Search Results (118)

To investigate the performance patterns of high-pressure water mist sprinklers with different flow coefficients in smoke containment and thermal insulation during fire suppression, this study conducted droplet size experiments and small-scale fire tests at 8 MPa pressure using six sprinkler types with flow coefficients (K) of 0.5, 0.7, 1.0, 1.2, 1.5, and 2.0. These findings were systematically analyzed in conjunction with FDS numerical simulations. Droplet size results indicate optimal atomization for K = 1.0, 1.2, and 1.5 sprinklers, producing fine droplets with concentrated distribution. Small-scale experiments and simulations further compared their smoke suppression and heat insulation performance. Findings show K = 1.5 delivers superior smoke suppression and cooling effects, reducing protected area temperatures by 20~45 °C compared to other conditions while minimizing smoke spread. Although visibility was slightly lower than at K = 1.2 due to droplet size and particle count, the overall performance was superior. This study conclusively identified K = 1.5 as the optimal flow parameter, providing experimental evidence and theoretical support for the engineering application of high-pressure water mist sprinklers. Full article

Antibacterial surfaces inspired by biological micro- and nanostructures, such as those found on the wings of cicadas and dragonflies, have attracted interest due to their ability to inhibit bacterial adhesion and damage microbial membranes without relying on chemical agents. However, conventional fabrication techniques like photolithography or nanoimprinting are limited by substrate shape, size, and high operational costs. In this study, we developed a scalable method using atmospheric-pressure low-temperature plasma (APLTP) to fabricate sharp-edged nanospikes on solvent-cast polymethyl methacrylate (PMMA) films. The nanospikes were formed through plasma-induced modification of pores in the film, followed by annealing to control surface wettability while maintaining structural sharpness. Atomic force microscopy confirmed the formation of micro/nanostructures, and contact angle measurements revealed reversible hydrophilicity. Antibacterial performance was evaluated against Escherichia coli using ISO 22196 standards. While the film with only plasma treatment reduced bacterial colonies by 30%, the film annealed after plasma treatment achieved an antibacterial activity value greater than 5, with bacterial counts below the detection limit (<10 CFU). These findings demonstrate that APLTP offers a practical route for large-area fabrication of biomimetic antibacterial coatings on flexible polymer substrates, holding promise for future applications in healthcare, packaging, and public hygiene. Full article

Background/Objectives: Leukoreduced low-titer group O whole blood (LTOWB) is a promising option for early transfusion in massive hemorrhages, by providing red blood cells (RBCs), plasma, and platelets in a single unit. This study aimed to assess the effects of pathogen reduction (PR) on the LTOWB quality and its suitability for emergency transfusions, including its post-thaw RBC usability. Methods: Whole blood from 24 donors was processed and analyzed over seven days, including post-thaw assessments. Hematological and coagulation parameters, along with atomic force microscopy, were used to assess the RBCs’ morphology, cytoskeletal integrity, and nanomechanical properties. Results: The PR reduced the leukocyte content while preserving platelet counts at the level of the control group. Although certain clotting factors, such as fibrinogen (p < 0.001) and factor VIII (p < 0.001), were diminished after the PR, thromboelastometry results remained within reference ranges, indicating a maintained hemostatic potential. Morphological changes in RBCs were observed, but the membrane elasticity remained stable throughout storage and after thawing, indicating preserved macromechanical properties essential for hemostasis. Conclusions: These findings demonstrate that LTOWB treated with partial a leukoreduction and PR maintains functional and structural integrity, supporting its potential utility as a safe and effective transfusion product for managing acute blood loss. Full article

Natural radionuclides may occur in groundwater and pose health risks when present in elevated concentrations. This study evaluates the quality of shallow groundwater in Nysa County (SW Poland) based on the activity concentrations of natural radionuclides radon (²²²Rn) and radium (²²⁶Ra) and estimates the associated radiological risk from water ingestion. Twenty-three groundwater samples were collected from private wells located within two distinct geological units: the Fore-Sudetic Block and the Opole Trough. Activity concentrations of ²²²Rn and ²²⁶Ra were measured using the liquid scintillation counting method. A spatial distribution model for ²²²Rn was developed using inverse distance weighting in QGIS. Local hydrogeochemical background levels were determined using the Q-Dixon test, interquartile range, and Shapiro–Wilk normality test. The background ranged from 2.6 to 3.9 Bq·L⁻¹ in the Opole Trough and from 0 to 10.7 Bq·L⁻¹ in the Fore-Sudetic Block. The lower detection limit (0.05 Bq·L⁻¹) for ²²⁶Ra activity concentration measurements was not exceeded. Effective dose rates were calculated in accordance with the recommendations of the International Commission on Radiological Protection and United Nations Scientific Committee on the Effects of Atomic Radiation. Doses ranged from <1 µSv to over 120 µSv·y⁻¹. Although all samples met national regulatory standards (≤1 mSv·y⁻¹), the World Health Organization reference level (0.1 mSv·y⁻¹) was exceeded in two cases. The results support the need for the radiological monitoring of unregulated private wells and provide a scientific basis for the refinement of legal frameworks and health protection strategies. Full article

