Search Results (151)

Wear, a critical factor governing the performance and durability of mechanical systems, is typically characterized using point-contact and line-contact test configurations. However, it remains unclear whether the wear trends observed in one test configuration would be observed in the other configuration under the same nominal conditions. In this study, ball-on-disk (ASTM G99) and block-on-ring (ASTM G77) tests were conducted under an identical maximum Hertzian contact stress and sliding speed, using the same material pair and lubricating oil, to clarify which contact configuration exhibits more wear and why. The results show that, under the same Hertzian contact stress, the line-contact configuration exhibits a specific wear rate two orders of magnitude higher than the point-contact configuration, despite exhibiting a lower and more stable coefficient of friction. The disk wear is negligible and the ball shows only mild material loss, whereas the line-contact system displays wear rates several orders of magnitude higher, with the rotating ring contributing the dominant share of the total wear. White-light interferometry and scanning electron microscopy observations reveal directional, groove-dominated surface morphologies on the ball and disk, while wear on the block is confined to edge-localized regions and the worn ring surface has smooth, polished morphology. Energy-dispersive X-ray spectroscopy confirms that a Zn- and P-rich tribofilm forms exclusively on the ring surface. Finite element analysis shows stress amplification at the finite line-contact edges, explaining the observed wear severity. These results demonstrate that matching Hertzian contact stress alone is insufficient to ensure comparable wear behavior between point and line contacts. Full article

A Monte Carlo based fractal prediction model is proposed to describe the evolution of surface morphology during the running-in process. The model accounts for the random and fractal characteristics of worn surfaces. The Weierstrass–Mandelbrot function is employed to simulate rough surfaces and establish the correlation between fractal dimension and surface roughness. By integrating traditional sliding wear models with surface effect functions, a unified prediction framework is developed. Experiments are conducted to obtain worn surface parameters and calculate fractal dimensions at different running-in stages. Model parameters are optimized by minimizing the variance between experimental and predicted results. Monte Carlo simulations are then introduced to represent the stochastic nature of the friction system, thereby improving prediction accuracy and objectivity. The proposed model reveals locally random yet globally convergent patterns, which are consistent with experimental observations. It effectively captures the stochastic evolution of surface morphology and provides a reliable approach for predicting worn surface behavior during running-in. Full article

Reconstructing original cusp dimensions in worn molars represents a fundamental challenge across dentistry, anthropology, and paleontology, as dental wear obscures critical morphological information. In this proof-of-concept study, we present a standardized machine learning pipeline for predicting original cusp height, specifically the horn tips of the enamel–dentine junction (EDJ), in worn lower molars using three-dimensional morphometric data from micro-computed tomography (micro-CT). We analyzed 40 permanent lower first (M1) and second (M2) molars from four hominin groups, systematically evaluated across three wear stages: original, moderately worn (worn1), and severely worn (worn2). Morphometric variables including height, area, and volume were quantified for each cusp, with Random Forest and multiple linear regression models developed individually and combined through ensemble methods. To mimic realistic reconstruction scenarios while preserving a known ground truth, models were trained on unworn specimens (original EDJ morphology) and tested on other teeth after digitally simulated wear (worn1 and worn2). Predictive performance was evaluated using root mean square error (RMSE) and coefficient of determination (R²). Our results demonstrate that under moderate wear (worn1), the ensemble models achieved normalized RMSE values between 11% and 17%. Absolute errors typically below 0.25 mm for most cusps, with R² values up to ~0.69. Performance deteriorated under severe wear (worn2), particularly for morphologically variable cusps such as the hypoconid and entoconid, but generally remained within sub-millimetric error ranges for several structures. Random Forests and linear models showed complementary strengths, and the ensemble generally offered the most stable performance across cusps and wear states. To enhance transparency and accessibility, we provide a comprehensive, user-friendly software pipeline including pre-trained models, automated prediction scripts, standardized data templates, and detailed documentation. This implementation allows researchers without advanced machine learning expertise to explore EDJ-based reconstruction from standard morphometric measurements in new datasets, while explicitly acknowledging the limitations imposed by our modest and taxonomically unbalanced sample. More broadly, the framework represents an initial step toward predicting complete crown morphology, including enamel thickness, in worn or damaged teeth. As such, it offers a validated methodological foundation for future developments in cusp and crown reconstruction in both clinical and evolutionary dental research. Full article

