Search Results (4,352)

This study aimed to investigate the influence of the synthesis parameters on the corrosion resistance of 3D-printed Inconel 718 components. Samples were fabricated using laser powder bed fusion (PBF-LB/M) with different angles of inclination. Corrosion tests were conducted by immersion for 1000 h in a 3.5% aqueous NaCl solution at 20 °C and 45 °C, and by the potentiodynamic polarization measurements. Detailed analysis of changes in morphology, chemical composition, and roughness of 3D prints was performed using scanning electron microscopy, combined with energy-dispersive X-ray spectroscopy, and optical profilometry. To quantify the dissolution of alloy components during the long-term measurements, the post-corrosion solutions were analyzed using microwave plasma–atomic emission spectroscopy. The obtained results demonstrate that inclination angle significantly affects corrosion rate and electrochemical kinetics, with measurable differences in mass loss, Icorr values, and surface degradation morphology observed between orientations. The findings indicate that build orientation governs microstructural anisotropy and surface characteristics, which in turn influence corrosion susceptibility. The novelty of this work lies in the systematic and multi-method evaluation of inclination angle as an independent structural parameter controlling corrosion kinetics in PBF-LB/M-fabricated Inconel 718, providing new insight into structure–corrosion relationships in additively manufactured nickel-based superalloys. Full article

Background/Objectives: Hand loss or severe impairment significantly reduces quality of life by restricting essential daily activities and professional tasks. Despite advances in prosthetics, challenges remain in affordability, accessibility, and usability. This study aimed to design and develop a low-cost, ergonomic bionic hand prototype that integrates sustainable fabrication, intuitive control, and modular electronics. Methods: A user-centred design process guided by iterative prototyping, anatomical modelling, and functional validation. The prototype was manufactured using 3D printing techniques and assembled with modular electronic components. The design included segmented fingers, independent thumb articulation, and a tendon-like actuation system driven by micro-motors. Control was implemented through an ESP32-based board and a Bluetooth-enabled mobile application. Durability was preliminarily assessed through 500 grasp–release cycles. Results: Experimental validation confirmed the feasibility of both precision and power grips. The pinch grip successfully lifted objects to 120 g, and the power grip up to 85 g, corresponding to effective output forces of approximately 1.2 N and 0.83 N, respectively. The final prototype weighed ~350 g and maintained reliable performance during 500 grasp–release cycles. Conclusions: The developed bionic hand demonstrates that an affordable, ergonomic, and functional prosthetic can be achieved through sustainable 3D printing and accessible electronics. Future work will focus on enhancing actuation strength, long-term durability, and integration of sensory feedback, with the long-term objective of clinical testing and scalable production. Full article

The 316L stainless steel (316L SS) and high-entropy alloys (HEAs) are leading candidates for radiation-tolerant structural materials in nuclear environments. Additive manufacturing (AM) enables tailored microstructures through unique thermal histories, producing high dislocation densities and sub-grain features that act as effective sinks for irradiation-induced defects. In this work, a direct quantitative comparison of helium (He) irradiation response, particularly bubble formation, is conducted between 316L SS fabricated using laser powder bed fusion (LPBF) and CoCrFeNi HEAs fabricated by laser-directed energy deposition (LDED), both possessing a face-centered cubic (FCC) crystal structure and comparable principal elemental constituents. The samples were subjected to ex situ He ion irradiation using 200 keV He⁺ ions to a peak damage dose of 10 dpa at 25 °C, 400 °C, and 600 °C at the CINT User Facility at Los Alamos National Laboratory. Post-irradiation microstructural characterization was performed using transmission electron microscopy at the IVEM-Tandem Facility at Argonne National Laboratory. For LPBF 316L SS, the areal bubble density decreases from approximately 5.1 × 10⁴ µm⁻² at 25 °C to 2.1 × 10³ µm⁻² at 600 °C, while the mean bubble diameter increases from 2.9 nm to 37.4 nm. The CoCrFeNi HEA exhibits a similar trend but retains a higher areal bubble density at elevated temperatures, with values of 2.1 × 10⁴ µm⁻² at 400 °C and 3.7 × 10³ µm⁻² at 600 °C, along with a larger mean bubble size at 400 °C compared to 316L SS. These results highlight the combined roles of AM-induced microstructures, alloy compositions, and irradiation temperatures in governing He damage evolution in FCC alloys, providing guidance for the development of radiation-tolerant materials for advanced nuclear energy applications. Full article

