Search Results (560)

Quantum Dots (QDs) are nanoparticles that are highly desirable for biomedical applications such as drug delivery, cellular tracking, and imaging due to their fluorescent and tunable optical properties. However, the biochemical mechanism of their interaction with intracellular proteins that regulate cytoskeletal organization remains poorly understood. While previous studies have shown QDs’ ability to interact with actin and alter actin dynamics, their impacts on actin-binding proteins have not been explored. In this study, we investigated the interaction between CdSe/ZnS QDs and the actin-binding protein, α-actinin, and assessed its impact on actin cytoskeletal organization. Our results demonstrated a strong interaction between QDs and α-actinin, which impeded an α-actinin-mediated filamentous actin (F-actin) bundling, as well as compromised the activity of α-actinin in preventing actin depolymerization. Furthermore, the physics-based modeling and simulations carried out at physiological temperatures supported these findings by identifying stable interaction surfaces between QDs and α-actinin. This study provides mechanistic insight into nanoparticle–protein interactions and highlights the potential cytoskeletal toxicity associated with it. Full article

Artificial intelligence (AI) and machine learning (ML) algorithms possess the capability to accelerate the design of novel materials; however, their advancement in materials science is severely hindered by a fundamental deficit of experimental data, commonly referred to as data starvation. Unlike solution-based chemistry, where high-throughput (HT) technologies are a well-established standard, the automated synthesis of solid materials—particularly polymers and multicomponent composites—poses an extreme engineering challenge. Furthermore, the traditional, manual research model is inherently flawed by human bias, notably the systematic non-publication of negative results, which deprives AI models of critical boundary information regarding the design space. This paper is the first in a three-part review series defining the architecture of a fully automated, unbiased “data factory” for closed-loop discovery. This section focuses on the physical foundations of the HT workflow: experimental planning, automated synthesis, and material management. Emphasis is placed on the paradigm shift from classical, discrete Design of Experiments (DoE) to the novel concept of Continuous Gradient DoE. It reviews how robotic platforms utilizing precise gravimetric and volumetric feeders, integrated with extruders and in-line capillary rheology, enable the seamless, high-throughput manufacturing of thermoplastics and composites. Moreover, an innovative approach to sample logistics is presented, redefining classical storage patterns through the implementation of Continuous Material Management. This encompasses direct physical tagging (e.g., inkjet marking on continuous filaments or films), spool-based transport systems, and precise, real-time metadata mapping. As demonstrated, the integration of these systems yields an order-of-magnitude increase in productivity (generating tens of thousands of novel material variants annually), a radical reduction in unit costs, and the production of terabytes of standardized, machine-readable data. Establishing this reliable hardware and analytical infrastructure represents the essential first step toward unlocking the full potential of artificial intelligence in advanced materials engineering. Full article

This work investigates the potential of additive manufacturing (AM) technologies for prototyping and developing functional components in thermal systems, with particular emphasis on thermal and mechanical performance. The study focuses on two complementary prototyping strategies: (i) the use of metal-filled polymer filaments in Fused Deposition Modeling (FDM), also known as Material Extrusion (MEX) according to ISO/ASTM 52900:2022, and (ii) a hybrid approach combining polymer 3D printing with conductive coating and electrochemical copper deposition. While metal-filled filaments provide a rapid and low-cost solution for early-stage prototyping, their mechanical properties remain similar to those of the polymer matrix, limiting their applicability in load-bearing structures. In contrast, the hybrid method enables the fabrication of hollow metallic geometries with improved thermal and electrical conductivity. This approach is more time-consuming and process-intensive and is therefore considered a subsequent stage in the prototyping workflow following initial MEX-based design iterations. Compared with conventional polymer-based MEX, several AM approaches enable the development and fabrication of fully metallic or metal-functional structures, including Powder Bed Fusion (PBF), Directed Energy Deposition (DED), and hybrid polymer–metal methods based on electroplating. Furthermore, understanding mechanical properties such as tensile strength is essential for assessing the applicability of AM materials in energy system components. The results contribute to bridging the gap between rapid prototyping and the implementation of advanced AM technologies in thermal-related applications. Full article

