Lubricants

20 pages, 3032 KB

Open AccessArticle

Nonlinear Wear Modelling in Lubricated Pin-on-Disc Contacts Using the Archard–Bayer Law with FEM Validation for Sheet Metal Forming

by Tobias B. Humpf, Maximilian A. Oppold, Anjali K. M. DeSilva, Muditha Kulatunga and Wolfgang Rimkus

Lubricants 2026, 14(7), 255; https://doi.org/10.3390/lubricants14070255 (registering DOI) - 29 Jun 2026

Abstract

Accurate prediction of wear in lubricated metal-to-metal contacts remains a critical challenge, as calibration parameters derived from laboratory tests often lack transferability to finite element method (FEM) simulations. While classical linear Archard models are widely applied, they fail to capture the nonlinear load-dependent [...] Read more.

Accurate prediction of wear in lubricated metal-to-metal contacts remains a critical challenge, as calibration parameters derived from laboratory tests often lack transferability to finite element method (FEM) simulations. While classical linear Archard models are widely applied, they fail to capture the nonlinear load-dependent wear behavior observed under varying operating conditions. This study addresses this limitation by developing and validating a nonlinear wear formulation based on the Archard–Bayer law within a coupled experimental–numerical framework. A comprehensive Pin-on-Disc test matrix was conducted under lubricated conditions using carbide–steel contacts across varying loads and cycle counts. Wear progression was quantified and analysed using outlier-corrected weighted regression, yielding a force exponent

m_{e x p} = 1.58 \pm 0.34

and cycle exponent

n_{e x p} = 0.41 \pm 0.17

. The calibrated nonlinear model was implemented in a FEM environment and systematically evaluated across multiple loading scenarios. The nonlinear formulation demonstrates improved predictive capability compared to the classical linear Archard model, particularly under higher load conditions (15 N–20 N), where deviations between simulation and experiment remain below 11%. The FEM-calibrated exponent (m = 1.35) lies within the 95% confidence interval of the experimental value, indicating that numerical adjustments required for stability are statistically non-significant. The results show that nonlinear wear models provide a more accurate representation of load-dependent wear behavior but require constrained calibration ranges for reliable application. The proposed methodology enables robust transfer of experimentally derived wear parameters into FEM simulations and provides a practical basis for tool-life prediction, parameter tuning, and model deployment in sheet metal forming processes. Full article

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30 pages, 2913 KB

Open AccessArticle

A Mechanism-Informed Gaussian Process Surrogate Model for Solid-Particle Erosion Prediction in Gas–Solid Bent Pipe Flows

by Junyan Ma, Jiafu Yang, Wenwen Yang, Yonggang Song, Adilanmu Sitahong, Duoming Pan and Yong Huang

Lubricants 2026, 14(7), 254; https://doi.org/10.3390/lubricants14070254 (registering DOI) - 27 Jun 2026

Abstract

In cold hydrogenation processes, bent pipes are highly susceptible to severe localized erosion under hydrogen–silica powder gas–solid two-phase flow. However, high-fidelity numerical simulations are computationally expensive and thus inadequate for rapid assessment under multiple operating conditions. To overcome this limitation, an MI-UK-GPR-based method [...] Read more.

In cold hydrogenation processes, bent pipes are highly susceptible to severe localized erosion under hydrogen–silica powder gas–solid two-phase flow. However, high-fidelity numerical simulations are computationally expensive and thus inadequate for rapid assessment under multiple operating conditions. To overcome this limitation, an MI-UK-GPR-based method is proposed for predicting the erosion rate of cold hydrogenation bent pipes. Based on a validated CFD model, six input variables, namely pipe inner diameter, curvature ratio, bend angle, particle mass flow rate, particle size, and particle velocity, were selected. Latin hypercube sampling was employed to generate parameter combinations, and the corresponding maximum erosion rates were obtained through high-fidelity CFD simulations to construct an LHS-CFD sample database. The input variables were then normalized, and the maximum erosion rates were log-transformed. On this basis, an MI-UK-GPR model integrating a mechanistic trend term with a Gaussian process residual term was developed to capture both the global trend of erosion peaks and local nonlinear deviations. Model performance was assessed using leave-one-out cross-validation with MAE, RMSE, MAPE, R², and PICP as evaluation metrics. The results show that, under leave-one-out cross-validation, the proposed MI-UK-GPR model achieved an MAE of 7.10 × 10⁻⁵, an RMSE of 1.29 × 10⁻⁴, a MAPE of 14.53%, an R² of 0.9573, and a PICP of 88.33%, outperforming RSM, SVR, and ordinary GPR in terms of overall prediction performance. In addition, for 50 independent operating conditions, the total computational time of parameterized CFD batch simulations was 5083.51 s, whereas the trained MI-UK-GPR model required only 0.004860 s, corresponding to a speedup of approximately 1.05 × 10⁶. Overall, the proposed method provides a physically consistent, uncertainty-aware, and computationally efficient framework for rapid erosion assessment of cold hydrogenation elbows under multiple operating conditions. Full article

