Search Results (214)

Surface topography affects the functional properties of machined surfaces. To assess these effects, special parameters were developed. Among them, the hybrid parameters rms. slope Sdq and the developed interfacial areal ratio Sdr are of high significance. However, these parameters are interrelated. Sdr can be estimated from Sdq using the special formula. The connections between these parameters were studied in this work depending on the sampling interval. Sixty-four surface topographies, after various machining treatments, were measured by white light interferometer Talysurf CCI Lite and analysed. The same measurement condition was performed for all surfaces. The application of the formula that interrelated the hybrid parameters was tested for different sampling intervals. It was found that the Sdq parameter was strongly linearly correlated with the Sdr parameter, independent of the sampling interval. The dependence between hybrid parameters had a nonlinear character. The estimation of the Sdr parameter based on the values of the Sdq parameter yielded very accurate results for smooth surfaces, independent of the sampling interval. Relative errors in estimating Sdq based on Sdr decreased as the sampling interval increased. High errors corresponded to surfaces with high roughness amplitude. A proposal was presented for sampling interval selection. Because hybrid parameters are interrelated, one parameter should be selected for the description of the areal surface texture. The Sdq parameter is recommended because of its lower sensitivity to measurement errors than the Sdr parameter. Full article

This study aimed to evaluate the impact of UVC (Ultraviolet C Radiation), detergent foam, and alcohol (70%) sterilization methods on the surface morphology of acrylonitrile–butadiene–styrene (ABS) specimens using a novel SEM (Scanning Electron Microscope) image processing approach. Twelve 3D-printed specimens were prepared, and five concentric circular regions of interest (ROIs) per specimen were analyzed. Three quantitative descriptors—defect area fraction, anisotropy ratio, and RMS (Root Mean Square) roughness—were extracted to assess surface alterations. To validate the image-based findings, EDX (Energy-Dispersive X-ray Spectroscopy) elemental analysis for carbon (C), nitrogen (N), and oxygen (O) was employed as a complementary and traditional benchmark technique. Statistical comparisons and p-value heat maps revealed strong convergence between SEM and EDX results. UVC sterilization consistently preserved surface morphology and elemental stability, showing the lowest defect fraction (p = 0.2684), balanced anisotropy (p = 0.02481), and minimal oxygen incorporation (O = 7.6). Foam sterilization produced intermediate effects, with significant anisotropy changes (p = 0.007456) and reduced nitrogen (19.6). Alcohol sterilization induced the most severe damage, characterized by high defect density, increased roughness, and elemental imbalance (N = 17.3, O = 13.9), confirming oxidative degradation. The convergence of SEM and EDX outcomes demonstrates that SEM image processing is a reliable novel method validated by traditional elemental analysis. Together, these approaches provide a robust framework for ranking sterilization efficacy, with UVC identified as the most favorable method, detergent foam as an acceptable alternative, and alcohol as the least effective due to its destabilizing effects. Full article

Germanium (Ge) has long been regarded as a promising channel material, owing to its superior carrier mobility and highly tunable electronic band structure. The new generation of low-power electronics is approaching the formation of fully depleted (FD) transistors on Si-on-insulator (SOl) and Ge-on-insulator (GOl) substrates. In this work, we present a full process of a novel FDGOI transistor formed on a strained GOI with low defect density. This scalable and industry-compatible approach enables the formation of uniform 50 nm thick Ge layers by using spinning wet etch with ultrasmooth surfaces (RMS roughness = 0.262 nm) and a low etch-pit density of ~10⁵ cm⁻². Electrical measurements reveal excellent carrier transport properties, with back-gate (BG) transistors achieving mobilities of 550–600 cm²/V·s, while front-gate (FG) devices exhibit sharp switching behavior and steep subthreshold slopes, yielding I_ON/I_OFF ratios up to 10⁵. Temperature-dependent measurements further demonstrate a pronounced enhancement of device performance: the I_ON/I_OFF ratio increases to 106, the subthreshold swing (SS) decreases from 179 mV/dec at room temperature to 137 mV/dec at 120 K, and the threshold-voltage shift with temperature is as low as 1.87 mV/K across the range of 30–300 K. Such behavior highlights the potential of band-gap engineering for precise threshold-voltage control. Taken together, these results establish GOI as a CMOS-compatible material platform and provide a solid technological basis for the development of next-generation low-power transistors beyond conventional CMOS scaling. Full article

