Search Results (128)

The manufacture of lightweight components is one of the most important requirements in the automotive and aerospace industries. Gears, on the other hand, are among the heaviest parts in terms of their total weight. Accordingly, a spur gear was considered, the body of which was configured as a lattice structure to make it lightweight. In addition, the structure was optimized by topology optimization using ProTOP software. Subsequently, the gear was manufactured by a selective laser melting process by using a strong and lightweight material, namely Ti-6Al-4V. This study defeated the problems of manufacturing orientation, surface roughness, support structure, and bending due to the high thermal gradient in the selective laser melting process. To experimentally investigate the benefits of such a lightweight gear body structure, a new test rig with a closed loop was developed. This rig enabled measurements of strains in the gear ring, hub, and tooth root. The experimental results confirmed that a specifically designed and selectively laser-melted, lightweight cellular lattice structure in the gear body can significantly influence strain. This is especially significant with respect to strain levels and their time-dependent variations in the hub section of the gear body. Full article

This paper introduces new structures ($\mathcal{DV}$, $\mathcal{FL}$) on a set $\mathrm{\Xi }$. They will be known as diving structures and floating structures. The pairs $(\mathrm{\Xi },\mathcal{DV})$, $(\mathrm{\Xi },\mathcal{FL})$ will be called diving spaces and floating spaces, respectively. These structures are not related to each other and are not related to any of the previous common structures such as topology, ideal, filter, grill or primal. We study some properties to characterize these new notions. Separation axioms and connectedness will be defined in these new spaces. When $\mathbb{R}$ is an equivalence relation on $\mathrm{\Xi }$, rough sets in diving spaces and rough sets in floating spaces will also be defined. Thus, $(\mathrm{\Xi },\mathbb{R},\mathcal{DV})$ and $(\mathrm{\Xi },\mathbb{R},\mathcal{FL})$ are called the diving approximation spaces and the floating approximation spaces, respectively. Full article

Cellulose nanofibril (CNF) is a sort of novel nanomaterial directly extracted from plant resources, inheriting the advantages of cellulose as a cheap, green and renewable material for the development of new-generation eco-friendly electronics. In recent years, CNF-based triboelectric nanogenerator (TENG) has attracted increasing research interests, as the unique chemical, morphological, and electrical properties of CNF render the device with considerable flexibility, mechanical strength, and triboelectric output. In this study, we explore the use of isoreticular metal-organic frameworks (IRMOF) as functional filler to improve the performance of CNF based TENGs. Two types of IRMOFs that own the same network topology, namely IRMOF-1 and its aminated version IRMOF-3, are embedded with CNF to fabricated TENGs; their contribution to triboelectric output enhancement, including the roughness effect induced by large particles as well as the charge induction effect arisen from -NH₂ groups, are discussed. The performance-enhanced CNF-based TENG with 0.6 wt.% of IRMOF-3 is utilized to harvest mechanical energy from human activities and charge commercial capacitors, from which the electrical energy is sufficient to light up light-emitting diodes (LEDs) and drive low-power electronic devices. In addition, a locomotor analysis system is established by assembling the above TENGs and capacitors into a 3 × 3 sensing array, which allowed signal extraction from each sensing unit to display a motion distribution map. These results demonstrate the great potential of CNF/IRMOF-based TENGs for development of self-powered sensing devices for long-term motion monitoring. Full article

This study employed response surface methodology to optimize the conditions for ultrahigh-pressure-assisted enzymatic extraction (UHPEE) of pectin from hawthorn using cellulase. The effects of this method on the characteristics of the extracted pectin were investigated. The optimal extraction parameters were determined to be a solid-to-liquid ratio of 1:70 g/mL, an extraction pressure of approximately 300 MPa, and a holding time of roughly 600 s, yielding a pectin recovery of 4.02%. The optimized UHPEE process resulted in reductions in both the degree of esterification and molecular weight of the pectin, while concurrently increasing the content of total galacturonic acid and total polyphenols. Ion chromatography analysis identified five monosaccharides in the hawthorn pectin, with galacturonic acid being the most predominant. Fourier-transform infrared spectroscopy (FT-IR) and scanning electron microscopy (SEM) analyses revealed the presence of characteristic absorption peaks of pectin and a rough surface topology with a loose, flaky structure, respectively. Rheological measurements demonstrated that the hawthorn pectin exhibited shear-thinning behavior, characteristic of a pseudoplastic fluid. In vitro antioxidant assays showed that hawthorn pectin scavenged 1,1-diphenyl-2-picrylhydrazyl (DPPH) radicals with a rate of 92.72%, comparably to vitamin C at the same concentration (96.30%). These results indicate that the optimized UHPEE method is a more efficient technique for extracting hawthorn pectin and effectively enhances its antioxidant activity, suggesting its potential application in the food industry. Full article

