Search Results (226)

Recent advances in chiplet architectures, heterogeneous integration, 2.5D/3D packaging, high-performance computing, and RF applications have increased the demand for high-density vertical interconnects and low-loss packaging platforms. Glass substrates have attracted considerable attention for next-generation advanced packaging because of their low dielectric loss, high dimensional stability, smooth surface, and compatibility with large-area panel-level processing. Through-glass vias (TGVs) are essential vertical interconnect structures that enable the electrical integration of glass substrates. This focused review summarizes TGV technologies for glass-based advanced packaging from the perspectives of via formation, seed layer deposition, metallization, Cu filling, defect formation, reliability, and plugging-based alternative architectures. Representative TGV formation methods, including laser drilling, selective laser etching, laser-induced deep etching, wet/dry etching, and photosensitive glass processing, are compared. Metallization approaches based on sputtering, electroless plating, ALD/CVD, and hybrid processes are discussed together with Cu electroplating strategies such as conformal plating, bottom-up filling, pulse or pulse-reverse plating, and engineered-geometry filling. Key defects, including voids, seams, pinch-off, seed discontinuity, Cu/glass interfacial delamination, glass cracking, and Cu protrusion, are reviewed in relation to thermomechanical reliability. Finally, polymer/dielectric plugging, plugging/re-drilling, conductive paste plugging, and hybrid Cu/plugging structures are discussed as application-specific alternatives for balancing electrical performance, reliability, manufacturability, yield, and cost. Full article

Residual stresses and distortions are critical challenges in laser beam powder bed fusion (PBF-LB) of Ti6Al4V components (PBF-LB/M/Ti6Al4V), impacting structural integrity and dimensional accuracy. This study assesses the inherent strain method (ISM) as a computationally efficient alternative to full thermomechanical simulations for predicting these effects. By integrating ISM with experimental validation via the contour method, the research provides specific insights into stress distribution patterns in geometries featuring stress concentrators such as notches. Results demonstrate a strong correlation between simulation and experimental data, particularly at the mid-height regions. Quantitatively, the orthotropic ISM successfully predicted the peak residual stress at 1101.4 MPa, showing excellent agreement within a 4% error margin against the experimental maximum of 1144 MPa captured via the contour method. These findings underscore how ISM can be effectively applied to practical engineering components to predict high-stress zones, enabling the design of distortion-compensated parts without the high computational cost of traditional models. Ultimately, this method facilitates more robust process optimization and enhances the quality and reliability of Ti6Al4V components manufactured via PBF-LB. Full article

Plantar orthoses play an important role in podiatric care, as they help to redistribute plantar loads, improve foot function, and support the treatment of various conditions, including diabetic foot disease. In this context, additive manufacturing has substantially expanded the capacity to produce customized orthoses through digital geometry acquisition, computational design, and controlled fabrication. From a biomimetic and bionic perspective, 3D-printed plantar orthoses can be understood as engineered interfaces that reproduce, support, or modulate key biomechanical functions of the human foot, including load redistribution, shock attenuation, adaptive stiffness, and gait stabilization. Additive manufacturing enables these biological and biomechanical principles to be translated into patient-specific devices through controlled geometry, graded structures, and material selection. Moreover, from a sustainability perspective, recycled polylactic acid (rPLA) has emerged as a material of potential interest for this type of application, not only because of its compatibility with 3D-printing processes but also because it offers the possibility of reusing polymer waste and reducing the consumption of virgin raw materials in devices whose service life may be limited. This review examines the conditional viability of recycled PLA for 3D-printed plantar orthoses by integrating direct clinical evidence on orthotic function with indirect technical evidence from material-level and process-level studies. The reviewed literature indicates that recycled PLA may offer environmental and economic benefits; however, repeated thermomechanical reprocessing may alter viscosity, dimensional consistency, crystallinity, interlayer adhesion, and mechanical reliability. Recent orthosis-focused studies show that extrusion-based technologies can be applied to customized insoles, lattice or internally reinforced structures, multimaterial systems, and emerging smart concepts; however, most of these developments still rely on virgin or ad hoc-designed materials rather than recycled feedstocks. Overall, the available evidence suggests that recycled PLA should not yet be regarded as a direct substitute for virgin PLA in plantar orthoses. At present, the evidence supporting the use of recycled PLA in plantar orthoses is predominantly indirect and technical rather than directly clinical. Its use appears technically promising, but its viability remains conditional and depends on feedstock traceability, control of the manufacturing process, the suitability of material properties for device function, and validation of the orthosis under clinical conditions. Full article

