Search Results (42)

The integration of functional ingredients into 3D food printing formulations presents both opportunities and challenges, particularly regarding the printability and structural integrity of the final product. This study investigates the effect of incorporating omega-3 fatty acids encapsulated in pea protein into a model food gel composed of gelatin and iota-carrageenan. Four formulations with varying concentrations of encapsulated omega-3 (0%, 3%, 3.75%, and 6%) were evaluated for their rheological, textural, and printability properties. Rheological analysis revealed a progressive increase in storage modulus (G′) from 1200 Pa (0%) to 2000 Pa (6%), indicating enhanced elastic behavior. Extrusion analysis showed a reduction in maximum extrusion force from 325 N (0%) to 250 N (6%), and an increase in buffer time from 390 s to 500 s. Print fidelity at time 0 showed minimal deviation in the checkerboard geometry (area deviation: −12%), while the concentric cylinder showed the highest stability over 60 min (height deviation: 9%). These findings highlight the potential of using encapsulated bioactive compounds in 3D food printing to develop functional foods with tailored nutritional and mechanical properties. Full article

Laminate plate and shell structures with symmetric cross-ply configurations are widely used due to their high stiffness-to-weight ratio. However, conventional lamination theories rely on simplifying assumptions that may introduce inaccuracies. This study evaluates the predictive capability of such theories by integrating multiple micromechanics models with First-Order Shear Deformation Theory (FSDT), and comparing the results against voxel-based finite element modeling (VB-FEM), which serves as a high-fidelity numerical reference. A range of models—including Voigt–Reuss, Chamis, Halpin–Tsai, Bridging, and two iterative isotropized formulations—are assessed for unidirectional laminae with fiber volume fractions from 40% to 73%. Quantitative comparison reveals that while all models predict the longitudinal modulus accurately, significant deviations arise in predicting transverse and shear properties. The Bridging Model consistently yields the closest agreement with VB-FEM across all five elastic constants, maintaining accuracy even at high volume fractions where the modified Halpin–Tsai model begins to fail. Discrepancies in micromechanics-based lamina properties propagate to laminate-level stiffness predictions, highlighting the critical role of model selection. These findings establish VB-FEM as a valuable tool for validating analytical models and guide improved modeling strategies for laminated composite design. Full article

Polyvinyl alcohol cryogels (PVA-C) are promising materials for vascular tissue engineering due to their biocompatibility, hydrophilicity, and tuneable mechanical properties. This study investigates the mechanical performance of multi-layered PVA-C constructs fabricated via sub-zero extrusion-based three-dimensional (3D) bioprinting. Samples with two, four, and six alternating layers were evaluated to assess the effect of layered architecture on elastic and viscoelastic behaviour. Uniaxial tensile testing revealed that increasing the number of layers led to a moderate reduction in stiffness; for instance, at 20% strain, six-layered constructs showed a significantly lower (p < 0.05) Young’s modulus (36.7 ± 2.5 kPa) compared to two-layered ones (47.3 ± 3.1 kPa). Stress–strain curves exhibited nonlinear characteristics, better captured by quadratic (as opposed to linear) fitting, within the tested strain range (≤40%). Dynamic mechanical analysis demonstrated a frequency-independent storage modulus (E′) across 1–10 Hz, with subtle variations in viscoelastic response linked to the number of layers. Visual inspection confirmed improved print fidelity and hydration retention in thicker constructs. These findings demonstrate that a multi-layered design influences the mechanical profile of PVA-C and suggests potential for functionally graded design strategies to enhance compliance matching and mimic the biomechanics of native vessels in small-diameter vascular grafts. Full article

The integration of digital twin technology with structural health monitoring (SHM) is revolutionizing the assessment and maintenance of critical infrastructure, particularly bridges. Digital twins—virtual, data-driven replicas of physical structures—enable real-time monitoring by continuously synchronizing sensor data with computational models. This study presents the development of a real-time digital twin for a three-span steel railway bridge, utilizing a high-fidelity finite element (FE) model built using OpenSeesPy v 3.5 and instrumented with 18 strategically placed accelerometers. The dynamic properties of the bridge are extracted using Stochastic Subspace Identification (SSI), enabling an accurate estimation of modal parameters. To enhance the fidelity of the digital twin, a genetic algorithm-based model-updating strategy is implemented, optimizing the steel elastic modulus to minimize discrepancies between measured and simulated frequencies and mode shapes. The results demonstrate a remarkable reduction in frequency errors (below 5%) and a significant improvement in modal shape correlation (MAC > 0.93 post-calibration), confirming the model’s ability to reflect the bridge’s true condition. This work underscores the potential of digital twins in predictive maintenance, early damage detection, and life-cycle management of bridge infrastructure, offering a scalable framework for real-time SHM in complex structural systems. Full article

