Search Results (2,026)

The spatial heterodyne spectrometer is an interferometric spectrometer specifically designed for particular detection targets, capable of achieving ultra-high spectral resolution within a designated spectral range. As the demand for signal detection accuracy continues to increase, the extraction of accurate target spectra from spatial heterodyne interferograms has become increasingly important. This paper applies a deep neural network to the spectral reconstruction of specific spatial heterodyne interferograms. The spectral reconstruction model, SRDNN, was trained using CO₂ data simulated by the SCIATRAN radiative transfer model and the principles of spatial heterodyne spectroscopy. The results indicate that SRDNN has excellent CO₂ spectral reconstruction performance, with an evaluation index $R^2$ of 0.9943 and an $MSE$ of 0.00021. The average difference between the reconstructed spectra and the target spectra is only 0.371%. Furthermore, the method was further validated using experimental data obtained from a spatial heterodyne spectrometer. The remarkable spectral reconstruction results and excellent evaluation indicators once again demonstrated the universality and effectiveness of the method. Finally, the robustness of the method was studied using noisy experimental data. The results demonstrate that the method can accurately reconstruct spectra from interferograms with slight noise without requiring additional processing, simplifying the spectral reconstruction process. This work is expected to provide novel methods and effective solutions for the spectral reconstruction of specific targets detected by spatial heterodyne spectrometers. Full article

To address the limitations of low detection efficiency and poor spatial resolution of traditional cable insulation diagnosis methods, a novel cable insulation diagnosis method based on impedance spectroscopy has been proposed. An impedance spectroscopy analysis model of the frequency response of high-voltage single-core cables under different aging conditions has been established. The initial classification of insulation condition is achieved based on the impedance phase deviation between the test cable and the reference cable. Under localized aging conditions, the impedance phase spectroscopy is more than twice as sensitive to dielectric changes as the amplitude spectroscopy. Leveraging this advantage, a multi-parameter diagnostic framework is developed that integrates key spectral features such as the first phase angle zero-crossing frequency, initial phase, and resonance peak amplitude. The proposed method enables quantitative estimation of aging severity, spatial extent, and location. This technique offers a non-invasive, high-resolution solution for advanced cable health diagnostics and provides a foundation for practical deployment of power system asset management. Full article

This article presents a review of several non-exclusive pathways for the sequestration of soil organic carbon, which can be classified into two large classical groups: the modification of plant and microbial macromolecules and the abiotic and microbial neoformation of humic substances. Classical studies have established a causal relationship between aromatic structures and the stability of soil humus (traditional hypotheses regarding lignin and aromatic microbial metabolites as primary precursors for soil organic matter). However, further evidence has emerged that underscores the significance of humification mechanisms based solely on aliphatics. The precursors may be carbohydrates, which may be transformed by the effects of fire or catalytic dehydration reactions in soil. Furthermore, humic-type structures may be formed through the condensation of unsaturated fatty acids or the alteration of aliphatic biomacromolecules, such as cutins, suberins, and non-hydrolysable plant polyesters. In addition to the intrinsic value of understanding the potential for carbon sequestration in diverse soil types, biogeochemical models of the carbon cycle necessitate the assessment of the total quantity, nature, provenance, and resilience of the sequestered organic matter. This emphasises the necessity of applying specific techniques to gain insights into their molecular structures. The application of appropriate analytical techniques to soil organic matter, including sequential chemolysis or thermal degradation combined with isotopic analysis and high-resolution mass spectrometry, derivative spectroscopy (visible and infrared), or ¹³C magnetic resonance after selective degradation, enables the simultaneous assessment of the concurrent biophysicochemical stabilisation mechanisms of C in soils. Full article