This paper investigates the valorization of peanut shell powder (PSP), an abundant agro-industrial residue, as a biofiller for the development of sustainable 3D printable PLA-based composites for food packaging applications. A low-filled biocomposite containing 2.5 wt.% PSP was successfully processed into filament with dimensional tolerances suitable for fused deposition modeling printing. Thermal and melt flow analyses demonstrated that PSP marginally reduced the thermal stability of PLA while preserving its thermal transition temperatures and increasing the melt flow rate up to 51%. Differential scanning calorimetry revealed a slight increase in crystallinity in biocomposite filament compared to neat PLA pellets, mainly associated with thermo-mechanical processing of the extrusion, while the lower crystallinity degree relative to PLA extrudate suggested a negligible nucleating effect of PSP. To optimize print quality, different extrusion temperatures and infill flow rates were evaluated. The best mechanical performance was achieved at 200 °C and 130% flow rate, where reduced inter-filament porosity (5.2%) resulted in improved tensile strength and stiffness compared with the other printing conditions. Although mechanical properties remained lower than neat PLA, the material proved suitable for non-structural packaging applications. Prototype packaging boxes were fabricated and tested for the storage of fresh-cut melon. Compared with neat PLA packaging, the PLA-PSP system better preserved fruit firmness over 10 days, inhibited fungal growth, and delayed visible deterioration, highlighting the potential active role of PSP in food preservation. Anaerobic biodegradation tests conducted under mesophilic conditions confirmed that the addition of PSP did not hinder PLA biodegradability and slightly enhanced methane production. Overall, the results demonstrate that peanut shell waste can be effectively upcycled into functional 3D-printable biocomposites for sustainable packaging solutions. Full article

Accurate calculation of mutual inductance (MI) between solenoid coils is essential for system design, but complex geometries and spatial arrangements make it challenging. This paper presents a modified analytical method for calculating the MI between two circular-wound air-core solenoid coils arbitrarily oriented in three-dimensional (3D) space. The analytical model used to calculate the MI between two solenoid coils is based on the use of magnetic vector potential (MVP). The helical structure of the solenoid coils is represented by successive coaxial circular filaments arranged along their central axes. Each filament is represented by an equivalent regular polygon with a sufficient number of sides. The proposed approach allows the MI between two solenoid coils to be calculated using a single analytical formula, without imposing restrictions on the relative positions of the coils, while taking lateral and angular misalignments into account. The modified analytical model is validated for accuracy and applicability by comparing its results with experimental measurements and FEM-based simulation results for coil systems with different diameters, turn numbers, and turn pitches. The MI results for various angular and lateral misalignments are in good agreement with experimental measurements and FEM results. The MI calculation model proposed in this work provides a fast and reliable tool for analyzing the electromagnetic behavior of coupled coil systems, designing inductive power transfer systems, and assessing electromagnetic compatibility. Full article