In this paper, I will discuss a topic concerning part–whole structures in the nominal and verbal domain. Specifically, I will address the question of whether there is a universal mechanism for the individuation of entities and events by exploring parallels between singulatives and semelfactives in Slavic. Singulatives are derived unit nouns, whereas semelfactives are punctual verbs that describe a brief event which culminates by returning to the initial state. Cross-linguistically, singulative morphology often alternates with collective marking, whereas semelfactives alternate with iteratives. Collectives and iteratives describe homogenous groupings of entities and events, respectively. From a conceptual perspective, both singulatives and semelfactives individuate to the effect of singular bounded unit reference and in the literature, the parallel between the mass count/distinction and aspect has often been drawn. In Slavic, singulative and semelfactive morphologies share a component; specifically, both markers involve a nasal -n and a vocalic component, e.g., compare Russian gorox ‘peas (as a mass)’ ∼goroš-in-a ‘a pea’ and prygať ‘to jump (repeatedly)’ ∼ pryg-nu-ť ‘to jump once’. I will argue that the singulative -in and semelfactive -nu are complex and both involve the very same -n, which denotes a declustering atomizer modeled in mereotopological terms. Full article

The nanoporous structure of coal is crucial for the occurrence and development of coalbed methane (CBM). This study, leveraging the combined characterization of atomic force microscopy (AFM) and Gwyddion software (v2.62), investigated six anthracite samples with varying degrees of metamorphism (R_o = 2.11–3.36%). It revealed the intrinsic relationships between their nanoporous structures, surface morphologies, fractal characteristics, and coalification processes. The research found that as R_o increases, the surface relief of coal decreases significantly, with pore structures evolving from being macropore-dominated to micropore-enriched, and the surface tending towards smoothness. Surface roughness parameters (R_a, R_q) exhibit a negative correlation with R_o. Quantitative data indicate that area porosity, pore count, and shape factor positively correlate with metamorphic grade, while mean pore diameter negatively correlates with it. The fractal dimensions calculated using the variance partition method, cube-counting method, triangular prism measurement method, and power spectrum method all show nonlinear correlations with R_o, moisture (M_ad), ash content (A_ad), and volatile matter (V_daf). Among these, the fractal dimension obtained by the triangular prism measurement method has the highest correlation with R_o, A_ad, and V_daf, while the variance partition method shows the highest correlation with M_ad. This study clarifies the regulatory mechanisms of coalification on the evolution of nanoporous structures and surface properties, providing a crucial theoretical foundation for the precise evaluation and efficient exploitation strategies of CBM reservoirs. Full article

The increasing prevalence of antibiotic-resistant bacteria has intensified the need for innovative antibacterial surfaces, particularly in biomedical applications. Traditional approaches often rely on chemical agents alone, which may lead to diminishing efficacy over time. To address this, we investigated the development of a novel antibacterial surface by combining the inherent antimicrobial properties of copper with an engineered surface topography on a biopolymer matrix. A copper–poly-L-lactic acid (Cu-PLLA) composite system was fabricated using sputtering deposition followed by controlled thermal treatment to induce wrinkle-like micro- and nanostructures on the surface. The surface morphology was characterized using scanning electron microscopy (SEM) and atomic force microscopy (AFM), confirming the formation of hierarchical wrinkle patterns. The chemical composition and distribution of copper were analyzed via energy-dispersive X-ray spectroscopy (EDS). Antibacterial performance was assessed against both Gram-negative Escherichia coli and Gram-positive Staphylococcus aureus using standard colony count reduction assays. The Cu-PLLA wrinkled surfaces demonstrated significantly enhanced bactericidal activity compared with flat PLLA and copper-free controls, a finding attributed to a synergistic effect of mechanical membrane disruption and copper-mediated chemical toxicity. These findings suggest that biopolymer–metal hybrid surfaces with engineered topography offer a promising strategy for developing next-generation antibacterial materials suitable for biomedical and clinical use. Full article