Accurate Remaining Useful Life (RUL) prediction of TFT-LCD modules is critical for industrial predictive maintenance, yet it remains heavily challenged by complex degradation mechanisms in different climates. Traditional purely data-driven models (SVR, LSTM) often lack physical interpretability, struggling to filter out environmental noise or predict irreversible failures. To address this, we propose a highly reliable prognostic tool based on a Physics-Informed Gaussian Process Regression (PI-GPR) framework, by embedding cumulative thermal load and thermo-mechanical stress into the model’s prior function. Evaluated using one-year field exposure data, the physical constraints empower the model to accurately predict device lifetime under highly variable environments, including luminance fluctuations in tropical hygrothermal conditions and device failures in cold environments. Quantitative results demonstrate that the unified PI-GPR framework achieves an outstanding coefficient of determination (R² = 0.93) and reduces the RUL prediction error to merely 7.5 days, significantly outperforming conventional shallow learning, deep sequence, and standard probabilistic baselines. Ultimately, this study provides a robust, physically grounded methodology for the health monitoring and life cycle management of display modules in practical industrial applications. Full article

The increasing demand for new products and the development of new technologies have inspired a search for novel materials that are able to satisfy the increasing exigencies of higher resistance against aggressive environments, enhanced thermomechanical properties, finer and better controlled microstructures and improved reliability and durability in service [...] Full article

Clamp band separation mechanisms are widely used in spacecraft interfaces, and the clamp band preload is a key factor governing both connection reliability and separation performance. The conventional torque-control method is susceptible to friction-induced preload non-uniformity in clamp band separation mechanisms. To overcome this limitation, thermal preloading has been proposed as an alternative installation method. In this paper, a thermo-mechanical analytical model is established for clamp band separation mechanisms during thermal preloading based on curved-beam and thin-shell theories. Theoretical analysis shows that the preload distribution can be divided into three characteristic zones: a stick zone, a slip zone, and a separation zone. In the stick zone, the preload remains constant and is mainly governed by thermal stress and structural relative stiffness. In the slip zone, friction dominates the load transfer, leading to a non-uniform preload distribution. In the separation zone, local disengagement occurs near the clamp band joint end due to the eccentricity-induced bending moment. The proposed model is validated by finite element simulations, and parametric studies are conducted to reveal the effects of friction coefficient and structural geometric parameters on preload distribution. Based on the theoretical model, a zoned-heating method is proposed to improve preload uniformity, providing a useful reference for optimizing the thermal preloading method. Full article

With the continuous advancement of thrust-to-weight ratios in modern aero-engines, turbine inlet temperatures have reached levels that far exceed the thermal endurance limits of conventional superalloys and emerging ceramic matrix composites (CMCs). Consequently, thermal barrier coatings (TBCs) and environmental barrier coatings (EBCs) have become indispensable multifunctional systems for hot-section component protection. This review systematically delineates the evolutionary trajectory of TBC/EBC systems, transitioning from traditional yttria-stabilized zirconia (YSZ) and simple silicates to advanced multi-rare-earth-doped oxides, A₂B₂O₇ pyrochlore structures, and high-entropy ceramic systems. A critical comparative assessment is provided regarding their phase stability, thermal-physical properties, and durability challenges above 1200 °C. Furthermore, this paper provides an in-depth analysis of high-temperature degradation mechanisms, focusing on the thermochemical and thermomechanical interactions under calcium-magnesium-alumino-silicate (CMAS) attack, water-oxygen corrosion, and molten salt infiltration. By synthesizing current research gaps, we highlight the trade-offs between low thermal conductivity, high toughness, and environmental resistance. Finally, a strategic roadmap for next-generation coatings is proposed, emphasizing the integration of high-entropy material design, multi-scale structural optimization, and AI-driven life prediction models to meet the stringent reliability requirements of future propulsion systems. Full article

