Search Results (91)

With the rapid advancement of high-precision optical systems, increasingly stringent demands are imposed on the surface figure accuracy of optical components. The magnitude of residual stress in multilayer films directly influences the post-coating surface figure stability of these components, making the control of multilayer film stress a critical factor in enhancing optical surface figure accuracy. In this study, which addresses the process constraints and substrate damage risks associated with conventional annealing-based stress compensation for large-aperture optical components, we introduce an active stress engineering strategy rooted in in situ deposition process optimization. By systematically tailoring film deposition parameters and adjusting the thickness modulation ratio of TiO₂ and SiO₂, we achieve dynamic compensation of residual stress in multilayer structures. This approach demonstrates broad applicability across diverse optical coatings, where it effectively mitigates stress-induced surface distortions. Unlike annealing methods, this intrinsic stress polarity manipulation strategy obviates the need for high-temperature post-processing, eliminating risks of material decomposition or substrate degradation. By enabling precise nanoscale stress regulation in large-aperture films through controlled process parameters, it provides essential technical support for manufacturing ultra-precision optical devices, such as next-generation laser systems and space-based stress wave detection instruments, where minimal stress-induced deformation is paramount to functional performance. Full article

Large-fruited cranberry (Vaccinium macrocarpon Aiton) is a species known for its highly valued fruit and is typically propagated vegetatively through the rooting of stem cuttings. Studies on the rooting of stem cuttings of large-fruited cranberry have shown that the morphological traits of the root system are a key indicator of the effectiveness of this process. To support rooting, gel coatings based on polysaccharides and containing auxins, especially the indole-3-butyric acid (IBA) W4 variant, were developed and applied. These significantly influenced root length (increase of 44.6% compared to control W0), surface area (increase of 32.4% compared to W0), volume (increase of 26.7% compared to W0), and average thickness, which translated into better nutrient uptake and a higher degree of plant nourishment. The W4 coating, combining mineral components, polysaccharides, and IBA, reduced transpiration and maintained moisture, promoting effective rooting. The associated metabolic changes were confirmed by analyses of oxidative stress markers and chlorophyll fluorescence. The study demonstrated that enhanced root system development was closely linked with the increased accumulation of macro- and micronutrients in the aerial parts of the plants, directly contributing to improved growth and potential yield. These findings highlight that effective rooting—achieved through the targeted metabolic stabilisation of the rooting environment—is essential for the successful vegetative propagation of large-fruited cranberry. Full article

The use of zinc oxide nanoparticles (ZnO-NPs) is a promising strategy to enhance zinc availability and promote plant growth due to their physicochemical properties and biocompatibility. This study evaluated the effects of ZnO-NP morphology (spherical and hexagonal), maltodextrin (MD) surface coating, and a concentration range of 0–2000 mg L⁻¹ on growth and gas exchange in bell pepper seedlings. ZnO-NPs increased seedling height, especially at 750 and 1000 mg L⁻¹ for MD-coated spherical NPs and at 250 and 500 mg L⁻¹ for MD-coated hexagonal NPs. Spherical NPs also enhanced stem diameter, root length, and the dry weight of roots and stems. Leaf dry weight was highest with MD-coated spherical NPs, while hexagonal forms had milder effects. Dose–response analysis revealed that, with the exception of hexagonal MD-coated NPs, the total dry weight of seedlings stabilized at concentrations ranging 219.6 to 313.6 mg L⁻¹. Gas exchange parameters were significantly influenced by the evaluated factors. Uncoated hexagonal NPs at 1500 mg L⁻¹ increased the photosynthetic rate by 239%. MD coating improved performance, particularly in spherical NPs at 750 and 1000 mg L⁻¹. The transpiration rate rose with MD-coated hexagonal NPs at 500–2000 mg L⁻¹, and SPAD units increased with both morphologies. Overall, this study confirms that ZnO-NP morphology and surface coating play key roles in enhancing growth and physiological responses in bell pepper seedlings. Full article

