Friction最新文献

Lubricants are essential in machining as they significantly affect workpiece surface quality. However, due to the diversity of lubricant types and the complexity of infiltration physics, there remains an urgent need to improve infiltration performance based on the underlying physical processes. This paper systematically reviews the infiltration mechanisms of lubricants under different machining conditions. First, the influence of lubricant morphological characteristics and physicochemical properties on infiltration behavior is analyzed at the microscale, clarifying the mechanisms governing different states, including liquid, gas, and multiphase flow. Second, the interaction between tool geometric boundary conditions and lubricant infiltration behavior is examined, providing an evaluation of infiltration performance at the workpiece surface. Finally, the microscopic mechanisms of lubricant behavior under the influence of typical energy fields are discussed, and the regulation effect of these fields on lubricant infiltration is revealed. This review offers a theoretical reference for advancing the understanding of lubricant infiltration mechanisms and improving infiltration performance in machining.

In this study, lauric acid was introduced in the growth of thickener of calcium sulfonate grease, and the low temperature fluidity and drop point of the grease were greatly improved by regulating the morphology of the thickener and the oil fixing ability of the surface. The aspect ratio of thickener was increased from 1 to 5, and the specific surface area was increased by 40.12%. At the same consistency, the low temperature similar viscosity decreased by 11.63%, and the drop point increased by nearly 100 ℃. By comparing the effects of lauric acid, amine and alcohol with different polar end groups on the surface adsorbability and wettability of the thickener, it was found that the adsorption quality of the three molecules was similar, but only lauric acid and amine could significantly improve the lipophilicity of the surface of the thickener and increase the drop point of the grease by nearly 100 ℃. Through molecular dynamics simulation, it is found that the alkyl chain of linear acid and amine molecules adsorbed on the surface of the thickener is almost perpendicular to the surface of the thickener, which makes the interface base oil difficult to slip, increases the adsorbed oil content and the effective radius of the thickener, and effectively increases the drop point of the grease. The long alkyl chain of the linear chain alcohol molecules is almost parallel to the surface of the thickener, which has little effect on the physicochemical properties of the grease.

The present research investigates the effects of re-entrant auxetic structure’s on friction-induced vibrational behaviour of 3D printed Polylactic acid (PLA) samples. A series of re-entrant auxetic specimens with different re-entrant angles were prepared for sliding wear tests. The results showed that with the increase in re-entrant angles, the negative Poisson ratio becomes greater. Accordingly, the specimen showed less vibration during the sliding wear process, with a lower average friction coefficient. As a result, the wear resistance of the specimens with embedded re-entrant structures was clearly improved. Microscopic images revealed that surface fatigue wear was effectively prevented with the re-entrant structures, thanks to their energy absorption and vibration insulation capacities. The findings demonstrated that 3D printing technology could provide a new route for the design and fabrication of high wear resistant engineering components by creating complex functional structures to control and optimize their dynamic behaviour and, thus tribological performance.

Physics-informed neural network (PINN) provides a novel method for understanding the mechanical behavior of tribology contacts, and the deformation of the contacting body plays a pivotal role in determining the contact scenario of dry and elastohydrodynamic lubricated (EHL) contacts. Here, we delineate the design and construction of the PINN for obtaining elastic deformations under Hertzian pressure. The PINN obtains the elastic deformation by transforming the linear elasticity equation into an optimized neural network, which presents a new method for obtaining elastic deformation in tribological contacts. Our results are consistent with the results from finite element method. Hence, we envision that our method has great application potential in dry and EHL contacts in the prediction of elastic deformation.

Tread modification has gained significant attention in recent years as a means to address the issue of wheel hollow wear. The wear resulting from tread modification can alter the wheel profile, thereby impacting the wheel–rail contact relationship and vehicle dynamics performance. Consequently, it is crucial to understand the influence of tread modification on wheel wear. This study proposes a prediction method for the wheel profile’s comprehensive wear (WPCW) for high-speed trains, considering the impacts of both the wheel–rail interaction and the tread modification on the wheel profile comprehensive wear. First, simulation models are established to quantify wheel wear resulting from wheel–rail interactions and tread modification. Subsequently, the coupling relationship between the two models is subsequently strengthened by incorporating iterative calculation processes, resulting in the prediction model of the wheel profile comprehensive wear. Finally, the prediction method is calibrated and verified through measured data. The simulation results obtained using this method align with the measured results, confirming the feasibility of the proposed prediction method and its applicability in predicting the WPCW for high-speed trains.

