Friction最新文献

The separation of oil-in-water emulsion is an urgent challenge because its massive production and discharge from daily and industrial activities have caused severe hazards to the ecosystem and serious threats to human health. Membrane technology is considered an outstanding solution strategy for the separation of oil-in-water emulsions due to its unique advantages of low cost, high efficiency, easy operation, and environmental friendliness. However, the membrane is easily fouled by the emulsion oil droplets during the separation process, causing a sharp decline in permeation flux, which greatly inhibits the long-term use of the membrane and largely shortens the membrane’s life. Recently, it was found that endowing the membranes with special wettability e.g., superhydrophilic and superoleophobic can greatly enhance the permeability of the continuous water phase and inhibit the adhesion of oil droplets, thus promoting the separation performance and anti-oil-fouling property of membrane for oily emulsions. In this paper, we review and discuss the recent developments in membranes with special wettability for separating oil-in-water emulsions, including the mechanism analysis of emulsion separation membrane, membrane fouling issues, design strategies, and representative studies for enhancing the membrane’s anti-oil-fouling ability and emulsion separation performance.

Humans rely on their fingers to sense and interact with external environment. Understanding the tribological behavior between finger skin and object surface is crucial for various fields, including tactile perception, product appearance design, and electronic skin research. Quantitatively describing finger frictional behavior is always challenging, given the complex structure of the finger. In this study, the texture and sliding direction dependence of finger skin friction was quantified based on explicit mathematic models. The proposed double-layer model of finger skin effectively described the nonlinear elastic response of skin and predicted the scaling-law of effective elastic modulus with contact radius. Additionally, the skin friction model on textured surface considering adhesion and deformation factors was established. It revealed that adhesive term dominated finger friction behavior in daily life, and suggested that object texture size mainly influenced friction-induced vibrations rather than the average friction force. Combined with digital image correlation (DIC) technique, the effect of sliding direction on finger friction was analyzed. It was found that the anisotropy in finger friction was governed by the finger’s ratchet pawl structure, which also contributes to enhanced stick-slip vibrations in the distal sliding direction. The proposed friction models can offer valuable insights into the underlying mechanism of skin friction under various operating conditions, and can provide quantitative guidance for effectively encoding friction into haptics.

The tribological properties of self-lubricating composites are influenced by many variables and complex mechanisms. Data-driven methods, including machine learning (ML) algorithms, can yield a better comprehensive understanding of complex problems under the influence of multiple parameters, typically for how tribological performances and material properties correlate. Correlation of friction coefficients and wear rates of copper/aluminum-graphite (Cu/Al-graphite) self-lubricating composites with their inherent material properties (composition, lubricant content, particle size, processing process, and interfacial bonding strength) and the variables related to the testing method (normal load, sliding speed, and sliding distance) were analyzed using traditional approaches, followed by modeling and prediction of tribological properties through five different ML algorithms, namely support vector machine (SVM), K-Nearest neighbor (KNN), random forest (RF), eXtreme gradient boosting (XGBoost), and least-squares boosting (LSBoost), based on the tribology experimental data. Results demonstrated that ML models could satisfactorily predict friction coefficient and wear rate from the material properties and testing method variables data. Herein, the LSBoost model based on the integrated learning algorithm presented the best prediction performance for friction coefficients and wear rates, with R² of 0.9219 and 0.9243, respectively. Feature importance analysis also revealed that the content of graphite and the hardness of the matrix have the greatest influence on the friction coefficients, and the normal load, the content of graphite, and the hardness of the matrix influence the wear rates the most.

Plastoelastohydrodynamic lubrication of rough surfaces (R-PEHL) is a cutting-edge area of research in interface fluid-structure coupling analysis. The existing R-PEHL model calculates the elastic-plastic deformation of rough surface by the Love equation in a semi-infinite space smooth surface, which deviates from the actual surface. Therefore, it is an innovative work to study the exact solution of elastic-plastic deformation of rough surface and its influence on the solution results of R-PEHL model. In this paper, a new contact calculation model of plastoelastohydrodynamic lubrication (PEHL) with three-dimensional (3D) rough surface is proposed by integrating numerical method of EHL and finite element method. The new model eliminates an original error introduced by the assumption of semi-infinite space in contact calculation, providing wide applicability and high accuracy. Under the given rough surfaces and working conditions, the study reveals that: (1) the oil film pressure calculated by the new model is lower than that of the smooth surface in semi-infinite space by 200–800 MPa; (2) the Mises stress of the new model is 2.5%–26.6% higher than that of the smooth surface in semi-infinite space; (3) compared with the semi-infinite space assumption, the rough surface plastic deformation of the new model is increased by 71%–173%, and the local plastic deformation singularity may appear under the semi-infinite space assumption; (4) the plastic deformation caused by the first contact cycle on the rough surface of the new model accounts for 66.7%–92.9% of the total plastic deformation, and the plastic deformation of the semi-infinite space accounts for 50%–83.3%. This study resolves the contradiction between the smooth surface assumption and the rough surface in the existing R-PEHL model, establishing a solid logic foundation for the accurate solution of R-PEHL model.