The ODYSEA (Ocean DYnamics and Surface Exchange with the Atmosphere) mission will provide simultaneous two-dimensional measurements of currents and winds for the first time. According to the ODYSEA radar concept, with a high incidence angle, current noise is primarily driven by backscattered power, which is triggered by wind speed. Therefore, random noise will affect the quality of observations. In low wind conditions, the absence of surface roughness increases the noise level considerably, to the point where the measurement becomes unusable, as the error can exceed 3 m/s at 5 km posting compared to mean current amplitudes of tens of cm/s. Winds higher than 7.5 m/s enable current measurements at 5 km posting with an RMS accuracy below 50 cm/s, but derivatives of currents will amplify noise, hampering the understanding of ocean dynamics and the interaction between the ocean and the atmosphere. In this context, this study shows the advantages and limitations of using noise-reduction algorithms. A convolutional neural network, a UNet inspired by the work of the SWOT (Surface Water and Ocean Topography) mission, is trained and tested on simulated radial velocities that are representative of the global ocean. The results are compared with those of classical smoothing: an Adaptive Gaussian Smoother whose filtering transfer function is optimized based on local wind speed (e.g., more smoothing in regions of low wind). The UNet outperforms the kernel smoother everywhere with our simulated dataset, especially in low wind conditions (SNR << 1) where the smoother essentially removes all velocities whereas the UNet mitigates random noise while preserving most of the signal of interest. Error is reduced by a factor of 30 and structures down to 30 km are reconstructed accurately. The UNet also enables the reconstruction of the main eddies and fronts in the relative vorticity field. It shows good robustness and stability in new scenarios. Full article

The fatigue of wood mortise–tenon (M–T) joints commonly results from the looseness of the joints when subjected to long-term cyclic load. It is of critical importance to comprehensively understand the fatigue of M–T joints to know what occurs in M–T joints However, fatigue evolution progression (FEP) of M–T joints has been rarely studied. This study mainly aimed to investigate the FEP of the roughness of mortise (R_M) and tenon (R_T), and the friction coefficient of the non-glued round-end beech wood M–T joint when subjected to cyclic load to provide basic data for numerically modelling the FEP of the M–T joint. The effects of cyclic load amplitude (CLA) (150 N, 200 N, 250 N, and 300 N) and cyclic load count (CLC) (25%, 50%, 75%, and 100% fatigue life) on R_M, R_T, and the friction coefficient were investigated. The results demonstrate that the CLA and CLC have significant effects on R_M, R_T, and the friction coefficient of the M–T joint. The R_M, R_T, and friction coefficient of the M–T joint decrease non-linearly as the CLA and CLC increase, complying with the power law function. The R_M, R_T, and friction coefficient of M–T joints are reduced by a large margin within the CLC of the initial 25% fatigue life, and these reductions decelerate from a CLC of 75% to 100% for all CLAs. The relationships between the friction coefficient and R_M and R_T at each CLA can be well fitted by a quadratic model during FEP. This study provides a new insight to comprehensively understand the FEP of the round-end M–T joint and supplies basic data for numerically modelling the FEP of the M–T joint. Full article

The single-crystal diamond (SCD) possessing both favorable dielectric properties and low stress is esteemed as the ideal material for terahertz windows. The intrinsic step-like growth pattern of SCD can easily lead to stress concentration and a decrease in dielectric performance. In this study, a “two-step method” was designed to optimize the growth mode of SCD. A novel large platform growth pattern has been achieved by controlling diamond seed crystal etching and the epitaxial layer growth process. The experimental results indicate that, compared with the traditional step-like growth model, the root mean square (RMS) roughness of as-prepared SCD reduced from 5 nanometers (step growth) to 0.4~1.0 nanometers (platform growth) within a 5 μm × 5 μm area. Furthermore, the growth step height difference diminished from 30 nm to 3~4 nm, thereby mitigating stress induced by steps to a mere 0.1976 GPa. Additionally, at frequencies ranging from 0.1 to 3 THz, the diamond windows exhibit lower refractive index, dielectric constant, and dielectric loss. Finally, large platform growth effectively reduces phenomena such as dislocation pile-up brought about by step growth, achieving low-damage ultra-precision machining of diamond windows measuring 1 mm in diameter. Full article

