Search Results (3,406)

Grouting technology can be employed to repair cracks in an aquifer to maintain its stability; however, existing grouting materials tend to come with problems such as low flexural strength, poor cracking resistance, and the coupled effects of fiber reinforcement and sulfoaluminate cement (SAC) addition on hydrate evolution, and pore-refinement and crack-resistance mechanisms in coal-based solid-waste cementitious grouts remain insufficiently understood. In this paper, fiber-modified coal-based solid-waste grouting (F-CWG) materials were prepared by mixing different contents of sulfoaluminate cement (SAC) and different fibers. The mechanical strength, microstructure, hydration products, and pore evolution characteristics were analyzed by means of mechanical property tests, energy-dispersive X-ray spectroscopy (SEM/EDS), X-ray diffraction (XRD), thermogravimetric analysis (TGA), and nuclear magnetic resonance (NMR). The results show that the mechanical strength decreases at first due to insufficient early-stage hydration products. Specifically, the 28 d compressive and flexural strengths decrease from 15.34 MPa and 4.55 MPa at 0% SAC to 8.18 MPa and 2.99 MPa at 40% SAC but increase again to 13.36 MPa and 3.79 MPa at 60% SAC as the formation of ettringite (AFt) and C–S–H is promoted with higher SAC content. Among the tested fibers, a dosage of 0.6% generally improves mechanical strength and refines pore structure, with PVA and steel fibers showing the most pronounced effects. Our results reveal the mechanism behind the enhancement of cracking resistance in F-CWG materials, providing a scientific basis for grouting and water-preservation mining, and are of great significance in improving the utilization rate of coal-based solid waste. Full article

Alkaline water electrolysis remains one of the leading and most mature technologies for large-scale hydrogen production. Its advantages stem from the use of inexpensive, earth-abundant materials and well-established industrial deployment, yet the technology continues to face challenges, including sluggish hydrogen evolution reaction (HER) kinetics and energy-efficiency limitations compared with acidic electrolysis systems. This review provides a comprehensive overview of the fundamental principles governing alkaline electrolysis, encompassing electrolyte chemistry, electrode materials, electrochemical mechanisms, and the roles of overpotentials, cell resistances, and surface morphology in determining system performance. Key developments in catalytic materials are discussed, highlighting both noble-metal and non-noble-metal electrocatalysts, as well as advanced approaches to surface modification and nanostructuring designed to enhance catalytic activity and long-term stability. Particular emphasis is placed on the emerging strategy of in situ ionic activation, wherein transition-metal ions and oxyanions are introduced directly into the operating electrolyte. These species dynamically interact with electrode surfaces under polarization, inducing real-time surface reconstruction, improving water dissociation kinetics, tuning hydrogen adsorption energies, and extending electrode durability. Results derived from polarization measurements, electrochemical impedance spectroscopy, and surface morphology analyses consistently demonstrate that ionic activators, such as Ni–Co–Mo systems, significantly increase the HER performance through substantial increase in surface roughness and increased intrinsic electrocatalytic activity through synergy of d-metals. By integrating both historical context and recent research findings, this review underscores the potential of ionic activation as a scalable and cost-effective way toward improving the efficiency of alkaline water electrolysis and accelerating progress toward sustainable, large-scale green hydrogen production. Full article

This paper presents the results of a comprehensive technological study of three bronze sculptures from the Jin Empire period (1115–1234 AD) from the collection of the Museum of Archaeology and Ethnography at the Institute of History, Archaeology and Ethnography of the Peoples of the Far East, Far Eastern Branch of the Russian Academy of Sciences (IHAE FEB RAS). Using photon-counting computed tomography (PCCT) and energy-dispersive X-ray spectroscopy (EDS), the production techniques were reconstructed, differences in alloy composition were identified, and specific features of the casting processes were determined. Tomographic analysis revealed two fundamentally different manufacturing approaches: a multi-stage technology involving the use of different alloys and the assembly of separately cast elements, and a single-cast technology with a homogeneous structure. Elemental analysis of the three sculptures using EDS demonstrated significant compositional variability—from 21% to 67% copper and from 9% to 69% tin in different parts of the objects—confirming the complexity of the technological processes. An expanded study of 20 bronze sculptures using portable X-ray fluorescence analysis (pXRF) allowed for the identification of four typological alloy groups: classic balanced lead–tin bronzes (Cu 30–58%, Sn 16–23%, Pb 16–28%), high-lead bronzes (Pb up to 52%), high-tin bronzes (Sn up to 30%), and low-tin alloys (Sn less than 11%). The morphological features of the sculptures suggest one of their possible interpretations as ancestor spirits used in ritual practices. The research findings contribute to the study of Jurchen metallurgical traditions and demonstrate the potential of interdisciplinary, non-destructive analytical methods for reconstructing the technological, social, and cultural aspects of medieval Far Eastern societies. Full article