Three-dimensional printing is promising in the pharmaceutical industry for personalized medicine, on-demand production, tailored drug loading, etc. Pressure-assisted microsyringe (PAM) printing is popular due to its low cost, simple operation, and compatibility with heat-sensitive drugs but is limited by ink formulations lacking the essential characteristics, impacting their performance. This study evaluates inks based on sodium alginate (SA), hydroxypropyl cellulose (HPC H), and hydroxypropyl methylcellulose (HPMC K100 and K4) for PAM 3D printing by analyzing their rheology. The formulations included the model drug Fenofibrate, functional excipients (e.g., mannitol, polyethylene glycol, etc.), and water or water–ethanol mixtures. Pills and thin films as an oral dosage were printed using a 410 μm nozzle, a 10 mm/s speed, a 50% infill density, and a 60 kPa pressure. Among the various formulated inks, only the ink containing 0.8% SA achieved successful prints with the desired shape fidelity, linked to its rheological properties, which were assessed using flow, amplitude sweep, and thixotropy tests. This study concludes that (i) an ink’s rheological properties—viscosity, shear thinning, viscoelasticity, modulus, flow point, recovery, etc.—have to be considered to determine whether it will print well; (ii) printability is independent of the dosage form; and (iii) the optimal inks are viscoelastic solids with specific rheological traits. This research provides insights for developing polymer-based inks for effective PAM 3D printing in pharmaceuticals. Full article

Stimuli-responsive hydrogels hold immense promise for biomedical applications, but conventional gelation processes often struggle to achieve the precision and complexity required for advanced functionalities such as soft robotics, targeted drug delivery, and tissue engineering. This study introduces a class of 3D-printable magnetic hydrogels with tunable stiffness, adhesion, and magnetic responsiveness, prepared through a simple and efficient “one-pot” method. This approach enables precise control over the hydrogel’s mechanical properties, with an elastic modulus ranging from 43 kPa to 277 kPa, tensile strength from 93 kPa to 421 kPa, and toughness from 243 kJ/m³ to 1400 kJ/m³, achieved by modulating the concentrations of acrylamide (AM) and Fe₃O₄ nanoparticles. These hydrogels exhibit rapid heating under an alternating magnetic field, reaching 44.4 °C within 600 s at 15 wt%, demonstrating the potential for use in mild magnetic hyperthermia. Furthermore, the integration of Fe₃O₄ nanoparticles and nanoclay into the AM precursor optimizes the rheological properties and ensures high printability, enabling the fabrication of complex, high-fidelity structures through extrusion-based 3D printing. Compared to existing magnetic hydrogels, our 3D-printable platform uniquely combines adjustable mechanical properties, strong adhesion, and multifunctionality, offering enhanced capabilities for use in magnetic actuation and hyperthermia in biomedical applications. This advancement marks a significant step toward the scalable production of next-generation intelligent hydrogels for precision medicine and bioengineering. Full article

The fractional Brownian field is often used to reproduce the fractal properties of complex heterogeneous media, which closely represent real-world geological materials. Studying elastic wave transport in this type of heterogeneous media is essential for advancing knowledge in geophysics, seismology, and rock mechanics. In this paper, we numerically investigate the wavefield evolution and arrival behavior of elastic wave propagation in a two-dimensional fractional Brownian field characterized by the standard deviation (σ) and the Hurst exponent (H). Using a high-fidelity finite element model, we quantify the influence of these parameters on wavefront morphology, wave arrival synchronization, and energy decay. Our results reveal that increased matrix heterogeneity with higher σ and lower H values leads to pronounced wavefront roughness, asynchronous arrival phenomena, and increscent energy decay, attributed to enhanced scattering and modulus variability. For smaller H values, rougher modulus distributions scatter wave energy more intensely, producing more coda waves and distorted wavefronts, while smoother fields with larger H fields promote smoother wave propagation. Higher σ amplifies these effects by increasing modulus variability, resulting in more attenuated wave energy and substantial wavefield disturbance. This study contributes to a quantitative understanding of how fractal heterogeneity modulates wave transport and energy attenuation in random media. Our findings hold practical significance for geophysical exploration and seismic tomography, as well as aiding in subsurface imaging and structural evaluation within fractured or stratified rock formations. Full article