This present study epitomises the fabrication of Cu-15%WC-X%Gr (X = 0, 3, 6, 9, 12) hybrid composites through a microwave sintering process. The synthesised composites were evaluated for hardness and compression strength as per ASTM standards. The composite corresponding to Cu-15%WC-9%Gr shows the optimal compression strength of 395 MPa. Based on this, the composite corresponding to the maximum compression strength was selected for subsequent wear investigations under dry, oil, and SiC nanofluid lubrication conditions. The SiC nanofluids were prepared by dispersing 1 wt% SiC, 1.5 wt% SiC, and 2 wt% SiC nanoparticles in soluble oils. Increasing the nanoparticle content enhanced both the thermal conductivity and zeta potential, indicating an improved heat transfer and dispersion stability. The wear test under different lubricating regimes demonstrates that the lubricating type had a pronounced influence on the wear rate and C.O.F. The minimum rate of wear of 0.0235 mm³/m and C.O.F. of 0.28 were achieved for the 2 wt% SiC nanofluid lubrication. The worn surfaces under dry and oil-lubricated regimes revealed prominent microcracks and delamination wear. In contrast, surfaces tested under nanofluid lubrication exhibited smoother grooves with minimal surface damage and an absence of microcracking. Full article

Energy conservation and efficiency enhancement necessitate continuous advancement in the development and preparation of multifunctional, high-performance lubricant additives. This paper reports three novel ashless, phosphorus-free, multifunctional nitrogen-containing heterocyclic dialkyl dithiocarbamate derivative additives (Py-2-DBDTC, PDM-DBDTC, and BZT-DBDTC). Thermal stability, oxidation resistance, and tribological properties were investigated for the synthesized additives. All three additives demonstrated excellent thermal stability and oxidation resistance. Furthermore, their extreme-pressure properties improved by 116.33% or more compared to the base oil, while wear reduction rates also exceeded 58.32%. Under both point-to-point and point-on-flat friction conditions, the friction-reducing performance of all three additives was equally outstanding. Across a broad temperature range (25 °C–150 °C), all additives maintained their friction-reducing properties. Analysis of the worn surface morphology reveals that all three additives undergo tribochemical reactions during the friction process, forming tribofilms containing sulfur elements. Research indicates that introducing different nitrogen-containing heterocyclic structures into dialkyl dithiocarbamates can effectively enhance the adsorption capacity of the additives on metal surfaces and promote the formation of tribofilms at the friction interface, thereby significantly improving tribological performance. These systematic investigations not only provide important guidance for the molecular design and industrial application of multifunctional lubricant additives but also further advance the development of sustainable lubrication technologies. Full article

Al₂O₃-TiC/6061Al composites were fabricated via in situ powder metallurgy using 6061 Al, TiO₂, and graphite powders as starting materials. The effects of sintering temperature and ceramic particle content on the microstructure and mechanical properties of the composites were investigated. The wear performance of composites sintered at 1200 °C with varying ceramic particle content was also examined. The results indicate that the microstructure of the composite varied with the sintering temperature. At 1000 °C and 1100 °C, the microstructure primarily consisted of Al₃Ti, Al₂O₃, and TiC phases. At 1200 °C and 1250 °C, the microstructure was predominantly composed of Al₂O₃ and TiC phases. The 6061 Al-12% (TiO₂ + C) composite sintered at 1200 °C exhibited a tensile strength of 246 MPa, an elongation of 12.7%, and a microhardness of 104.2 HV_0.1. Regarding wear performance, the wear behavior of the composites under different loads at 1200 °C was studied. Under a 30 N load, the 6061 Al-12% (TiO₂ + C) composite demonstrated the lowest friction coefficient and wear rate, measured at 0.253 and 0.396 mm³·N⁻¹·m⁻¹, respectively. Analysis of the worn surface morphology under a 30 N load indicates that the dominant wear mechanism for the 6061 aluminum alloy is delamination wear, whereas for the 6061 Al-12% (TiO₂ + C) composite, it is primarily abrasive wear. Full article