Green technologies are actively being used to produce nanosized zinc oxide, which is in demand for water purification processes to remove pollutants. Despite the success of the green synthesis of ZnO nanoparticles, no scientific approach exists for selecting plant extracts to produce nanoparticles with the desired properties. This study shows that the antioxidant activity of the plant extracts used is a key parameter influencing the properties of the resulting ZnO nanoparticles. This conclusion is based on the results of nanoparticle synthesis with the use of various plant extracts. The antioxidant activity of the extracts increases in the following order: plum–gooseberry–black currant–strawberry–sea buckthorn. The synthesized ZnO nanoparticles were characterized by UV–visible spectroscopy, transmission electron microscopy, and energy-dispersive X-ray spectroscopy. The catalytic properties of ZnO nanoparticles were tested under the degradation of a synthetic methylene blue dye after exposure to UV light. We found that with an increase in the AOA of plant extracts, the size of the nanoparticles decreases, while their photocatalytic activity increases. The smallest (d = 13 nm), most uniform in size (polydispersity index 0.1), and most catalytically active ZnO nanoparticles with a small band gap (2.85 eV) were obtained using the sea buckthorn extract with the highest AOA, pH 10 of the reaction mixture and 0.1 M Zn(CH₃COO)₂∙2H₂O as a precursor salt. ZnO nanoparticles synthesized in the sea buckthorn extract demonstrated the highest dye photodegradation efficiency (96.4%) compared with other nanoparticles. The established patterns demonstrate the “antioxidant activity–size–catalytic activity” triad can be considered as a practical guide for obtaining ZnO nanoparticles of a given size and with given properties for environmental remediation applications. Full article

Near-infrared (NIR) spectroscopy has emerged as a pivotal non-destructive analytical technique within the cheese industry, offering rapid and precise insights into the chemical composition and quality attributes of various cheese types. This review explores the evolution of NIR spectral sensors, highlighting key technological advancements and their integration into cheese production processes as well as final products already in markets. In addition, the review discusses challenges such as calibration complexities, the influence of sample heterogeneity and the need for robust data and interpretation models through spectroscopy coupled with AI methods. The future potential of NIR spectral sensors, including real-time in-line monitoring and the development of portable devices for on-site analysis, is also examined. This review aims to provide a critical assessment of current NIR spectral sensors and their impact on the cheese industry, offering insights for researchers and industry professionals aiming to enhance quality control and innovation in cheese production, as well as authenticity and fraud studies. The review concludes that the integration of advanced NIR spectroscopy with AI represents a transformative approach for the cheese industry, enabling more accurate, efficient and sustainable quality assessment practices that can strengthen both production consistency and consumer trust. Full article

Listeria monocytogenes (LM) contamination constitutes a paramount global threat to food safety, necessitating the urgent development of advanced, rapid, and non-destructive detection methodologies to ensure food security. This study successfully synthesized Bi₂WO₆ nanoflowers through optimized feed ratios of raw materials and further functionalized them with noble metal Au to construct a high-performance Au-Bi₂WO₆ composite nanomaterial. The composite exhibited high sensing performance toward acetoin, including high sensitivity (R_a/R_g = 36.9@50 ppm), rapid response–recovery kinetics (13/12 s), and excellent selectivity. Through UV-Vis diffuse reflectance spectroscopy (UV-Vis DRS) and X-ray photoelectron spectroscopy (XPS) characterizations, efficient electron exchange between Au and Bi₂WO₆ was confirmed. This electron exchange increased the initial resistance of the material, effectively enhancing the response value toward the target gas. Furthermore, the chemical sensitization effect of Au significantly increased the surface-active oxygen content, promoted gas–solid interfacial reactions, and improved the adsorption capacity for target gases. Compared to conventional turbidimetry, the Au-Bi₂WO₆ nanoflower-based gas sensor demonstrates superior practical potential, offering a novel technological approach for non-destructive and rapid detection of foodborne pathogens. Full article