The contact of a rigid body with nominally flat rough surface and an elastic half-space is considered. To solve the contact problem, the Greenwood-Williamson statistical model and the localization principle are used. The developed contact model allows us to investigate the surface approach and the real contact area with taking into account the asperities interaction. It is shown that the mutual influence of asperities changes not only contact characteristics at the macroscale, but also the contact pressure distribution at the microscale. As follows from the results, the inclusion in the contact model of the effect of the mutual influence of asperities is especially significant for studying the real contact area, as well as the contact characteristics at high applied loads. The results calculated according to the proposed approach are in a good agreement with the experimentally observed effects, i.e., the real contact area saturation and the additional compliance exhaustion.

The formation of tribolayers may play significant influences on fretting wear. At elevated temperature, the adhesion among wear debris and the increased diffusion rate facilitate the formation of tribolayers. However, the intensification of oxidation at elevated temperature and the low diffusion rate in oxides may play an adverse role. The present study aims to investigate the role of temperature in tribolayers in fretting wear using a γ-TiAl alloy. Scanning electron microscope, energy dispersive spectrometer, Raman spectrometer, transmission electron microscope and nanoindentation were utilized to investigate the wear debris, tribolayers, and wear scars. The fretting tests showed that, compared with that at room temperature (RT) and 350 °C, significant reduction in wear rate and decrease in the fluctuation of friction coefficient occurred at 550 and 750 °C. It was further revealed that when temperature raised from room temperature (RT) to 750 °C, the oxidation of the wear debris increased slightly and the diffusion coefficients increased prominently, which facilities the formation of well tribo-sintered tribolayers. The well tribo-sintered tribolayers presented homogenous structure, nanocrystalline grains with excellent mechanical properties, and resulted in the improvement in the fretting wear resistance of the γ-TiAl alloy at 550 and 750 °C.

The boundary lubrication mechanism at the articulating surface of natural synovial joints has been the subject of much discussion in tribology. In this study, to elucidate the lubricating function of the superficial area of articular cartilage and synovial fluid (SF), cartilage specimens were processed with four different treatments: gentle and severe washing with detergent, incubation in NaCl solution, and trypsin digestion to selectively remove certain constituents from the cartilage surface. Subsequently, the frictional characteristics were examined in phosphate-buffered saline (PBS) and SF against glass. Angularly reciprocating sliding tests with a spherical glass probe and square articular cartilage specimens were performed at low contact loads in the mN range to extract the frictional behavior in the superficial area of the cartilage specimens. Meanwhile, the cartilage surface was observed to confirm the effects of treatments on the morphology of the cartilage surface using a fluorescence microscope and water-immersion methods. The coefficient of friction (COF) of the prepared cartilage specimens was varied from 0.05 to over 0.3 in PBS. However, a certain group of cartilage specimens exhibited a low COF of less than 0.1 with limited variation. For the low COF group of specimens, all four treatments increased the COF in PBS to different extents, and fluorescence microscopy revealed that the integrity of the cartilage surface was deteriorated by treatments. This means that the intact cartilage surface had lubricating constituents to maintain low friction, and the removal of such constituents resulted in the loss of the intrinsic boundary lubricity of the cartilage surface. The variation in the COF of the cartilage specimens was suppressed in SF because it had a clear boundary lubrication effect on the cartilage surface. The lubricating effect of SF could be confirmed even after degenerative treatment.

This experimental study investigates the friction and wear of three coatings commonly used in industrial applications, particularly in hydrodynamic bearings. The three materials under investigation were Babbitt, polyether ether ketone (PEEK) reinforced with 15% carbon fibers, and PEEK reinforced with 20% carbon fibers. The first polymer material was extruded, while the other was produced by fused deposition modelling (FDM). The materials were subjected to sliding tests in a pin-on-disc configuration, with a steel ball serving as the counter surface. The tests were conducted at room temperature, with a load of 10 N and under three different lubrication conditions: dry, grease, and oil. The linear speed was set at 0.3 m/s for the dry and semi-solid lubrication tests, while for the oil tests, the speed was set at 0.25 m/s. The greases used had consistency grades of NGLI 000 and NGLI 2. An ISO VG 68 circulation oil was used for the oil lubrication tests. Additionally, thermodynamic analyses were performed under the most severe conditions (i.e., dry) to investigate the steel-Babbitt and steel-PEEK contact.