Phase wrapping is a common phenomenon in optical full-field imaging or measurement systems. It arises from large phase retardations and results in wrapped-phase maps that contain essential information about surface roughness and topology. However, these maps are often degraded by noise, such as speckle and Gaussian, which reduces the measurement accuracy and complicates phase reconstruction. Denoising such data is a fundamental problem in computer vision and plays a critical role in biomedical imaging modalities like Full-Field Optical Interferometry. In this paper, we propose WPD-Net (Wrapped-Phase Denoising Network), a lightweight deep learning-based neural network specifically designed to restore phase images corrupted by high noise levels. The network architecture integrates a shallow feature extraction module, a series of Residual Dense Attention Blocks (RDABs), and a dense feature fusion module. The RDABs incorporate attention mechanisms that help the network focus on critical features and suppress irrelevant noise, especially in high-frequency or complex regions. Additionally, WPD-Net employs a growth-rate-based feature expansion strategy to enhance multi-scale feature representation and improve phase continuity. We evaluate the model’s performance on both synthetic and experimentally acquired datasets and compare it with other state-of-the-art deep learning-based denoising methods. The results demonstrate that WPD-Net achieves superior noise suppression while preserving fine structural details even with mixed speckle and Gaussian noises. The proposed method is expected to enable fast image processing, allowing unwrapped biomedical images to be retrieved in real time. Full article

This report uses computational fluid dynamics (CFDs) to investigate the aerodynamics of a rubber O-ring, with a focus on assessing the influence of fluid velocity and surface topology whilst providing a detailed methodology that promotes correct procedures. A steady state scenario was set up, modelling laminar airflow across two O-rings with 5 μm and 100 μm surface finishes, respectively. Analysis showed that increasing the fluid velocity from 0.01 m/s to 2 m/s significantly translates the separation points downstream, consolidating wake regions behind the airfoil. The CFD simulations also infer that as the fluid velocity increases, the frictional drag coefficients decrease from 3.13 to 0.11, and the pressure drag coefficients increase from 0.55 to 0.6, implying that the recirculation of flowlines behind the O-ring becomes the most hindering factor on aerodynamics. Conversely, variations in surface roughness showed negligible effects on the flow field. This insensitivity is attributed to the low Reynolds number (Re) used in all simulations, where a roughness of 5 μm or 100 μm remains well within the laminar sublayer, therefore minimising their impact on boundary layer disruption and flow separation. Full article

The fractal dimension is a non-Euclidean measurement of how a fractal fills space and how irregular that arrangement is. Water distribution systems are non-Euclidean fractals whose fractal dimensions have provided insight into mathematical models to achieve optimal, minimum-cost designs. These insights are inconclusive, as they have not yet generalized the behavior of the fractal dimension of the hydraulic gradient surface of feasible designs with respect to near-optimal solutions. To approach a mathematical description for optimality in design and operation, this paper studied the fractal dimension of the energy, infrastructural, and flow distributions of mono-objective and biobjective designs. Mono-objective designs were obtained from the Optimal Power Use Surface, while biobjective designs used NSGA-II, OPUS/NSGA-II, and GALAXY. Their corresponding fractal dimensions were computed using the box-covering algorithm. Results show that the fractal dimension only depends on the topology. From this finding, fractal analysis is proposed as a tool to define topology in the design of water distribution systems to further minimize costs obtained using current design methodologies. Pipe roughness and demand sensitivity analyses revealed weak fractal behavior, suggesting the operative use of the fractal dimension as a pipe aging and demand variation indicator. Full article

Several different topologies utilizing ideals are created and compared with previous topologies. The results show that the previous ones are weaker than the current ones and that the current ones are stronger. The merits of these topologies are proposed, and the smallest and largest among them are identified; this merit distinguishes the present study from previous ones. Afterwards, these topologies are employed to conduct more in-depth investigations on broadened rough sets. The proposed approximate models are particularly significant as applied to rough sets because they diminish vagueness and uncertainty compared to prior models. Moreover, the proposed models stand out from their predecessors because they can compare all types of approximations, display all the features described by Pawlak, and possess the property of monotonicity across any relations. Furthermore, a medical application is showcased to emphasize the significance of the current findings. Additionally, the advantages of the adopted approach are examined, alongside an evaluation of its limitations. The paper wraps up with the essential features of the proposed manner and recommend avenues for future research. Full article

