Search Results (3,587)

Lithium–sulfur (Li–S) batteries hold great promise for next-generation energy storage owing to their ultrahigh theoretical energy density; however, their practical application is severely hampered by the polysulfide shuttle effect and the penetration of lithium dendrites through the separator. In this work, a carboxyl-containing anionic polymer (TPU-DMBA) is synthesized and composited with Ketjen Black (KB), and the resulting mixture is coated onto a commercial polypropylene separator via a simple doctor-blade method. In this design, the porous KB network provides physical adsorption to capture polysulfides, while the dissociated carboxylate groups (–COO⁻) generate strong electrostatic repulsion against negatively charged polysulfide anions (S_n²⁻). This dual-mechanism strategy—adding electrostatic repulsion on the basis of physical adsorption—effectively suppresses the shuttle effect. In addition, the flexible polymer backbone increases the tensile strength of the separator by approximately 30%, enhancing its resistance against dendrite penetration. The carbon material also significantly improves electrolyte wettability (the contact angle decreases from 41.6° to 11.7°) and ionic conductivity (from 0.48 × 10⁻³ to 0.88 × 10⁻³ S cm⁻¹). The polymer itself acts as a binder, eliminating the need for additional binder addition. Benefiting from the synergy of electrostatic repulsion, physical adsorption, and mechanical reinforcement, the prepared modified separator endows the Li–S battery with an initial specific discharge capacity of 1373.15 mAh g⁻¹ at 0.1 C and an initial discharge capacity of 714.46 mAh g⁻¹ at a high rate of 2 C. After 200 cycles at 2 C, the capacity remains 577.93 mAh g⁻¹, with a capacity retention of 80.89%. This work provides a low-cost, scalable, and binder-free separator modification strategy that simultaneously suppresses the polysulfide shuttle and resists dendrite growth, opening a new and effective pathway toward practical high-performance Li–S batteries. Full article

Acorns (Quercus spp.) are an underutilized forest resource with recognized nutritional and bioactive potential, making them promising candidates for the development of sustainable plant-based functional foods. This study aimed to valorize acorns through the formulation of two novel acorn-based products, a plant-based beverage, and a pudding, and to assess their nutritional properties, sensory acceptability, and, for the beverage, refrigerated shelf-life stability. The beverage was optimized as a neutral-flavored milk alternative, using sodium alginate as a natural clean-label stabilizer to enhance emulsion stability and physicochemical properties. The final formulation exhibited low energy density and a lipid profile rich in monounsaturated fatty acids, contributing to its nutritional and functional value. Throughout 63 days of storage at 4 °C, sodium alginate effectively prevented phase separation and supported the retention of antioxidant capacity, as evidenced by stable ferric reducing antioxidant power (FRAP) and total phenolic content, although ABTS radical scavenging activity declined over time. No microbial growth was detected during storage, confirming the adequacy of the applied thermal treatment and aseptic filling procedures applied. The acorn-based pudding, developed by adapting a traditional egg-based recipe, functioned as a proof of concept illustrating the technological versatility of acorns across distinct plant-based matrices, exhibiting a nutritional profile comparable to commercial counterparts and high consumer acceptability. Overall, this work demonstrates the technological feasibility and versatility of incorporating acorns into plant-based food matrices, supporting their potential as sustainable ingredients for the development of innovative value-added foods and contributing to the valorization of forest resources. Full article

The development of highly efficient and stable photoanodes is essential for advancing photoelectrochemical cathodic protection towards practical applications. Herein, a novel ternary sulfide heterojunction was engineered through the construction of a three-dimensional interlocked architecture of ZnIn₂S₄ on SnIn₄S₈ nanosheets via a sequential hydrothermal synthesis. This unique three-dimensional interlocked configuration creates an intimate interface and continuous charge transfer highways, effectively addressing the slow electron movement and poor interfacial contact that plague conventional photoelectrodes. Spectroscopic and electrochemical analyses verified the formation of a Type-II band alignment, which drives the directional migration of photogenerated electrons from ZnIn₂S₄ to SnIn₄S₈ under an intrinsic built-in electric field. Upon coupling with 304 stainless steel, the ZnIn₂S₄/SnIn₄S₃ heterojunction exhibited outstanding photoelectrochemical cathodic protection performance. It delivered impressive photocurrent densities of 15.22, 19.76, and 72.27 μA·cm⁻² in 3.5 wt% NaCl, 0.1 M Na₂S₂O₃, and 0.1 M Na₂S/NaOH electrolytes, respectively, along with a prominent 720 mV cathodic potential shift in the Na₂S/NaOH system. Most importantly, its good activity and stability in the scavenger-free 3.5 wt% NaCl solution and natural seawater highlight the strong practical potential of this 3D interlocked photoanode for sustainable marine metal corrosion control. Through a strategic multi-electrolyte assessment, the underlying protection mechanisms were decoupled, revealing that the synergy between the heterojunction-induced charge separation enabled by the three-dimensional interlocked structure and electrolyte-specific hole scavenging is key to the enhanced performance. Full article