The increasing demand for high-performance and multifunctional polymer materials has driven interest in improving the mechanical properties of polymer components produced through additive manufacturing. This study aims to systematically investigate and comparatively evaluate the effects of low-content nanofiller incorporation on the structural, thermal, and mechanical performance of PLA-based materials produced via fused deposition modeling (FDM), with a focus on identifying filler-dependent behavior under different loading conditions. In this study, polylactic acid (PLA) composites reinforced with 0.5 wt.% graphene (Gr) and 0.5 wt.% silver (Ag) nanoparticles, added separately, were produced using fused deposition modeling (FDM) and comparatively investigated. Each nanofiller was incorporated individually into PLA-based filaments, and standard test specimens were fabricated via 3D printing. Structural, thermal, and mechanical properties were evaluated using tensile, compressive, and three-point bending tests, along with SEM, EDS, XRD, FTIR, DSC, and TGA analyses. The results showed that pure PLA exhibited typical brittle behavior and a single-stage thermal degradation profile. The tensile strength of pure PLA was 41.93 MPa, and the flexural strength was 70.76 MPa. The addition of 0.5 wt.% graphene led to noticeable improvements, particularly in flexural properties, while only a minimal (almost negligible) increase was observed in tensile strength, with tensile strength increasing to 42.24 MPa (+0.74%) and flexural strength increasing to 110.78 MPa (+56.6%). In contrast, 0.5 wt.% Ag exhibited mixed and load-dependent mechanical behavior, with slight improvements in flexural strength but reductions in tensile and compressive properties, where tensile strength decreased to 22.13 MPa (−47.2%) while flexural strength increased to 112.06 MPa (+58.3%). Structural and thermal analyses indicated that both nanofillers did not significantly alter the PLA matrix chemically, while contributing to controlled changes in material properties primarily through physical interactions. The novelty of this work lies in the comparative evaluation of graphene and silver nanoparticle reinforcement at a fixed low loading level within FDM-processed PLA, combined with a comprehensive and correlated analysis of mechanical, structural, and thermal behavior on the same specimen sets, enabling a clearer understanding of filler-dependent performance mechanisms in additively manufactured nanocomposites. Overall, it was concluded that low-rate nanofiller additions, when properly dispersed, may lead to selective improvements in the performance of PLA-based composites depending on filler type and loading mode, and show potential for advanced engineering applications such as lightweight structural components, functional sensors, and additive-manufactured parts requiring tailored mechanical performance and multifunctionality. Full article

The global transition from petrochemical to sustainable bio-based plastics has been strongly supported by electrospinning (ES), a versatile nanotechnology enabling the fabrication of ultrathin fibers with multifunctional properties. The solution ES process alongside the uniform fibers, a characteristic “beads-on-string” morphology, consisting of alternating cylindrical and spindle-like segments, is frequently observed. Once considered undesirable, these structures are now recognized as functional fibrous architectures with enhanced properties. This work explores the valorization of beaded fibers through combined experimental characterization and modeling, aiming to evaluate the impact of beading on drug diffusion and delivery performance. Poly(3-hydroxybutyrate) (PHB) was selected as the model biopolyester and dipyridamole (DPD) as the model drug. Ultrathin fibers were fabricated using the laboratory electrospinning device, EFV-1 (ICP, Moscow, Russia). The distance between the capillary nozzle and the anodic collector was set to 180 mm, with the capillary tip radius equal to 0.35 mm, and applied voltage between the electrodes was kept constant at 18 kV. Drug release profiles were obtained by simulating DPD diffusion in ellipsoidal (beads) and cylindrical fiber domains. Ultrathin fibers were fabricated by solution electrospinning under environmental conditions (at ambient temperature, 50% relative humidity). Morphology was analyzed via SEM, thermal properties via DSC, and structure via FTIR spectroscopy at different temperatures, including the melting point (~170 °C). Drug release kinetics were monitored using a UV-Vis spectroscopy. The impact of DPD diffusion within the ellipsoidal and cylindrical constituents of polymer filaments was considered to modulate release profiles for the development of innovative pharmaceutical platforms. Diffusion controlled drug release was computationally modeled using a specially designed simulation program, in good agreement with experimental data. The results demonstrate that morphological parameters significantly affect diffusion and release kinetics. The controlled exploitation of bead-on-string architectures may enable the design of electrospun materials with tunable absorption of pollutant filtration, mechanical performance, and flexibility in drug release profiles, for sustainable biopolymers like PHB. Full article

This study presents findings of an experimental and analytical approach investigating the relationship between the performance of individual corner joints and overall performance of furniture cabinets constructed with auxetic fasteners. The moment capacities and stiffness of cabinets assembled with different auxetic fasteners were also compared. For this purpose, 12 different auxetic fasteners were produced using three-dimensional printing technology. Cabinet bodies were constructed out of 18 mm particleboard (PB), while fasteners were produced using polylactic acid (PLA), acrylonitrile butadiene styrene (ABS), and acrylonitrile styrene acrylate (ASA) filaments. Cabinets were subjected to diagonal static loading to determine their moment capacity and stiffness. In total, 60 full-scale cabinets were prepared and tested using 12 different fasteners (3 filaments, 2 fastener lengths, and 2 fastener types), with 5 replications for each configuration. The results indicate that filament, and particularly fastener type, had a significant effect on moment capacity and stiffness, whereas fastener length was not statistically significant. Among the tested filaments, PLA exhibited the best performance. Cabinets assembled with H-type fasteners showed higher moment capacities and stiffness compared to those with K-type fasteners. The proposed semi-analytical model developed provides reasonable estimates for predicting the overall performance of cabinets based on individual corner joint tests. Full article