18 pages, 4132 KB

Open AccessArticle

Impact of Test Speed and Lubrication Conditions on Dynamic Testing of Total Knee Endoprostheses

by Paul Henke, Daniel Thiele, Leo Ruehrmund, Annett Klinder, Sven Krueger, Philipp Damm, Maeruan Kebbach and Rainer Bader

Lubricants 2026, 14(7), 253; https://doi.org/10.3390/lubricants14070253 (registering DOI) - 27 Jun 2026

Abstract

Preclinical testing is essential for evaluating new implant designs and materials for total knee replacement (TKR). Standardized wear tests, such as ISO 14243, are widely accepted but only partially represent physiological kinematics and kinetics, as they do not account for all six degrees [...] Read more.

Preclinical testing is essential for evaluating new implant designs and materials for total knee replacement (TKR). Standardized wear tests, such as ISO 14243, are widely accepted but only partially represent physiological kinematics and kinetics, as they do not account for all six degrees of freedom of the knee joint. More advanced setups, including robotic systems and joint simulators, enable complex load cases; however, the influence of lubrication conditions and testing speeds remains insufficiently standardized. This study investigated the kinematic and kinetic effects of different lubrication conditions (dry, synthetic synovial fluid, silicone oil) and speeds (static, 10%, 50%, 100% of normal gait) in a joint simulator setup using a posterior cruciate ligament-retaining TKR during level walking. Complementary pin-on-disk measurements revealed significant dependencies on both lubrication and speed. During joint simulator tests, omitting lubrication resulted in more than double the maximum flexion–extension moment, while the range of anterior–posterior femoral translation increased by approximately 73%. At 50% and 100% speed, silicone lubrication yielded results comparable to static tests, in contrast to the dry and synthetic synovial fluid conditions. These findings demonstrate that physiologically relevant lubrication and appropriate test speeds are essential for obtaining reliable results in experimental studies of TKR dynamics. Full article

(This article belongs to the Special Issue Experimental Modelling of Tribosystems)

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17 pages, 7098 KB

Open AccessArticle

Positive Antiwear Interaction Between ZDDP and CNTs, GNPs and FLGs Under Boundary Lubrication

by Juan Pablo Abdelnabe, Walter Roberto Tuckart, Eduardo Tomanik, Wania Christinelli and Germán Prieto

Lubricants 2026, 14(7), 252; https://doi.org/10.3390/lubricants14070252 (registering DOI) - 26 Jun 2026

Abstract

Industrial gear contacts operate under mixed-to-boundary lubrication where reliable antiwear protection is essential. This study assesses whether carbon nanomaterials can enhance the performance of zinc dialkyldithiophosphate (ZDDP) under severe conditions. A crossed-cylinder Reichert configuration (2 GPa, 75 °C, 1 m/s) with PAO6 was [...] Read more.

Industrial gear contacts operate under mixed-to-boundary lubrication where reliable antiwear protection is essential. This study assesses whether carbon nanomaterials can enhance the performance of zinc dialkyldithiophosphate (ZDDP) under severe conditions. A crossed-cylinder Reichert configuration (2 GPa, 75 °C, 1 m/s) with PAO6 was used to test ZDDP (1 wt%) and its blends with carbon nanotubes (CNT, 0.05 wt%), graphene nanoplatelets (GNP, 0.05 wt%), and few-layer graphene (FLG, 0.05 wt%) at 1, 10 and 60 min. The lubrication regime was boundary. Friction, specific wear rate (k), and tribofilm coverage were quantified. Oils containing only carbon nanoparticles could not sustain the test (seizure within minutes), confirming the necessity of ZDDP. After 60 min, average CoF remained similar across formulations and largely governed by ZDDP. By contrast, wear showed marked differences: relative to ZDDP alone (A), ZDDP + CNT (F) and ZDDP + GNP (G) reduced k by 52% and 48%, respectively, and exhibited higher tribofilm coverage (F = 68%, G = 72% vs. A = 57%). Time-resolved tests revealed that long-duration degradation was mitigated in F and G: from 10 to 60 min, k rose by 72% (F) and 58% (G) versus 159% for A; coverage decreased by only 8% (F) and 3% (G) versus 22% for A. SEM–EDS indicated no major differences in average elemental chemistry among formulations, suggesting an improvement on tribofilm coverage/stability rather than compositional change. Full article

(This article belongs to the Special Issue Modern Tribological Solutions in Renewable Power Systems)

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16 pages, 6098 KB

Open AccessArticle

Tribological Investigation of Wear-Resistant Friction Pairs for Miniature Linear Ultrasonic Motors

by Huajie Qu, Meiqin Liang and Zhongpu Wen

Lubricants 2026, 14(7), 251; https://doi.org/10.3390/lubricants14070251 - 24 Jun 2026

Abstract

To solve the drawbacks of conventional long-cycle wear tests for miniature standing- wave linear ultrasonic motors, an accelerated equivalent wear model and test system were proposed in this work. After primary screening of multiple pair materials, graphite and Al₂O₃ were [...] Read more.