This study developed high-oxygen-barrier active bilayer packaging films by combining corona-treated low-density polyethylene (LDPE) with chitosan/glycerol (CS/Gl) and carvacrol@natural zeolite (CV@NZ) nanohybrid layers using industrially scalable processes. LDPE film was surface-activated via ambient-pressure corona treatment (0.75 s/cm² at 45 kV, 30 W) and assembled with solution-cast CS/Gl or CS/Gl/CV@NZ monolayers via hot-pressing (110 °C, 1 min). Corona treatment enabled robust interfacial adhesion, evidenced by statistical equivalence between monolayer and bilayer mechanical properties. Incorporation of 10 wt.% CV@NZ nanohybrid increased elastic modulus by 60% (to ≈2970 MPa) and tensile strength by 30% (to ≈50 MPa). The LDPE-CS/Gl film achieved a 64-fold reduction in oxygen permeability; CV@NZ incorporation maintained excellent barrier performance (22-fold reduction). Antioxidant potency increased 16-fold upon CV@NZ incorporation. The LDPE-CS/Gl/CV@NZ film demonstrated exceptional antibacterial activity (5.08–5.30 log reductions; >99.999% kill) against both Listeria monocytogenes and Escherichia coli—substantially exceeding additive effects—confirming synergistic action between chitosan and carvacrol. In fresh minced pork preservation (8 days, 4 °C), the active film achieved a 1.73 log reduction in Total Viable Count (98.2% inhibition) and extended microbiological shelf life from 6 to beyond 8 days (33% increase). The bilayer configuration utilizes only 40% of the total thickness as biopolymer, aligning with circular economy principles. Unlike conventional high-barrier films (e.g., PA/PE) which require complex compatibilization for recycling, the water-soluble chitosan layer in this bilayer design can be readily separated from the LDPE backbone, enabling recovery of a pure polymer stream. This work demonstrates a feasible pathway for developing next-generation active packaging that combines a high oxygen barrier, potent antioxidant activity, and exceptional antimicrobial efficacy through industrially scalable manufacturing. Full article

Nowadays, remote sensing images are characterized by significant scale variations, a high density of small targets, and complex background conditions, which pose substantial challenges for small-object detection. To address these issues, we propose EMWMS-YOLO, a lightweight and efficient detection framework built upon YOLOv11n. Specifically, an Efficient Multi-Scale Cross-Layer Extraction (EMSCLE) backbone is designed by integrating the Dual-Branch Feature Extraction (DBFE), Multi-Scale Feature Perception (MSFP), and Spatial Pyramid Pooling Fast with Large Separable Kernel Attention (SPPF-LSKA) modules, enabling effective multi-scale feature extraction and cross-channel interaction. Furthermore, a Multi-Scale Adaptive Feature Fusion (MSAFF) neck architecture, composed of the Channel-Enhanced Convolution (CEC) and Multi-Scale Gated Feature Fusion (MSGFF) modules, is introduced to dynamically fuse cross-scale features and enhance salient target responses while suppressing background noise. In addition, the WaveletPool module replaces conventional pooling operations to reduce information loss and feature aliasing while preserving structural details. A Detect-MultiSEAM detection head is constructed by embedding a multi-scale spatial enhancement attention mechanism, which improves feature representation under complex conditions and reduces missed detections and false positives. Finally, the ShapeIoU loss function is employed to better model geometric and morphological properties, thereby improving localization accuracy. Experimental results on the VEDAI and NWPU-VHR-10 datasets demonstrate that the proposed method achieves improvements of 9.8% and 4.1% in mAP50 over the YOLOv11n baseline, respectively, verifying its effectiveness in small-object detection. Full article