Wave Energy Converters (WECs) depend on hydraulic Power Take-Off (PTO) systems in which elastomeric seals must withstand wear, fatigue, and corrosion under harsh marine loading. This study quantitatively compares two commercial polyurethane seals (E1-E2) with custom-compounded Ethylene propylene diene monomer rubber (EPDM) formulations (E3–E5) using reciprocating wear tests (ASTM G133) at 3–10 N and 10–30 mm/s. It is noted that all experiments were conducted under dry conditions at room temperature as a baseline assessment, and the findings provide foundational insight prior to considering lubrication, hydraulic fluid effects, and marine environmental conditions relevant to WEC operation. Coefficient of friction (COF), specific wear rate, and worn-surface morphology were assessed to determine material durability. The commercial thermoplastic polyurethane (TPU) grades exhibited high hardness (93–94 Shore A), low wear rates (2.29–1.93 × 10⁻⁴ mm³/Nm), and shallow wear scars (≤380 µm). Carbon-black-reinforced EPDM (E3) produced the lowest wear rate among all samples (1.45 × 10⁻⁴ mm³ N⁻¹ m⁻¹) and the longest predicted service life (6.2 years), whereas silica-filled and plasticized EPDMs (E4, E5) showed higher wear (2.44–2.88 × 10⁻⁴ mm³/Nm) and broader deformation zones. Archard-based lifetime estimates at 10 N and 30 mm/s ranged from 3.1 to 6.2 years across materials. These results demonstrate that optimized EPDM formulations can serve as cost-effective alternatives to commercial TPUs for medium-load hydraulic sealing applications while providing a quantitative basis for material selection and life prediction. Full article

The study of wear topography in self-lubricating joint bearings is of significant importance for evaluating their service life. In this work, an image dataset was acquired using a white-light interferometer, and the topographical height and color of the images were standardized. Images of worn bearing specimens subjected to 72,000 swing cycles at a frequency of 2 Hz under loads of 100 N, 150 N, 200 N, and 250 N were optimized to construct a processed image dataset. To overcome the limitations of traditional recognition methods in fully capturing both global and local image-based metrics, an improved residual neural network (ResNet) model was proposed. Comparative results with CNN, CapsNet, and conventional ResNet models indicate that, on the processed image dataset, the proposed method improved recognition accuracy by 34% relative to traditional approaches, and by 19% compared to the conventional ResNet. This study provides a novel approach and perspective for investigating the wear topography of self-lubricating joint bearings. Full article

Continuous use of clear aligners modifies the oral environment and may favor bacterial colonization. Integration of topical fluoride-based agents could strengthen enamel and reduce biofilm formation. This study evaluated the effects of a galenic fluoride-mint spray (225–250 ppm fluoride and 1–2% peppermint essential oil) on salivary fluoride concentration and bacterial biofilm during orthodontic treatment. Ten patients using 3D-printed nighttime aligners were enrolled. Saliva samples were analyzed with an ion-selective electrode (ISE) at baseline, immediately after inserting the sprayed aligners and after 15, 30, 45 min post application. Biofilm morphology was qualitatively assessed by scanning electron microscope (SEM) in three aligners: unused, worn 14 nights without spray, worn 14 nights with spray. Salivary fluoride increased from 0.7–0.8 mg/L at baseline to 5.96 mg/L when the spray was applied on a new aligner and 8.42 mg/L on a used aligner, then progressively decreased, returning close to baseline at 45 min with the new aligner and remaining higher with the used aligner. SEM images showed mature and heterogeneous biofilm on used aligners without the spray, while aligners with nightly spray application exhibited qualitatively reduced and less organized surface deposits. The fluoride- and mint-based spray rapidly increases salivary fluoride and reduces biofilm formation on nighttime clear aligners, improving preventive oral health during orthodontic treatment. Full article