With the rapid development of clean and low-carbon energy systems, non-metallic pipelines have become increasingly important in urban gas distribution, water supply, and emerging energy-transport applications, including hydrogen service. As a critical joining technology that governs system integrity and long-term operational safety, electrofusion welding requires a comprehensive and mechanism-oriented understanding beyond empirical process control. In this study, a review is conducted on research published over the past decade in the field of electrofusion welding of non-metallic pipelines, with emphasis on fundamental technical issues including the formation and evolution of temperature fields, characteristics of the molten fusion zone and defect development, and thermo-mechanical coupling with residual stress generation. Based on a synthesis of the literature, the review clarifies the global research landscape, core research communities, and underlying knowledge structure. The results indicate a clear transition of the field from empirically driven parameter optimization toward a mechanism-based and process-controllable paradigm centered on temperature field evolution, fusion zone development, and thermo-mechanical behavior. Current research hotspots converge on HDPE material adaptability, welding process regulation, and the long-term reliability of welded joints. Building on these insights, future research directions are discussed, including mechanism-driven process design, intelligent defect identification based on multi-source data, and full-life reliability assessment under service conditions. This review provides a theoretical framework to support process optimization and engineering application of electrofusion welding in non-metallic pipeline systems. Full article

Bipolar plates are critical components of proton exchange membrane fuel cells (PEMFCs), strongly influencing thermal management, mechanical stability, and overall system efficiency. In this study, an integrated framework combining multiphysics simulation, artificial intelligence (AI), and data augmentation techniques was developed for PEMFC bipolar plate optimization. A coupled thermal–structural finite element model was established in COMSOL Multiphysics to evaluate temperature distribution, thermal stress, and structural deformation under varying operating conditions. A total of 80 parametric design cases were generated by varying six key parameters: hole radius, plate thickness, heating power, manifold pressure, plate number, and heat transfer coefficient. The dataset was expanded using SMOTE, GAN, and LLM-based augmentation techniques and used to train ANN, LR, RF, XGBoost, and SVR models. Model performance was evaluated using 5-fold cross-validation with MAE, RMSE, and LogCosh metrics. The results showed that ensemble tree-based methods, particularly RF and XGBoost, achieved the highest prediction accuracy and computational efficiency. XGBoost produced the best temperature prediction performance for the SMOTE-based dataset (RMSE = 3.668), while RF achieved the lowest stress prediction error (RMSE = 0.0490). GAN-augmented datasets provided stable and reliable predictions, whereas LLM-generated datasets resulted in higher prediction errors and lower physical consistency. Feature importance analysis revealed that plate thickness dominates displacement prediction (≈0.72 importance), manifold pressure governs stress behavior (≈0.999), and heating power is the primary factor affecting temperature prediction. The proposed AI-assisted surrogate modeling framework enables rapid and accurate thermo-mechanical prediction while significantly reducing computational cost compared to conventional multiphysics simulations. The findings demonstrate that integrating physics-based simulations with data-driven approaches provides an efficient strategy for the optimization of next-generation PEM fuel cell bipolar plates. Full article