To solve the drawbacks of conventional long-cycle wear tests for miniature standing- wave linear ultrasonic motors, an accelerated equivalent wear model and test system were proposed in this work. After primary screening of multiple pair materials, graphite and Al₂O₃ were adopted to modify epoxy films. The optimal friction pair is composed of 6061 hard anodic oxidation film and ECA105 composite film. The matched pair exhibits excellent driving stability and low wear loss, with fatigue wear as the main wear form. Graphite and Al₂O₃ exert synergistic anti-wear and load-bearing effects via forming a stable transfer film on the friction interface. Experimental results confirm that the accelerated test is equivalent to a full-life durability test. The presented method and optimized friction pair can effectively guide the development of high-performance ultrasonic motors. Full article

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14 pages, 3908 KB

Open AccessArticle

Micro vs. Nano: Effect of BN Additives on the Rheological and Tribological Properties of Lithium Grease

by Gaobo Lou, Xiaoling Yao, Yuhao Fang and Yifan Chen

Lubricants 2026, 14(7), 250; https://doi.org/10.3390/lubricants14070250 - 24 Jun 2026

Abstract

The influence of BN particle size on lithium grease performance was systematically compared among a base grease (Li), a micro-BN (3 µm, 0.1 wt%) modified grease (Li + 0.1% mBN), and a nano-BN (50 nm, 0.1 wt%) modified grease (Li + 0.1% nBN). [...] Read more.

The influence of BN particle size on lithium grease performance was systematically compared among a base grease (Li), a micro-BN (3 µm, 0.1 wt%) modified grease (Li + 0.1% mBN), and a nano-BN (50 nm, 0.1 wt%) modified grease (Li + 0.1% nBN). SEM shows that addition nano-BN leads to a more compact soap fiber networks, whereas micro-BN tends to agglomerate and provides limited reinforcement, leaving the base grease with a loose, porous network. Consequently, Li + 0.1% nBN outperforms both Li and Li + 0.1% mBN in dropping point (199.5 °C vs. 194.9 °C and 198.6 °C), oil separation (0.39% vs. 0.64% and 0.44%), and flow point (49% vs. 45% and 47%). Its plateau modulus is significantly higher, reflecting stronger network entanglement. However, Li + 0.1% nBN shows lower structural recovery (61.0%) than Li (65.8%) and Li + 0.1% mBN (67.2%) due to rigid particle–fiber junctions. Notably, Li + 0.1% mBN exhibits a unique frequency-dependent viscoelasticity: higher tanδ at low frequencies but lower tanδ at high frequencies relative to Li. Tribologically, Li + 0.1% nBN reduces friction coefficient by 35% and wear scar diameter by 12.7% compared with Li, outperforming Li + 0.1% mBN. XPS confirms a protective hybrid tribofilm (BN + organic nitrogen species + iron oxides) on the nano-BN lubricated surface. Particle size critically governs BN–fiber interactions and the resulting rheological and tribological performance. Full article

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21 pages, 3219 KB

Open AccessArticle

A New Condition Diagnosis Method for Ball Bearings Using Ultrasonic Visualization and Light CNN

by Hangyeol Jo, Sung-Ho Hong, Choon-Su Park, Moonsuk Kim, Miao Dai and Sang-Woo Ban

Lubricants 2026, 14(7), 249; https://doi.org/10.3390/lubricants14070249 - 23 Jun 2026

Abstract

Early fault diagnosis of ball bearings is essential for maintaining the reliability of rotating machinery and preventing unexpected downtime. This study proposes a fault diagnosis framework that combines non-contact ultrasonic visualization with a lightweight convolutional neural network (Light CNN). Seven bearing conditions, including [...] Read more.

Early fault diagnosis of ball bearings is essential for maintaining the reliability of rotating machinery and preventing unexpected downtime. This study proposes a fault diagnosis framework that combines non-contact ultrasonic visualization with a lightweight convolutional neural network (Light CNN). Seven bearing conditions, including ferrous particle contamination and grease starvation, were investigated using ultrasonic, vibration, and acoustic emission (AE) sensors under identical experimental conditions. Sa-liency-map extraction and two-dimensional histogram analysis were applied to ultrasonic RGB images to generate compact feature representations, which were compressed into 20 × 20 feature maps and used as inputs to a three-layer Light CNN. The proposed method achieved an average classification accuracy of 99.98% and an F1-score of 99.98%. In addition, an average inference throughput of 11.47 IPS was obtained, representing approximately ten times higher computational efficiency than vibration- and AE-based approach-es. Stable diagnostic performance was also maintained under a low-speed operating condition of 500 rpm. These results demonstrate the effectiveness of combining ultrasonic visualization and a lightweight CNN for accurate and computationally efficient bearing fault diagnosis. Full article

(This article belongs to the Special Issue Multiphysics Modelling in Bearing Lubrication)

34 pages, 6374 KB

Open AccessArticle

A Study on the Vibration Characteristics of Cage-Less Ball Bearings Following Local Damage to the Grooves

by Enwen Zhou, Jingwei Zhang, Lili Fan, Hui Qi, Yuan Zhang and Huanqing Zhang

Lubricants 2026, 14(7), 248; https://doi.org/10.3390/lubricants14070248 - 23 Jun 2026

Abstract

When the magnetic field of a magnetic levitation bearing is lost, the cage-less ball bearing acts as a backup bearing to support the falling spindle. To ensure uniform distribution of the rolling elements in the cage-less ball bearing, researchers have designed local functional [...] Read more.