Hybrid organic–inorganic composites based on biopolymers and nanoclays are attracting increasing interest for the development of functional materials in biomedical and agricultural applications. In this work, elongated alginate/halloysite nanotube (Alg/HNT) composite filaments were fabricated through a wet-spinning process assisted by syringe-based extrusion. Alg/HNT dispersions with different inorganic/organic ratios were first screened in terms of colloidal stability and injectability in order to identify suitable formulations for extrusion. The influence of key processing parameters, including the extrusion flow rate and calcium chloride concentration in the coagulation bath, was then systematically investigated to elucidate their effect on filament morphology and structure. Optical and scanning electron microscopy revealed that filament diameter can be tuned by varying the CaCl₂ concentration, while partial alignment of alginate chains along the extrusion direction was observed. Halloysite nanotubes were homogeneously distributed within the polymer matrix, mainly as micro-sized aggregates. Finally, the nanotubes were chemically functionalized with caffeine, as a model molecule, and incorporated into the alginate filaments, demonstrating the feasibility of introducing specific functionalities into wet-spun Alg/HNT composite fibers. These results establish a reproducible strategy for the fabrication of alginate/HNT filaments with tunable morphology and functionalizable nanotube interfaces, providing a versatile platform for the development of sustainable hybrid biopolymer materials. Full article

Flexible thermoplastic polyurethane (TPU) materials fabricated using fused deposition modeling (FDM) are increasingly used in engineering and biomedical applications where exposure to moisture is unavoidable. However, the relationship between material hardness, water absorption, diffusion behaviour, and dimensional stability remains insufficiently understood and investigated. In this study, the hygroscopic behaviour of eight commercially available TPU filaments (60A–98A Shore hardness) was systematically investigated. Specimens were produced using an FDM 3D printer under controlled processing conditions and immersed in physiological solution (0.9% NaCl) for up to 96 h. Water absorption, dimensional changes, and diffusion characteristics were analyzed. Diffusion coefficients were determined using the Fickian diffusion model based on the initial stage of water uptake. The results suggest a transition in behaviour between lower- and higher-hardness materials. Softer TPU materials (60A–85A) exhibited higher water absorption (up to ~1.80%) and an apparent linear trend between hardness and absorption within the investigated material group (R² = 0.999). In contrast, higher-hardness materials (89A–98A) showed lower absorption (~1.18–1.42%) and a weaker apparent relationship with hardness (R² = 0.4214). Diffusion coefficients ranged from 1.40 × 10⁻¹³ to 3.40 × 10⁻¹² m² s⁻¹, with no monotonic dependence on hardness. Additionally, no clear correlation between diffusion kinetics and equilibrium absorption or volumetric expansion was observed. These findings indicate that hygroscopic behaviour of FDM-printed TPU materials cannot be reliably predicted based solely on hardness, and that diffusion, absorption, and swelling may be influenced by different mechanisms. The identified transition from hardness-dependent to behaviour potentially influenced by material structure provides new insight for the design and selection of flexible polymer components in moisture-exposed environments, particularly in biomedical applications. Full article

