Applied Research最新文献

This review comprehensively examines the durability issues and technological advancements of nickel-based alloys in high-temperature service conditions, focusing on oxidation, creep, thermal shock, and corrosion performance, as well as the underlying mechanisms of crack formation and suppression in laser cladding. It first explores the roles and limitations of alloy composition, microstructure control, and surface modification in enhancing high-temperature oxidation and creep resistance. Then, it thoroughly analyzes the impacts of thermal stress, solidification shrinkage, and elemental segregation during laser cladding on crack formation, and summarizes crack-suppression strategies like reducing dilution, adjusting laser energy density, altering scanning speed, and adding small amounts of Mo. The review notes that while nickel-based alloys show significant mechanical and chemical stability in high-temperature environments, they still face challenges in balancing microstructure and macro-properties, co-optimizing multiple properties, and controlling processing costs. Future research should focus on developing multi-scale, multi-physical, field-coupled theoretical models, finely tuning process parameters, and establishing unified evaluation standards to promote the widespread use of nickel-based alloys in key sectors like aviation and energy.

Traditional architectural methods are changing because of the widespread use of 3D printing technology in large-scale construction, offering new avenues for efficiency, sustainability, and innovative design. This review explores the latest advancements and strategic developments that are shaping this field. It features real-world examples of large-scale 3D-printed structures, highlighting the advantages such as cost efficiency, faster project delivery, and reduced material wastage. The review explores cutting-edge 3D printing systems designed for building and analyzes their strengths and weaknesses. Commonly used 3D printing methods, including contour crafting, concrete printing, and D-shape technology, are examined with a comparison of their performance, material adaptability, and scalability. The role of advanced numerical modeling techniques, such as computational fluid dynamics (CFD) and finite element method (FEM) simulations, is emphasized for optimizing process parameters, predicting material behavior and potential defects ensuring the structural integrity of 3D-printed structures. Additionally, the incorporation of machine learning (ML) techniques in 3D construction printing is also discussed. This exhibits how predictive algorithms and real-time monitoring enhance process efficiency, and adaptability by exhibiting their role in 3D design, process optimization, material properties detection and quality inspection of printed materials. Through the synthesis of current knowledge and identifying opportunities for further research, this paper aims to inspire the widespread application of 3D printing in the construction sector and pave the way for its continued evolution.

In the packaging sector, biobased and biodegradable materials have garnered increasing interest due to their potential to mitigate the environmental impact of fossil-based plastics. In pursuit of sustainable alternatives to plastic packaging, we present a novel approach utilizing ethyl cellulose (EC) and zinc oxide nanoparticles (ZnO NPs) to develop sustainable polymer nanocomposite films. These films, with uniform thickness (~65 µm) and varying ZnO NP weight percentages were synthesized via in situ synthesis and ultrasonication for uniform dispersion. Comprehensive assessments of surface structures, optical properties, mechanical strengths, and antimicrobial efficacies were conducted, revealing promising enhancements compared to EC films. FTIR revealed interactions between carboxyl groups of EC and ZnO NPs. XRD and HRTEM confirmed ZnO's hexagonal wurtzite structure with a particle size of 30–35 nm. FESEM images showed uniformly dispersed ZnONPs in the films. Energy dispersive X-ray (EDX) spectroscopy analysis validated the purity of ZnO nanoparticles and the homogeneity of the nanocomposite film. UV-visible spectroscopy indicated increased optical band gaps (up to 3.26 eV), augmenting their potential applications in energy sectors. Mechanical analysis showcased enhanced tensile strength (43.98 MPa). Moreover, a higher thermal stability (maximum degradation temperature of 335°C) was achieved. AFM illustrated improved hydrophobicity. Crucially, all composite films exhibited superior antibacterial properties against S. aureus and E. coli, as confirmed by FESEM analysis, underscoring their efficacy as antimicrobial packaging materials.

This study explores human enamel erosion to improve oral hygiene strategies. In 2020, UK households spent approximately 1.5 billion British pounds on dental services. Consuming sugary foods fosters bacterial plaque, creating an acidic milieu that attacks enamel. Here, dentists recommend brushing immediately. However, acidic foods and beverages reduce enamel hardness almost instantly. For this case, dentists recommend to wait 30 min before brushing. A paradox which justifies the question: What is the optimal oral hygiene routine for simultaneous ingestion of food containing sugar and acidic beverages? Using in-liquid nanoindentation and scanning electron microscopy, we investigated enamel erosion under different acidic milieus. Inspired by a Nature article on the discovery of enamel micropores, largely overlooked in dental research, we identified these structures as primary targets of erosion. Coupled with insights from biomimetic practices, we propose an innovative oral hygiene solution. We developed a model toothbrush enabling immediate postmeal use, featuring soft, hollow bristles filled with antibacterial agents like thymol. Regarding the efficiency in removing deposits that harbor bacteria this novel approach surpasses mouthwash–toothpaste combinations. Thus, we provide the first practical solution to the “sweet and sour” paradox, potentially reducing dental care costs and enhancing dental health outcomes.