When the magnetic field of a magnetic levitation bearing is lost, the cage-less ball bearing acts as a backup bearing to support the falling spindle. To ensure uniform distribution of the rolling elements in the cage-less ball bearing, researchers have designed local functional grooves on the outer ring raceway. However, the periodic motion of the rolling elements causes damage to these grooves, leading to discrete failure of the rolling elements and resulting in vibration during bearing operation. Therefore, this paper investigates the dynamic characteristics of the rolling elements and the factors influencing bearing vibration following damage to the local functional grooves in caged ball bearings. A vibration model for bearings with damaged functional grooves is established, and the research is conducted through theoretical analysis, numerical simulation, and experimental validation. Full article

(This article belongs to the Special Issue Tribological Characteristics of Bearing System, 4th Edition)

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20 pages, 5681 KB

Open AccessReview

Improving Particle Sampling Efficiency in Laboratory Brake Wear Emission Systems: A Review

by Adolfo Senatore, Ibrahim Sulimieh and Oleksii Nosko

Lubricants 2026, 14(6), 247; https://doi.org/10.3390/lubricants14060247 - 20 Jun 2026

Abstract

Non-exhaust emissions (NEEs), particularly brake wear particles (BWPs), have become a dominant source of traffic-related particulate matter (PM), accounting for approximately 77% of PM10 and 60% of PM2.5 emissions. Accurate quantification of these emissions is essential under increasingly stringent regulations such as Euro [...] Read more.

Non-exhaust emissions (NEEs), particularly brake wear particles (BWPs), have become a dominant source of traffic-related particulate matter (PM), accounting for approximately 77% of PM10 and 60% of PM2.5 emissions. Accurate quantification of these emissions is essential under increasingly stringent regulations such as Euro 7. However, measurement reliability is strongly influenced by particle transport and sampling losses. This review provides a state-of-the-art analysis of laboratory-scale methodologies for investigating BWP emissions, focusing on pin-on-disc (PoD) tribometers and inertia dynamometer systems. Particular attention is given to chamber design, airflow management, sampling configurations, and the mechanisms governing particle transport efficiency. The literature indicates that PoD systems are often affected by complex and non-uniform flow fields, leading to incomplete particle capture and reduced representativeness, whereas inertia dynamometers, especially when coupled with constant volume sampling (CVS), provide more controlled and reproducible conditions. Key loss mechanisms, including inertial deposition, diffusion, gravitational settling, and non-isokinetic sampling effects, are major contributors to uncertainty. The reviewed studies highlight that aerodynamic limitations in PoD systems, particularly box-shaped chambers, promote flow recirculation and particle losses. Advanced optimization approaches that combine artificial neural networks (ANNs) with computational fluid dynamics (CFD) simulations show strong potential to improve system design and measurement reliability. Full article

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27 pages, 4069 KB

Open AccessArticle

A Two-Scale Dynamic Friction Model Incorporating Measured Roll Roughness for Mixed-Lubricated Cold Rolling Interfaces

by Huajie Wu, Qiaoyi Wang, Laihua Tao, Xin Jiang and Longwei Geng

Lubricants 2026, 14(6), 246; https://doi.org/10.3390/lubricants14060246 - 20 Jun 2026

Abstract

Friction at the cold rolling interface is affected jointly by the surface roughness, lubrication state, local pressure, and relative sliding. A constant friction coefficient is therefore insufficient to describe its non-uniform distribution along the contact arc. Accordingly, this study proposes a macro–micro two-scale [...] Read more.