This study investigates the antioxidant, antimicrobial, and antitumor activities of Taraxacum officinale (Dandelion) and Artemisia annua (Sweet Wormwood) extracts, along with their role in the green synthesis of gold (AuNPs) and silver nanoparticles (AgNPs). Bioreduction was achieved using aqueous and ethanolic extracts (100 mg/mL), enabling solvent-dependent comparisons. Nanoparticles were characterized using ultraviolet–visible spectroscopy (UV–Vis), fluorescence spectroscopy, scanning electron microscopy (SEM), dynamic light scattering (DLS), high-resolution transmission electron microscopy (HRTEM), and zeta potential analysis. Each technique revealed complementary aspects of nanoparticle morphology, size, and stability, with UV–Vis indicating aggregation states and DLS confirming solvent-related size variation even at 3–5% ethanol. Gold nanoparticles synthesized from Dandelion showed strong antibacterial activity against Staphylococcus aureus, while silver nanoparticles from both plants were effective against Escherichia coli. Cytotoxicity assays indicated that silver nanoparticles obtained from ethanolic Dandelion extract containing 3% ethanol in aqueous solution (AgNPsE_ETOH3%-D) significantly reduced LoVo (p = 4.58 × 10⁻³) and MDA-MB-231 (p = 7.20 × 10⁻⁵) cell viability, with high selectivity indices (SI), suggesting low toxicity toward normal cells. Gold nanoparticles synthesized from aqueous Dandelion extract (AuNPsEaq-D) also showed favorable SI values (2.16 for LoVo and 8.41 for MDA-MB-231). Although some formulations demonstrated lower selectivity (SI < 1.5), the findings support the therapeutic potential of these biogenic nanoparticles. Further in vivo studies and pharmacokinetic evaluations are required to validate their clinical applicability. Full article

Complex oxides with the general formula Gd₂(Ti_1−xZr_x)₂O₇ are promising candidates for radioactive waste immobilization due to their capacity to withstand radiation by dissipating part of the free energy driving defect creation and phase transitions. In this study, samples with varying zirconium content (xZr = 0.00, 0.15, 0.25, 0.375, 0.56, 0.75, 0.85, 1.00) were synthesized via the sol–gel method and thermally treated at 500 °C to obtain nanosized powders mimicking the defective structure of irradiated materials. Synchrotron-based techniques were employed to investigate their structural properties: High-Resolution X-ray Powder Diffraction (HR-XRPD) was used to assess long-range structure, while Pair Distribution Function (PDF) analysis and Extended X-ray Absorption Fine Structure (EXAFS) spectroscopy provided insights into the local structure. HR-XRPD data revealed that samples with low Zr content (xZr ≤ 0.25) are amorphous. Increasing Zr concentration led to the emergence of a crystalline phase identified as defective fluorite (xZr = 0.375, 0.56). Samples with the highest Zr content (xZr ≥ 0.75) were fully crystalline and exhibited only the fluorite phase. The experimental G(r) functions of the fully crystalline samples in the low r range are suitably fitted by the Weberite structure, mapping the relaxations induced by structural disorder in defective fluorite. These structural insights informed the subsequent EXAFS analysis at the Zr-K and Gd-L₃ edges, confirming the splitting of the cation–cation distances associated with different metal species. Moreover, EXAFS provided a local structural description of the amorphous phases, identifying a consistent Gd-O distance across all compositions. Full article

Bioactive glasses are known for their surface reactivity and ability to bond with bone tissue through the formation of hydroxyapatite. This study investigates the effects of substituting ultrapure water with natural geothermal waters from the Azores in the sol–gel synthesis of 45S5 and MgO-modified bioglasses. Using high-resolution X-ray photoelectron spectroscopy (XPS), we examined how the mineral composition of the waters influenced the chemical environment and network connectivity of the glass surface. The presence of trace ions, such as Mg²⁺, Sr²⁺, Zn²⁺, and B³⁺, altered the silicate structure, as evidenced by binding energy shifts and peak deconvolution in O 1s, Si 2p, P 2p, Ca 2p, and Na 1s spectra. Thermal treatment further promoted polymerization and reduced hydroxylation. Our findings suggest that mineral-rich waters act as functional agents, modulating the reactivity and structure of bioactive glass surfaces in eco-sustainable synthesis routes. Full article