Microfluidic devices offer promising solutions for automating various biological and chemical procedures. Epoxy resin, known for its excellent mechanical properties, chemical resistance, and thermal stability, is widely used in high-performance microfluidic devices. However, the poor printability of epoxy has limited its application in 3D printing technologies for fabricating epoxy-based microfluidic devices. In this study, fumed silica is introduced into epoxy resin to formulate a yield-stress fluid suspension as a support bath for embedded 3D printing (e-3DP). The study demonstrates that increasing the fumed silica concentration from 3.0% to 9.0% (w/v) enhances the yield stress from 9.46 Pa to 56.41 Pa, the compressive modulus from 19.79 MPa to 36.34 MPa, and the fracture strength from 148.16 MPa to 168.78 MPa, while reducing the thixotropic time from 6.58 s to 1.32 s, albeit with a 61.3% decrease in the transparency ratio. The 6.0% (w/v) fumed silica–epoxy suspension is selected based on a balance between yield stress, transparency, and mechanical performance, enabling high-fidelity filament formation. Two representative microfluidic devices are successfully fabricated, demonstrating the feasibility of a fumed silica–epoxy suspension for the customizable e-3DP of epoxy-based microfluidic devices. Full article

The heterogeneity in fracture formation significantly influences the hydraulic fracture propagation among adjacent wells, underscoring the urgency to comprehend the underlying fracture mechanisms. Specifically, in shale gas or oil extraction fracturing operations, stress interactions among neighboring fracturing clusters, or mutual interference during the propagation of parallel fractures, are commonplace. At present, there is relatively little research on the sensitivity parameters of adjacent borehole fracture propagation morphology. Consequently, we employed ABAQUS software 2022 to construct a numerical model simulating the fracturing of adjacent boreholes in opposing directions. Upon validating the model’s fidelity, we systematically explored the influence of various engineering and geological factors on fracture morphology and propagation length. Our findings revealed a three-phase evolution: independent fracture propagation, subsequent mutual repulsion, and, ultimately, mutual attraction. It is worth noting that increasing the elastic modulus from 10 GPa to 80 GPa, and increasing the crack length by 16.30%, is beneficial for crack propagation, while the horizontal stress difference profoundly shapes the crack mode, but has a relatively small impact on the overall crack length. When HSD increases from 0 MPa to 15 MPa, the total crack length only changes by 1.24%. In addition, the filtration coefficient of the reservoir is a key determining factor that has a significant impact on the morphology and length of cracks generated by adjacent boreholes. Increasing the filtration coefficient from 1 × 10⁻¹⁴ m³/s/Pa to 5 × 10⁻¹² m³/s/Pa reduces the total length of cracks by 60.77%. Notably, an optimal injection rate exists, optimizing fracturing outcomes. Conversely, the viscosity of the fracturing fluid exerts a limited influence on fracture morphology and length within the confines of this simulation, allowing for the selection of a suitable viscosity to ensure smooth proppant transport during actual fracturing operations. In designing fracturing parameters, it is imperative to aim for sufficient fracture propagation length while harnessing “stress interference” to foster the development of intricate fracture networks. Ultimately, our research findings serve as a solid foundation for engineering practices involving hydraulic fracture propagation in adjacent boreholes undergoing opposing fracturing operations. Full article