Sustainable alternatives to synthetic polymer-based sanitary napkins are essential to reduce the environmental impact and health concerns. This study presents a method for using water hyacinth (Eichhornia crassipes), an invasive aquatic weed, as biomass to produce biodegradable absorbent material for sanitary pads. Water hyacinth fibers were treated with an alkaline solution and incorporated into the absorbent core. Morphological, chemical, structural, functional, microbiological, and biodegradability evaluations were then conducted systematically. Scanning electron microscopy showed that non-cellulosic components were successfully removed, producing a rougher surface topology and enhanced fiber interactions. Fourier-transform infrared spectroscopy confirmed structural changes in cellulose after treatment. Additionally, X-ray diffraction showed that the crystallinity index increased from 53.21% in untreated fibers to 62.56% in treated fibers, indicating improved order and stability. The developed absorbent sanitary pad showed rapid fluid uptake, absorbing 10 mL within three seconds while maintaining a skin-compatible neutral pH of 6.87, as specified in Indian Standard IS 5405:1980. Microbial contamination remained low, with a total bacterial count of 360 CFU/g, no yeast or mold at ≤1 CFU/g, and no presence of Staphylococcus aureus. Soil burial tests showed 70% biodegradability at 40 days and approximately 95% at 60 days, indicating high biodegradability. These findings demonstrate the potential of water hyacinth as an inexpensive and environmentally friendly material for manufacturing hygienic sanitary pads, highlighting the sustainability benefits of valorizing invasive biomass and reducing reliance on synthetic polymers. Full article

PCB surface defect detection plays a critical role in ensuring electronics manufacturing quality. To address the challenges of small target defect detection, this study proposes PCB-YOLO, an enhanced lightweight detector based on YOLOv8n. PCB-YOLO introduces three key improvements. First, a RepViT-EMA Fusion Architecture (REFA) module is designed for deep backbone layers to strengthen feature extraction while suppressing background interference from complex circuit patterns. Second, a Multi-Scale Grouped Aggregation (MSGA) module is developed to reduce feature redundancy and improve spatial-semantic information extraction for multi-scale defects. Third, a Pixel-level Intersection over Union (PIoU) loss function is proposed to enable pixel-level IoU calculation with enhanced angular and area constraints for more precise localization. Extensive experiments on the PKU-Market-PCB dataset demonstrate that PCB-YOLO achieves 98.4% mAP@0.5, 97.4% recall, and 96.1% precision with only 2.4 M parameters, 6.9 G FLOPs, and an inference speed of 224 FPS, outperforming multiple state-of-the-art methods while maintaining real-time capability. Additional experiments on the DeepPCB dataset yield 99.0% mAP@0.5 and 80.4% mAP@0.5:0.95, confirming the cross-dataset generalization ability of the proposed method. Full article

Perovskite solar cells (PSCs) have rapidly evolved into one of the most promising photovoltaic technologies, achieving power conversion efficiencies comparable to established silicon devices while offering unique advantages such as low weight, mechanical flexibility, and low-temperature, solution-based manufacturing. These attributes, combined with recently demonstrated tolerance to high-energy particle irradiation, position PSCs as compelling candidates for next-generation space power systems. This perspective work summarizes recent advances in PSC development for space environments, focusing on their behaviour under key stressors such as radiation (e.g., electrons, protons, gamma rays, and neutrons), ultraviolet exposure, extreme thermal cycling, and ultra-high vacuum. Progress in material design, device architecture, self-healing mechanisms, and encapsulation strategies is discussed, along with early in-orbit and suborbital demonstrations. Remaining challenges, including long-term stability, encapsulation reliability, large-area scalability, and the need for standardized space-qualification protocols, are also outlined. Indeed, PSCs represent a compelling opportunity for next-generation space photovoltaics, provided that targeted materials and engineering solutions address critical issues of encapsulation and durability under combined stressors to ensure reliable operation in harsh extraterrestrial conditions. Full article