The chemical composition, mineral composition, and mineral distribution characteristics of steel slag were characterized through petrographic analysis, X-ray diffraction (XRD), and particle size analysis. Limestone, silica, and silicomanganese slag were blended with converter steel slag to fabricate a reconstructed steel slag. Through burden calculation, the chemical composition ratio of this reconstructed steel slag approximated the silicate phase region. The high-temperature reconstruction process outside the furnace was simulated through reheating. The composition, structure, and cementitious characteristics of the reconstructed steel slag were investigated through X-ray diffraction (XRD), FactSage software (FactSage version 7.0 (GTT-Technologies, Aachen, Germany, 2015))analysis, scanning electron microscopy–energy dispersive spectroscopy (SEM–EDS) analysis, setting time determination, compressive strength measurement, and thermodynamic computation. The findings indicated that the primary mineral compositions of the reconstructed steel slag were predominantly silicates, such as Ca₃Al₂O₆, Ca₂SiO₄, Ca₂MgSi₂O₇, Ca₂Al(AlSiO₇), Ca₂(SiO₄), and FeAlMgO₄. In comparison with the original steel slag, these compositions underwent substantial alterations. The α′-C₂S phase appears at 1100 K and gradually transforms into α-C₂S at 1650 K. The liquid phase begins to precipitate at approximately 1550 K. Spinel exists in the temperature range from 1300 to 1700 K, and Ca₃MgSi₂O₈ melts into the liquid phase at 1400 K. As the temperature increases to 1600 K, the minerals C₂AF, Ca₂Fe₂O₅, and Ca₂Al₂O₅ gradually melt into the liquid phase. Melilite melts into the liquid phase at 1700 K. It was observed that the initial and final setting times of the reconstructed steel slag exhibited reductions of 7 and 43 min, respectively, in comparison to those of the original steel slag. In comparison with steel slag, the compressive strength of the reconstructed steel slag exhibited an increase of 0.6 MPa at the 3-day strength stage, 1.6 MPa at the 7-day strength stage, and 3.4 MPa at the 28-day strength stage. The reduction in setting time and the enhancement in compressive strength verified the improved cementitious activity of the reconstructed steel slag. Thermodynamic calculations of the principal reactions of the reconstructed steel slag at elevated temperatures verified that the primary reaction at 1748 K is thermodynamically favorable. Full article

Photocatalytic membrane reactors (PMRs) are an innovative technology for water treatment, effectively combining membrane filtration and photocatalysis to enhance contaminant removal while enabling the regeneration of fouled membranes. In this study, a new porous film of chitosan that was impregnated with TiO₂ was developed and coated onto a ceramic support by spin coating to form a new porous immobilized PMR. The formed membrane was tested for two reasons: the removal of methylene blue dye by a dead-end filtration process and to demonstrate its ability to self-regenerate under UV exposure. The selective layer of the membrane was characterized using FTIR spectroscopy, X-ray diffraction, scanning electron microscopy (SEM), and water permeability tests. The results confirmed the formation of an amorphous film with no chemical interaction between chitosan and TiO₂. The membrane exhibited an average water permeability of 10.72 L/m²·h·bar, classifying it as either ultrafiltration (UF) or nanofiltration (NF). Dead-end filtration of methylene blue (10 mg L⁻¹) achieved 99% dye removal based on UV–vis analysis of the permeate, while flux declined rapidly due to fouling. Subsequent UV irradiation removed the deposited dye layer and restored approximately 50% of the initial flux, indicating partial self-regeneration. Overall, spin-coated chitosan–TiO₂ layers on ceramic supports provide high dye removal and photocatalytically assisted flux recovery, and further work should quantify photocatalytic degradation during regeneration. Full article

In this work, an archeological adhesive collected at Cantagrilli (near Florence) was chemically analyzed by applying gas chromatography/mass spectrometry, infrared spectroscopy, and nuclear magnetic resonance spectrometry combined with the archeobotanical investigations. Data identify triterpenes, aged anhydride, benzoyl resin, and gelatinized starch in the sample. The multi-analytical approach allowed us to identify some molecular compounds, as well as their state of chemical decomposition (especially by applying the mass spectrometry techniques). On the other hand, archeobotanical measurements have provided useful but not unequivocal information regarding the possible origin of triterpenes from some terrestrial plants, combined with the presence of microorganisms and transformed chemicals (such as starch modified into gelatin). All this information is very useful to Prehistoric Archeologists for understanding the cultural processes and technologies used by ancient populations. Full article