Background: Complex bone defects are challenging to treat. Autografting is the gold standard for regenerating bone defects; however, its limitations include donor-site morbidity and increased surgical complexity. Advancements in 3D bioprinting (3DBP) offer a promising alternative for viable bone grafts. In this experiment, gels composed of varying levels of gelatin methacrylate (GelMA) and hydroxyapatite (HA) and gelatin concentrations are explored. The objective was to increase the hydroxyapatite content and find the upper limit before the printability was compromised and determine its effect on the mechanical properties and cell viability. Methods: Design of Experiments (DoE) was used to design 13 hydrogel bioinks of various GelMA/HA concentrations. These bioinks were assessed in terms of their pipettability and equilibrium modulus. An optimal bioink was designed using the DoE data to produce the greatest stiffness while still being pipettable. Three bioinks, one with the DoE-designed maximal stiffness, one with the experimentally defined maximal stiffness, and a literature-based control, were then printed using a 3D bioprinter and assessed for print fidelity. The resulting hydrogels were combined with human bone-marrow-derived mesenchymal stromal cells (hMSCs) and evaluated for cell viability. Results: The DoE ANOVA analysis indicated that the augmented three-level factorial design model used was a good fit (p < 0.0001). Using the model, DoE correctly predicted that a composite hydrogel consisting of 12.3% GelMA, 15.7% HA, and 2% gelatin would produce the maximum equilibrium modulus while still being pipettable. The hydrogel with the most optimal print fidelity was 10% GelMA, 2% HA, and 5% gelatin. There were no significant differences in the cell viability within the hydrogels from day 2 to day 7 (p > 0.05). There was, however, a significantly lower cell viability in the gel composed of 12.3% GelMA, 15.7% HA, and 2% gelatin compared to the other gels with a lower HA concentration (p < 0.05), showing that a higher HA content or print pressure may be cytotoxic within hydrogels. Conclusions: Extrusion-based 3DBP offers significant advantages for bone–tissue implants due to its high customizability. This study demonstrates that it is possible to create printable bone-like grafts from GelMA and HA with an increased HA content, favorable mechanical properties (145 kPa), and a greater than 80% cell viability. Full article

This paper presents an optimal weighted modulus (OWM) algorithm able to conceal secret messages in a high dynamic range image encoded via the RGBE format, consisting of the red, green, blue, and exponent channels. In contrast to current state-of-the-art schemes, which mainly employ limited and vulnerable homogeneous representations, our OWM scheme exploits four channels and an embedding weight to conceal secret messages, thereby offering more embedding capacities and undetectability against steganalytic tools. To reduce the impact on the luminance variation, we confine the maximal change incurred in the exponent channel when embedding secret messages. In addition, we propose an SEC scheme to eliminate the pixel saturation problem, even though a pixel contains values close to the boundary extreme. As a result, the stego images produced not only exhibit high quality but also comply with the RGBE encoding format, making them able to resist malicious steganalytic detection. The experimental results show that our scheme offers larger embedding rates, between 2.8074 and 5.7549 bits per pixel, and the average PSNR value for twelve tone-mapped images is over 48 dB. In addition, the HDR VDP 3.0 metric demonstrates the high fidelity of stego HDR images, where the average Q value is close to the upper bound of 10.0. Our scheme can defeat RS steganalytic attacks and resist image compatibility attacks. A comparison result confirms that our scheme outperforms six current state-of-the-art schemes. Full article

In this work, a sodium alginate-based copolymer grafted by thermoresponsive poly(N-isopropylacrylamide) (PNIPAM) chains was used as gelator (Alg-g-PNIPAM) in combination with methylcellulose (MC). It was found that the mechanical properties of the resulting gel could be enhanced by the addition of MC and calcium ions (Ca²⁺). The proposed network is formed via a dual crosslinking mechanism including ionic interactions among Ca²⁺ and carboxyl groups and secondary hydrophobic associations of PNIPAM chains. MC was found to further reinforce the dynamic moduli of the resulting gels (i.e., a storage modulus of ca. 1500 Pa at physiological body and post-printing temperature), rendering them suitable for 3D printing in biomedical applications. The polymer networks were stable and retained their printed fidelity with minimum erosion as low as 6% for up to seven days. Furthermore, adhered pre-osteoblastic cells on Alg-g-PNIPAM/MC printed scaffolds presented 80% viability compared to tissue culture polystyrene control, and more importantly, they promoted the osteogenic potential, as indicated by the increased alkaline phosphatase activity, calcium, and collagen production relative to the Alg-g-PNIPAM control scaffolds. Specifically, ALP activity and collagen secreted by cells were significantly enhanced in Alg-g-PNIPAM/MC scaffolds compared to the Alg-g-PNIPAM counterparts, demonstrating their potential in bone tissue engineering. Full article