In the field of printed circuit board (PCB) manufacturing, surface defect detection serves as a critical process in the production line, directly impacting the quality and safety of subsequent electronic products. However, accurately detecting tiny surface defects in real time remains a significant challenge given the complex layouts of PCBs. To address this issue, this study proposes a novel Ghost-BiFPN-Efficient-YOLOv8 (GBE-YOLOv8) model architecture for PCB defect detection based on an improved YOLOv8n. The backbone network of the model employs lightweight Ghost Conv to partially replace regular convolutions, thereby reducing computational complexity and parameter count. The neck network incorporates a multi-stage feature fusion module named G-C2f and a dynamic weighting module named BiFPN-Concat to enhance the model’s ability to characterize PCB defects. The model’s head network employs an Efficient Head that combines mixed depthwise convolution and partial convolution, further optimizing detection accuracy and computational efficiency. Simultaneously, a comprehensive evaluation of model performance was conducted using publicly available datasets. And the working mechanisms of each improved method were analyzed through class activation heatmaps to further enhance the interpretability of the model. Experimental results demonstrate that compared to the baseline model and several other state-of-the-art object detection algorithms, the proposed method exhibits significant advantages across various evaluation metrics, and its mAP@0.5, mAP@0.5:0.95, parameters, GFLOPs and FPS achieve 98.9%, 61.4%, 2.6 M, 7.5 and 252, respectively. Furthermore, each optimization method achieves the expected design purpose, and the combined application of all optimization methods enables the model to strike an optimal balance between detection accuracy and computational complexity. Consequently, this research can provide a reliable technical solution for high-precision real-time detection of surface defects on PCBs in industrial production lines. Full article

In the manufacturing process of advanced integrated circuits, electron beam inspection equipment is crucial for yield assurance, while vibration poses a core challenge affecting its precision and speed. Vibrations in production line equipment are mostly multi-frequency; However, research findings in this field remain limited. Moreover, existing compensation schemes often struggle to meet industrial-grade precision and real-time requirements. This paper presents the design and implementation of a high-speed electron beam vibration compensation system based on positioning. The system incorporates state-of-the-art laser positioning and electrostatic scanning deflectors, and features an integrated signal processing and compensation signal output module. The study involved improvements and optimizations to the positioning processing analysis and compensation module, control software and algorithms, and calibration software and algorithms, demonstrating superior performance compared to existing methods. System validation data demonstrates that the proposed scheme effectively compensates for both single-frequency and multi-frequency disturbances at frequencies below 200 Hz, achieving an average attenuation of 50% to 90% and a repetitive compensation accuracy of less than 0.3 nm. These metrics meet the industrial application requirements for electron beam inspection equipment. The overall error in long-term repeatability tests complies with the stability demands of industrial production lines, confirming its practical applicability in production environments. Full article

The applications of machine learning (ML) in power electronics are expanding with time, providing effective tools that reduce design complexity and enhance predictive accuracy. In high-power semiconductor devices, such as thyristors and high-power diodes, electrical parameters may directly influence electro-thermal behavior, reliability, and overall device performance. Consequently, accurate prediction and classification of average current are critical to ensure optimal device selection, optimize design, and assess performance. In this article, a comprehensive dataset based on data from industrial thyristors capturing electrical and structural parameters relevant to current handling capability is utilized to classify and predict the average current of devices. Additionally, Shapley additive explanation (SHAP) analysis has been performed, highlighting the importance of crucial parameters and identifying the impact of each parameter on model output. Moreover, several ML models, including artificial neural networks (ANNs), support vector machines (SVMs), ensembles, and Gaussian process regression (GPR) are implemented and then compared to assess their performance. The proposed methodology provides manufacturers and designers with data-driven design tools that enhance reliability assessments and facilitate optimized device selection for high-power applications. Full article

