Tribology Letters最新文献

Polymers are inherently scratch-sensitive due to their ease of deformation and damage. Polycarbonate (PC) offers excellent optical clarity and mechanical resilience, yet has limited engineering usage due to its vulnerability to surface scratching. Utilizing patterned surfaces while maintaining transparency is a viable strategy to achieve improved scratch resistance of PC. In this study, effect of micro-imprinted surface patterns, specifically, 10 µm holes and pillars, on the frictional and scratch behavior of PC was investigated using a combined experimental and finite element methods (FEM) approach. Standardized scratch tests (ASTM D7027-20/ISO 19252:08) and high-resolution confocal microscopy were chosen to assess damage resistance, while the dynamic stress distribution and contact area evolution during scratching were captured via FEM. Results demonstrate that hole-patterned surfaces exhibit superior scratch resistance compared to pillar-patterned and flat surfaces. This improvement is attributed to the reduction in contact area, lower coefficient of friction, and a possible “air cushion” effect generated by the trapped air within the holes, which provides additional resistance. Although pillar structures initially reduce the friction coefficient, they are prone to early mechanical failure due to stress concentration. This study presents a predictive mechanistic framework that extends the existing literature by incorporating fluid–structure interaction effects, offering a promising avenue for designing scratch-resistant polymers.

Surface damage due to electric potential is one of the primary reliability concerns for electric vehicle drive units. This paper for the first time identifies specific lubricant components which promote such damage. The work can help design new e-Fluids that improve EV reliability. Recent experimental studies have shown substantial effects of electric potential across a lubricated contact on contact friction and surface damage; these studies primarily used either pure base oil or fully formulated commercial lubricants. However, the specific behavior of key additive components, such as friction modifiers (FMs), under electric fields remains poorly understood. In this study, a series of model fluids consisting of base oil and single FMs of different types was systematically designed to isolate the effects of individual additives. Friction and wear properties under DC electric field (2 V and <50 mA) and mixed lubrication conditions were comparatively evaluated using a ball on disc tribometer, suitably modified to apply electric potential across the contact. While base oil alone and base oil +MoDTC solution exhibited only mild surface damage, all six solutions tested containing organic friction modifiers (OFMs) showed pronounced groove wear on the cathodic side. Among these, OFMs with amino group (–NH₂), such as oleylamine (OAm), led to the highest friction and wear increase under electrified conditions. A fully formulated e-Fluid containing OAm as a FM exhibited a similar surface damage pattern, despite the presence of other additives in the formulation. Interestingly, this characteristic response was substantially mitigated when the amino group (–NH₂) was replaced with a dimethyl-amino group, –N(CH₃)₂, suggesting that the chemical reactivity and/or steric hindrance of the OFM polar head play a crucial role in the observed phenomena. Based on experimental findings, the underlying wear mechanism is postulated to be electrochemical polishing, a type of corrosive-abrasive wear. It is speculated that OFMs electrochemically react on cathodic metal(oxide) surfaces in the presence of oxygen, promoted by an applied electric field, to form a thin and soft layer that is easily abraded by the oxidized anode surface. This study provides valuable insights into designing electrically robust e-Fluids with desirable tribological properties to improve reliability and efficiency of modern EV drivetrains.

Graphical Abstract

Predicting the friction behavior of diamond-like carbon (DLC) coatings remains a key challenge in tribology due to the complex interplay of test conditions, material properties, and experimental variability. Although literature data are abundant, they are often non-standardized and are reported under highly variable conditions, which hinders their systematic reuse for predictive modeling. This study introduces a machine learning (ML) framework that exploits heterogeneous data with a focus on physical relevance and robustness. A dataset of approximately 4100 points (including 410 friction coefficient points) was compiled from an extensive literature review. Two modeling scenarios are defined: the first uses mechanical, structural, and tribological descriptors; the second adds chemical composition features, offering more detail but reducing dataset size. Six machine learning models are evaluated under standardized training conditions to predict friction. Model performance is evaluated using standard metrics. Extra Trees (ET) and Artificial Neural Networks (ANNs) achieve the highest performance. SHAP (SHapley Additive exPlanations) analysis identifies temperature and hertz pressure as dominant predictors, consistent with the tribological observations. Incorporating chemical composition improved prediction accuracy but reduced dataset size, highlighting a key trade-off between data completeness and feature richness. SHAP analysis shows that while temperature and hertz pressure remain key predictors, the importance of humidity increases, reflecting that chemical inputs enhance not only accuracy but also the physical interpretability of the models. The results demonstrate that literature-based data can support robust and physically meaningful friction modeling when feature richness is balanced with careful control of data quality.

The scraping process is a key technique for enhancing lubrication and improving surface flatness in mechanical joint surfaces. However, the microscopic contact mechanism remains poorly understood due to the complexity and randomness of scraping. To overcome the limitations of traditional single-Gaussian rough surface models in mixed lubrication analysis, this study develops a novel bi-Gaussian stratified contact stiffness model. This model achieves a more accurate description of interface contact behavior by accurately characterizing the topography features of the scraped surface. Based on the probability density function (PDF) of bi-Gaussian surfaces, the modified Brake model is used to develop a solid contact stiffness model for the scraped surface. This model is then corrected by treating the lower Gaussian surface as a substrate. Subsequently, the average Reynolds equation is applied to model the liquid contact stiffness and solid–liquid coupling through the oil film thickness. Contact stiffness experiments conducted on scraped surfaces with three accuracy levels verify the proposed model. Finally, parametric studies are performed using the established model to evaluate the effects of both the proportion and roughness of the upper Gaussian surface on the resultant solid and liquid contact stiffness. The results indicate that under a 40 kN load, increasing the proportion of the upper Gaussian surface from 40 to 90% increased the total contact stiffness by approximately 21%, and reducing its roughness from 6 μm to 1 μm increased the total contact stiffness by approximately 52%.