Friction at the cold rolling interface is affected jointly by the surface roughness, lubrication state, local pressure, and relative sliding. A constant friction coefficient is therefore insufficient to describe its non-uniform distribution along the contact arc. Accordingly, this study proposes a macro–micro two-scale mixed-lubrication and dynamic friction model based on the measured roll roughness. First, the measured roll roughness profile was represented within a finite effective scale interval by a scaled and truncated Weierstrass–Mandelbrot (W–M) function. The parameters D and G were obtained as finite-scale W–M roughness parameters and were introduced into a mixed-lubrication load-sharing model to calculate the local mixed-lubrication friction coefficient. The pressure distribution along the contact arc was calculated using the Karman equation, and the local macroscopic pressure was mapped to a representative microscopic contact load. Finally, the mixed-lubrication friction coefficient was used to calibrate the dynamic friction factor separately in the forward-slip and backward-slip zones, and the friction stress distribution along the contact arc was calculated. For the selected effective scale interval and preprocessing procedure, the fitted W–M roughness parameters were D = 1.528 and G = 9.15 × 10⁻⁸ m. The W–M parameter D had a more significant influence on the mixed-lubrication friction coefficient and load-sharing behavior than the scale parameter G. Increasing the rolling speed strengthened the oil-film load-carrying effect and reduced the equivalent interfacial friction coefficient. The friction stress was positive in the backward-slip zone and negative in the forward-slip zone, with a direction reversal near the neutral point. Field forward-slip inversion showed that both the simulated and measured equivalent friction coefficients decreased with increasing rolling speed, with a difference of approximately 0.009~0.017. The proposed model can capture the main trend of cold rolling interfacial friction with variations in the rolling speed and contact state. Full article

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24 pages, 3587 KB

Open AccessArticle

Thermo-Tribological Degradation and Lubrication Collapse in a High-Mileage Gasoline Engine: A Real-Engine Case Study

by Iliyan Damyanov, Durhan Saliev, Iliyana Naydenova, Ivaylo Peev, Hristo Konakchiev and Iliyan Ognyanov

Lubricants 2026, 14(6), 245; https://doi.org/10.3390/lubricants14060245 - 19 Jun 2026

Abstract

Thermal overload in internal combustion engines may progressively destabilize lubricant-film integrity and promote severe tribological deterioration within highly stressed contact interfaces. This study investigates the thermo-tribological degradation sequence of a high-mileage gasoline engine subjected to prolonged idle operation under impaired cooling conditions, ultimately [...] Read more.

Thermal overload in internal combustion engines may progressively destabilize lubricant-film integrity and promote severe tribological deterioration within highly stressed contact interfaces. This study investigates the thermo-tribological degradation sequence of a high-mileage gasoline engine subjected to prolonged idle operation under impaired cooling conditions, ultimately resulting in engine seizure. The investigated engine had accumulated 356,724 km, while the lubricant had remained in service for approximately 26,724 km prior to the experiment. The post-failure investigation combined teardown inspection, geometrical camshaft assessment, reverse gravimetric reconstruction, hydraulic tappet surface profiling, XRF surface characterization, laboratory oil analysis, and SEM/EDS evaluation of wear debris. The results demonstrated strongly localized degradation concentrated primarily within the cam–tappet interfaces. Severe non-uniform camshaft wear was accompanied by pronounced hydraulic tappet surface damage and evidence of unstable boundary-lubrication conditions. Laboratory oil analysis revealed elevated wear-metal concentrations, depletion of the alkaline reserve, increased oxidation indicators, and a final Class D oil condition assessment. SEM/EDS characterization identified Fe-bearing wear debris associated with sustained material removal and debris recirculation during the final degradation stage. The combined evidence supports a coupled thermo-tribological degradation mechanism involving lubricant deterioration, boundary-lubrication instability, adhesive wear acceleration, oxidative surface degradation, and debris-assisted surface damage preceding final engine seizure. The present case study provides experimentally documented evidence of lubrication collapse under real-engine thermal runaway conditions and highlights the critical role of lubricant condition in maintaining tribological stability under severe thermal loading. Full article

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16 pages, 2340 KB

Open AccessArticle

Role of Working Pressure and Deposition Power on the Tribological Performance of TiAlN Thin Films

by Kamlesh V. Chauhan, Sushant Rawal, Nicky P. Patel, Dattatraya Subhedar and Vandan V. Vyas

Lubricants 2026, 14(6), 244; https://doi.org/10.3390/lubricants14060244 - 18 Jun 2026

Abstract

The choice of brass as the substrate due to its widespread use in soft non-ferrous industrial components such as bearings and electrical connectors creates the primary basis of novelty in this study. While prior tribological studies on titanium aluminum nitride (TiAlN) coatings is [...] Read more.

The choice of brass as the substrate due to its widespread use in soft non-ferrous industrial components such as bearings and electrical connectors creates the primary basis of novelty in this study. While prior tribological studies on titanium aluminum nitride (TiAlN) coatings is primarily focused on hard substrates such as steel and WC–Co, this work addresses the research gap by presenting a systematic investigation of the combined influence of sputtering power and working pressure on TiAlN coatings deposited on brass. Application of TiAlN coatings on brass surfaces was accomplished using magnetron sputtering. Within the scope of this study, the influence of sputtering power and working pressure on the tribological and structural attributes of TiAlN films is evaluated. The analysis of surface morphology is carried out using scanning electron microscopy (SEM), while structural characteristics revealed a progressive increment in the intensity of the (103) and (107) peaks with variation in deposition parameters. An analysis was conducted to evaluate the tribological properties of the TiAlN coating using a pin-on-disk tribometer. The study involved varying the speeds, loads, and sliding lengths. The optimized condition achieved wear reduction as high as 22% compared to uncoated brass at a sliding distance of 785 m, which highlights the strong dependence of wear performance on deposition parameters. The wear rates of TiAlN-coated brass ranged between 1.03 × 10⁻³ and 5.87 × 10⁻⁴ mm³/Nm depending on parameters like load, sliding distance and speed. Conversely, TiAlN-coated brass pins prepared at varying power showed wear rates ranging from 1.83 × 10⁻⁴ to 5.87 × 10⁻⁴ mm³/Nm. These findings demonstrate that optimization of TiAlN coating parameters on brass can significantly enhance wear resistance, which ultimately improves the durability and performance of engineering components in tribological applications. Full article