This study aims to develop a stress-optimized ultra-broadband beam-splitting coating that integrates four spectral bands by analyzing the beam-splitting properties of coatings spanning visible to medium and long-wave infrared regions. A beam-splitting coating was deposited on a Ge substrate using ion-beam-assisted thermal evaporation, employing Ge, ZnS, and YbF₃ as coating materials. The designed coating exhibits high reflectance in the 0.5–0.8 μm and 0.9–1.7 μm wavelength bands while maintaining high transmittance in the 3–5 μm and 8–12 μm bands. The optimal deposition process for a single-layer coating was established, at a 45° incidence angle, the beam-splitting coating achieved an average reflectance (Rave) of 86.6% in the 0.9–1.7 μm band and 93.7% in the 0.9–1.7 μm band, alongside an average transmittance (Tave) of 91.36% in the 3–5 μm band and 91.3% in the 8–12 μm band. The antireflection coating achieved a single-side Tave of 98.5% in the 3–5 μm band and 97% in the 8–12 μm band. The coating uniformity exceeded 99.6%. To optimize the surface profile, a single-layer Ge coating was added to the rear surface, resulting in a root mean square deviation of less than 0.0007 μm, achieved the same precision of the surface profile successfully. The deposited beam-splitting coating possessed high surface profile precision, and successfully achieved high reflectance in the visible to short-wave infrared range and high transmittance in the medium- and long-wave infrared range. The coating demonstrated excellent adhesion, abrasion resistance, and structural integrity, with no wrinkling, cracking, or delamination. Full article

Tungsten Inert Gas (TIG) welding is a widespread welding process used in the industry for high-quality joints. However, this welding process suffers from lower productivity. Activated Tungsten Inert Gas (ATIG) is a variant of the TIG that aims to increase the depth penetration capability of conventional TIG welding. This is achieved by applying a thin coating of activating flux material onto the workpiece surface before welding. This work investigates the effect of the thermophysical properties of individual metallic oxide fluxes on 316L stainless steel weld morphology. Four levels of current intensity (120, 150, 180, 200 A) are considered. The weld speed up to 15 cm/min and arc length of 2 mm are maintained constant. Thirteen oxides were tested under various levels of current intensity in addition to multiple thermophysical properties combinations, and the depth penetration (D) and the aspect ratio (R) were recorded. This process has provided 52 combinations (13 oxides * 4 currents). Based on the numerical observations, linear and nonlinear models for describing the effect of the thermophysical parameters on the weld characteristics were tuned using a particle swarm optimization algorithm. While the linear model provided good prediction accuracy, the nonlinear exponential model outperformed the linear one for the depth yielding a mean absolute percentage error of 17%, a coefficient of determination of 0.8266, and a root mean square error of 0.9665 mm. The inverse optimization process, where the depth penetration ranged from 1.5 mm to 12 mm, thus covering a large spectrum of industries, the automotive, power plants, and construction industries, was solved to determine the envelopes’ lower and upper limits of optimal oxide thermophysical properties. The results that allowed the design of the fluxes to be used in advance were promising since they provided the oxide designer with the numerical ranges of the oxide components to achieve the targeted depths. Future directions of this work can be built around investigating additional nonlinear models, including saturation and dead-zone, to efficiently estimate the effect of the thermophysical properties on the welding process of other materials. Full article

In this study, a comprehensive machine learning (ML) model was developed to predict and optimize boride coating thickness on steel surfaces based on boriding parameters such as temperature, time, boriding media, method, and alloy composition. In a dataset of 375 published experimental results, 19 features were applied as inputs to predict the boride layer thickness in various steel alloys. ML algorithms were evaluated using performance metrics like Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and R². Among the ML algorithms tested, XGBoost exhibited the highest accuracy. XGBoost achieved an R² of 0.9152, RMSE of 29.57, and MAE of 18.44. Incorporating feature selection and categorical variables enhanced model precision. Additionally, a deep neural network (DNN) architecture demonstrated robust predictive performance, achieving an R² of 0.93. Experimental validation was conducted using 316L stainless steel (SS), borided at 900 °C and 950 °C for 2 h and 4 h. The DNN model effectively predicted the boride thickness under these conditions, aligning closely with the observed values and confirming the models’ reliability. The findings underscore the potential of ML to optimize boriding processes, offering valuable insights into the relationships between boriding parameters and coating outcomes, thereby advancing surface modification technologies. Full article