Titanium and its alloys are widely used in endoprostheses. The naturally formed titanium dioxide film on titanium surfaces improves chemical stability and enhances implant biocompatibility. However, oxidised titanium surfaces may also promote bacterial adhesion and biofilm formation, contributing to implant-associated infections. Therefore, surface modification represents a key strategy for controlling microbial–implant interactions. This article focuses widely used titanium alloy Ti-6Al-4V treated with a laser beam, which induces surface colour changes as a result of oxide formation. Laser processing enables controlled formation of micro- and nanoscale features, structural reconstructions, and defects that may influence the surface electrical charge and, consequently, cell immobilisation. Thus, the surface colour, electrical potential, and cell immobilisation capacity are likely interrelated. From a manufacturing perspective, titanium oxide colouring facilitates quality control and process reproducibility, as surface colour provides a rapid, non-destructive visual indicator of oxide thickness and treatment consistency. This study aims to identify correlations among surface colour, electrical potential, and cell immobilisation capacity on laser-treated titanium alloys. A relationship between the optical properties, electronic structure, and biological response of laser-processed titanium oxide films is established. Specifically, the blue colour saturation of the oxide film is inversely correlated with the electron work function. A more saturated blue corresponds to a lower work function, indicating a higher positive surface charge density. This shift is attributed to changes in electron affinity, likely resulting from laser-induced structural reconstruction and defect formation within the oxide layer. The proposed changes in electronic structure are supported by modifications in the electronic density of states, analysed using near-threshold photoelectron spectroscopy. The biological response is directly linked to these physical changes: enhanced immobilisation of yeast (Saccharomyces cerevisiae) cells on the treated alloy surface correlates with the electron work function. These results may assist in the development of controlled titanium oxide surfaces with enhanced biocompatibility. Full article

N,N-Dimethyl-1,3-propanediamine (DMAPA) is an important aliphatic diamine widely used in fine chemical manufacturing. Its industrial production traditionally relies on Raney nickel catalysts, which suffer from pyrophoric hazards and limited selectivity due to imine condensation side reactions. To address these challenges, we report an Al₂O₃-supported Ni-Cu alloy catalyst as an efficient alternative for the selective hydrogenation of N,N-dimethylaminopropionitrile (DMAPN). The optimized Ni₃₀Cu₅/Al₂O₃ catalyst achieves complete DMAPN conversion and over 90% DMAPA selectivity under industrially relevant conditions (120 °C, 2.5 MPa H₂). X-ray diffraction, X-ray photoelectron spectroscopy, and transmission electron microscopy analyses confirm the formation of substitutional Ni-Cu alloy nanoparticles, where Cu incorporation induces both geometric isolation of Ni ensembles and electronic modulation of surface active sites, thereby suppressing condensation-derived by-products. In addition, an NH₃/ethanol-assisted process further improves selectivity while reducing autogenous operating pressure. Overall, this work demonstrates a safe and highly selective catalytic system for primary diamine synthesis, providing a practical alternative to conventional Raney Ni-based processes. Full article

Additive manufacturing is transforming high-frequency electronics prototyping by offering a sustainable and cost-effective alternative to traditional methods. This work addresses and demonstrates two areas: the use of 3D printing for millimeter-wave (mmWave) antennas, and chip-to-chip or chip-to-PCB interconnects. Both approaches facilitate reduced material waste. A 47 GHz series-fed microstrip patch array was printed on flexible Kapton using aerosol jet technology, showing performance comparable to etched arrays on Roger’s substrates. Crucially, the Kapton film can be peeled off after testing, allowing the reuse of expensive low-loss substrates. Therefore, this method supports rapid, low-waste prototyping. To address future chip-to-chip and chip-to-PCB mmWave interconnect limitations, XTPL’s Ultra-Precise Dispensing (UPD) was used to fabricate 3D-printed micro-interconnects. At 73 GHz, these interconnect structures achieved return loss better than 10 dB and insertion loss under 1 dB—outperforming traditional bondwires. Together, these results show 3D printing’s potential to enable sustainable, high-performance mmWave RF systems. Full article