The goal of this study is to develop an efficient machine learning framework for designing high-hardness multi-metal nitride coatings, overcoming the limitations of traditional trial-and-error methods. The development of multicomponent metal nitride hard coatings via multi-arc ion plating remains a significant challenge due to the vast compositional search space. Although theoretical studies in macroscopic, mesoscopic, and microscopic domains exist, these often focus on idealized models and lack effective coupling across scales, leading to time-consuming and labor-intensive traditional methods. With advancements in materials genomics and data mining, machine learning has become a powerful tool in material discovery. In this work, we construct a compositional search space for multicomponent nitrides based on electronic configuration, valence electron count, electronegativity, and oxidation states of metal elements in unary nitrides. The search space is further constrained by FCC crystal structure and hardness theory. By incorporating a feature library with micro-, meso-, and macro-structural characteristics and using clustering analysis with theoretical intermediate variables, the model enriches dataset information and enhances predictive accuracy by reducing experimental errors. This model is successfully applied to design multicomponent metal nitride coatings using a literature-derived database of 233 entries. Experimental validation confirms the model’s predictions, and clustering is used to minimize experimental and data errors, yielding a strong agreement between predicted optimal molar ratios of metal elements and nitrogen and measured hardness performance. Of the 100 Vickers hardness (HV) predictions made by the model using input features like molar ratios of metal elements (e.g., Ti, Al, Cr, Zr) and atomic size mismatch, 82 exceeded the dataset’s maximum hardness, with the best sample achieving a prediction accuracy of 91.6% validated against experimental measurements. This approach offers a robust strategy for designing high-performance coatings with optimized hardness. Full article

Accurate State of Charge (SOC) estimation is critical for optimizing the performance and longevity of lithium-ion batteries (LIBs), which are widely used in applications ranging from electric vehicles to renewable energy storage. Traditional SOC estimation methods, such as Coulomb counting and open-circuit voltage measurement, suffer from cumulative errors and slow response times. This paper proposes a novel machine learning-based approach for SOC estimation by integrating Electrochemical Impedance Spectroscopy (EIS) with the SHapley Additive exPlanations (SHAP) method, Atom Search Optimization (ASO), and Light Gradient Boosting Machine (LightGBM). This study focuses on large-capacity lithium iron phosphate (LFP) batteries (3.2 V, 104 Ah), addressing a gap in existing research. EIS data collected at various SOC levels and temperatures were processed using SHAP for feature extraction (FE), and the ASO–LightGBM model was employed for SOC prediction. Experimental results demonstrate that the proposed SHAP–ASO–LightGBM method significantly improves estimation accuracy, achieving an RMSE of 3.3%, MAE of 1.86%, and R² of 0.99, outperforming traditional methods like LSTM and DNN. The findings highlight the potential of EIS and machine learning (ML) for robust SOC estimation in large-capacity LIBs. Full article

Meat provides a favorable environment for the growth of microorganisms, so increasingly advanced methods are being sought to ensure the rapid detection of their presence and determine the degree of contamination. These measures are intended to ensure consumer health and reduce food losses. The aim of this study was to evaluate the suitability of a thermal imaging camera and FT-IR spectrophotometry for microbiological quality control of poultry meat. This study used poultry meat fillets packaged in a modified atmosphere and stored at 4 °C for 10 days. During the successive days of storage, the following were determined: the total number of microorganisms, the count of Enterobacteriaceae, the temperature of the samples tested using a thermal imaging camera, and the spectral data contained in the spectra recorded by the FT technique of IR spectroscopy. The results were analyzed using Tukey’s test in the STATISTICA 13.3 statistical program with an assumed significance level of α ≤ 0.05. Spectral data obtained by the FT-IR method were subjected to interpretation using the T.Q. Analyst 8 program. This study found that the number of microorganisms increased between the 2nd and 10th days of storage for the poultry meat samples of four log CFU/g, leading to a temperature increase of 2.61 °C, and also, the intensities and frequencies of selected IR bands generated by vibrations of various groups of atoms changed, including functional groups present in the compounds contained in the tested samples. It was shown that modern techniques such as FT-IR spectroscopy and thermal imaging cameras have significant potential applications in the food industry for assessing the microbiological quality of food. Full article

As a crucial energy source and chemical raw material, coal’s micro-pore structure holds a pivotal influence on the occurrence and development of coalbed methane (CBM). This study systematically analyzed the nano-pore structure, surface roughness, and fractal characteristics of six coal samples with varying volatile matter content (V_daf) using Atomic Force Microscopy (AFM) combined with Scanning Electron Microscopy (SEM), revealing the correlation between volatile matter and the micro-physical properties of coal. Through AFM three-dimensional topographical observations, it was found that coal samples with higher volatile matter exhibited significant gorge-like undulations on their surfaces, with pores predominantly being irregular macropores, whereas low volatile matter coal samples had smoother surfaces with dense and regular pores. Additionally, the surface roughness parameters (R_a, R_q) of coal positively correlated with volatile matter content. Meanwhile, quantitative analysis of nano-pore parameters using Gwyddion software showed that an increase in volatile matter led to a decline in pore count, shape factor, and area porosity, while the average pore diameter increased. The fractal dimension of samples with different volatile matter contents was calculated, revealing a decrease in fractal dimension with rising volatile matter. Nano-ring analysis indicated that the total number of nano-rings was significantly higher in low volatile matter coal samples compared to high volatile matter ones, but the nano-ring roughness (R_r) increased with volatile matter content. SEM images further validated the AFM results. Through multi-scale characterization and quantitative analysis, this study clarified the extent to which volatile matter affects the nano-pore structure and surface properties of coal, providing critical data support for efficient CBM development and reservoir evaluation. Full article