Understanding the influence of topography on wettability is essential for improving the modeling of superhydrophobic surfaces. Moreover, wetting predictions can foresee corrosion, biological contamination, self-cleaning properties, and all phenomena related to wetting. In this context, this research work reports the experimental corroboration of a novel theoretical model for stochastic surfaces that relates the static contact angle for the heterogeneous wetting of surfaces to the root mean square (RMS) slope of the surface structures, allowing wetting prediction through topography. For this study, hydrophobic and superhydrophobic alumina thin films with gradual roughness were constructed. The films were deposited on glass using the dip-coating technique, textured with boiling water, and functionalized to achieve low surface energy using Dynasylan F-8815. Surface wettability was characterized using the sessile drop technique, and the RMS slope of the alumina surfaces was quantified using the atomic force microscopy (AFM) technique. The model, presented here for the first time, fits the experimental data, allowing wetting prediction for hydrophobic and superhydrophobic surfaces considering static contact angles. As expected, topography plays a fundamental role in achieving superhydrophobicity. Therefore, defining a topographic criterion, as performed here, for obtaining superhydrophobic surfaces is highly relevant to reduce the production costs of these surfaces and also enable new production processes and designs. Full article

Depending on the obturation technique, the tooth and surrounding tissues may heat up during root canal filling, particularly with warm methods. This study aimed to analyze the temperature increase in the periradicular and -apical region during various warm obturation techniques with a present simulated periodontal blood flow. Seventy-five extracted human teeth were shortened to 11 mm (cut-grinder Primus diamond cutting device; Walter Messner GmbH, Oststeinbek, Germany) and prepared using the ProTaper Gold system (Dentsply Sirona Inc., Charlotte, NC, USA) ISO size 40/.06. Specimens were prepared to ensure stable fluid circulation in an artificially created periodontal space, and the procedure was recorded with a thermal infrared camera (VarioCAM HD; InfraTec GmbH Infrarotsensorik und Messtechnik, Dresden, Germany). The following obturation methods were applied: I, cold single-cone obturation (control group); II, gutta-percha-coated rigid carrier technique (GuttaFusion); III, squirting technique (injection technique); IV, continuous wave technique; and V, Schilder technique. Statistical analysis was performed using the Kruskal–Wallis test, followed by the Mann–Whitney pairwise test using the sequential Bonferroni procedure for significant differences (p < 0.05). The Schilder technique with 0 mL/min showed the lowest temperature change, with a median of 0.00 °C (max. 0.00 °C, min. 0.00 °C, IQR 0.00 °C). In contrast, the continuous wave technique at a circulation rate of 2.6 mL/min exhibited the highest temperature change, with a median of 3.76 °C (max. 5.33 °C, min. 2.42 °C, IQR 1.46 °C). Although warm obturation techniques can increase surface temperature, none of the methods produced changes that were potentially damaging to the periodontium or surrounding bone. Full article

Green structures, such as green roofs or green façades, are great examples of climate change mitigation. Their impact is mainly focused on roofs in the area of overheating reduction. In this paper, initial measurement results of a green façade experimental test setup are provided. The green façade uses an innovative board from recycled materials with vegetation rooted directly on the board. The tested green façade is divided into three segments. These segments differ from each other in their watering regimes, which are crucial for cooling effectiveness. Watering operates with the assistance of gravity; water flows from the top gutter through the boards. In this paper, these three segments are compared to each other with respect to temperatures on the surface of a regular external thermal insulation composite system façade (ETICS) during two summer days. The green façade showed an impact on the temperature in the ventilated air gap, where the temperature is almost the same as the outdoor air temperature in the morning with direct solar radiation on the façade and lower than the outdoor air temperature in the afternoon. At the peaks, the surface temperatures within the air cavity surface are up to 8 °C lower than those on a new white ETICS coating. This demonstrates a cooling potential, although the surface temperatures are always higher than the outdoor air temperatures during daylight hours. Full article

