Search Results (16,090)

The auxetic reentrant structure, one of the most widely studied negative Poisson’s ratio structures for its geometric simplicity, has long seen limited applications due to challenges emanating from its inherent design when built from a single rigid or flexible material. This paper aims to address these challenges by taking advantage of dual-material extrusion technology and density gradient design strategy. Two density gradient reentrant auxetic structures are proposed and fabricated using material extrusion additive manufacturing in single-material (flexible) and dual-material (rigid/flexible) modes, with the introduction of a novel dual-material interface design. In-plane compression tests are carried out to assess the energy absorption characteristics of the structures. The results show that dual-material structures exhibit higher yield stress, mean crushing force, peak crushing force, and maximum crushing force, as well as superior specific energy, energy dissipation, and energy release compared to single-material structures. Dual-material structures also demonstrate high lateral stiffness, minimizing elastic instability, a highly desirable feature for reusable energy-absorbing structures with high shape recovery capability. The results substantiate the significance of the synergy between the dual-material and density gradient designs proposed in this study. Overall, the key findings of the study may serve as a reliable reference for the design of future lightweight energy-absorbing structures. 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

Background: This in vitro study evaluated the effect of hydroxyapatite nanoparticle (nano-HAp) incorporation on surface roughness and Vickers hardness of a 3D-printed crown resin after thermocycling. Methods: Disk-shaped specimens (N = 84) were modified and fabricated with 0%, 1%, 2%, and 3% nano-HAp. Surface roughness (Ra) and Vickers hardness (VHN) were measured before and after thermocycling (5000 cycles). Surface morphology was qualitatively assessed using FE-SEM. Data were analyzed using two-way mixed-design ANOVA (α = 0.05). Results: Thermocycling increased surface roughness and reduced hardness in all groups. Ra values were highest in the 3% nano-HAp group after thermocycling (1.16 ± 0.47 µm). Baseline Vickers hardness differed significantly among nano-HAp concentrations, and hardness decreased after thermocycling in all groups; however, the 3% nano-HAp group exhibited the highest post-thermocycling hardness values (24.66 ± 1.51 VHN), which should be interpreted in the context of its higher baseline hardness. FE-SEM observations suggested increased surface irregularities with higher nano-HAp concentrations after thermocycling. Conclusions: Nano-HAp incorporation influenced both surface and mechanical properties, with 3% concentration showing higher hardness after aging but increased roughness. Full article

The widespread adoption of additive manufacturing, particularly selective laser sintering (SLS), has raised concerns about the disposal of unused thermoplastic powder residues, such as polyamide 12 (PA12). The high cost of PA12 and its degradation during the SLS process highlight the need for sustainable reuse strategies. This study evaluates the feasibility of reprocessing non-sintered PA12 powder without the addition of virgin material through fused deposition modeling (FDM) and injection molding (IM). Thermal analysis showed that the material retains processing temperatures comparable to virgin PA12. However, a significant reduction in melt flow index (≈61%) was observed, reflecting reduced processability and suggesting molecular-level changes affecting chain mobility. Injection molding demonstrated consistent mechanical behavior and good ductility, confirming its suitability for processing recycled PA12. In contrast, FDM processing resulted in higher variability and reduced ductility, mainly due to limitations in interlayer bonding associated with the increased viscosity of the material. Overall, the results highlight injection molding as a robust route for the valorization of non-sintered PA12, while FDM remains a feasible but less reliable alternative requiring further optimization. Full article

Smart hydrogel systems with stimuli-responsive properties are increasingly being investigated in combination with advanced additive manufacturing techniques for targeted drug delivery and wound healing in regenerative medicine; however, their clinical translation remains limited by challenges related to material performance, design complexity, and manufacturing scalability. This review analyzes recent developments in smart hydrogel design and 4D-printed scaffolds, with emphasis on programmable and stimuli-responsive architectures. The literature is selectively evaluated based on relevance to (i) hydrogel structure–property relationships, (ii) 3D/4D printing strategies, and (iii) demonstrated performance in drug delivery and wound healing applications. The analysis highlights design approaches enabling spatiotemporal control of drug release and dynamic scaffold behavior, while also examining how fabrication methods influence functional outcomes. Major limitations are critically assessed, including issues of reproducibility, mechanical stability, long-term performance, and the gap between experimental studies and clinical application. Challenges in defining and implementing 4D printing in biomedical contexts are discussed as well. Overall, this review identifies current design trade-offs, outlines priorities for improving reliability and translational potential, and synthesizes emerging trends in 3D and 4D printed hydrogel scaffolds for precision drug delivery and regenerative wound therapy. Full article