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21 pages, 15728 KB

Open AccessArticle

Comparative Microstructural, Mechanical, and Tribological Evaluation of Cu Matrix Composites Reinforced with B₄C, B, Cr, Co, Al₂O₃, and Graphite via Powder Metallurgy

by Cevher Kursat Macit, Turan Gürgenç, Bunyamin Aksakal and Naim Aslan

Lubricants 2026, 14(6), 243; https://doi.org/10.3390/lubricants14060243 - 18 Jun 2026

Abstract

Copper and its alloys are widely used in electrical, automotive, aerospace, and energy applications because of their excellent thermal and electrical conductivity. However, the low hardness and poor wear resistance of pure Cu limit its use under tribologically demanding sliding conditions. In this [...] Read more.

Copper and its alloys are widely used in electrical, automotive, aerospace, and energy applications because of their excellent thermal and electrical conductivity. However, the low hardness and poor wear resistance of pure Cu limit its use under tribologically demanding sliding conditions. In this study, Cu matrix composites reinforced with 1 wt.% boron carbide (B₄C), boron (B), chromium (Cr), cobalt (Co), alumina (Al₂O₃), and graphite (Gr) were fabricated by powder metallurgy and comparatively evaluated under identical processing and testing conditions. Phase constitution and microstructural characteristics were analyzed by XRD, SEM, and EDS, while mechanical and tribological behavior was assessed by Vickers hardness and dry sliding wear tests. All reinforcements improved the hardness of the Cu matrix compared with unreinforced Cu. The hardness increase followed the order Cu–B₄C (68.91%) > Cu–B (66.43%) > Cu–Gr (63.97%) > Cu–Al₂O₃ (61.79%) > Cu–Cr (42.69%) > Cu–Co (36.04%). Dry sliding wear tests, performed under a 10 N normal load, 0.05 m s⁻¹ sliding speed, and 1000 m sliding distance against a 316L stainless-steel ball, showed that all reinforced composites exhibited lower mass loss and more stable sliding behavior than pure Cu. Among all samples, Cu–B₄C displayed the best wear performance, with a 154.8% improvement in wear resistance relative to pure Cu. SEM analysis of the worn surfaces revealed that reinforcement addition reduced severe plastic deformation, groove formation, and delamination, leading to a more stable wear regime. Graphite- and boron-containing composites benefited from interfacial lubrication and contact stabilization, whereas B₄C and Al₂O₃ improved wear resistance through rigid-particle strengthening and enhanced load-bearing capacity. By comparing ceramic, metalloid, metallic, oxide, and solid-lubricating reinforcements at the same low addition level and under identical processing and testing conditions, this study provides a reinforcement-selection framework for Cu-based composites requiring improved hardness and dry-sliding durability. Full article

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21 pages, 6459 KB

Open AccessArticle

Tool Wear Condition Prediction Method Based on Sparse Identification of Nonlinear Dynamics (SINDy)

by Mengyao Si, Xinhang Shang, Li Sun, Yaqing Dong and Xue Jiang

Lubricants 2026, 14(6), 242; https://doi.org/10.3390/lubricants14060242 - 17 Jun 2026

Abstract

Current deep learning methods for tool wear monitoring suffer from poor interpretability and struggle to reveal the intrinsic relationship between signals and wear states. To address this issue, this paper presents an interpretable tool wear monitoring method based on Sparse Identification of Nonlinear [...] Read more.

Current deep learning methods for tool wear monitoring suffer from poor interpretability and struggle to reveal the intrinsic relationship between signals and wear states. To address this issue, this paper presents an interpretable tool wear monitoring method based on Sparse Identification of Nonlinear Dynamics (SINDy). Multi-domain features are extracted from cutting force and acoustic emission signals to construct a time series. The SINDy algorithm is used to identify ordinary differential equations that describe the evolution of tool wear. An iterative “predict-validate-correct” mechanism is applied to optimize model parameters. Experimental results show that the mean absolute percentage error (MAPE) between the predicted and actual values is below 6%. Moreover, the optimal model demonstrates an average MAPE as low as 0.067% in cross-condition tests. This study provides an effective solution for online tool wear monitoring that achieves high precision, strong generalization, and physical interpretability. Full article