Fusarium spp. can cause root rot in alfalfa, leading to the death of the whole plant, which seriously affects the yield and quality of alfalfa. This study used a Fusarium acuminatum strain labeled with green fluorescent protein (GFP) to observe the infection process of F. acuminatum on alfalfa by confocal fluorescence microscopy. The aim of this study was to reveal the infection mechanism of alfalfa Fusarium root rot at the cellular histological level. The results showed that conidia of F. acuminatum attached to the surface of the root and germinated at one day post-inoculation, the mycelium then entered the vascular bundle tissue of the alfalfa root at 5 days post-inoculation, reached the base of the plant stem at 14 days post-inoculation, and colonized the stem of the first and second compound leaf at 28 and 49 days post-inoculation, respectively. Moreover, the experiment, which sprayed a spore suspension, showed that the conidia of F. acuminatum could spread through the air to infect the pericarp and seed coat tissue of the pod. For the first time, we report the infection process of alfalfa Fusarium root rot caused by F. acuminatum and clarify that F. acuminatum can initially infect the root tissue of alfalfa, colonize the bottom stem of the plant through systematic infection, and eventually cause the plant to wilt and die. The results reveal the infection mechanism of F. acuminatum at the cell level via histology and provide theoretical support for the development of control strategies and key control technologies for alfalfa root rot. Full article

Wheat sharp eyespot is a prevalent soil-borne disease that causes substantial economic losses in agriculture. Metconazole, a new triazole broad-spectrum fungicide, has demonstrated effective control of soil-borne diseases. Multi-walled carbon nanotubes (MWCNTs) are an innovative adsorbent material known for their large surface area and high absorptive capacity. This study identifies MWCNTs as the optimal adsorption material for metconazole, achieving an adsorption rate of 85.27% under optimal conditions (stirring time of 30 min and feeding ratio of 6:1). The optimized formula consists of 1.5% dispersant sodium wood, 1% emulsifier BY-112, 2% AEO-15, 3% glycol, 3% filmogen, and 4% red dyes. A 0.5% MWCNT–metconazole suspension concentrate for seed coating (FSC) significantly enhances the inhibitory effect of metconazole on wheat growth and promotes root development. At the tillering stage, a coating ratio of 1:100 shows a marked impact on wheat growth, and MWCNTs can improve the control effect of metconazole to Rhizoctonia cerealis. This work offers a novel approach for applying metconazole in a wheat suspension concentrate for seed coating. Full article

Agrochemicals can now be protected from harsh environments like pH, light, temperature, and more with the help of a drug-loading system. This has allowed the creation of targeted and continuous release functions for pesticides and fertilizers, as well as the precise application, reduction, and efficiency of agrochemicals. All of these benefits have been made possible by the recent advancements in the field of nanomaterials. A simple procedure known as electrospinning can be used to create nanofibers from natural and synthetic polymers. Nanofibers have come to be recognized as one of the sustainable routes with enormous applicability in different fields. In agriculture, a promising strategy may entail plant protection and growth through the encapsulating of numerous bio-active molecules as pesticides and fertilizers for intelligent administration at the desired places. Owing to their permeability, tiny dimensions, and large surface area, nanofibers can regulate the rate at which agrochemicals are released. This slows down the rate at which the fertilizer dissolves and permits the release of coated fertilizer gradually over time, which is more effectively absorbed by plant roots, as well as the efficiency of pesticides. Thus, modern agriculture requires products and formulations that are more efficient and environmentally friendly than traditional agrochemicals. In addition to highlighting the significance and originality of using nanofibers and offering a brief explanation of the electrospinning technology, the review article’s main goal is to provide a thorough summary of the research leading to breakthroughs in the nanoencapsulation of fertilizers and pesticides. Full article