In this study, we introduce a high-resolution, high-speed thermal imaging technique using Raman spectroscopy to simultaneously measure the temperature of a substrate and a channel. By modifying the Raman spectrometer, we achieved a measurement speed faster than commercial spectrometers. This system demonstrated a sub-micron spatial resolution and the ability to measure the temperatures of the Si substrate and GaN channel simultaneously. During high-current operation, we observed significant self-heating in the GaN channel, with hotspots 100 °C higher than the surroundings, while the Si substrate showed an even temperature distribution. The ability to detect hotspots can help secure the reliability of devices through early failure analysis and can also be used for improvement research to reduce hotspots. These findings highlight the potential of this technique for early defect inspection and device improvement research. This study provides a novel and effective method for measuring the sub-micron resolution temperature distribution in devices, which can be applied to various semiconductor devices, including SiC-based power devices. Full article

The monolithic integration of III-V semiconductors with silicon (Si) is a critical step toward advancing optoelectronic and photonic devices. In this work, we present GaAs nanoheteroepitaxy (NHE) on Si nanotips using gas-source molecular beam epitaxy (GS-MBE). We discuss the selective growth of fully relaxed GaAs nanoislands on complementary metal oxide semiconductor (CMOS)-compatible Si(001) nanotip wafers. Nanotip wafers were fabricated using a state-of-the-art 0.13 μm SiGe Bipolar CMOS pilot line on 200 mm wafers. Our investigation focuses on understanding the influence of the growth conditions on the morphology, crystalline structure, and defect formation of the GaAs islands. The morphological, structural, and optical properties of the GaAs islands were characterized using scanning electron microscopy, high-resolution X-ray diffraction, and photoluminescence spectroscopy. For samples with less deposition, the GaAs islands exhibit a monomodal size distribution, with an average effective diameter ranging between 100 and 280 nm. These islands display four distinct facet orientations corresponding to the {001} planes. As the deposition increases, larger islands with multiple crystallographic facets emerge, accompanied by a transition from a monomodal to a bimodal growth mode. Single twinning is observed in all samples. However, with increasing deposition, not only a bimodal size distribution occurs, but also the volume fraction of the twinned material increases significantly. These findings shed light on the growth dynamics of nanoheteroepitaxial GaAs and contribute to ongoing efforts toward CMOS-compatible Si-based nanophotonic technologies. Full article

A previously undescribed cis-clerodane diterpenoid, diangelate solidagoic acid J (1), along with two known cis-clerodane diterpenoids, solidagoic acid C (2) and solidagoic acid D (3), as well as two known unsaturated monoacylglycerols, 1-linoleoyl glycerol (4) and 1-α-linolenoyl glycerol (5), were isolated and characterized from the n-hexane leaf extract of Solidago gigantea (giant goldenrod). Compounds 2–5 were identified first in this species, and compounds 4 and 5 are reported here for the first time in the Solidago genus. The bioassay-guided isolation procedure included thin-layer chromatography (TLC) coupled with a Bacillus subtilis antibacterial assay, preparative flash column chromatography, and TLC–mass spectrometry (MS). Their structures were elucidated via extensive spectroscopic and spectrometric techniques such as one- and two-dimensional nuclear magnetic resonance (NMR) spectroscopy and high-resolution tandem mass spectrometry (HRMS/MS). The antimicrobial activities of the isolated compounds were evaluated by a microdilution assay. All compounds exhibited weak to moderate antibacterial activity against the Gram-positive plant pathogen Clavibacter michiganensis, with MIC values ranging from 17 to 133 µg/mL, with compound 5 being the most potent. Only compound 1 was active against Curtobacterium flaccumfaciens pv. flaccumfaciens, while compound 3 demonstrated a weak antibacterial effect against B. subtilis and Rhodococcus fascians. Additionally, the growth of B. subtilis and R. fascians was moderately inhibited by compounds 1 and 5, respectively. None of the tested compounds showed antibacterial activity against Gram-negative Pseudomonas syringae pv. tomato and Xanthomonas arboricola pv. pruni. No bactericidal activity was observed against the tested microorganisms. Compounds 2 and 3 displayed weak antifungal activity against the crop pathogens Bipolaris sorokiniana and Fusarium graminearum. Our results demonstrate the efficacy of bioassay-guided strategies in facilitating the discovery of novel bioactive compounds. Full article

