioning

confidence: 99%

Recent Advances in Preparation and Testing Methods of Engine-Based Nanolubricants: A State-of-the-Art Review

et al. 2021

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Reducing power losses in engines is considered a key parameter of their efficiency improvement. Nanotechnology, as an interface technology, is considered one of the most promising strategies for this purpose. As a consumable liquid, researchers have studied nanolubricants through the last decade as potential engine oil. Nanolubricants were shown to cause a considerable reduction in the engine frictional and thermal losses, and fuel consumption as well. Despite that, numerous drawbacks regarding the quality of the processed nanolubricants were discerned. This includes the dispersion stability of these fluids and the lack of actual engine experiments. It has been shown that the selection criteria of nanoparticles to be used as lubricant additives for internal combustion engines is considered a complex process. Many factors have to be considered to investigate and follow up with their characteristics. The selection methodology includes tribological and rheological behaviours, thermal stability, dispersion stability, as well as engine performance. Through the last decade, studies on nanolubricants related to internal combustion engines focused only on one to three of these factors, with little concern towards the other factors that would have a considerable effect on their final behaviour. In this review study, recent works concerning nanolubricants are discussed and summarized. A complete image of the designing parameters for this approach is presented, to afford an effective product as engine lubricant.

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“…In their study of the effect of CNTs on engine friction, Kałużny et al determined that the use of a low concentration of CNTs (0.03%) significantly reduces engine friction by 6%. Vibration reduction of up to 30% was also achieved using 0.03% CNTs [17]. Another work conducted by Rawat et al explored the effect of the addition of CuO and ZnO nanoparticles on the tribological performance of paraffin-oil-based lithium grease.…”

Section: Introductionmentioning

confidence: 99%

Manufacturable Novel Nanogrease with Superb Physical Properties

et al. 2021

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High-performance nanogrease manufactured from carbon nanomaterials is observed to be stable and homogeneous and have superb physical properties, such as thermal and electrical conductivities, compared with current commercial greases made of lithium, calcium, and aluminum. For the first time, carbon nanomaterials have been observed to disperse well as the sole thickeners in oil systems, e.g., polyalphaolefin and polyester (ROYCO), without the aid of any chemical surfactants. Three-dimensional percolation network structures that exist among carbon nanomaterials are easily scalable, which can be attributed to the intermolecular van der Waals forces. Moreover, the introduction of hydrogen bonding in any form to grease significantly increases its thermal and electrical conductivities and substantially reduces the weight percentage of carbon nanomaterials needed to fabricate stable grease. For example, loading of only 1.4 wt% hydroxyl-functionalized multiwalled carbon nanotube (MWNT-OH) with Krytox XHT750 oil leads to a 37.8% increase in thermal conductivity. Moreover, 75% glycerol, 25% water, and 4.5 wt% MWNT-OH yielded the lowest electrical resistivity of 10.0 Ω cm. This finding can be extended to hydrogen bonding materials with functional groups, such as OH, COOH, F, and NH. The nanogrease reported in this study has been manufactured using the three-roll mill method, which is an easy and cost-effective method, as the loading weight percentage of carbon nanomaterials to fabricate stable grease decreases from 12 wt% to 3-4 wt%. Furthermore, the process is easily scalable, reproduced, and optimized. This novel high-performance nanogrease has a high commercial value and numerous applications and could replace current commercial greases.

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Reducing friction and engine vibrations with trace amounts of carbon nanotubes in the lubricating oil

Cited by 40 publications

References 35 publications

Machine Learning Approach for Application-Tailored Nanolubricants’ Design

Machine Learning Approach for Application-Tailored Nanolubricants’ Design

Recent Advances in Preparation and Testing Methods of Engine-Based Nanolubricants: A State-of-the-Art Review

Manufacturable Novel Nanogrease with Superb Physical Properties

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