Search Results (209)

Conventional casting of high-entropy alloys was constrained by multi-principal element solidification behavior and was prone to severe grain boundary segregation and microstructural inhomogeneity, limiting their service performance in extreme environments. Bridgman directional solidification can help to achieve oriented columnar grain growth and mitigate micro-segregation via tailored matching of a temperature gradient, G, and a growth rate, V, yet its stable solidification relied on a high G/V ratio, imposing stringent requirements on equipment and process control. Trace rare earth elements are suggested to potentially stabilize the interfacial morphology and effectively broaden the processing window of Bridgman directional solidification through melt purification and modulation of the solid–liquid interfacial energy based on extrapolation from conventional casting and thermodynamic principles; however, direct experimental confirmation in Bridgman-processed HEAs remains scarce. This review summarizes the solidification microstructure evolution of high-entropy alloys fabricated by the Bridgman method, elucidates the regulatory mechanisms of rare earth microalloying on phase selection, solute partitioning behavior, and interface stability, and reveals the strengthening effects and corrosion performance variations under the synergistic interaction of processing parameters and chemical compositions. Finally, future perspectives are provided regarding interfacial reactions, compositional homogeneity control, and the lack of design criteria in Bridgman-based rare earth composite fabrication systems. Full article

The edge-defined film-fed growth (EFG) method is the dominant industrial technique for producing large-area β-Ga₂O₃ single-crystal substrates, but thermal stress-induced dislocation generation remains a critical barrier. This work presents a coupled thermo-mechanical finite-element framework for thermal-stress management in EFG-grown β-Ga₂O₃. The central methodological contribution is a 500-sample gradient-boosting surrogate sensitivity analysis ($R^2=0.955$, mean absolute error (MAE) $=11.3$ MPa) that quantitatively decomposes thermal-stress variance into controllable process factors and irreducible material-property uncertainties. The physical foundation comprises two enabling elements: (i) the full 21-component monoclinic Voigt stiffness matrix with explicit crystal–model coordinate mapping, for which the orthotropic model is rigorously shown to be exact in 2D plane strain through an exact kinematic theorem showing that the 2D plane-strain results of prior orthotropic EFG analyses are unaffected by the coupling terms, while the monoclinic formulation provides the essential foundation for future 3D studies; and (ii) a dimensionless and numerical justification for omitting melt convection, which enables 100% solver convergence (500/500 Latin hypercube samples) with stress errors < 1.5 MPa. Afterheater temperature $T_{\mathrm{AH}}$ is the leading controllable parameter (35.9%), nearly tied with the elastic constant $C_{33}$ (35.5%), followed by the thermal-expansion component ${\alpha }_c$ (15.9%). Elevating $T_{\mathrm{AH}}$ from 1900 K to 1950 K reduces the peak von Mises stress by ∼29% (COMSOL Multiphysics 6.2-verified); the 2D plane-strain baseline anchors the surrogate analysis at ${\sigma }_{max}=223$ MPa, while the afterheater-free 3D configuration gives ${\sigma }_{max}=187$ MPa at the crystal periphery near the solid–liquid interface. The isotropic approximation underestimates peak stress by 39.6%, confirming that directional anisotropy is essential for quantitatively reliable thermal stress prediction in monoclinic oxide crystals. Full article

The precise control of droplet movement on surfaces remains a major challenge in the field of smart surfaces. Conventional systems based on light, electric, or magnetic stimuli often require the addition of corresponding photothermal, conductive, or magnetic particles into the droplets, which may lead to droplet contamination and hinder encapsulation of drugs or cells for practical application. In the present study, a photo-responsive composite functional surface was designed and prepared. The functional surface contains a liquid crystal elastomer (LCE) layer which is placed underneath a pre-lubricated polydimethylsiloxane surface. Taking advantage of the photo-induced thermal response of the cross-linked LCE network, upon local irradiation with ultraviolet light, the illuminated region of the LCE layer rapidly generates dynamic heating, creating a temperature gradient across the droplet. This gradient alters the surface tension of the solid surface, disrupts the symmetry of contact angles of the droplet, thereby inducing directional droplet movement along the surfaces. The present study provides a non-contact and fast approach for the fabrication of smart surfaces towards more complex droplet manipulation. Full article