The construction of artificial microorganisms often relies on the transfer of genomes from donor to acceptor cells. This synthetic biology approach has been considerably fostered by the J. Craig Venter Institute but apparently depends on the use of microorganisms, which are very closely related. One reason for this limitation of the “creative potential” of “classical” transformation is the requirement for adequate “fitting” of newly synthesized polypeptide components, directed by the donor genome, to interacting counterparts encoded by the pre-existing acceptor genome. Transformation was introduced in 1928 by Frederick Griffith in the course of the demonstration of the instability of pneumococci and their conversion from rough, non-pathogenic into smooth, virulent variants. Subsequently, this method turned out to be critical for the identification of DNA as the sole matter of inheritance. Importantly, the initial experimental design (1.0) also considered the inheritance of both structural (e.g., plasma membranes) and cybernetic information (e.g., metabolite fluxes), which, in cooperation, determine topological and cellular heredity, as well as fusion and blending of bacterial cells. In contrast, subsequent experimental designs (1.X) were focused on the use of whole-cell homogenates and, thereafter, of soluble and water-clear fractions deprived of all information and macromolecules other than those directing protein synthesis, including outer-membrane vesicles, bacterial prions, lipopolysaccharides, lipoproteins, cytoskeletal elements, and complexes thereof. Identification of the reasons for this narrowing may be helpful in understanding the potential of transformation for the creation of novel microorganisms. Full article

The surface topology and fractal dimension of ultrathin silver and gold films have been investigated utilizing atomic force microscopy. These films were formed at the early stages of metal deposition through thermal evaporation and have pre-percolation thicknesses. They contain both metallic and insulating (void) phases, making them metal–dielectric composites. We identified the main parameters of the microstructure, such as the size of the metallic particles and surface roughness, as well as the dependence of these parameters on the film thickness and substrate parameters. Approaches to processing data, including correlation analysis, were employed. An analysis of dependencies and an explanation of their appearance were conducted. The discussion also addressed the limitations of using atomic force microscopy for studying ultrathin metal films. We determined the various types of fractal dimensions, considering the film topology for two- as well as three-dimensional objects. Depending on the actual dimensions of the phase boundary for silver films, a maximum was found. Different approaches to determining the fractal dimensions in 3Ds case show a similar dependence, but different values. Full article

This paper introduces a novel topology (upper approximated G-topology) on vertex sets of graphs using rough upper approximation neighborhoods, extending prior work on graph-induced topologies. Key results include characterizing discrete/indiscrete topologies for complete graphs, cycle graphs, and bipartite graphs (Theorems 1–3). The discrete topology for cycle graphs $C_n$, $n>5$, is particularly insightful. Exploring further, we delve into the continuity and isomorphism of graph mappings. Subsequently, we apply these findings to enhance radar chart graphical methods through the analysis of corresponding graph structures. These applications demonstrate practical relevance, linking graph structures to data visualization. Full article

The interrelationships between the topological features, such as surface roughness deduced from atomic force microscopy (AFM), and wettability properties expressed by the contact angle of a water droplet on the surface of nanostructured wide bandgap oxide films prepared by spray pyrolysis are investigated for a wide range of compositions. A direct relationship between the surface roughness and the value of the contact angle was found for nanocomposite (In₂O₃)_1−x(MgO)_x, (In_1−xGa_x)₂O₃, and Zn_1−xMg_xO films, for which both the surface roughness and the contact angle increase with the increasing x-value. On the other hand, in ITO films doped with Ga, it was found that the surface roughness increases by increasing the Ga doping, while the contact angle decreases. Both the surface roughness and the contact angle proved to increase in Ga₂O₃ films when they were alloyed with Al₂O₃, similar to other nanocomposite films. An inverse relationship was revealed for a nanocomposite formed from Ga₂O₃ and SnO₂. The contact angle for a (Ga₂O₃)_0.75(SnO₂)_0.25 film was larger as compared to that of the Ga₂O₃ film, while the surface roughness was lower, similar to ITO films. The highest value of the contact angle equal to 128° was found for a (In₂O₃)_1−x(MgO)_x film with an x-value of 0.8, and the largest RMS roughness of 20 nm was showed by a Ga_1.75Al_0.25O₃ film. The optical properties of the prepared films were also analyzed from optical absorption spectroscopy, demonstrating their bandgap variation in the range of (4 to 4.85) eV, corresponding to the middle ultraviolet spectral range. Full article