Most long-term mobile EEG monitoring systems require professional application of the electrodes, which makes them inconvenient for everyday use. Additionally, many materials that facilitate EEG application, such as dry electrodes, may cause discomfort when worn for longer periods of time. To address these problems, we designed flex-printed EEG electrode grids (trEEGrid) and evaluated signal quality based on two pre-applied conductive materials. Self-applicable trEEGrid patches with a conductive solid hydrogel and a novel silicone-based dry material were used in a day-long (5–6 h) recording session, which included a 4 h continuous recording of impedance levels, as well as two auditory task recordings in the morning and afternoon. The signal-to-noise ratio (SNR) of the auditory evoked potentials (AEPs), AEP morphology, and impedance levels of the conductive materials were compared to evaluate overall signal quality, and further comparisons took place between the morning and afternoon sessions to evaluate signal deterioration over time. Comparable impedance values were observed for both silicone and hydrogel materials, but the silicone material exhibited a higher outlier rate, with impedance values over 200 kΩ. Over time, the impedance values increased for the silicone material and decreased for the hydrogel material. The morphology of the AEP was reproduced comparably well with both materials, with reasonable SNRs in both the morning and the afternoon. In conclusion, when combined with flex-printed electrode grids, silicone and hydrogel materials make it feasible to collect high-quality long-term EEG signals with high wearing comfort. Full article

This study presents a comparative evaluation of injection-moulded PA12 composites reinforced with AlSi10Mg and 304 SS fillers, with emphasis on microstructure–property correlations linking powder morphology, mechanical performance, thermal stability, and tribological behaviour. Powder characterization revealed distinct morphologies—fine spherical AlSi10Mg particles (D50 ≈ 32 µm) dispersed uniformly in the matrix—while SS particles (D50 ≈ 245 µm) tended to agglomerate, leading to interfacial voids. Tensile testing showed that the elastic modulus of neat PA12 (0.95 GPa) increased by 20% and 28% with 20 wt% AlSi10Mg and SS, respectively. However, tensile strength decreased from 35.04 MPa (PA12) to 32.18 MPa (20 wt% AlSi10Mg) and 31.03 MPa (20 wt% 304 SS), consistent with stress concentrations around particle clusters. Hardness values remained nearly unchanged at 96–98 Shore D across all composites. Thermal analysis indicated that AlSi10Mg promoted crystallization, increasing crystallinity from 31% (PA12) to 34% and raising Tm by 2 °C. In contrast, 304 SS reduced crystallinity to 28% but significantly improved thermal stability, shifting Tonset from 405 °C (PA12) to 426 °C at 20 wt%. Tribological tests demonstrated substantial improvements: the coefficient of friction decreased from 0.42 (PA12) to 0.34 (AlSi10Mg) and 0.29 (304 SS), while wear rates dropped by 40% and 55%, respectively. SEM confirmed smoother worn surfaces in AlSi10Mg composites and abrasive grooves in 304 SS composites. The findings show that AlSi10Mg is advantageous for smoother surfaces and improved crystallinity, while SS enhances stiffness, wear resistance, and thermal endurance, providing design guidelines for PA12 composites in aerospace, automotive, and engineering applications. Full article

Tool wear detection is very important in CNC machine tool cutting. Once the tool is excessively worn, it is not only easy to cause the workpiece to be scrapped, but even to damage the machine. Therefore, common external turning tools of CNC machines are studied. The effect of tool nose wear on machining accuracy was analyzed by a building mathematical model. According to different wear conditions, a linear detection method based on edge images and input features was proposed to detect the main and secondary cutting edges, which helped determine the theoretical center of the tool nose and build a morphological visual model. For different error cases, the axial and radial error compensation strategies were proposed, respectively. By comparing the experimental data of four kinds of workpieces before and after compensation machining, the average errors of them were reduced separately, and the maximum value reached 79.2%, which verified the effectiveness of the compensation strategy. The intelligent compensation strategies will significantly improve the micro-machining accuracy and efficiency of the external turning tools in CNC machines. Full article