The crystalline structure of semiconductor materials significantly alters their photophysical properties. Halide perovskites have rapidly become a cornerstone in optoelectronics due to their exceptional optoelectronic properties, including high absorption coefficients, long carrier diffusion lengths, and remarkable defect tolerance. The geometrical dimensionality of halide perovskites plays a crucial role in determining their optoelectronic properties, particularly in both steady-state and excited-state dynamics. However, the influence of dimensional tuning on the hot carrier dynamics and recombination pathways in methylammonium lead bromide (MAPbBr₃) perovskites remains insufficiently explored. In this study, we systematically investigate the impact of geometric dimensionality on the structural and excited-state properties of MAPbBr₃, ranging from bulk single crystals to nanocrystalline forms. Our results show that reducing the size from single crystals to nanocrystals (NCs) leads to a significant bandgap widening, from 2.16 eV to 2.74 eV, accompanied by a decrease in crystallite size. Ultrafast transient absorption spectroscopy reveals that hot carrier relaxation occurs more rapidly in NCs (13 ps) compared to polycrystalline thin films (39 ps). Furthermore, the carrier recombination lifetime is extended in bulk forms, which we attribute to band dispersion effects resulting from enhanced energy level overlaps as the material transitions from nanoscale to bulk dimensions. These findings provide critical insights into the role of dimensionality in tuning the photophysical behavior of halide perovskites, offering valuable guidance for their application in next-generation optoelectronic devices.

Thermal regulation in miniaturized electronics with heterogeneous heat generation profiles has emerged as a pivotal challenge for sustaining performance and reliability in next-generation technologies. To address these thermal challenges, this study explores an electronic cooling system combining nano-encapsulated phase change material (NEPCM) with convection–radiation coupling. The system features a partitioned cavity with three different heat-generating blocks, divided by a conductive plate into an open section (cooled by natural convection and radiation) and a porous closed section saturated with NEPCM. Using the Galerkin finite element method, cooling efficiency is analyzed across critical parameters: PCM properties (melting temperature T_f = 300–315 K, Stefan number Ste = 0.4–1), plate geometry (thickness e = 0.04–0.24 cm, displacement d = 2.7–3.6 cm), radiative effects (emissivity ε = 0.1–0.9), nanoparticle concentration (%), porous media (Da = 10⁻⁵–10⁻²) and the cavity inclination angle ($��\alpha �\; �=�\; �-�\; �9�\; �0^{°}�$ to $��9�\; �0^{°}�$). The findings reveal that the maximum temperatures of the blocks can vary significantly, with reductions exceeding 7% when key parameters, such as Darcy number and cavity inclination angle, are optimized. In contrast, other parameters have a more limited influence, resulting in variations not exceeding 2%. These insights highlight the importance of selecting appropriate parameters for enhanced thermal management in electronic applications.

Many manufacturers offer resins that are advertised as transparent. Transparent 3D printed parts are not only visually attractive, but this feature is often required for practical use, for example, in optical parts. The manufacturers themselves point out that achieving optimal light transmittance requires appropriate post-processing. In this study, we evaluate the transparency of 10 types of commercial 3D printing resins by measuring their light transmittance. Each resin was used to print sample tiles that were post-processed in eight different ways. The light transmittance of each sample was then measured using a commercial spectrophotometer to determine which post-processing methods yielded the best transmittance properties for flat objects printed using different resins. We also evaluate the impact of post-processing methods on the chromaticity measures and surface roughness of the sample tiles. Finally, we assess the effect of samples' exposure to direct sunlight by comparing light transmittance measurements taken at two different time points. Our results show that to ensure the highest level of transparency, it is crucial to coat the parts with a layer of clear varnish. For such samples, transmittance averages nearly 24% higher than for the unvarnished ones.

This paper addresses the growing need for efficient and precise automated testing of automotive electronic control units (ECUs), specifically focusing on the NIO NV11 massage seat controller. Traditional manual testing methods suffer from significant inefficiencies and accuracy limitations, while existing automated systems lack specialized load modeling and seamless integration with manufacturing execution systems (MES). The proposed solution aims to bridge these gaps through a comprehensive testing framework. The system integrates hardware and software components to enable end-to-end automation. The hardware core consists of an industrial computer (IPC) interfacing via the local interconnect network (LIN) bus, complemented by a Flash burning module, LIN communication interface, and programmable power supply. A custom test fixture facilitates uninterrupted transitions from functional verification to data uploading, while digital instrumentation ensures fine-grained testing precision. The software architecture leverages intelligent algorithms for adaptive parameter adjustment and real-time data analysis. Experimental results demonstrate notable performance improvements: testing time is reduced by ~30% compared to traditional methods, while error rates decrease by around 20%, ensuring high repeatability and accuracy. The system's modular design enables straightforward adaptation to other automotive ECUs, such as anti-lock braking systems (ABS) and electronic stability programs (ESP), with minimal modifications. Industrial deployment has validated its ability to enhance testing efficiency, reliability, and flexibility in meeting evolving automotive quality control demands. This study contributes a robust automated testing framework that combines hardware-software integration with intelligent algorithms, addressing critical gaps in existing solutions. The system's scalability and adaptability position it as a valuable asset for advancing ECU testing in the automotive industry, with future developments targeting AI-driven predictive maintenance and expanded application scenarios. The abbreviations are shown in the “Abbreviations” section.