Background: Lipid nanoparticles are widely investigated as oral drug delivery systems, but their intestinal performance remains difficult to predict based only on physicochemical properties. This study aimed to elucidate how the lipid matrix composition influences the intestinal permeation of curcumin from lipid nanoparticles. Methods: Curcumin-loaded nanoemulsions, nanostructured lipid carriers with defined solid-to-liquid lipid ratios, and solid lipid nanoparticles were prepared by high-pressure homogenization. All formulations were characterized with respect to particle size, polydispersity index, and zeta potential before and after simulated intestinal pre-incubation in a simplified SDS-containing intestinal fluid. Intestinal permeation was evaluated ex vivo using porcine gut tissue by analysis of semi-quantitative fluorescence-based permeation readouts (ART) and mean permeation depth (MPD) after 30 and 60 min. Results: All formulations maintained stable physicochemical properties with particle sizes around 200 nm and negative zeta potentials; pre-incubation increased the negativity of the zeta potential but left particle size unchanged. Despite similar attributes, the formulations differed in intestinal curcumin permeation based on time and composition. At 30 min, nanoemulsions and mixed nanostructured lipid carriers achieved the highest performance. By 60 min, lipid carriers with more liquid lipid significantly increased both the fluorescence intensity and the depth of curcumin permeation, while other systems showed little further improvement. Conclusions: The intestinal permeation of drug from lipid nanoparticles is governed by the lipid matrix architecture and its interaction with the hydrated intestinal environment, which together affect drug-release kinetics and the ability to sustain a trans-epithelial concentration gradient over time. Thus, optimizing oral lipid nanoparticles requires time-resolved, biologically relevant models rather than physicochemical characterization alone, consistent with observed similar matrix-driven effects in dermal delivery systems. Full article

Oleogels, in which liquid oils are structured into semi-solid matrices by oleogelators, have been widely investigated as animal fat replacers in meat products, where they lower saturated fatty acid content while helping preserve texture, structure, and emulsion stability. The reported gains are substantial: structuring PUFA-rich oils to replace pork backfat has raised the PUFA/SFA ratio around 3.6-fold and cut the n-6/n-3 ratio up to 23-fold in burgers, while cellulose- and wax-structured systems have reduced saturated fat from roughly 42% to 15% of total fat in patties. In parallel, oleogels and structurally related gels act as carriers for lipophilic bioactives such as carotenoids, curcumin, phytosterols, and omega-3 fatty acids, improving oxidative stability and modulating digestive release, with encapsulation efficiencies exceeding 90% in some systems. Whether one structured-lipid system can perform both roles inside a meat matrix remains largely untested: direct evidence for classical oleogels is confined to a few cases, most clearly curcumin-loaded beeswax oleogels in pork burgers, which retained antioxidant protection through chilled storage and cooking. This review integrates the fat-replacement and bioactive-delivery studies, separates classical oleogels from gelled emulsions, Pickering emulsions, and bigels, and stratifies studies by level of evidence. Because most current support comes from related systems, it is framed as a perspective that maps this evidence gradient and defines the experiments required to validate dual-function oleogels under realistic meat processing and storage conditions. Full article

Cariprazine (CAR) and lurasidone (LUR) are antipsychotic drugs used to treat schizophrenia. These drugs are relatively new in clinical practice, and there is a need to optimise and develop analytical methods for their determination in various biological matrices for biomedical analysis. To date, the detection of these drugs has been performed in serum and urine, but there are no methods for determining these drugs in saliva. In the first part of this study, various chromatographic systems were compared using high-performance liquid chromatography with diode array detection (HPLC-DAD) or coupled with quadrupole–linear ion trap tandem mass spectrometry (HPLC-QTRAP-MS/MS), taking into account the retention of tested compounds, system efficiency and peak symmetry. Next, a simple, rapid, and sensitive HPLC-QTRAP-MS/MS method has been developed for the determination of CAR and LUR in human serum, urine, and, for the first time, in saliva samples. Solid-phase extraction (SPE) was used for sample pre-treatment. Quantifications were carried out using a Polar RP column with a mobile phase consisting of acetonitrile and a formate buffer at pH 4.0 in gradient mode. The method was successfully applied for the determination of CAR and LUR in biological samples obtained from psychiatric patients. The findings suggest that saliva may be a non-invasive alternative for the quantification of free levels of investigated drugs, although further studies are required to clarify its relationship with plasma concentrations. Full article