This study reviews the scientific use of chest-strap wearables, analyzing their advantages and limitations, following PRISMA guidelines. Eligible studies assessed chest-strap devices in adults and reported physiological outcomes such as heart rate, heart rate variability, R–R intervals, or electrocardiographic waveform morphology. Studies involving implanted devices, wrist-worn wearables, or lacking validation against reference standards were excluded. Searches were conducted in PubMed, Scopus, Web of Science, and ScienceDirect for studies published in the last 10 years. The quality of the studies was assessed using the Mixed Methods Appraisal Tool, and results were synthesized narratively. Thirty-two studies were included. The most frequently evaluated devices were the Polar H10 and Zephyr BioHarness 3.0, which showed strong correlations with electrocardiography at rest and during light-to-moderate activity. Reported limitations included motion artefacts, poor strap placement, sweating, and degradation of the skin–electrode interface. None of the devices had CE or FDA approval for clinical use, and most studies were conducted in controlled settings, limiting generalizability. Ergonomic concerns such as discomfort during prolonged wear and restricted mobility were also noted. Overall, chest-strap sensors showed good validity and were widely used in validation studies. However, technical refinements and large-scale field trials are needed for broader clinical and occupational application. This review is registered in PROSPERO and is part of the SIREN project. Full article

This study examines the incorporation of chopped glass fiber and nano-silica into epoxy, focusing on their effects on the tribological and mechanical properties. Three reinforcement ratios (1 wt.%, 3 wt.%, and 5 wt.%) were analyzed by scratch tests and profilometric analysis. The coefficient of friction (COF), scratch depth, and scratch width values of the unreinforced epoxy resin were measured as 0.45, 37.73 µm and 479 µm, respectively. The addition of glass fibers contributed to improved scratch performance by restricting material removal and stabilizing groove morphology, although higher fiber ratios caused an increase in COF. The results indicated that nano-silica increased scratch resistance with a COF of 0.42 at 5 wt.%, giving a scratch depth of 19.92 µm and a scratch width of 166 µm. Glass fiber also improved scratch performance, although there were high COF values for higher ratios, which could be due to the aggregation effect of the fibers. Statistical validation of the results was carried out through the Taguchi method and ANOVA analyses. These analyses showed that reinforcement type and ratio played an important role in scratch behavior. SEM analyses of worn surfaces showed that nano-silica can dissipate stress and minimize plastic deformation to yield improved scratch morphology. Overall, the results emphasize the complementary role of glass fiber and nano-silica reinforcements in improving the scratch resistance of epoxy resin for industrial applications. Full article

Aluminium metal matrix composites (AMMCs) incorporate aluminium alloys reinforced with fibres (continuous/discontinuous), whiskers, or particulate. These materials were engineered as advanced solutions for demanding sectors including construction, aerospace, automotive, and marine. Micro- and nano-scale reinforcing particles typically enable attainment of exceptional combined properties, including reduced density with ultra-high strength, enhanced fatigue strength, superior creep resistance, high specific strength, and specific stiffness. Microstructural, mechanical, and tribological characterizations were performed, evaluating input parameters like reinforcement weight percentage, applied normal load, sliding speed, and sliding distance. Fabricated nanocomposites underwent tribometer testing to quantify abrasive and erosive wear behaviour. Multiple investigations employed the Taguchi technique with regression modelling. Analysis of variance (ANOVA) assessed the influence of varied test constraints. Applied load constituted the most significant factor affecting the physical/statistical attributes of nanocomposites. Sliding velocity critically governed the coefficient of friction (COF), becoming highly significant for minimizing COF and wear loss. In this review, the reinforcement homogeneity, fractural behaviour, and worn surface morphology of AMMCswere examined. Full article