Wearable and skin-mounted electronics demand encapsulation designs that simultaneously provide strong barrier performance, mechanical reliability, and transferability under ultrathin conditions. In this study, a residual stress-balanced transferable encapsulation platform was developed by integrating a urethane-based copolymer superstrate [p(IEM-co-HEMA)] with inorganic thin films. The polymer, deposited via initiated chemical vapor deposition (iCVD), offered over 90% optical transmittance, low RMS roughness (1–3 nm), and excellent solvent resistance, providing a stable base for inorganic barrier integration. An ALD Al₂O₃/ZnO nano-stratified barrier initially delivered effective moisture blocking, but tensile stress accumulation imposed a critical thickness of 30 nm, where the WVTR plateaued at ~2.5 × 10⁻⁴ g/m²/day. To overcome this limitation, a 40 nm e-beam SiO₂ capping layer was added, introducing compressive stress via atomic peening and stabilizing Al₂O₃ interfaces through Si–O–Al bonding. This stress-balanced design doubled the critical thickness to 60 nm and reduced the WVTR to 3.75 × 10⁻⁵ g/m²/day, representing an order-of-magnitude improvement. OLEDs fabricated on this ultrathin platform preserved J–V–L characteristics and efficiency (~4.5–5.0 cd/A) after water-assisted transfer and on-skin deformation, while maintaining LT80 lifetimes of 140–190 h at 400 cd/m² and stable emission for over 20 days in ambient storage. These results demonstrate that the stress-balanced encapsulation platform provides a practical route to meet the durability and reliability requirements of next-generation wearable optoelectronic devices. Full article

Wavefront aberrations caused by thermal flows or arising from the quality of optical components can significantly impair wireless communication links. Such aberrations may result in an increased error rate in the received signal, leading to data loss in laser communication applications. In this study, we explored a newly developed combined stochastic gradient descent optimization algorithm aimed at compensating for optical distortions. The algorithm we developed exhibits linear time and space complexity and demonstrates low sensitivity to variations in input parameters. Furthermore, its implementation is relatively straightforward and does not necessitate an in-depth understanding of the underlying system, in contrast to the Stochastic Parallel Gradient Descent (SPGD) method. In addition, a developed switch-mode approach allows us to use a stochastic component of the algorithm as a rapid, rough-tuning mechanism, while the gradient descent component is used as a slower, more precise fine-tuning method. This dual-mode operation proves particularly advantageous in scenarios where there are no rapid dynamic wavefront distortions. The results demonstrated that the proposed algorithm significantly enhanced the total collected power of the beam passing through the 10 μm diaphragm that simulated a 10 μm fiber core, increasing it from 0.33 mW to 2.3 mW. Furthermore, the residual root mean square (RMS) aberration was reduced from 0.63 μm to 0.12 μm, which suggests a potential improvement in coupling efficiency from 0.1 to 0.6. Full article

Semi-rigid tool polishing is widely used in the high-precision manufacturing of electroless nickel surface due to its stable material removal and high efficiency in correcting mid- and high-frequency profile errors. However, predicting mid-frequency errors remains challenging due to the complexity of their underlying sources. In this study, a theoretical model for semi-rigid tool polishing was developed based on multi-scale contact theory, incorporating a bridging model, rough surface contact, and Hertzian contact mechanics. The model accounts for the effects of tool surface roughness, polishing force, and path spacing. A series of experiments on diamond-turned electroless nickel mirrors was conducted to quantitatively evaluate the model’s feasibility and accuracy. The results demonstrate that the model can effectively predict mid-frequency errors, reveal the material removal mechanisms in semi-rigid polishing, and guide the optimization of process parameters. Ultimately, a surface with mid-frequency errors of 0.59 nm Rms (measured over a 1.26 mm × 0.94 mm window) was achieved, closely matching the predicted value of 0.64 nm. Full article

The polymer deposition layer (PDL) formed during inductively coupled plasma (ICP) processing significantly limits the figuring accuracy and surface quality of fused silica optics. This study investigates the formation mechanism, composition, and evolution of the PDL under varying dwell times and proposes an innovative dwell time gradient strategy to suppress roughness deterioration. A significant disparity in hardness and elastic modulus between the deposition layer and the substrate is revealed, explaining its preferential removal and protective buffering effect in computer-controlled optical surfacing (CCOS). A hybrid ICP-CCOS polishing process was developed for processing a ϕ100 mm fused silica mirror. The results show that within 33 min, the surface graphic error RMS was significantly reduced from 58.006 nm to 12.111 nm, and within 90 min, the surface roughness was ultra-precisely reduced from Ra 1.719 nm to Ra 0.151 nm. The average processing efficiency was approximately 0.63 cm²/min. Critically, a damage-free, ultra-smooth surface without subsurface damage (SSD) was successfully achieved. This hybrid process enables the simultaneous optimization of figure accuracy and roughness, eliminating the need for iterative figuring cycles. It provides a novel theoretical framework for high-precision figuring and post-ICP polymer removal, advancing the efficient fabrication of high-performance optics. Full article