Escherichia coli (E. coli) is a well-established indicator of faecal pollution and a potent pathogen linked to numerous gastrointestinal and systemic illnesses. Ensuring public safety requires rapid and sensitive detection methods capable of real-time, on-site deployment. Many conventional techniques are either laborious, time-intensive, costly, or require complex infrastructure, limiting their applicability in field settings. Raman spectroscopy offers label-free molecular fingerprinting; however, its inherently weak scattering signals restrict its effectiveness as a standalone technique. Surface-Enhanced Raman Spectroscopy (SERS) overcomes this limitation by exploiting plasmonic enhancement from nanostructured metallic substrates—most commonly gold, silver, copper, and aluminium. Despite the commercial availability of SERS-active substrates, challenges remain in achieving high reproducibility, long-term stability, and true field applicability, necessitating the development of integrated lab-on-chip platforms and portable, handheld Raman devices. This review critically examines recent advances in SERS-based E. coli detection across water and perishable food products with particular emphasis on the evolution of SERS substrate design, the incorporation of biosensing elements, and the integration of electrochemical and microfluidic systems. By contrasting conventional SERS approaches with next-generation biosensing strategies, this paper outlines pathways toward robust, real-time pathogen detection technologies suitable for both laboratory and field applications. Full article

The structural and electrochemical properties of gold nanoparticles biosynthesized from Rhus coriaria L. (Rc@AuNPs) were comprehensively investigated and characterized. R. coriaria (sumac) served as a natural gold reducing and capping agent due to its rich polyphenolic and phytochemical composition, enabling the sustainable, low-cost, and environmentally friendly synthesis of Rc@AuNPs. The electrochemical behavior of the hybrid material was evaluated using cyclic voltammetry (CV), galvanostatic charge–discharge (GCD), and electrochemical impedance spectroscopy (EIS). Rc@AuNPs exhibited specific capacitances of 129.48 F/g, 156.32 F/g, and 280.37 F/g in H₂SO₄, Na₂SO₄, and KOH electrolytes, respectively, indicating strong potential for supercapacitor and energy-storage applications. GCD analysis further showed C_sp values of 107.69 F/g (H₂SO₄), 133.23 F/g (Na₂SO₄), and 348.34 F/g (KOH), confirming the highest charge-storage performance in basic media. EIS measurements supported these results, yielding equivalent series resistance (ESR) values of 67.96 Ω in H₂SO₄, 64.42 Ω in Na₂SO₄, and a notably lower 24.43 Ω in KOH, consistent with its higher ionic conductivity and more efficient charge transfer. Overall, the superior C_sp and low ESR observed in KOH demonstrate the excellent capacitive behavior of Rc@AuNPs. These biosynthesized gold nanoparticles represent a promising and sustainable electrode material for high-performance energy-storage technologies. Full article

The single-step Rydberg excitation of cesium atoms requires a 319 nm ultraviolet laser with a narrow laser linewidth, high frequency stability, and high output power. To meet these requirements, in this work, we construct a high-power, single-frequency UV laser system at this wavelength. In this system, the frequency stabilization of the 1560.492 nm seed laser is critical to the performance of the ultraviolet laser. We employ nonlinear frequency conversion technology, the 1560.492 nm laser is frequency-doubled to 780.246 nm via a single pass through a PPLN crystal, and function integration is realized based on the modular parameter adjustment interface provided by the PyRPL software. Subsequently, the 1560.492 nm laser is stabilized to the $D_2$ hyperfine transition line of Rb-87 atoms using polarization spectroscopy (PS) and radio-frequency-modulated saturation absorption spectroscopy (RF-SAS). A comparative study of these two techniques shows that RF-SAS achieves superior stabilization performance, with the residual frequency fluctuation of the frequency-doubled laser being 1.07 MHz over 30 min. According to frequency doubling theory, the actual residual frequency fluctuation of the 1560.492 nm fundamental-frequency laser can be calculated as 0.535 MHz. Compared with our earlier scheme that utilized an ultra-low-expansion (ULE) optical cavity as a frequency reference, the present scheme eliminates the long-term drift induced by environmental factors. In contrast to frequency stabilization relying on discrete instruments, this integrated scheme significantly reduces the cost, simplifies the system architecture, saves space, and greatly enhances the flexibility and controllability of the system. It therefore provides a reliable and cost-effective solution to ensure the portability and practicability of high-performance UV laser sources. This high-precision frequency stabilization scheme directly guarantees the performance of the 319 nm UV laser, suppressing its linewidth below 10 kHz. Thus, it fully meets the stringent laser linewidth and frequency stability requirements for the single-step Rydberg excitation of cesium atoms and provides a reliable light source foundation for subsequent precision spectroscopic measurements. Full article