This study aims to develop a high-generalizability machine learning framework for predicting the homogenized mechanical properties of short fiber-reinforced polymer composites. The ensemble machine learning model (EML) employs a stacking algorithm using three base models of Extra Trees (ET), eXtreme Gradient Boosting machine (XGBoost), and Light Gradient Boosting machine (LGBM). A micromechanical model of a two-step homogenization algorithm is adopted and verified as an effective approach to composite modeling with randomly distributed fibers, which is integrated with finite element simulations for providing a high-quality ground-truth dataset. The model performance is thoroughly assessed for its accuracy, efficiency, interpretability, and generalizability. The results suggest that: (1) the EML model outperforms the base members on prediction accuracy, achieving $R^2$ values of 0.988 and 0.952 on the train and test datasets, respectively; (2) the SHapley Additive exPlanations (SHAP) analysis identifies the Young’s modulus of matrix, fiber, and fiber content as the top three factors influencing the homogenized properties, whereas the anisotropy is predominantly determined by the fiber orientations; (3) the EML model showcases good generalization capability on experimental data, and it has been shown to be more effective than high-fidelity computational models by significantly lowering computational costs while maintaining high accuracy. Full article

The ice generation is one of the challenges facing the methane hydrate depressurization, which, however, has not been fully addressed by existing numerical models for hydrate-bearing sediments (HBS). In this study, we develop a high-fidelity, fully coupled thermo-hydro-mechanical-chemical numerical model that incorporates the effect of ice. The model, developed using COMSOL, takes into account water–ice phase change, thermally induced cryogenic suction and constitutive relation in HBS. It is verified well against the temperature, pressure and cumulative gas production of Masuda’s experiment. The model is then employed to investigate multiphysical responses and gas/water production when ice generation is induced by setting a low outlet pressure. The results reveal that ice forms near the outlet boundary of the specimen center, leading to a reduction in intrinsic permeability and fluid velocity and an increase in the bulk modulus of ice-HBS. This enhanced bulk modulus results in higher porosity under axial load. Although the exothermic effect of ice generation promotes the hydrate dissociation, the effect on cumulative gas production is negligible after the ice melts. A negative correlation between ice saturation and water production rate is observed, indicating that a higher gas–water ratio can be achieved by adjusting the ice duration during hydrate production. The developed coupled model proves to be crucial for understanding the effect of ice on hydrate exploitation. Full article

Microfluidics is a rapidly advancing technology with expansive applications but has been restricted by slow, laborious fabrication techniques for polydimethylsiloxane (PDMS)-based devices. Currently, 3D printing promises to address this challenge with high-resolution commercial systems but is limited by a lack of material advances in generating high-fidelity parts with micron-scale features. To overcome this limitation, a low-viscosity, photopolymerizable PDMS resin was formulated with a methacrylate-PDMS copolymer, methacrylate-PDMS telechelic polymer, photoabsorber, Sudan I, photosensitizer, 2-isopropylthioxanthone, and a photoinitiator, 2,4,6-trimethyl benzoyl diphenylphosphine oxide. The performance of this resin was validated on a digital light processing (DLP) 3D printer, an Asiga MAX X27 UV. Resin resolution, part fidelity, mechanical properties, gas permeability, optical transparency, and biocompatibility were investigated. This resin produced resolved, unobstructed channels as small as 38.4 (±5.0) µm tall and membranes as thin as 30.9 (±0.5) µm. The printed material had an elongation at break of 58.6% ± 18.8%, Young’s modulus of 0.30 ± 0.04 MPa, and was highly permeable to O₂ (596 Barrers) and CO₂ (3071 Barrers). Following the ethanol extraction of the unreacted components, this material demonstrated optical clarity and transparency (>80% transmission) and viability as a substrate for in vitro tissue culture. This paper presents a high-resolution, PDMS 3D-printing resin for the facile fabrication of microfluidic and biomedical devices. Full article