Our first-principles calculations have unveiled a profound influence of varied external charges on the energy levels and spin distributions of zero-, one-, and two-dimensional carbon nanomaterials. By leveraging the Fermi distribution formula, we systematically analyze the temperature-dependent electron occupancy probabilities of the highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO). Notably, configurations with specific additional electron loads exhibit a stable total occupancy of HOMO + LUMO equal to 1 across a wide temperature range, forming a robust basis for orbital qubits. This stability persists even under Fermi energy corrections, demonstrating minimal temperature sensitivity up to 300 K. Furthermore, we identify a universal criterion—E_HOMO + E_LUMO = 2E_Fermi—that governs qubit feasibility across diverse carbon nanostructures, independent of dimensionality or atom count. Experimental validation via charge injection methods (e.g., gate modulation or electron beam irradiation) is supported by existing precedents in carbon-based quantum devices. Our findings establish low-dimensional carbon nanomaterials as versatile, scalable platforms for quantum computing, combining thermal stability and dimensional adaptability, thus bridging theoretical insights with practical quantum engineering. Full article

In the realm of quantum communication and photonic technologies, the extension of coherence time for photon wave packets is essential for improving system efficacy. This research introduces a methodology for measuring coherence time utilizing an unbalanced fiber interferometer, specifically designed for tunable pulse-width photon wave packets produced by cold atoms. By synchronously generating write pulses, signal light, and frequency-locking light from a single laser source, the study effectively mitigated frequency discrepancies that typically arise from the use of multiple light sources. The implementation of frequency-resolved photon counting under phase-locked conditions was accomplished through the application of polarization filtering and cascaded filtering techniques. The experimental results indicated that the periodicity of frequency shifts in interference fringe patterns diminishes as the differences in delay arm lengths increase, while fluctuations in fiber length and high-frequency laser jitter adversely affect interference visibility. Through an analysis of the correlation between delay and photon counts, the coherence time of the write laser was determined to be 2.56 µs, whereas the Stokes photons produced through interactions with cold atoms exhibited a reduced coherence time of 1.23 µs. The findings suggest that enhancements in laser bandwidth compression and fiber phase stability could further prolong the coherence time of photon wave packets generated by cold atoms, thereby providing valuable technical support for high-fidelity quantum information processing. Full article

In this research, polymer composite sheets were developed by blending poly (vinylidene fluoride-co-hexafluoropropylene) or P(VDF-HFP) with varying concentrations of barium sulfate (BaSO₄) for X-ray shielding applications. The photon counting technique was used to evaluate the composite shielding characteristics through the linear attenuation coefficient. Surface properties, including surface morphology, hydrophobicity, and surface energy, were analyzed using an atomic force microscope (AFM) and a water contact angle machine. Scanning electron microscopy (SEM) was employed to investigate the microstructural distribution and dispersion of BaSO₄ particles within the polymer matrix, providing insights into the composite’s uniformity and structural integrity. Additionally, the bulk properties of the composite polymer sheets, such as crystal structures, tensile strength, and thermal stability, were examined. The results demonstrate that increasing the concentration of BaSO₄ in BaSO₄/P(VDF-HFP) composite sheets significantly improves their X-ray attenuation capabilities. Moreover, higher BaSO₄ concentrations enhance the material’s hydrophobicity, flexibility, and thermal stability, highlighting the potential of these composites for advanced radiation shielding applications. Full article

First, we discuss a common feature of single-phase pure metals and amorphous and high-entropy alloys: the maximum value of hardness corresponding to a valence electron count (VEC) value of around 6.5–7. This correlation is explained by the coincidence that by subtracting the number of sp valence electrons (Nsp = 2) from the VEC we obtain the maximal number of unpaired d electrons, N_d = 4.5–5 in the 3d, 4d, and 5d rows of transition elements. These unpaired d electrons form orbital overlap bonding, which is stronger than the isotropic metallic bonds of a delocalized electron cloud. The more unpaired d electrons there are, the higher the bonding strength. Second, we will discuss the hardness formulas derived from cohesion energy and shear modulus. We will demonstrate that both types of formulas originate in the electrostatic energy density of metallic bonds, expressing a 1/R⁴ dependence. Finally, we show that only two parameters are sufficient to estimate hardness: the atomic radius and the cohesion-based valence. In the case of alloys, our formula gives a lower bound on the hardness only. It is not suitable for calculation of the hardness increase caused by solid solution, grain size, precipitation, and phase mixture. Full article