Laser powder bed fusion (LPBF) has emerged as a transformative additive manufacturing technique for fabricating architected cellular metallic structures, offering tailored properties for diverse biomedical applications. These structures are particularly well-suited for bone implants, scaffolds, and other load-bearing medical devices due to their ability to achieve lightweight designs, enhanced mechanical properties, and customized geometries. However, the complex interactions between LPBF process parameters and the resulting structural and mechanical properties pose significant challenges in achieving the precision and reliability required for clinical applications. This review provides a comprehensive analysis of the effects of LPBF process parameters, including laser power, scanning speed, and layer thickness, on key attributes such as dimensional accuracy, density, surface roughness, and microstructure. Their influence on the mechanical performance, including strength, fatigue resistance, and functional properties, is critically examined, with specific attention to biomedical relevance. The impact of lattice design factors, such as topology, unit cell size, and orientation, is also discussed, underscoring their role in optimizing biocompatibility and structural integrity for medical applications. Challenges such as surface defects, geometric inaccuracies, and microstructural inconsistencies are highlighted as key barriers to the broader adoption of LPBF in biomedical fields. Future perspectives focus on advancing LPBF technologies through process optimization and integration with advanced computational tools, such as machine learning, to enable efficient manufacturing of complex, patient-specific architectures. By addressing these challenges, LPBF has the potential to revolutionize the development of next-generation biomaterials, tailored to meet evolving clinical needs and improve patient outcomes. Full article

Triply periodic minimal surface (TPMS) structures raised significant interest in several areas of research due to their unique properties and broad range of applications. The aim of the paper is to verify if such complex metamaterials can be fabricated effectively without defects that could compromise their mechanical response. An implicit modeling approach was used to generate eight novel TPMS structures and one stochastic topology. Multiple specimens were fabricated from a photopolymeric resin using a stereolithography (SLA) technique, and an analysis of the manufactured samples was carried out in terms of surface quality, dimensional and mass deviations, and internal porosity of the material. Laser scanning showed no significant deviations from the designed geometry but highlighted errors during the post-processing stages of manufacturing. Surface analysis resulted in an average roughness of 2.47 µm, a value specific to well-controlled additive manufacturing (AM) techniques. A microscopic examination portrays common types of defects, while an ultrasonic non-destructive inspection method showed no indication of defects in the depth of the samples. Sectioning the samples through water jet cutting exposed interior surfaces with better homogeneity than the exterior ones and the absence of a layer-by-layer aspect. Overall, the samples displayed no major defects and good accuracy, with minor inconsistencies and methods of mitigating them having been presented. Full article

The simulation of additive manufacturing has become a prominent research area in the past decade. Process physics simulations are employed to replicate laser powder bed fusion (L-PBF) manufacturing processes, aiming to predict potential issues through simulated data. This study focuses on calculating surface roughness by utilizing 3D surface topology extracted from simulated data, as surface roughness significantly influences part quality. Accurately predicting surface roughness using a simulation remains a persistent challenge. To address this challenge, the L-PBF technique with two different cases (pre- and post-contouring) was simulated using two-step process physics simulations. The discrete element method was utilized to simulate powder spreading, followed by the Flow-3D melting simulation. Ten layers were simulated at three different linear energy density (LED) combinations for both cases, with samples positioned at a 30-degree angle to accommodate upskin and downskin effects. Furthermore, a three-dimensional representation of the melted region for each layer was generated using the thermal gradient output from the simulated data. All generated 3D layers were stacked and merged to consolidate a 3D representation of the overall sample. The surfaces (upskin, downskin, and side skins) were extracted from this merged sample. Subsequently, these surfaces were analyzed, and surface roughness (Sa values) was calculated using MATLAB. The obtained values were then compared with experimental results. The downskin surface roughness results from the simulation were found to be within the range of the experimental results. This alignment is attributed to the fact that the physics simulation primarily focuses on melt pool depth and width. These promising findings indicate the potential for accurately predicting surface roughness through simulation. Full article