Forest restoration depends on producing seedlings able to convert nursery inputs into functional traits that persist after outplanting. This study evaluated whether contrasting nursery resource-management profiles, derived from container volume, fertilization, and irrigation, shaped seedling quality and field establishment of Pinus devoniana. Seedlings were conditioned for six months under eight profiles and validated during one year under field conditions. Nursery evaluation included morphology, biomass allocation, Dickson Quality Index (DQI), nutrient status, and proline; field validation included survival, growth, ectomycorrhization, stomatal density, and lignification. Profiles differed significantly in root collar diameter, height, root biomass, total biomass, root–shoot ratio, and DQI. The 5 L fertilized and irrigated profile produced the highest integrated quality, with 140.9% more root biomass than the weakest root profile and 144.3% higher DQI than the lowest-quality profile. Nitrogen- and proline-separated nutrient and stress responses showed that higher nutrient status did not always imply lower stress. Field survival reached its highest value under the 5 L fertilized and irrigated profile, exceeding several 1 L profiles by 74.8%. DQI was positively associated with field survival (r = 0.71, p = 0.048), supporting a nursery-to-field carry-over effect. The findings highlight rooting space as a leverage point for improving reforestation outcomes. Full article

Object detection in optical remote sensing imagery faces persistent challenges from severe instance overlap, extreme spatial density, and motion or atmospheric blur. These degradations cause conventional detectors to over-mix neighboring instance features and fail to separate closely packed objects. To address these limitations, we propose SARC-DETR, a detection framework that augments the RT-DETR architecture with two complementary plug-in modules: Similarity Adaptive Convolution (SAC) and Receptive Field Cross Convolution (RCC). SAC introduces a reproducing-kernel-Hilbert-space (RKHS) motivated similarity gate that selectively suppresses responses inconsistent with local feature prototypes, thereby reducing cross-instance interference in overlapped and blurred regions. RCC constructs a large directional receptive field through orthogonal strip-based aggregation and content-adaptive fusion, enabling efficient long-range context capture without quadratic complexity overhead. Both modules can be integrated into existing DETR-style detectors without modifying the detection head or training protocol. On VisDrone2019-DET, SARC-DETR improves ${\mathbf{AP}}^{\mathbf{val}}$ from 29.7 to 34.8, ${\mathbf{AP}}_{50}^{\mathbf{val}}$ from 49.5 to 56.2, and ${\mathbf{AP}}_S^{\mathbf{val}}$ from 19.2 to 24.8. On DIOR, AP rises from 57.9 to 68.4, and on NWPU VHR-10, from 44.4 to 66.5, demonstrating robust cross-dataset generalization. After structural reparameterization, the additional overhead is less than 0.75 M parameters and 0.36 G FLOPs, confirming deployment suitability for UAV and satellite-based remote sensing applications. Full article

Rett syndrome is a severe neurodevelopmental disorder caused predominantly by loss-of-function mutations in the X-linked gene MECP2. In addition to a vast array of neurological and physiological impairments, patients also frequently develop severe osteopenia with increased fracture risk; however, the mechanisms underlying these skeletal defects are not completely understood. Previous work in Mecp2-null mouse models has suggested that osteopenia is mainly due to impaired osteoblast function and reduced bone formation. Here, we examined bone mass, microarchitecture, and remodeling parameters in a Mecp2-null mouse model during postnatal development, with a particular focus on osteoclast involvement. Microcomputed tomography and histomorphometric analyses showed reduced bone mineral density and trabecular bone volume, which are associated with increased trabecular separation and cortical thinning. These structural alterations were accompanied by increased osteoclast number per bone surface, elevated urinary deoxypyridinoline, and higher expression of osteoclast-associated genes, including Cathepsin K. Furthermore, gene expression analysis revealed an age-dependent shift in bone remodeling. At postnatal day 35, mutant mice showed reduced expression of Dlx5 and Dlx6, consistent with low bone turnover. By postnatal day 55, Rankl and Cathepsin K were markedly upregulated, suggesting an increase in osteoclast resorptive activity, while key osteoblast markers and the RANKL/OPG ratio did not change significantly. A potential cell-autonomous contribution of Mecp2 to osteoclast maturation is also suggested by the analysis of public transcriptomic datasets on human osteoclast differentiation. Together, our findings identify increased osteoclast activity as a significant contributor to Rett-associated osteopenia and suggest that skeletal pathology in Mecp2 deficiency progresses from an early low-turnover state to a later phase of increased osteoclast resorption. Full article