(This article belongs to the Special Issue Monitoring and Remaining Useful Life (RUL) Technology of Tool Wear)

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21 pages, 12132 KB

Open AccessArticle

Tool Wear Condition Monitoring Method Fusing Time- and Frequency-Domain Features via Cross-Attention

by Xingang Xie, Yeteng Li, Zhixuan He, Qian Deng, Yining Zhang and Tingshuo Zhang

Lubricants 2026, 14(6), 241; https://doi.org/10.3390/lubricants14060241 - 17 Jun 2026

Abstract

Signals generated during tool wear are nonlinear, non-stationary, and easily affected by machining noise, which makes reliable tool condition monitoring difficult in intelligent manufacturing. To address this issue, this study proposes a tool wear degree classification framework, FCTrans-CA, that fuses time-domain and frequency-domain [...] Read more.

Signals generated during tool wear are nonlinear, non-stationary, and easily affected by machining noise, which makes reliable tool condition monitoring difficult in intelligent manufacturing. To address this issue, this study proposes a tool wear degree classification framework, FCTrans-CA, that fuses time-domain and frequency-domain information through a lightweight cross-attention (CA) bridge. Fast Fourier transform (FFT) is first used to obtain frequency-domain representations. The raw time-domain signals are processed by a multi-scale one-dimensional convolutional neural network (MS-CNN) to extract temporal wear features, while the FFT-derived representations provide complementary spectral cues. These two feature streams are fused by an asymmetric CA module in which frequency-domain features guide the selection of wear-sensitive temporal features. K-means clustering is used to divide the measured flank wear (VB) trajectory of each tool into initial-, normal-, and severe-wear stages, thereby reducing subjectivity in label generation. Experiments on the PHM2010 milling dataset show that FCTrans-CA achieves 99.43% classification accuracy on 40,648 test samples. The results indicate that cross-domain feature interaction improves the separability of wear states and provides a reproducible data-driven route for tool wear monitoring. Full article

(This article belongs to the Special Issue Monitoring and Remaining Useful Life (RUL) Technology of Tool Wear)

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20 pages, 5347 KB

Open AccessArticle

Analysis of Under-Lubricated Condition for Journal Bearing with Coupled Tribological Behavior

by Nao Hu, Lili Lian, Liangtao Xie, Bingjie Ma, Sicong Sun, Jianguo Yang, Guanjun Zhang, Lei Hu and Jun Li

Lubricants 2026, 14(6), 240; https://doi.org/10.3390/lubricants14060240 - 17 Jun 2026

Abstract

Journal bearings are prone to failure due to lubrication state degradation under extreme operating conditions. To address the unclear transition mechanism and undefined state boundaries under insufficient lubrication, a coupled tribological model of engine journal bearings was established. Through parameter analysis and dynamic [...] Read more.

Journal bearings are prone to failure due to lubrication state degradation under extreme operating conditions. To address the unclear transition mechanism and undefined state boundaries under insufficient lubrication, a coupled tribological model of engine journal bearings was established. Through parameter analysis and dynamic failure mechanism study, the effects of radial clearance, temperature, rotational speed, load, and surface roughness on the lubrication state transition were revealed. The results indicate that radial clearance, oil temperature, rotational speed, applied load and surface roughness are all decisive factors for lubrication transition, and every parameter has its unique critical threshold; once exceeding the limit, the oil film integrity is damaged and the lubrication rapidly shifts from mixed lubrication toward boundary lubrication. After crossing critical thresholds, aggravated asperity contact further triggers continuous temperature rise and viscosity reduction, which may induce closed-loop thermal deterioration and eventually accelerate bearing failure. The research findings provide a theoretical basis for robust design and operational safety monitoring of journal bearings. Full article

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39 pages, 16942 KB

Open AccessReview

Laser Surface Texturing for Tribological Applications: Mechanisms, Surface Engineering Strategies, and Application-Oriented Design

by Jiaru Zhang, Tao Yu and Libin Lu

Lubricants 2026, 14(6), 239; https://doi.org/10.3390/lubricants14060239 - 14 Jun 2026

Abstract

Friction and wear are major factors affecting the efficiency and reliability of mechanical systems, leading to increasing interest in laser surface texturing (LST) for tribological surface engineering. This review summarizes the development of LST from conventional surface modification to multifunctional interface design and [...] Read more.

