Search Results (1,158)

Direct current (DC) surface flashover on polystyrene (PS) remains a critical bottleneck that impedes its reliable application in high-voltage insulation apparatus. To circumvent the protracted processing durations and stringent film-forming conditions inherent in conventional surface modification techniques, this study proposes a novel “liquid-film-assisted in situ rapid plasma curing” strategy. By harnessing atmospheric-pressure dielectric barrier discharge (DBD) technology within an argon ambient, the rapid (<6 min) and efficient deposition of a fluorosilane (FAS-13) functional coating onto the substrate was achieved. Microscopic characterizations coupled with isothermal surface potential decay (SPD) measurements reveal that this coating substantially mitigates the detrapping and surface migration of charge carriers. Macroscopic DC flashover testing corroborates that, under the optimal modification ratio, the surface breakdown voltage of PS is elevated to 14.04 kV, yielding an insulation gain of 26.94%. To elucidate the underlying physical mechanisms, density functional theory (DFT) calculations were conducted, revealing that the energy band misalignment between the wide-bandgap fluorinated layer and the substrate facilitates the construction of a high-density deep trap network (with a depth of ~0.8 eV) at the coating–substrate interface. By robustly anchoring primary electrons and inducing the formation of a homopolar space charge shielding layer, these deep traps physically arrest the evolution of the secondary electron emission avalanche (SEEA). Consequently, this work not only establishes a viable engineering framework for the rapid, large-scale surface reinforcement of DC insulation equipment but also provides profound quantum chemical insights into interfacial trap regulation within all-organic dielectrics. Full article

Laser-induced breakdown in water-rich biological media results from the interplay between primary photoionization processes and avalanche amplification of free electrons. Understanding this competition is essential for predicting ablation thresholds under ultrashort-pulse irradiation. In this work, we develop an analytical rate-equation model for the buildup of electron density in water-like biological tissues. It combines photoionization and chromophore ionization into a single seed-generation term, while avalanche ionization is described through a cascade gain factor. This formulation provides a framework for describing cascade electron-impact ionization processes in liquid-like media under strong-field excitation. Our approach gives an analytical expression for the temporal evolution of electron density driven by a Gaussian laser pulse and makes it possible to separate the contributions of direct ionization of water and ionization of chromophore centers. The analytical results are compared with numerical simulations that include carrier diffusion, bimolecular recombination and trapping. The comparison clarifies the roles of seed formation and cascade amplification in the growth of the electron population. The predicted dependence of threshold fluence on pulse duration agrees well with experimental data reported for water-like tissues such as the corneal tissues at a wavelength of 800 nm. The model provides a simple analytical picture of ultrafast plasma formation and electron-driven energy deposition in water-like biological media. Full article

Titanium matrix composites (TMCs) are increasingly vital in aerospace for their high specific strength and wear resistance, with compositional gradient design serving as a key strategy to mitigate thermophysical mismatches between ceramic and metal phases. This study utilized laser-directed energy deposition with concurrent wire-powder feeding (LDED-WP) to fabricate TiC/Ti6Al4V gradient composites, employing a laser power of 2700 W, wire feed rates of 110–150 cm/min, and calibrated powder feed rates ranging from 50.22 to 497.13 g/h. Along the build direction, the TiC content was progressively increased from 10 wt.% to 60 wt.%. Investigations into microstructural evolution revealed that the reinforcement morphology transitions from chain-like eutectic TiC to dendritic primary TiC, while the lamellarα-Ti width refines significantly from 4.07 ± 1.15 μm to 0.45 ± 0.29 μm. EBSD analysis confirmed that higher TiC concentrations weaken the characteristic <001> solidification texture, reducing intensity from 11.24 to 7.64. Furthermore, KAM analysis highlighted that thermal expansion and elastic modulus mismatches trigger substantial geometrically necessary dislocation (GND) accumulation at interfaces. Consequently, Vickers hardness improved by 164% along the gradient, peaking at 950 HV. Although the composite achieved an ultimate tensile strength of 630 MPa, the elongation was limited to 2.4% due to crack nucleation in TiC-rich regions and interfacial instability. Full article