Optical fiber sensors deployed in harsh industrial fields, e.g., high-temperature wet-oxygen, face severe challenges in signal attenuation and mechanical degradation. While amorphous silicon oxycarbide (a-SiOC) coatings offer a promising solution due to their adjustable thermo-mechanical properties, balancing their structural density with environmental stability remains a critical technical bottleneck. In this study, a-SiOC coatings were deposited on optical fibers using hexamethyldisilane (HMDS) and trace oxygen via radio-frequency capacitively coupled plasma-enhanced chemical vapor deposition (PECVD). A systematic investigation was conducted to determine the impact of deposition temperature (70–420 °C) on the precursor dissociation kinetics, microstructural evolution, and corrosion resistance of the coatings. An elevation in temperature promotes the elimination of organic terminal groups (–CH₃, –H) and enhances surface diffusion, driving the coating from a loose, carbon-rich “polymer-like” structure (dominated by Si–C bonds) to a dense, inorganic “silica-like” skeleton (dominated by Si–O–Si bonds). High-temperature corrosion tests in a wet-oxygen environment (500–900 °C) demonstrate that the failure mechanism is highly dependent on deposition temperature. Coatings deposited at low temperatures suffer catastrophic cracking due to pronounced oxidative shrinkage and the release of volatile species, whereas coatings deposited at 420 °C exhibit microcracking caused by severe carbon phase separation and stress concentration within the rigid inorganic network. In the present system, 350 °C is identified as the optimal deposition temperature, as it achieves the best balance of network densification and structural flexibility, while exhibiting the best mechanical performance. Full article

The rapid growth of data-intensive applications has increased the demand for efficient storage in large-scale key-value (KV) stores. Disaggregated memory architectures provide a scalable solution by separating compute and memory resources via RDMA. However, existing indexing schemes in these environments suffer from poor read efficiency, significantly degrading overall system throughput and scalability. Specifically, learned indexes often encounter substantial read amplification during remote data retrieval due to prediction errors. In addition, caching full keys incurs a high cache footprint, limiting the effective cache capacity on compute nodes and leading to additional remote memory accesses. This paper presents FPCache, a fingerprint-rectified learned index cache for disaggregated memory. We propose a fingerprint-assisted two-stage read approach to mitigate read amplification. FPCache first retrieves a compact fingerprint array for local matching. It then converts range reads into precise point accesses and directly reads the corresponding data item, thereby avoiding reading the entire range and reducing extra data transfers. Next, we design a fingerprint-offset compression strategy to maximize cache density. Leveraging fixed-length fingerprints and position offsets enables compute nodes to retain significantly more hotspot data within limited memory resources. Experimental evaluations using various YCSB workloads demonstrate that FPCache consistently outperforms state-of-the-art methods. Compared to systems like CHIME and ROLEX, FPCache improves system throughput by up to 62% and effectively maintains stable access efficiency under diverse data distributions. Full article

Covalent organic frameworks (COFs) are promising crystalline porous polymers for photocatalysis, yet their strong excitonic effects and rapid carrier recombination limit efficiency. However, strong excitonic effects and rapid electron–hole recombination remain key challenges. Herein, we employ density functional theory (DFT) and time-dependent density functional theory (TD-DFT) to systematically investigate the structure–activity relationships of three D–π–A-type COFs (COF-alkene, TapbBtt-COF, and TtaTpa-COF) for photocatalytic overall water splitting. Benchmarking identifies the M06L functional, SMD solvent model, and 6-311+G(2d,p) basis set as optimal. Our results reveal that molecular planarity, D–π–A configuration, and charge separation collectively govern performance. TtaTpa-COF exhibits the narrowest E_ex (2.47 eV), longest absorption wavelength (502.15 nm), and lowest hole–electron overlap (0.51), enabling efficient carrier separation. For the hydrogen evolution reaction (HER), TtaTpa-COF shows the most favorable *H adsorption free energy (0.04 eV) and lowest LUMO level (−2.8 eV), yielding the highest activity. Notably, the D–π–A system governs active-site selectivity: COF-alkene favors the alkene-linked carbon, whereas the other two favor imine nitrogen. For the oxygen evolution reaction (OER), all follow the adsorbate evolution mechanism with *OOH formation as the rate-determining step. TtaTpa-COF exhibits the lowest limiting potential (4.33 eV), indicating superior water oxidation kinetics. This work establishes a clear structure–activity relationship linking D–π–A architecture to photocatalytic performance, providing a rational design framework for high-activity COF-based photocatalysts. Full article

Electrocatalytic CO₂ reduction reaction (CO₂RR) to ethylene (C₂H₄) has emerged as a promising approach for converting CO₂ into valuable chemicals while utilizing renewable electricity. To facilitate the commercialization of this technology, a process-level techno-economic assessment (TEA) is constructed for a plant producing 100 tons/day of C₂H₄ from coal-power flue gas CO₂ using a membrane electrode assembly (MEA) electrolyzer and downstream gas separations. The model integrates (i) flue gas CO₂ capture by chemical absorption, (ii) CO₂RR to C₂H₄ with H₂ as the only co-product, and (iii) cathode off-gas separation by pressure swing adsorption (PSA) plus anode off-gas CO₂ recovery and recycle. A Cu₁₀–Sn catalyst measured in an H-cell is projected to MEA operation by scaling current density by 10×, yielding a “Case Study in This Article” scenario of j = 246 mA·cm⁻² and FE(C₂H₄) = 48.74%. Under this scenario, the total cost is 592.61 thousand USD/day (5926 USD/ton), dominated by electricity (39.8%). Scenario analysis shows that the total cost can decrease to 76,755.0 USD/day (767.6 USD/ton) under a future-outlook case with improved electrolyzer performance and low-cost power, enabling a net profit of 19,945.0 USD/day at an ethylene selling price of 967 USD/ton. Sensitivity analysis identifies FE(C₂H₄), full-cell voltage, and electricity price as the most influential variables. The results translate laboratory catalyst metrics into industrial cost drivers and clarify quantitative performance targets for commercialization. Full article