This contribution attempts to provide a state-of-the-art account of the physicochemical and biomedical properties of the plasma-sprayed hydroxylapatite (HAp) coatings that are routinely applied to the surfaces of metallic endoprosthetic and dental root implants designed to replace or restore the lost functions of diseased or damaged tissues of the human body. Even though the residence time of powder particles of HAp in the plasma jet is extremely short, the high temperature applied induces compositional and structural changes in the precursor HAp that severely affect its chemical and physical properties and in turn its biomedical performance. These changes are based on the incongruent melting behavior of HAp and can be traced, among many other analytical techniques, by high resolution synchrotron X-ray diffraction, vibrational (Raman) spectroscopy, and nuclear magnetic resonance (NMR) spectroscopy. In vivo reactions of the plasma-sprayed coatings to extracellular fluid (ECF) can be assessed and predicted by in vitro testing using simulated body fluids (SBFs) as proxy agents. Ways to safeguard the appropriate biological performance of HAp coatings in long-term service by controlling their phase content, porosity, surface roughness, residual stress distribution, and adhesion to the implant surface are being discussed. Full article

Root caries caused by cariogenic bacteria are a burden on a large number of individuals worldwide, especially the elderly. Applying a protective coating to exposed root surfaces has the potential to inhibit the development of caries, thus preserving natural teeth. This study aimed to develop a novel antibacterial coating to combat root caries and evaluate its effectiveness using the antibacterial monomer dimethylaminohexadecyl methacrylate (DMAHDM). DMAHDM was synthesized and incorporated into a resin consisting of 55.8% urethane dimethacrylate (UDMA) and 44.2% TEG-DVBE (UV) at a 10% mass fraction of glass filler. Multiple concentrations of DMAHDM were tested for their impact on the resin’s mechanical and physical properties. S. mutans biofilms grown on resin disks were analyzed for antibacterial efficacy. Cytotoxicity was assessed against human gingival fibroblasts (HGFs). The results showed an 8-log reduction in colony-forming units (CFUs) against S. mutans biofilm (mean ± sd; n = 6) (p < 0.05) when 5% DMAHDM was incorporated into the UV resin. There was a 90% reduction in metabolic activity and lactic acid production. A low level of cytotoxicity against HGF was observed without compromising the physical and mechanical properties of the resin. This coating material demonstrated promising physical properties, potent antibacterial effects, and low toxicity, suggesting its potential to protect exposed roots from caries in various dental procedures and among elderly individuals with gingival recession. Full article

This study begins by conducting side milling experiments on SKD11 using tungsten carbide TiAlN-coated end mills to compare the surface roughness performance between two combinations of milling process parameters (feed rate and radial depth of cut), along with three ultrasonic-assisted methods (rotary, dual-axis, and rotary combined with dual-axis). The results suggest that the rotary (z-axis oscillation) ultrasonic-assisted method may provide better performance. Subsequently, this superior ultrasonic-assisted method was applied both with and without laser locally preheating assistance, respectively. Using a Taguchi orthogonal array, milling process parameters (spindle speed, feed rate, and radial depth of cut) were planned for experiments with the same cutting tool and the workpiece just mentioned above. The surface roughness serves as the objective function while being constrained by cutting-tool life. The characteristics of the smaller-the-better in the Taguchi method were applied to determine the optimal combination of process parameters. Based on the optimal milling process parameters obtained and the superior hybrid-assisted method adopted, milling experiments were repeatedly performed to collect the data on cutting force and cutting-tool wear. Feature engineering was performed on the cutting force signals, and different domain characteristics from both the time and frequency domains were extracted. Hereafter, feature selection by random forest and data standardization were further applied to feature extractions, and the data processing was thus completed. For the processed data, a cutting-tool wear prediction model was constructed by ensemble learning. This method leverages various machine learning regression models, including decision tree, random forest, extremely randomized tree, light gradient boosting machine, extreme gradient boosting, AdaBoost, stochastic gradient descent, support vector regression, linear support vector regression, and multilayer perceptron. After hyper-parameter tuning, the ensemble voting regression prediction was performed based on these ten mentioned models. The experimental results demonstrate that the ensemble voting regression model surpasses the performance of each individual machine learning regression model. In addition, this regression model achieves a coefficient of determination (R²) of 0.94576, a root mean square error (RMSE) of 0.24348, a mean squared error (MSE) of 0.05928, and a mean absolute error (MAE) of 0.18182. Therefore, the ensemble learning approach has been proven to be a feasible and effective method for monitoring cutting-tool wear. Full article