This study presents a coupled numerical–experimental investigation into the early-age thermo-mechanical behaviour of 3D-printed concrete (3DPC), with particular emphasis on strength development, interlayer bonding, and thermally induced cracking that govern structural buildability and performance. A coupled multiphysics modelling framework was developed in COMSOL Multiphysics by integrating hydration kinetics, maturity theory, thermo-mechanical coupling, and a cohesive-zone-based interlayer damage formulation through user-defined time-dependent constitutive relationships and domain activation functions. The model simulated the temporal evolution of temperature, stiffness, stress development, and interlayer degradation during the early-age printing process. The model simulates the temporal evolution of temperature, stiffness, and interlayer damage and was validated against experimental results from compression, interlayer bond, and fracture tests conducted under varying printing time gaps and curing temperatures. The results demonstrate that increasing interlayer deposition intervals up to 60 min leads to reductions of approximately 38% in interlayer bond strength and a significant reduction in apparent compressive strength exceeding 80% between 0 and 60 min deposition delay. It should be noted that this reduction primarily reflects interlayer-dominated failure and loss of structural continuity rather than intrinsic degradation of the bulk cementitious matrix, primarily due to hydration discontinuity, moisture loss, and progressive substrate stiffening. Elevated curing temperatures further intensify thermal gradients, resulting in higher residual stresses and increased crack susceptibility at interlayer interfaces. The numerical predictions showed good agreement with the experimental responses, with peak-force prediction errors below 5% and RMSE values of approximately 0.30–0.45 kN along the post-peak softening, confirming the reliability of the proposed modelling approach. The findings highlight the critical importance of printing continuity and thermal control in governing early-age structural performance and provide quantitative guidance for optimising process parameters in extrusion-based 3D concrete printing. Full article

The reliable joining of thermoplastic composites is a critical requirement in modern manufacturing, where achieving zero-leakage joints is essential. For this application, ultrasonic welding is a highly efficient technology. Traditionally, standard heuristic methods and static experimental designs are used to optimize machine parameters. However, the process exhibits high stochastic variability due to complex, nonlinear thermomechanical interactions, which significantly influence the final seal quality and the reliability of the entire production system. This paper presents a practical prediction-optimization framework using a hybrid stacking ensemble neural network to process welding data. To improve the accuracy and stability of the manufacturing process, the predictive model is integrated with a Monte Carlo simulation. Evaluation showed that the proposed framework achieved the best performance among the evaluated benchmark models, with a coefficient of determination R² = 0.8523 and a mean absolute error MAE = 0.7224. The proposed framework identifies candidate optimized machine parameters in a simulation-based workflow and defines stable operating conditions for subsequent experimental validation, providing a bounded data-driven approach for minimizing leakage in ultrasonic welding. Full article

Underground Compressed Air Energy Storage (CAES) is a promising large-scale energy storage technology, yet its long-term operational safety is constrained by progressive tensile damage accumulation in lining structures under cyclic thermo-mechanical loading. Conventional steel-lined caverns are costly, while ordinary reinforced concrete linings require excessive reinforcement due to their limited tensile capacity, compromising the economic viability of CAES. This study proposes a Reinforced-Steel Fibre Concrete (R-SFC) lining as the structural load-bearing layer of CAES caverns, in which the steel fibres provide tensile and crack-propagation resistance and the rebars contribute supplementary tensile capacity. A 2D coupled thermo-mechanical damage-plasticity finite element model was developed in COMSOL Multiphysics and verified using published in situ monitoring data from operating CAES caverns. Parametric analyses of the steel fibre volume fraction, lining thickness, rebar diameter, and cavern diameter were then performed. The results show that the R-SFC lining significantly improves crack propagation resistance, reducing the maximum tensile damage by 41.3% relative to conventional reinforced concrete while lowering steel consumption. Within the lining–rock system, the concrete lining and the surrounding rock jointly resist the radial compressive load, while the steel fibres and rebars bear the hoop tensile stress. A thickness-to-diameter ratio of 1/8 to 1/5 is identified as the recommended geometric design range to balance lining damage against surrounding rock loading. Finally, an MOPSO algorithm coupled with a PSO-BP surrogate model is employed to balance lining tensile damage against cavern dimensions, yielding optimised parameter combinations particularly suitable for cavern diameters around 4 m. The study findings may provide a new lining solution and design reference for cost-effective and high-reliability underground gas storage. Full article