To accelerate the transition to sustainable energy, efficient methods for CO₂-free hydrogen production and carbon utilization are needed. This study presents a new, sustainable approach for the simultaneous production of hydrogen, valuable hydrocarbons, and functional carbon materials by converting methane in low-pressure microwave plasma. Compared to traditional methane reforming methods (such as steam reforming), our plasma-based process operates at low temperatures, eliminates direct CO₂ emissions, and enables the conversion of methane into three valuable products: (1) environmentally friendly hydrogen for fuel cells and energy storage systems, (2) a range of valuable organic products (C₂H₂, C₂H₄, C₂H₆), and (3) functional carbon films with self-improving catalytic properties. Optical emission spectroscopy (OES) and the Langmuir double probe method were used for plasma diagnostics, revealing an increase in the concentration of active species (CH, Hα, C₂) and electron temperature upon argon addition. The structure, morphology, and impurity composition of the deposited films were investigated using X-ray diffraction (XRD), scanning electron microscopy (SEM), and inductively coupled plasma mass spectrometry (ICP-MS), respectively. Gas-phase byproducts were analyzed using gas chromatography–mass spectrometry (GC-MS). Argon addition at an Ar/CH₄ ratio of 1 leads to the formation of carbon films with a more ordered structure, as confirmed by XRD data, and improved surface morphology. It was established that argon, by effectively participating in the excitation and dissociation processes of methane molecules through energy transfer from metastable states and increased electron temperature, optimizes plasma–chemical reactions, promoting the deposition of higher-quality carbon coatings. Full article

Additive manufacturing (AM) has emerged as a transformative technology across multiple industries, from aerospace to biomedical applications. The integration of artificial intelligence (AI) and machine learning (ML) into AM processes represents a paradigm shift toward intelligent, autonomous manufacturing systems. This comprehensive review synthesizes recent advances in AI/ML applications across the entire AM life cycle—from design optimization and process planning through in situ monitoring, closed-loop control, and post-process qualification. The analysis is organized by ISO/ASTM AM process families, including powder bed fusion (PBF), directed energy deposition (DED), material extrusion (MEX), vat photopolymerization (VP), binder jetting (BJ), material jetting (MJT), and sheet lamination (SL). For each process family, the review examines the specific AI/ML techniques employed, the data modalities utilized (thermal imaging, acoustic signals, in situ cameras, CT/NDE data), and the current state of deployment from research prototypes to industrial implementation. The analysis reveals that while significant progress has been made in single-stage ML applications such as defect detection and parameter optimization, truly integrated life cycle-wide AI-driven AM workflows remain largely aspirational. Key challenges are identified including data scarcity, model generalization across machines and materials, real-time control constraints, and certification requirements. Finally, future research directions are outlined toward autonomous AM systems enabled by physics-informed ML, digital twins, and hierarchical AI architectures. Full article

Hydrogen represents a promising clean and renewable energy source. Therefore, improving the efficiency of electrocatalysts is essential for effective hydrogen production. In this work, Ni electrocatalysts were synthesized via the electrodeposition method from ethaline deep eutectic solvent (DES) at 45 °C, 55 °C, and 65 °C under perpendicular (B_⊥) and parallel (B_‖) magnetic field directions relative to the electrode surface. Scanning electron microscopy (SEM) was employed to investigate the morphological study, which shows that Ni deposits under B_⊥ promote columnar grain growth, while B_‖ favors lateral, compact structures. Furthermore, moderate temperature (55 °C) in the case of using B_⊥ produced finer grains and smoother surfaces compared to other temperatures in the same direction, enhancing the catalytic performance for HER. Electrochemical techniques, including linear sweep voltammetry (LSV) and chronoamperometry, were employed to evaluate the catalytic performance for HER in 1 M NaOH and the adsorption–desorption process, respectively. The results suggest that efficient HER performance is associated with balanced hydrogen adsorption and desorption behavior. The Ni deposit at 55 °C under (B_⊥) exhibited the lowest overpotential (−215 mV) compared to the deposits at 45 °C and 65 °C under the same magnetic field direction, indicating superior overall HER performance. This performance is attributed to balanced hydrogen adsorption–desorption behavior despite the relatively high Tafel slope value (298 mV·dec⁻¹). However, the lowest Tafel slope among the whole samples prepared under both (B_⊥) and (B_‖) was found to be (219 mV·dec⁻¹), reflecting faster kinetics, which was obtained for the sample deposited at 45 °C under (B_‖). Full article

This work presents a machine-vision–based measurement and control framework for laser wire directed energy deposition (LWDED) processes. A visible-light camera system is used to capture meltpool images, from which a novel vision algorithm extracts the wire–meltpool interface location. By utilizing a camera that is rigidly mounted to the deposition head, the vision algorithm provides a relative measurement of the distance between the nozzle tip and the workpiece, also referred to as wire stickout. A proportional-derivative (PD) control strategy is implemented using the measured stickout as feedback to adjust deposition feedrate. Results show that the control system successfully compensates for improper layer height increments, enabling thin-wall builds to consistently reach target geometry. Full article