The tribo-magnetization process is significantly affected by thermal demagnetization resulting from frictional heating. However, an effective method for evaluating and controlling this dynamic influence on magnetization during sliding remains lacking. Herein, magnetization process against sliding is investigated at different sliding speeds under three distinct sliding conditions: ambient condition, liquid nitrogen and lubricated condition. Results reveal that the thermal demagnetization effect notably impacts tribo-magnetization at sliding speeds of ≥ 125 mm/s. A novel evaluating method of frictional heating is also proposed based on tribo-magnetization behavior during sliding. The impact of frictional heating on tribo-magnetization has been evaluated by applying the external magnetic field of 3 Oe and 5 Oe. Experimental results suggest that sliding-induced magnetization effect can be easily modified under external magnetic field for the sliding speed ≥ 180 mm/s. These insights provide valuable guidance for controlling magnetization process and assessing the friction heating on the sliding interface, while also enhancing the precise application of tribo-magnetization in wear monitoring.

This study introduces a new type of cantilever-probe system that extends atomic force microscopy to high-load, large-contact-area measurements, supporting friction studies from nano to millimeter scales. By using polymer cantilevers with colloidal microspheres, this customizable probe system (8–25 N/m cantilever stiffness; 0.08–2.5 mm probe radius) allows friction measurements on single-crystal MoS₂ under loads of 0.5–120 μN, contact areas of 0.02–10 μm², and contact pressures from 2 to 150 MPa, bridging nanoscale and microscale observations. Our findings reveal a novel scale effect, where the friction coefficient increases by a factor of 34 with a 30-fold increase in probe radius. This affordable alternative to commercial cantilevers also simplifies calibration and enhances accessibility for tribological studies in nanocomposites, MEMS/NEMS, and biological materials, offering a scalable tool for cross-scale friction research.

Graphical abstract

This paper aims to develop core–shell nanoparticles by combining CuO (core) and reduced graphene oxide (shell) as lubricant additives and understand their action under different slide-to-roll ratios. The SRRs evaluated were 50 and 200%, with nanoparticles concentrations of 0.05 and 0.1wt%. The worn tracks were characterized through WLI, SEM, TEM and Raman Spectroscopy. The results showed that the lubrication mechanism and tribofilm formation are strongly associated with the type of contact. At SRR 200%, nanolubricant reduced friction and wear; it was observed exfoliation of nanoparticles, the CuO acted as rolling, and the rGO sheet was deposited on a worn surface. On the other hand, for SRR 50% doesn´t decrease the friction coefficient; however, a thicker tribofilm was produced with nanoparticles.

Friction and lubrication of components in mechanical transmission systems are crucial to their transmission efficiency. As for the extreme conditions, the performance of traditional liquid lubricants would be degraded, which causes significant harm to the safe and reliable operation of equipment. Therefore, the development of a high-efficiency composite lubricant is particularly important. In this study, MXene@Triethanolamine borate nanocomposite were prepared via the ultrasonic intercalation method. Furthermore, the composites were characterized by scanning electron microscopy, X-ray diffraction, and Fourier transform infrared spectroscopy. The tribological properties of intercalated MXene@TB in the BMIMPF6 ionic liquid were evaluated under current using a ball-on-disk tribometer. The average friction coefficient of lubricant with 0.3% intercalated MXene@TB-1 was reduced by 9.8%, and its wear volume was also decreased by 36.1%. Additionally, the application of current can enhance the tribological performance of lubricant. Specifically, the wear volume of int-MXene@TB-2 was decreased by 52% due to the current-induced ion migration and lubricating film repair. Moreover, the application of current promotes the movement of nanoparticles within the ionic liquid, minimizing aggregation and further enhancing the formation of the lubrication film. The lubricant nanocomposite with high-efficiency friction reduction and anti-wear properties can be further applied in current-carrying friction field.

Graphical abstract

Benzothiazole is widely used in biomedical applications in recent studies, in this study we coordinated it with organic molybdenum to prepare three phosphorus-free benzothiazole-organic molybdenum friction modifiers with different structures and evaluated the lubrication performance in base oil PAO6. The results showed that the three additives exhibited different friction reduction and anti-wear effects due to their different molecular structures, with benzothiazole-molybdenum oleate amide (YSMo) showing the most significant lubrication performance. At 1.00 wt%, YSMo reduced the average coefficient of friction by 30.8% and the wear volume by 95.86%. The combination of sulfur-containing nitrogen heterocyclic compounds with molybdenum source significantly enhanced the lubrication performance and effectively reduced friction and wear through physical adsorption and the formation of a dense composite chemical friction protective film (containing components such as FeS, MoO₃, and MoS₂), which further confirmed that friction-generated MoS₂ has a positive effect on the tribological performance. The lubrication performance of YSMo was superior to that of the other two additives, which depended on the polar groups and chain lengths, which provides an important theoretical basis for further optimizing the design of lubricating additives.