Accurate malaria diagnosis is essential for effective case management and transmission control; however, the sensitivity, operational requirements, and field applicability of current conventional methods are limited. Hemozoin, an optically and magnetically active crystalline biomarker produced by Plasmodium species, offers a reagent-free target for next-generation diagnostics. This scoping review, following PRISMA-ScR and Joanna Briggs Institute guidance, synthesizes recent advances in hemozoin-based detection technologies and maps the current landscape. Twenty-four studies were reviewed, spanning eight major technology classes: magneto-optical platforms, magnetophoretic microdevices, photoacoustic detection, Raman/SERS spectroscopy, optical and hyperspectral imaging, NMR relaxometry, smartphone-based microscopy, and flow cytometry. Magneto-optical systems—including Hz-MOD, Gazelle™, and RMOD—demonstrated the highest operational readiness, with robust specificity but reduced sensitivity at low parasitemia. Photoacoustic Cytophone studies demonstrated promising sensitivity and noninvasive in vivo detection. Raman/SERS platforms achieved sub-100 infected cell/mL analytical sensitivity but remain laboratory-bound. Microfluidic and smartphone-based tools offer emerging, potentially low-cost alternatives. Across modalities, performance varied by parasite stage, with reduced detection of early ring forms. In conclusion, hemozoin-targeted diagnostics represent a rapidly evolving field with multiple viable translational pathways. While magneto-optical devices are closest to field deployment, further clinical validation, improved low-density detection, and standardized comparison across platforms are needed to support future adoption in malaria-endemic settings. Full article

Functional Near-Infrared Spectroscopy (fNIRS), a non-invasive neuroimaging technique, has demonstrated unique advantages in linguistic research in recent years. By monitoring changes in the concentrations of oxygenated and deoxygenated hemoglobin during cortical activation, fNIRS provides new insights into the mechanisms underlying language processing. Its ecological validity and high compatibility enable seamless integration into real-world environments, minimizing interference and ensuring the authenticity of the collected data. In the realm of linguistics, fNIRS has been applied to studies on language perception, function, acquisition, cross-linguistic processing, and the assessment of language disorders, revealing the intricate mechanisms of language processing and showcasing its potential for clinical applications. This article reviews the latest advancements in the utilization of fNIRS in linguistic research, aiming to provide valuable references for researchers and to foster deeper exploration and innovative development in this field. Meanwhile, this article systematically examines the limitations of fNIRS in current research, provides a critical assessment of its methodological and applicative value, and, on this basis, outlines future directions and potential breakthroughs for this technology in the field of language research. Full article

Raman spectroscopy is a non-destructive analytical technique based on molecular vibrational properties. However, its practical application is often challenged by weak scattering signals, complex spectra, and the high-dimensional nature of the data, which complicates accurate interpretation. Traditional chemometric methods are limited in handling complex, nonlinear Raman data and rely on tedious, expert-knowledge-based feature engineering. The fusion of data-driven Machine Learning (ML) and Deep Learning (DL) methods offers a robust solution, enabling the automatic learning of complex features from raw data and achieving high-accuracy classification and prediction. The present study employed a structured narrative review methodology to capture the research progress, current trends, and future directions in the field of ML-assisted Raman spectral classification. This review provides a comprehensive overview of the application of traditional ML models and advanced DL architectures in Raman spectral analysis. It highlights the latest applications of this technology across several key domains, including biomedical diagnostics, food safety and authentication, mineralogical classification, and plastic and microplastic identification. Despite recent progress, several challenges remain: limited training data, weak cross-dataset generalization, poor reproducibility, and limited interpretability of deep models. We also outline practical directions for future research. Full article