Additive manufacturing (AM) enables the fabrication of complex three-dimensional components with embedded internal flow channels, but the as-built inner surfaces often exhibit high roughness and poor surface-quality uniformity, particularly at non-coplanar corner regions such as sharp bends and junctions. Conventional abrasive flow machining (AFM) can improve the overall surface finish of such channels; however, corner regions commonly remain weak-removal zones because of local flow stagnation and insufficient abrasive action. To address this limitation, this study proposes a six-degree-of-freedom (6-DOF) robotic-arm-assisted liquid metal-driven abrasive flow (LM-AF) polishing strategy in which robotic pose regulation is used to guide the liquid metal droplet to designated corner regions while preserving its responsiveness to the electric field. Numerical simulations and conventional AFM experiments on S-shaped and M-shaped spatial channels were first conducted to identify the corner regions as the primary sources of polishing non-uniformity. A robotic posture-control framework was then established through manipulator kinematics, point-cloud-based flow-direction identification, and Rodrigues-matrix-based pose transformation. On this basis, localized secondary polishing was experimentally performed on an S-shaped channel using an AC electric-field-driven liquid-metal abrasive system. The results show that corner-region roughness was significantly reduced and approached the straight-channel benchmark after secondary polishing, demonstrating a marked improvement in inner-surface uniformity. This study provides a practical route for targeted compensation polishing in complex three-dimensional internal channels and offers a new framework for robotic-assisted post-processing of AM-fabricated flow paths. Full article

Adhesion between fused deposition modelling (FDM) printed polymers and textile substrates is critical for durable printed-on-textile hybrids. Since no dedicated test standard exists for additively manufactured textile interfaces, many studies use T-peel methods adapted from adhesive-bond standards. However, printed-on-textile joints are often governed by polymer penetration into the fabric and mechanical interlocking, rather than by a discrete adhesive layer. This work evaluates a fixture-based perpendicular (normal-separation) tensile method, using a circular dolly printed directly onto a cotton plain-weave substrate and a fully 3D-printable, threaded, self-aligning clamping assembly. Three representative filaments, namely polyethylene terephthalate glycol-modified (PETG), polylactic acid (PLA), and thermoplastic polyurethane (TPU), were tested using both the proposed pull-off method and an ISO 11339-type T-peel benchmark, with n = 8 specimens per polymer. The perpendicular method produced complete datasets for all polymers and clearly differentiated adhesion performance (TPU > PLA > PETG). In contrast, for T-peel, the standard evaluation window (25–125 mm) was completed for all PETG specimens but only for a subset of PLA specimens and a single TPU specimen. In the remaining tests, premature substrate failure prevented completion of this window, so the results could not be evaluated. Microscopy confirmed distinct interlocking morphologies across polymers, supporting the observed differences in failure behavior between peel and normal separation. Overall, the results indicate that perpendicular dolly pull-off testing is a practical and reproducible alternative for quantifying adhesion across a wider range of printed-on-textile bonding conditions. Full article

This work presents a methodology for the generation of continuous fibre trajectories based on principal stress directions in continuous fibre-reinforced additive manufacturing (CFAM). The material system considered consists of continuous carbon fibre (CCF-1.5K) embedded in a CFC-PA thermoplastic matrix. CFAM enables the deposition of fibres along tailored paths, allowing improved alignment with the load direction, compared to traditional composite manufacturing. In this way, the strong anisotropy of composite materials, typically considered a limitation, is exploited as a design opportunity by aligning fibres with the structural load paths. The proposed approach combines finite element analysis with a path generation procedure, including the computation of principal stress directions, the extraction of streamlines of the principal stress field, and a dedicated post-processing stage aimed at obtaining continuous and manufacturable fibre layouts. The effectiveness of the method is assessed through a finite element-based comparison with conventional fibre configurations, showing an increase in global stiffness of approximately 20% with respect to the best-performing unidirectional layout. In addition, the feasibility of the generated trajectories is demonstrated through printing tests performed on a continuous fibre additive manufacturing system. The results confirm that the proposed methodology enables the generation of physically realizable fibre paths while improving structural performance. Full article

