Friction最新文献

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.

Overcoats are predominantly employed to tackle tribological challenges in numerous moving mechanical systems. However, when overcoats are thinned down to sub-10 nm levels, their performance gets significantly compromised because of the dominance of surface and interface effects. Here, we discovered the efficacy of the chemistry of sub-10 nm thick carbon-based overcoats in regulating the friction and wear of rough ceramic surfaces, particularly those of Al₂O₃+TiC (AlTiC). Carbon overcoats up to 4 nm in thickness grown with low-energy (~4–5 eV) atoms/ions caused no significant changes in the tribological performance of AlTiC. However, carbon overcoats grown at a moderate energy of 90 eV experienced an exceptional reduction in friction and wear of AlTiC at similar thickness levels up to 4 nm. The addition of a 6 nm thick RF-sputtered carbon layer on top of these carbon overcoats caused no significant improvement in the tribological performance. However, the addition of a multilayer graphene overlayer was found to slightly reduce the friction further for the thicker carbon overcoats grown at 90 eV. Chemical bonding and carbon microstructural analyses, along with ion interaction simulations, were performed to elucidate the fundamental mechanisms behind the observed friction and wear performances. We discovered that the atomic mixing and high sp³ bonding caused by the 90 eV growth process primarily dictated the friction and wear control at ≤ 10 nm overcoat thicknesses. Thus, by adopting suitable carbon overcoat technology, excellent tribological properties can be attained even at sub-5 nm overcoat thickness levels, which is critical for numerous applications.

Assessing wear is an indispensable task across almost all engineering disciplines, and automated wear assessment would be highly desirable. To determine the occurrence of wear, machine learning strategies have already been successfully applied. However, classifying different types of wear remains challenging. Additionally, data scarcity is a major bottle neck that limits the applicability of machine learning models in certain areas such as biomedical engineering. Here, we present a method to accurately classify surface topographies representing the three most common types of mechanically induced wear: abrasive, erosive, and adhesive wear. First, a random forest (RF) classifier is trained on a list of parameters determined from 3-dimensional (3D) surface scans. Then, this method is adapted to a small dataset obtained from damaged cartilage tissue by using knowledge transfer principles. In detail, two random forest models are trained separately: a base model on a large training dataset obtained on synthetic samples, and a complementary model on the scarce cartilage data. After the separate training phases, the decision trees of both models are combined for inference on the scarce cartilage data. This model architecture provides a highly adaptable framework for assessing wear on biological samples and requires only a handful of training data. A similar approach might also be useful in many other areas of materials science where training data are difficult to obtain.

The microscopic topography of friction surfaces and system structural parameters are both critical factors influencing the characteristics of friction-induced vibration (FIV). However, no existing analytical model for FIV has incorporated these factors. To address this issue, we developed a novel coupled model to explore the combined effects of surface microscopic topography and structural parameters on the FIV characteristics. Furthermore, we conducted two friction-induced vibration and noise (FIVN) simulation experiments to validate the conclusions derived from the numerical simulations. The results showed a strong correlation between the microscopic surface morphological parameters and the friction surface's contact properties. A higher fractal dimension increases contact stiffness, whereas a larger fractal scale factor reduces contact stiffness. The contact damping initially increases and then decreases with changes in the fractal dimension. The surface microscopic parameters significantly affect the modal coupling characteristics and FIV. In a certain range of fractal dimension, modal coupling takes place in the friction system, and with an increase in the fractal scale factor, the region of system instability also grows. FIVN simulation experiments showed that smoother friction surfaces tend to result in high-intensity FIVN. Regarding the structural parameters, when the contact interface has a large fractal dimension and scale factor, structural changes do not significantly affect the system's modal coupling. However, when these parameters decrease, structural parameters exert a more substantial influence on modal coupling. In particular, when both the fractal dimension and scale factor are small, a reduced block thickness does not affect system stability, and FIV also minimal. As the thickness increases, modal coupling and unstable vibrations emerge in the system. Thus, for new brake pads with large block thicknesses, such as those used in high-speed trains, increasing the fractal dimension and scale factor of the friction surface is recommended to reduce high-intensity FIVN in the saturation stage.

Self-dispersed graphene crumpled ball (GCB) demonstrates exceptional tribological performance as lubricant additive under elevated temperature. However, the critical relationship between its unique wrinkle architecture, internal porosity characteristic, and the resultant dispersion stability/friction-reduction mechanism remains insufficiently explored. Particularly, the synergistic effects arising from structural hierarchy and surface chemistry modulation in high-temperature lubrication systems require systematic investigation. Herein, we propose a wrinkle engineering strategy guided by Stokes' law to fabricate surface modifier-free GCB with programmable three-dimensional geometries. Systematic investigations reveal that the degree of wrinkling on the GCB critically dominates the dispersion characteristics and the interlayer shearing resistance. Upon the molybdenum disulfide quantum dots deposited on GCB, a more consistent and robust tribo-chemical reaction film can be formed on the friction interface and in response to protect from severe damage. This complex achieves over 2-fold enhancement in antifriction efficiency compared with commercial high-temperature chain oil (CH-27Q). Overall, this study establishes a structure-performance paradigm for developing autonomous lubrication systems under extreme thermal conditions.

The role of additives in liquid superlubricity is regarded as a crucial element of the running-in process due to their role in reducing friction. Nevertheless, there has been minor investigation into rheological changes that occur during the process. This paper presents an examination of the evolution of film thickness over time and its subsequent behavior. The primary experiments were performed on an optical ball-on-disk tribometer, with the ability to control the percentage of slip. The film thickness was evaluated by optical interferometry and its rheological behavior was subsequently researched by rotational rheometer and viscometer. It was discovered that the primary contribution to the reduction in friction during running-in is better contact separation caused by the evaporation of water. However, the global behavior of the solution was found to have been changed by formation of a convoluted compound and probably by adsorption to contact surfaces. It causes a behavior that is more complex than that predicted by common elastohydrodynamic equations, but may result in a reduction of friction due to an increased separating layer.

Graphene and fullerene nanoparticles exhibit remarkable tribological performance in solid-liquid composite lubrication systems. However, the atomic-scale understanding of how surface topography influences their tribological behavior and performance is still limited. Herein, the influence mechanisms of surface topography features (achieved by regulating asperity amplitude and frequency parameters) on system lubrication performance and nanoparticle friction behavior were systematically investigated through friction experiments and molecular simulations. The results indicate that, at the micro-nanoscale, the amplitude parameter predominantly governs the surface roughness features and frictional resistance. This is because an increased amplitude strengthens the boundary lubrication effect, exacerbates stress concentration and structural deformation of graphene, and makes fullerene more likely to fill grooves and difficult to bear normal loads, thereby exacerbating friction and wear (friction coefficient increased by 59%). In contrast, the frequency parameter primarily determines the surface kurtosis features and normal force. At low frequency, low kurtosis features intensify the normal squeezing effect of asperities, inducing the hydrodynamic pressure effect of the base oil, thus enhancing lubrication performance (friction coefficient decreased by 22%). Compared with frequency, the pronounced influence of amplitude on lubrication state and interface contact behavior dominates the tribological properties of the system and the lubrication mechanism of the nanoparticles. Lower surface roughness and kurtosis features are critical for achieving efficient lubrication. This study offers valuable insights into the design of surface topography and the optimization of lubrication performance.