This study examines the influence of scale effects on the thermomechanical and structural performance of chemically cured, glass-fibre-reinforced polyester composites. Two reinforcement architectures—plain 0/90° fabric and biaxial fabric—were analysed to assess differences in resin flow, curing behaviour, and mechanical characteristics. Differential Scanning Calorimetry (DSC) was employed to characterise cross-linking kinetics at 15 °C, 19 °C, and 25 °C, demonstrating that higher cure temperatures markedly accelerate gelation and cross-linking. Composite plates were manufactured by Light Resin Transfer Moulding (L-RTM), and static tensile tests were conducted in accordance with PN-EN ISO 527-4. The results confirm that reinforcement architecture strongly affects processability and mechanical performance. The 0/90° fabric provided superior resin permeability and shorter infusion times, whereas the biaxial fabric required higher injection pressure and exhibited longer curing duration. Statistical analysis based on Weibull’s brittle strength theory verified the presence of scale effects: larger specimens displayed lower nominal strength due to a higher probability of internal flaws. Multiple regression modelling further revealed relationships between geometric and mechanical parameters: maximum (destructive) stress, Rm, was the dominant factor influencing both specimen thickness and number of layers, while deformation at maximum stress (εm) primarily determined specimen length. These findings highlight the necessity of accounting for size-dependent behaviour when designing and testing polymer composites. Considering scale effects enables more reliable extrapolation from laboratory-scale tests to full-scale components, thereby improving predictability and structural reliability in engineering applications. Full article

The reliable joining of ultra-thick aluminum alloy plates remains a critical technical challenge in modern industrial manufacturing, often hindered by defects such as porosity and excessive distortion associated with conventional fusion welding. The novelty of this work lies in the characterization of the intermediate layer overlapping zone in 110 mm ultra-thick plates, which has rarely been reported. The motivation is to overcome the limitations of single-pass FSW for thick plates, such as insufficient material flow and high tool forces, by adopting a sequential double-sided strategy. Furthermore, this technique may help moderate the through-thickness heat input variation, although no direct thermal measurements were made. The weld nugget zone consists of uniformly fine, recrystallized α-Al grains. In contrast, the heat-affected zone displays distinctly laminar grain structures. The overlapping regions within the intermediate layer, which undergo two thermal cycles, exhibit refined grain sizes. A well-defined interface is evident between the advancing-side weld nugget zone and the thermo-mechanically affected zone. The overall tensile strength of the FSW joint is approximately 81% of the base material, and the tensile specimen fractured at the interface between the thermo-mechanically affected zone and the heat-affected zone. Along the thickness of the weld joint, a “W”-shaped microhardness distribution is observed at the surface and subsurface, whereas the intermediate layer exhibits a distinct “V”-shaped profile. The lowest microhardness value is located in the intermediate layer overlapping area due to the insufficient heat input and limited grain growth in this region. In summary, under the specific welding parameters tested (130 rpm, 15 mm/min, 110 mm thick), double-sided friction stir welding produces defect-free joints in AA 5052-H32, suggesting its potential for thick-plate applications, offering a practical and effective solution for manufacturing high-performance aluminum alloy structures. Potential industrial applications include pressure vessels for chemical storage, ship hull structures, and heavy-duty transportation components where ultra-thick aluminum plates are required. Full article

The rapid advancement of high-performance computing has spurred growing demand for miniaturized, high-density, high-power, and highly reliable electronic packaging. Through-silicon via (TSV), as a pivotal technology enabling high-density integrated packaging, achieves vertical interconnection that reduces signal latency and power consumption while substantially improving system integration. However, inherent challenges persist due to coefficient of thermal expansion mismatches among heterogeneous materials in TSV and parasitic effects introduced by high-density TSV arrays, leading to critical concerns regarding thermomechanical reliability and signal integrity. This study focuses on TSV structures, investigating their thermomechanical reliability and electrical performance. First, the macro–micro model of 2.5D package structure was established to address cross-scale challenges based on Representative Volume Element (RVE) homogenization and sub-model technique. Then, an equivalent circuit model integrating transmission line network theory was developed and validated through full-wave electromagnetic simulations using S-parameter analysis to analyze signal transmission characteristics. Finally, by introducing an improved multi-objective grasshopper algorithm, the structural parameters of TSV are co-optimized using a genetic algorithm back propagation network (GA-BP) and an improved multi-objective grasshopper algorithm (IMOGOA) to enhance both thermomechanical reliability and electrical characteristics simultaneously. The proposed approach offers a practical and effective solution for improving the reliability and performance of high-density integrated packaging, providing valuable insights for future packaging design and optimization. Full article