As smart cities evolve, integrating new technologies into school transportation is becoming increasingly important to ensure student comfort and safety. Monitoring and enhancing comfort during daily commutes can significantly influence well-being and learning readiness. However, most existing research addresses isolated factors, which limits the development of comprehensive and scalable solutions. This study presents the design and implementation of a low-cost, generalized IoT-based system for monitoring comfort in school transportation. The system processes multiple environmental and operational signals, and these data are transmitted to a cloud computing platform for real-time analysis. Signal processing incorporates standardized metrics, such as root mean square (RMS) values from ISO 2631-1 for vibration assessment. In addition, machine learning techniques, including a Random Forest classifier and ensemble-based models, are applied to classify ride comfort levels using both road roughness and environmental variables. The results show that stacked multisensor fusion achieved a significant improvement in classification performance compared with vibration-only models. The platform also integrates route visualization with commuting time per student, providing valuable information to assess the impact of travel duration on school mobility. Full article

The study investigates the influence of bias voltage on the structural and morphological properties of aluminum nitride AlN (002) thin films deposited on sapphire substrates via reactive magnetron sputtering for high-frequency surface acoustic wave (SAW) devices. The results indicate that applying a positive bias voltage (>0 V) yields AlN films with compact and uniform surfaces. As bias increases, the deposition rate initially rises before declining, while root–mean–square (RMS) roughness progressively decreases, reaching a minimum at 100 V, significantly enhancing surface quality. X-ray diffraction (XRD) analysis reveals enhanced (002) preferential orientation with increasing bias, indicating improved crystallinity. These findings demonstrate that optimized bias voltage not only refines surface morphology but also strengthens crystal alignment, particularly along the (002) plane, making AlN films highly suitable for high-frequency SAW applications, and provides data for the preparation of higher-quality AlN films. Full article

Carrying out automobile stability and dynamic comfort involves a close examination of engine performance, such that fault detection at the early stage must be of the highest priority to reliability and effectiveness. The study evaluates the impact of malfunctions in mass air flow (MAF) sensors on diesel engine performance and stability, particularly on vibratory emissions. Employing experimental methods, defect and normal engine vibrations were analyzed in both time-domain and frequency spectral domain methodologies. Some statistical values, such as root mean square (RMS), kurtosis, mean, standard deviation, clearance factor, and shape factor, were employed to compare and characterize the vibration pattern. The results indicate that malfunctions in the MAF sensor are characterized by striking vibration amplitude enhancement and instability at high engine revolutions. These defects cause poor starting, misfire, and rough engine running, which affect combustion efficiency. Conclusions show excellent correlation among MAF sensor fault, combustion activity, and engine vibration, and this confirms the need for fault detection at the initial stage. With its enhancement in vibration analysis diagnostic capability, this contribution is significant to condition monitoring and predictive maintenance activities. Lastly, the study contributes to improving engine reliability, efficiency in operation, and performance overall in the automotive industry. Full article

With the increasing demand for high-performance ceramic guideways in precision industries, accurate flatness measurement of large-scale, rough ceramic surfaces remains challenging. This paper proposes a novel method combining oblique-incidence laser interferometry and sub-aperture stitching to overcome limitations of conventional techniques. The oblique-incidence approach enhances interference signal strength on low-reflectivity surfaces, while stitching integrates high-resolution sub-aperture measurements for full-surface characterization. Numerical simulations validated the method’s feasibility, showing consistent reconstruction of surfaces with flatness values of 1–20 μm. Experimental validation on a 1050 mm × 130 mm SiC guideway achieved a full-surface measurement with PV 2.76 μm and RMS 0.59 μm, demonstrating high agreement with traditional methods in polished regions. The technique enabled quick monitoring of a 39-h lapping process, converging flatness from 13.97 μm to 2.76 μm, proving its efficacy for in-process feedback in ultra-precision manufacturing. Full article

The main goal of this study was to investigate the properties of ZnO thin films, including pure films and those doped with indium (up to 8 mol%) that was deposited using a spray pyrolysis technique on glass and silicon substrates in order to prepare the position-sensitive structure, Si-SiO₂-ZnO:In. To this aim, the present work is focused on investigating the effect of indium concentration on the morphology, structure, and optical properties of the films. X-ray diffraction (XRD) analysis reveals a wurtzite polycrystalline structure. Scanning electron microscopy (SEM) images display a smooth and uniform surface characterized by closely packed nanocrystalline clusters. As the indium concentration rises to 8 mol%, the number of nuclei grows, resulting in uniformly distributed grains across the entire substrate surface. The estimated root mean square (RMS) roughness values for the thin films undoped and doped with 3 mol%, 5 mol%, and 8 mol% of ZnO measured using AFM are 6.13, 9.64, and 13.76 nm, respectively. The increase in indium concentration leads to a slight decrease in film transmittance. The measured LPV photosensitivity of about 44 mV/mm confirms the potential use of these thin films in practical applications. Full article