To address issues such as thermal stress concentration in metal bone implants produced via high-energy beam direct additive manufacturing, a method was proposed to fabricate porous titanium scaffolds. This approach combined Fused Deposition Modeling (FDM) with a debinding–sintering process. Ti/ABS composite filaments with titanium volume fractions of 35%, 40%, and 45% were successfully developed via a single-screw extrusion process. Their feasibility in the FDM process was subsequently verified. The effects of different processing parameters on the forming quality and dimensional accuracy of the green bodies were investigated. After debinding and sintering the composite scaffolds prepared with optimized parameters, structurally intact porous titanium scaffolds were obtained. Microscopic characterization shows that the scaffold surface consists primarily of titanium, and the pore structure remains intact. Furthermore, compression tests were performed on three types of porous titanium scaffolds with different porosities. The results indicate that the combination of ABS/titanium alloy composite filaments, FDM technology, and debinding–sintering post-processing enables the high-quality and efficient production of porous titanium scaffolds. The elastic modulus of the resulting scaffolds ranges from 1.2 to 1.6 GPa, and the compressive strength is between 25.7 and 68.3 MPa. The elastic modulus matches that of human cancellous bone. Meanwhile, the compressive strength is significantly higher than that of cancellous bone and falls between the values for cancellous and cortical bone. These mechanical properties meet the requirements for human bone, providing a new approach for the manufacture of orthopedic implants. Full article

This study evaluates the feasibility of airborne acoustic source localisation (ASL) for in situ crack localisation in industrial laser-based directed energy deposition (DED-LB/M) fabricated structures. A four-microphone array combined with a Generalised Cross-Correlation with Phase Transform (GCC-PHAT) algorithm was used to estimate crack positions from time differences of arrival (TDOAs) extracted from raw acoustic emissions during multi-layer single-track fabrication. Prior to experimentation, the microphone array geometry was numerically optimised under industrial placement constraints by introducing controlled TDOA perturbations and minimising three-dimensional localisation uncertainty using alpha-shape volume analysis. Experimental validation was performed on six-layer single-track structures, with estimated crack positions compared against post-process microscopic measurements. Localisation errors ranged from 12 to 68 mm in the X-direction, 0.7–32 mm in the Y-direction, and 5–100 mm in the Z-direction. While horizontal localisation demonstrated centimetre-scale accuracy for most cracks, depth estimation exhibited greater variability. The results confirm that airborne ASL can provide meaningful spatial information regarding crack formation during DED-LB/M. However, localisation performance remains sensitive to TDOA estimation accuracy, microphone array constraints, and the complex acoustic environment inherent to the process. This work demonstrates the industrial feasibility of ASL for in situ crack investigation while highlighting the need for further advancements in array design and signal processing to achieve robust three-dimensional defect localisation in additive manufacturing systems. Full article

Manufacturing high-performance turbomachinery blades remains one of the most demanding challenges in aerospace and energy engineering, requiring tight control over microstructure, geometry, and cooling architectures. Despite rapid progress in casting, machining, and additive manufacturing, the field lacks a structured classification that links process capabilities with blade functional requirements and future design trends. This review addresses that gap by introducing a new classification scheme for turbomachinery blade manufacturing technologies, organized into three complementary domains: (i) foundational fabrication routes (casting, forging, precision machining); (ii) advanced and hybrid processes (powder-bed fusion, directed-energy deposition, additive–subtractive systems, laser repair); and (iii) digital and intelligent manufacturing enablers (in situ monitoring, AI-driven process control, digital twins, and automated inspection). Within each class, the review maps process parameters to resulting structural performance, defect modes, cost drivers, and certification challenges. Special emphasis is placed on the manufacturing implications of emerging blade architectures, such as intricate internal cooling channels, gradient materials, and bio-inspired aerodynamic profiles. By consolidating disparate techniques into a structured taxonomy, this paper clarifies current limitations, identifies cross-technology synergies, and outlines priority research directions for achieving next-generation turbomachinery blade manufacturing. Full article

Hydrogen storage remains a key challenge in the transition toward sustainable energy systems, particularly for applications requiring high energy density and safe operation. Among various solid-state storage materials, magnesium hydride (MgH₂) is considered highly promising due to its high hydrogen capacity, low cost, and good reversibility; however, its practical application is hindered by slow kinetics and high thermodynamic stability. In this study, Mg and Ni coatings were deposited on Al₂O₃ based substrates using a direct current plasma spraying technique to develop a composite system for enhanced hydrogen storage performance. The influence of plasma torch parameters on coating characteristics was investigated, and the hydrogenation behavior was analyzed under controlled conditions (350 °C & 200 °C, 5 atm H₂). The structural, morphological, and compositional evolution of the coatings before and after hydrogenation was examined using SEM, EDS, XRD, and FTIR techniques. Results demonstrate that plasma-sprayed Mg coatings undergo significant morphological transformation after hydrogenation, including surface cracking, increased porosity, and phase conversion to MgH₂, confirming effective hydrogen uptake. In contrast, Ni coatings exhibit limited hydride formation but play a catalytic role by facilitating hydrogen dissociation and improving surface reactions. The influence of plasma power on coating quality and hydrogenation efficiency was also identified, with higher power leading to improved coating uniformity and enhanced MgH₂ formation. Additionally, a reaction–diffusion model was developed to evaluate the effect of temperature and hydrogen pressure on hydride layer growth. The model predicts an optimal temperature range (~300–330 °C) for MgH₂ formation, beyond which thermodynamic instability limits hydride stability. Overall, the study demonstrates that plasma-sprayed Mg/Ni coatings on granular substrates represent a promising approach for developing efficient hydrogen storage systems, combining improved kinetics, structural stability, and scalable processing. Full article