Friction and wear are major factors affecting the efficiency and reliability of mechanical systems, leading to increasing interest in laser surface texturing (LST) for tribological surface engineering. This review summarizes the development of LST from conventional surface modification to multifunctional interface design and discusses the underlying process–structure–performance relationships. Different lubrication-dependent mechanisms, including micro-hydrodynamic pressure generation, wear debris entrapment, contact stress regulation, metallurgical strengthening, and wettability control, are analyzed under hydrodynamic, boundary, and dry sliding conditions. Representative processing technologies, including nanosecond, ultrafast, direct laser interference patterning (DLIP), and liquid-assisted laser processing, are compared in terms of fabrication precision, thermal effects, scalability, and tribological performance. Recent advances in hybrid surface engineering strategies integrating textures with coatings, solid lubricants, and surface hardening treatments are also reviewed. Representative applications involving bearings, cutting tools, biomedical implants, advanced ceramics, and additively manufactured materials are discussed to summarize application-oriented texture design principles. Current limitations related to thermal damage, manufacturing efficiency, coating stability, and long-term reliability are critically evaluated. Future developments are expected to focus on multifunctional surface integration, large-area manufacturing, and AI-assisted optimization for application-specific tribological interface design. Full article

(This article belongs to the Special Issue Laser Surface Treatments for Tribological Applications)

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30 pages, 5698 KB

Open AccessReview

Research Progress on Bionic Functional Surfaces for Friction Reduction, Wear Resistance, and Anti-Adhesion in Agricultural Machinery

by Honglei Zhang, Tiantian Jing, Jun Zhang, Dong Lv and Zhong Tang

Lubricants 2026, 14(6), 238; https://doi.org/10.3390/lubricants14060238 - 12 Jun 2026

Abstract

This review explicitly focuses on agricultural attachments and executing components that interact directly with soil and crops, rather than the tractor vehicle itself. Operating within complex and variable farmland media environments, the key components of agricultural machinery have long been constrained by bottlenecks [...] Read more.

This review explicitly focuses on agricultural attachments and executing components that interact directly with soil and crops, rather than the tractor vehicle itself. Operating within complex and variable farmland media environments, the key components of agricultural machinery have long been constrained by bottlenecks such as high-energy draught resistance, severe solid–liquid interfacial adhesion, and intense abrasive wear. Bionic functional surfaces, based on the coupling of micro-geometric morphology and surface-interface physical chemistry, provide a scientific approach to overcoming traditional tribological limitations by reconstructing the contact mechanics and fluid dynamics boundaries at the interface. This paper presents a comprehensive review of the latest research progress regarding bionic functional surfaces in the fields of friction reduction, wear resistance, and anti-adhesion in agricultural machinery. The article systematically categorises typical biological prototypes, such as soil-burrowing animals, aquatic organisms, and plant leaves, alongside their multidimensional feature extraction methods. It provides an in-depth analysis of core interaction mechanisms, ranging from static air cushion effects and dynamic wetting evolution to active electro-osmotic soil detachment, interfacial stress redistribution, and microscopic wear debris capture. Furthermore, it evaluates the efficacy of cross-scale coupled numerical simulation technologies in resolving interfacial interactions. At the engineering application level, this review extensively discusses the field performance of bionic structures in typical operational scenarios, including draught reduction in tillage and land preparation, blockage prevention in seed-metering channels, and low-damage harvesting in agricultural machinery. Finally, countermeasures are proposed to address the fatigue degradation of bionic surfaces under alternating field loads and the barriers to the large-scale fabrication of large-sized components. The paper further highlights the development trend towards the deep integration of bionic tribology with digital twins and intelligent wear-state perception technologies, aiming to provide systematic underlying theoretical and technical references for the research and development of the next generation of intelligent agricultural equipment characterised by low energy consumption and a prolonged service life. Full article

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50 pages, 16217 KB

Open AccessReview

Cavitation in Machine Elements: A Critical Review of Cavitation Damage, Experimental Methods, Standardization Challenges, and Applied Digital Technologies

by Pavle Ljubojević, Tatjana Lazović and Marina Dojčinović

Lubricants 2026, 14(6), 237; https://doi.org/10.3390/lubricants14060237 - 11 Jun 2026

Abstract

Cavitation in machine elements is often accompanied by surface degradation, material loss, and a reduction in functional performance and reliability. Despite extensive research on cavitation in hydraulic systems, its role in the behavior and durability of machine elements remains insufficiently addressed. This paper [...] Read more.

Cavitation in machine elements is often accompanied by surface degradation, material loss, and a reduction in functional performance and reliability. Despite extensive research on cavitation in hydraulic systems, its role in the behavior and durability of machine elements remains insufficiently addressed. This paper presents a critical review of cavitation and cavitation-induced erosion in machine elements, based on an analysis of relevant literature and standards. The study covers different types of components, including gears, plain and rolling bearings, and seals, with particular attention to the mechanisms of damage and the methods used for their investigation. The analysis shows that, although the fundamental mechanisms of cavitation are well understood and standardized testing methods are available, their application to machine elements is limited. Existing standards are not sufficiently adapted to specific components, while current numerical and experimental approaches rarely provide a direct link between cavitation phenomena and material degradation. The findings indicate the need for improved standardization, development of integrated modelling approaches, and a closer connection between cavitation mechanisms and the performance characteristics of machine elements. The presented analysis is relevant for design, reliability assessment, maintenance strategies, and the development of cavitation-resistant machine components in hydraulic and mechanical systems. Full article

(This article belongs to the Special Issue Machine Design and Tribology)

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