Cyclone separators remain widely used for gas–solid separation, yet analytical prediction of cut size and pressure drop remains challenging. This study presents an explicit semi-empirical model for the cut size (d₅₀) of reverse-flow cyclones based on the radial particle equation of motion in cylindrical coordinates, with d₅₀ obtained by equating radial migration time and residence time. A closed-form solution is derived in the Stokes regime, whereas non-Stokes behavior is handled numerically through the Schiller–Naumann drag correction. Turbulence is incorporated through a phenomenological correction, and the grade–efficiency curve is represented by a logistic relation. The model was implemented in MATLAB R2025a and applied in a parametric study covering inlet velocity, particle density, cyclone diameter, and gas viscosity. A Euler-type pressure drop relation was included to examine the separation–energy trade-off. Validation on the Kim et al. benchmark using one calibration point per cyclone family and six independent verification cases yielded a mean absolute percentage error of 13.5% and a root mean square error of 0.22 μm for d₅₀; the paired pressure drop check gave a 2.8% mean absolute percentage error. A complementary benchmark based on Wang et al. using 15 cm 1D3D and 2D2D cyclones under actual-air and standard-air conditions further supported the family-calibrated use of the model. A separate scale-up test showed that constant swirl intensity similarity is not transferable across large diameter changes. The formulation provides a transparent reduced-order tool for preliminary design and sensitivity analysis. Full article

We briefly review our recent theoretical progress on one-neutron ($1n$) halo nuclei in the mass region of 15 ≲ A ≲ 50 from microscopic structure to reaction observables, by combining the deformed relativistic Hartree–Bogoliubov theory in continuum (DRHBc) and its triaxial extension (TRHBc) with the Glauber reaction model. In such an effective scheme, we first succeed in reproducing the enhanced reaction cross sections and narrow longitudinal momentum distributions of both the heaviest $1n$ p-wave halo nucleus ³⁷Mg and the heavier ³¹Ne on a carbon target, which are loosely bound and well-deformed systems with dominant p-wave configurations of the valence neutron. To test its capability for the lighter halo cases, we select neutron-rich carbon isotopes as examples. It turns out that the DRHBc + Glauber approaches are still valid for the s-wave halo in ¹⁵C, while a better description of the ground state for ¹⁹C requires the inclusion of exchange terms and tensor forces via the deformed relativistic Hartree–Fock–Bogoliubov (D-RHFB) model.Finally, these approaches are applied to search for heavier $1n$ halo candidates. It was suggested that ^40,42Al are promising candidates as $1n$ p-wave triaxial halo nuclei and ^43,45Si as $1n$ p-wave axial halo nuclei with prominent shape decoupling from the oblate core. Our studies cast a new light on future experimental measurements for new halo nuclei. Full article

Laser-induced breakdown in water-rich biological media results from the interplay between primary photoionization processes and avalanche amplification of free electrons. Understanding this competition is essential for predicting ablation thresholds under ultrashort-pulse irradiation. In this work, we develop an analytical rate-equation model for the buildup of electron density in water-like biological tissues. It combines photoionization and chromophore ionization into a single seed-generation term, while avalanche ionization is described through a cascade gain factor. This formulation provides a framework for describing cascade electron-impact ionization processes in liquid-like media under strong-field excitation. Our approach gives an analytical expression for the temporal evolution of electron density driven by a Gaussian laser pulse and makes it possible to separate the contributions of direct ionization of water and ionization of chromophore centers. The analytical results are compared with numerical simulations that include carrier diffusion, bimolecular recombination and trapping. The comparison clarifies the roles of seed formation and cascade amplification in the growth of the electron population. The predicted dependence of threshold fluence on pulse duration agrees well with experimental data reported for water-like tissues such as the corneal tissues at a wavelength of 800 nm. The model provides a simple analytical picture of ultrafast plasma formation and electron-driven energy deposition in water-like biological media. Full article