This study proposes a stress field data-driven prediction method that combines a finite element thermo-mechanical coupling model with a multi-machine learning framework. This method takes the inversion of stress based on the shrinkage behavior of deposition layers as the core logic, extracts the node displacement shrinkage during the cooling to solidification process of the melt pool in the thermal coupling simulation as the key feature input, and constructs extreme gradient boosting (XGBoost), Gaussian process regression (GPR), and deep convolutional neural network (DCNN) models, respectively, to achieve accurate prediction of nodal effect stress and triaxial stress in the laser directed energy deposition (L-DED) node process. The experimental results show that the XGBoost algorithm performs the best in various stress prediction indicators, and its generated stress distribution cloud map is highly consistent with the thermal coupling simulation results, suggesting a strong correlation between deposition layer shrinkage behavior and the stress field under the investigated conditions. In addition, compared to traditional finite element simulations, this method significantly improves computational efficiency while ensuring prediction accuracy, providing a new approach for rapid assessment of residual stresses. Full article

This study introduces a novel type of oscillating laser directed energy deposition (OL-DED) technology aimed at improving microstructure uniformity and enhancing wear resistance. The microstructure and wear resistance of the OL-DED coating were analyzed and compared with those of the traditional non-oscillating laser directed energy deposition (TL-DED) coating. The results indicate that the OL-DED coating exhibits superior performance, and the grain size of the OL-DED coating is significantly smaller than that of the TL-DED coating. Furthermore, the wear resistance of the OL-DED coating at room temperature and high temperatures exceeds that of the traditional TL-DED coating. The wear mechanisms at room temperature are primarily characterized by abrasive wear, adhesive wear, and oxidative wear, whereas those at high temperatures are mainly dominated by abrasive wear and oxidative wear, with a slight contribution from adhesive wear. Full article

Hybrid robotic manufacturing systems integrating additive and subtractive processes enable fabrication of complex, high-value components but are typically executed sequentially, resulting in long cycle times. Concurrent execution of Directed Energy Deposition (DED) and milling promises productivity gains but introduces coupled thermal, mechanical and spatial interactions that challenge conventional process planning. This work addresses the methodological problem of planning milling operations in the presence of an ongoing DED process. The concurrent planning task is formulated as a mixed-integer, nonlinear, multi-objective optimisation problem capturing sequencing and orientation decisions, cutting parameters and enabling temporal coupling to the deposition trajectory. A hierarchical, surrogate-assisted optimisation framework is proposed, combining unified decision-variable encoding, deterministic decoding and staged feasibility enforcement to ensure robotic executability. Disturbance mechanisms such as thermal interaction, particulate interference and pose-dependent dynamic compatibility are incorporated as modular objective abstractions, enabling systematic trade-offs between machining productivity and preservation of deposition process integrity. The proposed framework is demonstrated on a representative case study, enabling analysis of the interaction between spatial sequencing, temporal feasibility and disturbance-aware optimisation. The case study provides a controlled instantiation and illustrates its application to concurrent additive–subtractive planning under explicitly modelled temporal and disturbance constraints. Full article

Structural materials in nuclear energy, aerospace, and electronics face long-term irradiation by high-energy particles, triggering microscopic defect evolution and macroscopic performance degradation that limits service safety. This review provides a systematic overview of irradiation damage mechanisms, with particular emphasis on the role of surfaces. The discussion traces the evolution from initial defect generation through energy deposition and displacement cascades to the migration and aggregation of defects toward surfaces, culminating in their interactions with near-surface microstructures. A comparative analysis of damage behaviors in metals, ceramics, silicon-based materials, and polymers is presented, elucidating how distinct mechanisms arise from fundamental differences in crystal structure and chemical bonding. The integration of multiscale simulation techniques with advanced in situ characterization is highlighted as a critical approach for deciphering the cross-scale processes. Current strategies for enhancing radiation resistance including composition optimization, microstructure regulation, and interface design are summarized. Finally, the review outlines key challenges such as multi-field coupling damage characterization and long-term predictive modeling. Future research directions are foreseen to emphasize closer simulation–experiment integration and the design of smart, self-adapting materials, thereby providing comprehensive theoretical and technical support for the development of next-generation radiation-tolerant materials. Full article