Portland cement production accounts for roughly 8% of anthropogenic CO₂ emissions, driving interest in low-carbon geopolymer binders. One-part (“just-add-water”) geopolymers, which replace hazardous liquid activators with a dry, pre-blended solid activator, are especially suited to field deployment where handling safety and logistics are decisive. However, their formulation space is combinatorially vast, and trial-and-error development cannot efficiently navigate it. This paper reviews one-part geopolymer science, presents a new comparative and interpretable ML analysis of a published 80-mixture one-part fly-ash/ground granulated blast-furnace slag (GGBS, hereafter slag) geopolymer dataset from twelve studies, and proposes an AI-assisted design framework. The ML demonstration targets 28-day compressive strength only. Under leave-one-source-out (LOSO) cross-validation—the appropriate test for a literature-pooled dataset—gradient-boosted trees achieved R² = 0.61 (RMSE = 15.5 MPa; 95% bootstrap confidence interval on R², 0.44–0.75), well above a linear baseline (0.36), suggesting that non-linear structure transfers across studies; a random split gives a higher but less reliable R² = 0.90 on only 16 test mixtures. Because fly-ash and slag contents are near-perfectly anti-correlated ($r=-0.99$), we model the precursor axis as a single slag fraction descriptor; SHAP then identifies this precursor balance and the activator’s Na₂O dosage as the dominant statistical predictors of strength in this dataset, an ordering consistent with known activation chemistry; causal confirmation of these associations awaits the experimental validation stage of the proposed framework. Demonstrated for strength only, at paste level, the framework offers a transferable route toward multifunctional low-carbon binders for protective and infrastructure applications; the multifunctional extensions are proposed, but not yet demonstrated. Full article

Objectives: A high-performance liquid chromatography (HPLC) with mass spectrometry (MS) detection method was developed to quantify several tyrosine kinase inhibitors (TKIs) and their relevant metabolites. This method is suitable for therapeutic drug monitoring (TDM) of alectinib, brigatinib, dabrafenib, lenvatinib, lorlatinib, osimertinib and trametinib in patients with solid tumors using volumetric absorptive microsampling (VAMS^®). Methods: The HPLC-MS system contained four pumps, a Turboflow HTLC CycloneTM 1.0 × 50 mm solid phase extraction column for analyte enrichment, and a Kinetex 2.6 µm C18 100Å, 100 × 3.0 mm column for analyte separation. An acetonitrile–water gradient was used for the separation, and the ions generated by ESI (+)-ionization were detected in single-ion mode. This method was validated according to recent European Medicines Agency (EMA) and Food and Drug Administration (FDA) guidelines. Results: The accuracy and precision shown during method validation were within the acceptable limits for all analytes in plasma and whole blood. All analytes showed acceptable stability in both matrices for at least 28 days when stored at −21 °C. So far, 100 venous plasma and 94 capillary blood samples have been collected and analyzed. Conclusions: We developed a reliable method to quantify several TKIs from plasma and capillary blood, which is intended for TDM purposes in clinical practice. Full article

Long-term open-air storage of coal gangue (CG) can generate leachates containing oxidizable components contributing to chemical oxygen demand (COD), together with sulfate (SO₄²⁻) and fluoride (F⁻), yet their source-term behavior remains poorly understood. In this study, batch and column leaching tests were conducted on multi-source CG samples and combined with ToF-SIMS (surface compositional mapping), solid-phase TOC gradient leaching, and PHREEQC-XGBoost-SHAP modeling (coupled geochemical–machine learning analysis). Batch-leachate COD levels ranged from 4.6 to 68.0 mg/L, while SO₄²⁻ and F⁻ concentrations reached maxima of approximately 317 and 1.29 mg/L, respectively. During column leaching, COD levels and SO₄²⁻ concentrations were highest at low liquid-to-solid ratios (L/S) and subsequently decreased, with maximum initial values of 186.6 and 3074 mg/L, respectively, whereas F⁻ exhibited delayed and persistent release at approximately 0.3–2.3 mg/L. Solid-phase TOC did not directly predict the COD response, and ToF-SIMS revealed aliphatic organic fragments associated with aluminosilicate surfaces that weakened or were redistributed after leaching. The COD–DOC discrepancy further indicated that dissolved organic matter alone could not fully explain the COD response, although the possible contribution of inorganic reducing species requires direct verification. Within the modeled framework, the sulfate source-term coefficient accounted for 69.4–76.9% of the modeled influence at L/S = 0.5–2.0 L/kg, while the influence of the HFO surface complexation increased during later leaching. In contrast, the F⁻ source-term coefficient remained dominant over L/S = 0.5–10.0 L/kg, accounting for 97.0–97.9% of the modeled influence. These findings support parameter- and stage-specific monitoring and pollution control at CG disposal sites. Full article