Graphene-family materials show significant potential as electro-regulated lubrication additives due to their tunable properties under electrical stimuli. However, a comprehensive comparison of their performance in such conditions remains lacking, limiting their broader industrial adoption. This study explores the electro-regulated friction behavior of graphene (GN), graphene oxide (GO), and fluorinated graphene (FG) nanosheets as grease additives. Results indicate that GN additives demonstrated good antifriction and antiwear performance under constant negative electrical stimulation compared to GO and FG additives. It also demonstrates good stability and repeatability in friction regulation under varying electrical conditions, which is attributed to its deposition on contact surfaces, enhancing lubrication. Furthermore, the direction of electrical stimulation affects GN’s oxidation (or defect) level, with reduced oxidation levels (fewer defects) correlating to lower friction. These findings deepen the understanding of graphene-family materials and provide a basis for designing advanced nanoadditives with enhanced electro-regulated performance.

The advancement of aerospace and polar technologies has heightened the demand for lubricants capable of delivering stable performance under extreme temperature conditions while minimising friction and wear. However, existing lubrication systems remain inadequate for reliable operation within a broad thermal range of –50 to 350°C. In this study, we propose a wide-temperature lubricant formulation comprising chlorophenyl silicone oil (CPSO) as the base fluid, polydiethylsiloxane (PDES) as a compatibiliser, and pentaerythritol ester (PET) to enhance high-temperature anti-wear performance. At low temperatures (–50 to 25°C), the lubricant primarily functions via hydrodynamic mechanisms, maintaining fluid lubrication, although friction tends to increase with decreasing temperature. Above 200°C, a friction-induced nano-tribofilm, composed of metallic compounds and amorphous silicon oxides, forms on the surface, markedly enhancing anti-wear and friction-reducing properties. At 300°C, the hybrid lubricant reduces the wear rate of M50 steel by 86% and 61% compared with CPSO and PDES alone, respectively. Overall, this lubricant demonstrates outstanding tribological stability across a wide temperature range, offering crucial insights and support for developing advanced lubrication technologies suited for extreme environments.

Gallium-based liquid metal (GLM) is an amorphous metal that remains liquid at room temperature. It has important characteristics, such as high temperature resistance, high thermal conductivity, good electrical conductivity, favorable radiation resistance, and low saturated vapor pressure, and is thus an ideal lubricant in nuclear equipment, aerospace industry, and other engineering fields under extreme operating conditions. First, the physicochemical properties and the factors affecting the lubricity of GLM are reviewed in this paper. Furthermore, the lubrication mechanisms of GLM are elucidated in detail. Then the research progress in strategies to improve the lubricity of GLMs is summarized. After that, the applications of GLM in engineering tribology are also reviewed. Finally, the future developments of GLM as a special lubricant for extreme conditions are proposed.

This paper presents a novel friction control method that introduces internal stiffness inhomogeneity into soft material surfaces that slide on rough surfaces. This approach involves embedding hard particles within a soft material to control friction. When these particles encounter asperities on a rough surface during sliding, they trigger a local stick-slip-like motion that leads to energy dissipation and increased macroscopic friction. The validity of the concept was demonstrated through experiments using a simplified setup with triangular periodic one-dimensional roughness. This method is expected to be useful for designing various soft material sliding surfaces.

Understanding contact-induced damage is of paramount importance in the analysis of the lifespan and performance of surface coatings. In this work, we investigate the effects of dopants and interlayers on the structural durability of diamond-like carbon coatings (DLCs) and molybdenum disulfide (MoS₂) coatings on stainless steel via micro-scratch tests. The analysis of XPS survey spectra and Raman spectra of DLCs shows that the ratio of sp²/sp³ (i.e., the intensity ratio of sp² over sp³ obtained by XPS) is proportional to I_D/I_G, where I_D and I_G are the intensities of D and G bands of the Raman spectra. The analysis of the scratch tests reveals that there are three critical loads for the scratch-induced damage of the DLCs and MoS₂ coatings, corresponding, respectively, to the initiation of periodic V-cracking, the minimum load for periodic semicircle cracking or peel-off, and the minimum load for partial and periodic delamination. Dopants can reduce the friction coefficient of the DLCs and have negligible effect on the Ti/MoS₂ coatings. The Cr interlayer can better enhance the bonding strength between the DLCs and the steel substrate than the Si interlayer. Doping Cr and H can reduce the hardness of DLCs; doping Si can increase the hardness of the DLCs; and doping Ti, Pb, and PbTi can reduce the hardness of the MoS₂ coatings. Deep Symbolic Optimization (DSO) algorithm is used to establish nominal-mathematical formulations between the critical variables for the scratch test and the materials parameters of the surface coating. The DSO analysis demonstrates the feasibility of using “deep-learning” to establish “quantitative” relationships between the critical variables for mechanical deformation and materials parameters.