Polymer-based composites with magnetic properties are promising materials that are able to combine the usual polymer features (low density, high electrical resistance, enhanced flexibility, and processability, etc.) with magnetic properties typically associated with ferro- or ferrimagnetic metals, alloys or metal oxide. The combination of recycled NdFeB powders with additive manufacturing techniques based on material extrusion enables the production of magnetic composites. The novelty of this approach lies in the use of 3D printing supported by an external magnetic field, which is used to align the particles during the printing process and thus improve the final magnetic properties. This approach represents a sustainable strategy for the recovery of electronic waste, converting it into high-value-added magnetic materials intended for additive manufacturing applications. Micrometric particles made of a Neodymium–Iron–Boron (NdFeB) alloy are compounded with a flexible thermoplastic matrix made of polybutylene adipate-co-terephthalate (PBAT). The NdFeB alloy is recovered from permanent magnets of obsolete hard drives and is demagnetized, ground to powder under an inert atmosphere, and finally sieved to a particle size below 50 µm. The obtained powder is mixed with the polymer using a twin-screw extruder. The composite material containing the NdFeB particles is then processed to obtain a calibrated filament, used for the fused deposition modeling (FDM) three-dimensional (3D) printing of magnetic composites. To improve the composite’s ferromagnetic behavior, the particles were aligned along the stacking direction of the layers during the 3D FDM process by printing directly onto a permanent magnet placed on the build plate. Composites containing up to 50% by weight of recycled NdFeB powder were successfully processed using FDM technology, exhibiting increased stiffness, with the storage modulus rising from 123 to 178 MPa at 20 °C, while magnetic field-assisted printing increased the remanence from 11 to 28 emu/g and improved the reduced remanence from 0.21 to 0.49, corresponding to an estimated fourfold improvement in the magnetic energy product. Full article

Dual-material additive manufacturing enables the design of cellular structures with a tailored mechanical response through controlled material distribution and interfacial architecture. In this research, honeycomb structures fabricated by Fused Filament Fabrication (FFF) using dual-material TPU/PLA configurations have been systematically investigated. Particular emphasis is placed on interlocking TPU/PLA joint designs, implemented through tau-shaped and teeth-based geometries, to evaluate their role in load transfer and structural performance. An experimental–analytical model has been developed to characterize the compressive force–displacement response of dual-material honeycombs, capturing the three characteristic deformation regimes—initial stiffness, progressive collapse, and densification—while linking the effective stiffness to the underlying beam-lattice mechanics. The relative contributions of axial and bending deformation mechanisms are quantified through a comparative beam element approach, introducing dimensionless coefficients that reflect the governing deformation mode. The results reveal that the mechanical response is bending-dominated for the examined configurations. The configuration with PLA at the nodes and TPU at the struts exhibits a higher load-carrying capacity and a more stable collapse regime due to a more balanced axial–bending interaction. In contrast, alternative material distributions lead to earlier instability and reduced structural efficiency. The proposed analytical model demonstrates excellent agreement with the experimental data across all configurations. The results demonstrate that properly designed dual-material interlocks can enhance load transfer, decrease stress concentrations, and refine the overall mechanical performance of lightweight cellular structures. Full article

Brush seals, as a fundamental dynamic sealing technology in the aerospace and energy propulsion industries, require performance enhancement through instantaneous adjustment of the friction coefficient and force analysis of brush filaments. This paper establishes an instantaneous friction coefficient correction method based on the open volume between bristles and the backing plate. The downstream section of the double-row brush wire (2.6 mm) was quantitatively identified as the maximum leakage point, and it was found that the vortex characteristic length in the downstream area is approximately 1–3 times the bristle gap, with an increasing pressure ratio enhancing downstream turbulence and reducing gas leakage. A cantilever beam structural model was developed to assess the motion, force, and hysteresis properties of a single filament. Additionally, a porous medium model was utilized to elucidate the flow field and temperature distribution within the seal. The results suggest that the lag angle increases linearly over the first one-third of the brush wire’s length from the free end to the fixed end and is directly proportional to the pressure difference ΔP, reaching a maximum of 10.18°. The viscous drag causes the radial force y-component F_xy to increase and then decrease near the free end. The rear baffle contact force, F_b, shows variable peaks at two-thirds of the filament length. The displacement at the brush filament’s free end, the deflection angle, and the bending moment are directly proportional to the pressure differential. As pressure increases, the deformed region propagates toward the fixed end, and the maximum displacement at the free end of the brush wire reaches 13.04 mm. The leakage rate increases nearly linearly with ΔP and its deformation, reaching a maximum of 0.00849 m²/s. The pressure gradient growth rates of 164%, 73%, and 29% at the front baffle corner demonstrate that adding pressure chambers on front and rear baffles is optimal for high-pressure scenarios (ΔP > 0.3 MPa), while the formation of vortices between bristles and rotor reduces tip friction force and front-row turbulent disturbance, providing design guidance for extending seal service life. Full article