Real-time, high-resolution monitoring of chemically diverse water pollutants remains a critical challenge for smart water management. Here, we report a fully integrated, multi-modal nano-sensor array, combining graphene field-effect transistors, Ag/Au-nanostar surface-enhanced Raman spectroscopy substrates, and CdSe/ZnS quantum dot fluorescence, coupled to an edge-deployable CNN-LSTM architecture that fuses raw electrochemical, vibrational, and photoluminescent signals without manual feature engineering. The 45 mm × 20 mm microfluidic manifold enables continuous flow-through sampling, while 8-bit-quantised inference executes in 31 ms at <12 W. Laboratory calibration over 28,000 samples achieved limits of detection of 12 ppt (Pb²⁺), 17 pM (atrazine) and 87 ng L⁻¹ (nanoplastics), with R² ≥ 0.93 and a mean absolute percentage error <6%. A 24 h deployment in the Cherwell River reproduced natural concentration fluctuations with field R² ≥ 0.92. SHAP and Grad-CAM analyses reveal that the network bases its predictions on Dirac-point shifts, characteristic Raman bands, and early-time fluorescence-quenching kinetics, providing mechanistic interpretability. The platform therefore offers a scalable route to smart water grids, point-of-use drinking water sentinels, and rapid environmental incident response. Future work will address sensor drift through antifouling coatings, enhance cross-site generalisation via federated learning, and create physics-informed digital twins for self-calibrating global monitoring networks. Full article

Potassium (K), a critical macronutrient for the growth and development of Korla fragrant pear (Pyrus sinkiangensis Yu), plays a pivotal regulatory role in sugar-acid metabolism. Furthermore, K exhibits a highly specific response in near-infrared (NIR) spectroscopy compared to elements such as nitrogen (N) and phosphorus (P). Given its fundamental impact on fruit quality parameters, the development of rapid and non-destructive techniques for K determination is of significant importance for precision fertilization management. By measuring leaf potassium content at the fruit setting, expansion, and maturity stages (decreasing from 1.60% at fruit setting to 1.14% at maturity), this study reveals its dynamic change pattern and establishes a high-precision prediction model by combining near-infrared spectroscopy (NIRS) with machine learning algorithms. “Near-infrared spectroscopy coupled with machine learning can enable accurate, non-destructive monitoring of potassium dynamics in Korla pear leaves, with prediction accuracy (R²) exceeding 0.86 under field conditions.” We systematically collected a total of 9000 leaf samples from Korla fragrant pear orchards and acquired spectral data using a benchtop near-infrared spectrometer. After preprocessing and feature extraction, we determined the optimal modeling method for prediction accuracy through comparative analysis of multiple models. Multiplicative scatter correction (MSC) and first derivative (FD) are synergistically employed for preprocessing to eliminate scattering interference and enhance the resolution of characteristic peaks. Competitive adaptive reweighted sampling (CARS) is then utilized to screen five potassium-sensitive bands, specifically in the regions of 4003.5–4034.35 nm, 4458.62–4562.75 nm, and 5145.15–5249.29 nm, among others, which are associated with O-H stretching vibration and changes in water status. A comparison between random forest (RF) and BP neural network indicates that the MSC + FD–CARS–BP model exhibits the optimal performance, achieving coefficients of determination (R²) of 0.96% and 0.86% for the training and validation sets, respectively, root mean square errors (RMSE) of 0.098% and 0.103%, a residual predictive deviation (RPD) greater than 3, and a ratio of performance to interquartile range (RPIQ) of 4.22. Parameter optimization revealed that the BPNN model achieved optimal stability with 10 neurons in the hidden layer. The model facilitates rapid and non-destructive detection of leaf potassium content throughout the entire growth period of Korla fragrant pears, supporting precision fertilization in orchards. Moreover, it elucidates the physiological mechanism by which potassium influences spectral response through the regulation of water metabolism. Full article