Memristors are valuable elements with very good memory and switching features. They have minimal power consumption, nano-scale sizes, and a possibility for integration with high-density Complementary Metal Oxide Semiconductor (CMOS) integrated circuits. They are applicable in neural networks, memory crossbars, and different electronic devices. This work considers some improved and existing models for memristors, functioning at high-frequency signals with a high speed and very good effectiveness. The main parasitic parameters—series resistance, capacitance, and small-signal direct current (DC) voltage and current shifting signals—are taken into account. An additional leakage conductance is analyzed as a parasitic component. The influence of the parasitic parameters on the normal functioning of memristor-based circuits is analyzed and evaluated at hard-switching and soft-switching modes. For investigations of the main characteristics of the considered models and their applicability in memory arrays, Linear Technology Simulation Program with Integrated Circuits Emphasis (LTSPICE) library models are generated and analyzed. The considered models operate at low-, middle- and high-frequency signals, clearly demonstrating the main properties of memristors. Their appropriate operation in passive memory arrays is analyzed and established. The proposed models have a 26% enhanced accuracy in fitting experimental i-v relations. They ensure good memory and switching properties for memory arrays. This work could be a suitable step towards the design and manufacturing of ultra-high-density memristor-based integrated chips. Full article

This review critically analyzes the evolution of passive heat transfer enhancement in internal flows, charting a paradigm shift from momentum-based flow perturbation to the precise engineering of vortex structures. The central thesis is that the highest-performance, next-generation thermal systems will be realized through ‘flow field programming’—a unified design paradigm that intelligently architects vortex-topology and surface architecture across scales using smart materials, additive manufacturing, and artificial intelligence. This progression is traced from classical devices such as twisted tapes, which generate global swirl, to bio-inspired aerofoil inserts that efficiently produce discrete longitudinal vortices. The synergy achieved in compound systems—through the integration of geometries or the combination of inserts with advanced fluids—is identified as a key mechanism for surpassing traditional performance limits. Furthermore, applications in microscale and phase-change heat transfer, where surface engineering dominates, are explored. The novelty of this work lies in its synthesis of the underlying vortex-generation physics across diverse techniques and scales, introducing ‘flow field programming’ as a forward-looking framework for adaptive thermal management. This evolution—from static geometries to intelligent, responsive designs—is positioned to dramatically improve energy sustainability by enabling more compact, efficient, and adaptive thermal management across power generation, advanced electronics, and renewable energy systems. Full article

Background: Pantoprazole is a widely used proton pump inhibitor that is highly unstable under acidic conditions. This limits the performance of conventional formulations and typically requires enteric-coated dosage forms or alternative modified-release approaches. This study reports the development of polymeric matrix mini-tablets designed to protect pantoprazole during gastric exposure and to enable pH-dependent release under intestinal conditions. The formulations combine Eudragit^® S 100, a pH-dependent polymer, with HPMC, a hydrophilic matrix former that modulates drug release through hydration and swelling. Methods: Matrix mini-tablets were prepared by blending pantoprazole with selected excipients at optimised proportions and compressing the blends by direct compression using an eccentric tablet press. Powder blends and mini-tablets were characterised according to pharmacopoeial specifications. Analytical techniques—including High-Performance Liquid Chromatography (HPLC), Differential Scanning Calorimetry (DSC), Fourier-Transform Infrared Absorption Spectroscopy (FT-IR), Powder X-Ray Diffraction (PXRD), and Scanning Electron Microscopy (SEM)—were employed to evaluate drug content uniformity, thermal behaviour, and potential drug–excipient interactions. In vitro dissolution studies were performed under sequential pH conditions, and the release kinetics were analysed using mathematical models. Results: Dissolution testing identified formulations F2 and F6 as providing the most suitable gastro-resistant performance in the acidic stage, together with sustained release up to 24 h. Kinetic modelling supported formulation-dependent release mechanisms, and multivariate analysis (PCA) highlighted relationships between physico-mechanical attributes and drug-release behaviour. Conclusions: The proposed matrix system shows potential as a robust, coating-free platform for the modified delivery of acid-labile drugs using direct compression, simplifying manufacturing. These findings support the rational design of oral modified-release formulations based on polymeric matrices. Full article