Bird feathers possess functions such as water resistance, thermal insulation, and air permeability, providing inspiration for the design of functional fabrics. Based on the functional differentiation of different feather regions and the structural constraints associated with these functions, this study selected down feathers, feather vanes, hooklets, and fluffy feather filament node structures as biomimetic prototypes. Four biomimetic knitted structures were designed for outdoor environments with significant temperature fluctuations and for the thermo-moisture comfort needs of older adults. Through macro- and micro-structural feature extraction, three-dimensional modeling, and experimental testing, a multi-parameter evaluation system covering water resistance, thermal resistance, thermal insulation rate, air permeability, moisture vapor transmission, and moisture management was established to systematically evaluate the thermo-moisture regulation performance of the fabrics. The results showed that each structure exhibited distinct performance advantages: Structure 1 demonstrated the best thermal insulation performance; Structure 2 showed relatively superior water resistance and outstanding air permeability; Structure 4 exhibited relatively superior moisture vapor transmission and moisture management performance; and Structure 3 achieved the highest gray relational optimality value, indicating a relatively balanced thermo-moisture regulation capability. Among all performance indicators, air permeability showed the highest correlation with the knitted structures. Based on these results, and considering regional differences in heat generation and sweating across different body parts of older adults, this study further explored zonal application strategies for elderly outdoor clothing to improve wearing comfort and functionality under environments with fluctuating thermal conditions. Full article

Down quality is the core evaluation indicator of thermal insulation products, and its grade determination strictly complies with the down content index specified in the national standard GB/T 17685-2016 Feather and Down. Traditional down quality inspection adopts manual sorting and weighing methods, which are plagued by low efficiency, strong subjectivity and high error rates, thereby restricting the intelligent upgrading of the down industry. This study aims to develop an automatic down detection and quantitative grading method conforming to national standards based on deep learning. A down dataset consisting of 632 RGB images is constructed, with each image containing 5–10 individual down samples and covering five categories: mature down clusters, immature down clusters, down filaments, feathers, and yellow-tail down. Three mainstream frameworks including YOLOv8, YOLOv11 and YOLOv26 are trained for performance comparison. Precision, recall, mAP@50 and mAP@50-95 are adopted as evaluation metrics. In addition, this paper proposes a research idea for down content calculation and automatic classification and grading of down quality in accordance with relevant national standards. The experimental results demonstrate that the latest models do not necessarily achieve the optimal performance. The newly released YOLOv26n and YOLOv26m exhibit relatively low accuracy in the down detection task, with mAP@50 values of only 0.98556 and 0.99077, and recall rates of 0.95032 and 0.97848, respectively, failing to outperform their previous-generation counterparts. In contrast, YOLOv11n achieves the best comprehensive performance, with an mAP@50 of 0.99416, a precision of 0.99544, a recall of 0.99722, and an mAP@50-95 of 0.63464. Meanwhile, the model has only 2.58 M parameters, a computational complexity of 6.3 GFLOPs, and a single training time of approximately 6.7 min, achieving an optimal balance between detection accuracy and computational efficiency. All models show the highest detection accuracy for mature down clusters and yellow-tailed down, while slight confusion exists between immature down clusters and down filaments. This study verifies the feasibility of the YOLO series models in down quality inspection in accordance with national standards, and reveals that model architecture iteration does not necessarily lead to performance improvement on specific industrial datasets. The lightweight and robustly designed YOLOv11n presents greater practical value. The intelligent detection scheme proposed in this paper can assist in optimizing the traditional manual quality inspection workflow, alleviating the burden of manual counting and reducing subjective errors. It provides new ideas and technical references for the rapid screening and objective determination of down quality. Furthermore, the proposed research framework for automatic classification and grading of down quality is expected to promote the development of down quality inspection toward standardization, intelligence, and automation in the future. Full article