Three-dimensional integrated circuits (3D ICs) have emerged as a key technology to sustain scaling trends in the microelectronics industry. This advancement calls for a fundamental shift in how electrical interconnects are implemented, with through-silicon vias (TSVs) playing a pivotal role in enabling vertical connectivity between stacked chips. However, the metallization of TSVs traditionally involves elaborate and demanding processes, which can limit the speed and flexibility of prototyping and design modifications. In this paper, we investigate the use of Ultra-Precise Dispensing (UPD) technology of novel silver nanoparticle-based pastes as a simple and adaptable alternative to the metallization of TSVs process. The TSV filling process is outlined, followed by a detailed analysis of their morphology, filling quality, and electrical performance. We successfully achieve filled vias through a 280 μm thick silicon substrate with diameters down to 20 μm, resulting in an aspect ratio of up to 14:1, exhibiting favorable electrical properties. This work contributes to the achievement of dense, high-aspect ratio TSV fabrication using additive manufacturing, demonstrating a path towards reduced complexity of standard technology processes cycle, lower cost potential, and increased design flexibility. Full article

This study examines the relationship between manufacturing-specific foreign direct investment (FDI) and manufacturing output in ASEAN-6 countries over the period 2012–2022. While existing empirical studies largely rely on aggregate FDI measures, such evidence may obscure sector-specific mechanisms through which foreign investment affects production capacity and industrial performance. Focusing on manufacturing-oriented FDI allows for a more direct assessment of how sector-targeted investment is associated with industrial resilience and value-added stability, which represent the economic dimension of sustainability considered in this study. Sustained industrial output performance is proxied by manufacturing value added (GDPm) and interpreted as the manufacturing sector’s ability to maintain and expand value added over time amid macroeconomic volatility and external shocks. Using a balanced panel dataset of six ASEAN economies (ASEAN-6) with 66 country-year observations and a fixed-effects specification selected through standard model-selection tests, the results indicate that manufacturing-specific FDI is positively and statistically significantly associated with manufacturing output at the panel-average level. Manufacturing contribution to GDP also exhibits a strong positive association, while exchange rate movements are negatively associated with manufacturing output. Inflation is positively associated with output during the study period and is interpreted as a context-specific co-movement rather than a normative implication for long-run sustainability. To provide additional insight into shock-period dynamics, the analysis compares pre-COVID (2012–2019) and COVID/post-COVID (2020–2022) sub-period estimates. The positive association between manufacturing-oriented FDI and output is more pronounced before the pandemic. It weakens during the pandemic and early recovery years, consistent with supply-chain disruptions and temporarily reduced absorption capacity. The findings highlight the importance of sector-specific FDI, industrial structure, and macroeconomic stability in supporting manufacturing resilience in ASEAN-6 economies. Full article

Additively manufactured lattice structures have become a staple of optimized structural parts and are increasingly common in biomedical and chemical applications that require consideration of flow through porous architectures. However, design principles governing transport performance trail those established for mechanical optimization. Here, we introduce two complementary design frameworks that modify symmetry at both the unit cell and part scales to systematically tune internal transport. These approaches are further extended into patterned lattice structures, where multiple unit cell designs can be combined in one, two, or three dimensions to further regulate the internal flow. We find that identical global lattice geometries can arise from different unit cell basis and voxel plane orientations, with minimal changes in bulk geometric properties. Yet in parts with diameters of 12–35 mm, hydraulic diameters of 1–4 mm, and porosities ~80%, these design selections significantly affect the hydraulic tortuosity and fluid transport behavior. We further demonstrate performance from select designs that yield a new class of anisotropic lattices with strong sensitivity to flow direction that is tuned by the projected area perpendicular to flow. Collectively, these symmetry-informed, multi-order combinatorial design approaches enable predictable, direction-dependent transport design and expand the functional potential of lattice architectures across disciplines. 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