Rubusoside is the major sweet bioactive compound in Rubus chingii var. suavissimus (S.K.Lee) L.T.Lu, characterized by high sweetness, low caloric value, and favorable safety, with potential applications as a natural sweeteners and in functional foods. However, efficient green extraction technologies and their mechanisms remain insufficiently explored. Here, a microwave-assisted deep eutectic solvent (DES) system was developed for rubusoside recovery. The ternary DES composed of choline chloride, 1,2-propylene glycol, and 1,3-butanediol (1:2:2) showed the best performance and outperformed microwave-assisted water extraction. Response surface methodology identified optimal conditions of 33% moisture content, a liquid–solid ratio of 21 mL/g, 6 min, and 320 W, yielding 7.89 ± 0.25% rubusoside. Fourier-transform infrared spectroscopy, electrostatic potential, atoms-in-molecules theory, and independent gradient modelling based on Hirshfeld partition analyses revealed significant non-covalent interactions between the ternary DES and rubusoside. Scanning electron microscopy showed that DES and microwave treatment synergistically disrupted plant tissues and enhanced mass transfer. LX-28 macroporous resin enabled rubusoside separation, and the recovered DES retained stable performance after five reuse cycles. These results demonstrate a green, efficient, and recyclable strategy driven by cooperative hydrogen bonding and van der Waals interactions between the ternary DES and the rubusoside glycosyl moiety, together with DES–microwave-induced tissue disruption and mass-transfer enhancement. Full article

As a typical class of high-strength and high-conductivity materials, particle-reinforced copper matrix composites show great promise for application in critical conductive components. However, when such composites are prepared via melting methods, challenges such as the agglomeration of reinforcing particles and difficulty controlling their spatial distribution often arise, limiting the application of these composites in conductive parts. In this study, a phase-field method is employed with order parameters introduced to characterize the interaction between solid–liquid interfaces and reinforcing phases. By reconstructing the free-energy functional of the multi-phase-field model, the effects of undercooling and solid–liquid interface properties on particle–interface interactions are investigated. Simulations are conducted for solidification for different particle sizes and in different particle aggregation states, dynamically illustrating the evolution behavior of nanoparticles at the solid–liquid interface. The results indicate that particle migration velocity and distance rise with increased particle mobility due to reduced melt flow resistance. Higher undercooling accelerates solidification front propagation but curtails particle pushing distance, while the interface gradient coefficient (ε²) only inhibits particle migration distance with negligible influence on peak migration velocity. In single-crystal matrices, agglomerate morphology, orientation angle, and aggregation degree jointly affect migration behavior: irregular agglomerates undergo obvious morphological deformation, and migration distance increases when the orientation angle ranges from 0° to 90° and decreases with higher aggregation degrees. Fine particles are repelled to grain boundaries for agglomeration, whereas large particles are engulfed inside grains. Powders were fabricated via gas atomization, and the results of scanning electron microscopy characterization experiments confirm the simulation reliability. The results provide valuable insights for the controlled distribution of nanoparticles within composite materials. Full article

The power density of modern high-power integrated processors keeps rising rapidly. Among them, chiplet-based high-power AI accelerators exhibit local peak heat flux exceeding 1 kW/cm², which leads to concentrated hotspots, severe internal temperature gradients, device performance degradation and reliability deterioration. Conventional heat dissipation approaches are limited by the bottleneck of series interfacial thermal resistance and fail to meet the cooling demands of complex integrated architectures. Chip-level thermal management serves as a core method to suppress hotspots near heat sources and reduce overall system thermal resistance, which guarantees long-term stable operation of high-power integrated processors and plays a vital role in improving the energy efficiency and service life of computing platforms. This paper systematically reviews mainstream chip-level thermal management technologies for high-power integrated processors, covering heterogeneous integration of high-thermal-conductivity substrates, embedded microchannel liquid cooling, solid-state active heat pumps, multi-physics co-design and advanced packaging manufacturing processes. The basic working principles and state-of-the-art research progress of each cooling technology are elaborated in detail. The common engineering bottlenecks, including ultra-high heat flux endurance, packaging process compatibility, fluid leakage risks and multi-layer interfacial thermal resistance, are summarized, and the future development trends of this field are clarified. This review can provide comprehensive theoretical guidance for structural design and large-scale engineering implementation of near-junction thermal management solutions for various high-power integrated processors, especially high-computing-power AI accelerators. Full article