This work presents a novel approach to investigating epitaxial GaAsN layers and GaAsN-based p-i-n solar cell structures using light-assisted scanning capacitance microscopy (SCM) and spectroscopy. Due to the technological challenges in growing high-quality GaAsN with controlled nitrogen incorporation, the epitaxial layers often exhibit inhomogeneity in their opto-electrical properties. By combining localized cross-section SCM measurements with wavelength-tunable optical excitation (800–1600 nm), we resolved carrier concentration profiles, internal electric fields, and deep-level transitions across the device structure at a nanoscale resolution. A comparative analysis between electrochemical capacitance–voltage (EC-V) profiling and photoluminescence spectroscopy confirmed multiple localized transitions, attributed to compositional fluctuations and nitrogen-induced defects within GaAsN. The SCM method revealed spatial variations in energy states, including discrete nitrogen-rich regions and gradual variations in the nitrogen content throughout the layer depth, which are not recognizable using standard characterization methods. Our results demonstrate the unique capability of the photo-scanning capacitance microscopy and spectroscopy technique to provide spatially resolved insights into complex dilute nitride structures, offering a universal and accessible tool for semiconductor structures and optoelectronic devices evaluation. Full article

This review explores optical technologies for non-invasive glucose monitoring (NIGM) using aqueous humor (AH) as media, addressing the limitations of traditional invasive methods in diabetes management. It analyzes key techniques such as Raman spectroscopy, polarimetry, and mid- and near-infrared spectral methods, highlighting their respective challenges, alongside emerging hybrid approaches like photoacoustic spectroscopy and optical coherence tomography. Crucially, the practical realization of these optical methods for portable NIGM hinges on advanced instrumentation. Therefore, this review also details progress in compact NIR spectrometers. While conventional systems often lack suitability, significant advancements in on-chip technologies—including miniaturized dispersive spectrometers and various on-chip Fourier transform systems (e.g., spatial heterodyne, stationary wave integral, and temporally modulated FT systems)—utilizing integration platforms like SOI and SiN are promising. Such innovations offer the potential for high spectral resolution, large bandwidth, and miniaturization, which are essential for developing practical AH-based NIGM systems to improve diabetes care. Full article

The semi-synthesis of the (5R,7R,11bR)-9-(di(1H-indol-3-yl)methyl)-4,4,7,11b-tetramethyl-1,2,3,4,4a,5,6,6a,7,11,11a,11b-dodecahydrophenanthro[3,2-b]furan-5-yl acetate was performed via a pseudo-multicomponent reaction involving a double Friedel–Crafts alkylation between the natural product-derived aldehyde 6β-acetoxyvouacapane and the corresponding indole. The transformation was carried out under solvent-free mechanochemical conditions using mortar and pestle grinding, with ZnCl₂ as the catalyst. Structural elucidation of the target compound was accomplished using 1D and 2D NMR spectroscopy (¹H, ¹³C, COSY, HSQC, and HMBC), FT-IR, and high-resolution mass spectrometry (HRMS). Full article

Be stars are characterized by the presence of a circumstellar Keplerian disk formed from material ejected from the rapidly rotating stellar surface. This article presents recent observational and theoretical progress on two central aspects of this phenomenon: the mechanisms driving mass loss, and the fate of the ejected material. Using simultaneous TESS photometry and ground-based spectroscopy, we examine the short-term variability associated with discrete mass ejection events, or “flickers”, and review strong evidence linking them to pulsational activity near the stellar surface. Complementary 3D hydrodynamic simulations reproduce key observational signatures and establish that disk formation requires compact and asymmetric ejection sites with sufficient angular momentum to overcome re-accretion. In systems with binary companions, new high-resolution simulations resolve the outer disk for the first time and identify five dynamically distinct regions, including a circumsecondary disk and a circumbinary spiral outflow. Together, these results provide a coherent framework that traces the full life cycle of disk material from pulsation-driven ejection near the stellar surface to its final destination, whether re-accreted by the companion or lost from the system entirely. Full article