Poly(lactic-co-glycolic acid) (PLGA) is one of the most extensively investigated biodegradable polymers for biomedical applications, owing to its tunable degradation kinetics, established biocompatibility, and regulatory approval. In implantology, PLGA-based systems have emerged as versatile platforms for scaffolds, coatings, and localized drug delivery, aimed at enhancing osseointegration and tissue regeneration. This review provides a focused and up-to-date analysis of PLGA applications in dental and orthopedic implantology, with particular emphasis on advances reported over the past decade. Unlike previous reviews that predominantly address general drug delivery or broad tissue engineering applications, this work establishes a direct correlation between polymer composition (LA:GA ratio), processing strategies, and biological outcomes, including degradation behavior, mechanical performance, and host response. Special attention is given to multifunctional PLGA systems incorporating antibiotics, growth factors, and bioactive nanoparticles, highlighting their role in improving antibacterial efficacy and osteogenesis. Emerging technologies such as nanostructured composites, additive manufacturing, and stimuli-responsive delivery platforms are critically evaluated. Key limitations—including acidic degradation by-products, burst release kinetics, and translational barriers—are discussed in the context of clinical applicability. By integrating physicochemical design with biological performance and recent clinical trends (2024–2025), this review proposes a framework for the rational development of next-generation PLGA-based implant systems. Full article

Multi-objective flexible job shop scheduling requires balancing conflicting objectives while supporting real-time decision-making in industrial environments. However, although traditional metaheuristics are effective for global search, their high computational cost limits their applicability in time-sensitive scenarios. To address this issue, this paper proposes dual-pool guided preference-conditioned graph reinforcement learning (DPG-GRL), an encoder–decoder framework for the multi-objective flexible job shop scheduling problem. In DPG-GRL, a graph attention network encoder extracts operation and machine-level representations from a heterogeneous graph, while the decoder is conditioned on a preference vector to generate scheduling solutions with different trade-offs using a single trained policy. To improve sample efficiency and training stability, a dual-pool guidance mechanism is introduced, in which an offline expert pool provides a stable behavioral prior for policy initialization and an online elite pool continuously replays high-quality trajectories to refine the policy. Experimental results show that DPG-GRL outperforms representative multi-objective evolutionary algorithms, including the non-dominated sorting genetic algorithm II (NSGA-II) and the multi-objective evolutionary algorithm based on decomposition (MOEA/D), on synthetic instances, with more pronounced advantages in solution quality and inference efficiency as the problem scale grows. In addition, evaluations on public benchmark instances using a model trained only on the small synthetic setting demonstrate rapid Pareto-front approximation, high-quality solution sets, and promising generalization to unseen instances. These results indicate the potential of DPG-GRL for real-time production scheduling and energy-aware manufacturing. Full article

Snail mucus is increasingly investigated as a biologically compatible source of multifunctional biomolecules for pharmaceutical and dermatological use. However, the chemical profile and biological activities of mucus from the Moroccan endemic terrestrial snail Otala tingitana remain poorly characterized. In addition, the influence of heliciculture diet on the composition and functional properties of the mucus remains unclear. Here, O. tingitana was reared for 140 days under controlled conditions and fed a basal flour diet or the same diet supplemented with 3% Rosmarinus officinalis, Origanum compactum, or Thymus zygis subsp. zygis. Mucus from wild snails was included for comparison. Mucus samples were chemically profiled by GC–MS and evaluated for antibacterial activity, antioxidant capacity, wound-healing efficacy in mice, and histological anti-inflammatory effects, and evaluated semi-quantitatively based on the degree of inflammatory cell infiltration. GC–MS identified 13 compounds and demonstrated clear diet-dependent shifts in dominant components. All mucus samples exhibited broad-spectrum antibacterial activity against Staphylococcus aureus, Listeria monocytogenes, Escherichia coli, and Salmonella Typhimurium (inhibition zones 10.31–14.30 mm; MIC 120–240 µg/mL), with predominantly bactericidal profiles (MBC/MIC < 4) and significantly enhanced activity in plant-supplemented groups (p < 0.05). Antioxidant performance improved markedly with medicinal-plant supplementation, reaching low IC₅₀ values (best ≈ 1.18 mg/mL) compared with basal-diet mucus. In vivo, topical application accelerated wound closure, achieving complete healing in <21 days, versus 28 days in untreated controls. In addition, histological assessment showed faster resolution of inflammatory cell infiltration in treated groups. Collectively, these findings provide the first integrated evidence that O. tingitana mucus possesses antibacterial, antioxidant, wound-healing, and anti-inflammatory activities, and that heliciculture diet is a practical lever to optimize its bioactive profile. Further studies should prioritize standardized manufacturing, contaminant control, and safety/toxicology assessment before translational development. Full article