Integrating the “programmable” characteristics of smart materials with 3D printing technology enables the integration of structural design and manufacturing, showing broad application prospects in flexible electronics, aerospace, biomedicine, and other fields. Magnetically controlled smart fluids are characterized by flexible solid–liquid conversion, high driving efficiency, and high safety. By harnessing the distinctive characteristics of this material, manufacturing and actuation approaches for intelligent structures can be further diversified. Inspired by the sol–gel transformation mechanism of protoplasm, this paper proposes a composite 3D printing method for magnetic and non-magnetic materials. A magnetically controllable binary suspension system with strong thixotropic properties was constructed, and its microscopic self-assembly structure was characterized. The yield behavior, linear viscoelastic properties, and thixotropic recovery performance of the magnetic thixotropic fluid (MTF) were investigated through steady and dynamic rheological measurements, and the optimal rheological parameters for printing were determined. A 3D printing platform with coordinated control of a magnetic field and a motion system was built to further study and optimize the printing process. The supporting characteristics of the MTF on a silicone film and the deformation of the printed composite structure under a gradient magnetic field were studied. The composite 3D printing and its application in soft robotics may provide new insights for space exploration, biomedicine, military reconnaissance, and many other fields. Full article

An analytical method was established for the rapid determination of 45 pigments and preservatives in edible ink by ultra-high performance liquid chromatography coupled with triple quadrupole tandem mass spectrometry (UHPLC-MS/MS), which provides technical support for the composition analysis and industrial development of edible ink. The samples were easily extracted with 75% aqueous methanol solution and purified with a Captiva EMR-Lipid HF solid-phase extraction cartridge. After filtration through a polytetrafluoroethylene (PTFE) membrane, the analytes were determined by UHPLC-MS/MS under multiple reaction monitoring (MRM) mode in both positive and negative ion modes. Poroshell 120 AQ-C18 was selected as the analytical column, and valve switching timing control was adopted during the gradient elution process. The external standard method was used for quantitative analysis. In the established method, the 45 pigments and preservatives exhibited good linear relationships within the mass concentration range of 0.0002–200.0 μg/mL. The limits of detection (LOD) and limits of quantification (LOQ) were 0.0004–8.00 mg/kg and 0.001–20.00 mg/kg, respectively. Using 25% aqueous glycerol solution as the blank matrix, the recoveries of analytes at different spiked levels met the detection requirements. The established method is simple and rapid, and can be applied to the qualitative and quantitative detection of typical pigments and preservatives in edible ink. Full article

In the Czochralski process of silicon single-crystal growth, the V/G value at the solid–liquid interface is a key parameter affecting intrinsic crystal defects. However, online V/G detection remains difficult because the temperature gradient G cannot be directly measured, while multi-condition distribution shifts and limited labeled data reduce the robustness of data-driven models. To address these issues, this paper proposes DWC-ISBiGNN, an adaptive multi-condition invariant feature extraction method based on the Invariant-Specific Bidirectional Graph Neural Network. The proposed method introduces dynamic sample graph construction with stage-aware global nodes to capture non-stationary process correlations, source-domain credibility weighting to suppress negative transfer, and a semi-supervised training framework combining stage-conditional alignment with teacher–student regression consistency to exploit unlabeled target-domain data. Experiments on industrial data from a 12-inch silicon single-crystal production line show that DWC-ISBiGNN achieves an RMSE of 0.0041, an MAE of 0.00285, and an $R^2$ of 0.9549. Compared with the original IS-BiGNN, the RMSE is reduced by 32.6%, and $R^2$ is increased by 5.43 percentage points. The results demonstrate that the proposed method provides an effective soft-sensing approach for V/G prediction under multiple operating conditions. Full article