Search Results (1,271)

Rising volumes of textile waste necessitate the development of more efficient recycling systems, with a primary focus on the optimization of sorting technologies. Near-infrared (NIR) spectroscopy is a state-of-the-art method for fiber identification; however, its accuracy in quantifying textile blends, particularly common polyester/cotton blend textiles, still requires refinement. This study explores the potential and limitations of NIR spectroscopy for quantifying cotton content in post-consumer textiles. A lab-scale NIR sorter and a handheld NIR spectrometer in complementary wavelength ranges were applied to a diverse range of post-consumer textile samples to test model accuracies. Results show that the commonly assumed 10% accuracy threshold in industrial sorting can be exceeded, especially when excluding textiles with <35% cotton content. Identifying and excluding the range of non-linearity significantly improved the model’s performance. The final models achieved an RMSEP of 6.6% and bias of −0.9% for the NIR sorter and an RMSEP of 3.1% and bias of −0.6% for the handheld NIR spectrometer. This study also assessed how textile characteristics—such as color, structure, product type, and alkaline treatment—affect spectral behavior and model accuracy, highlighting their importance for refining quantification when high-purity inputs are needed. By identifying current limitations and potential sources of errors, this study provides a foundation for improving NIR-based models. Full article

Carbon monoxide (CO) is a major toxic gas emitted from vehicle exhaust, industrial processes, and incomplete fuel combustion, posing serious environmental and health risks. Catalytic oxidation of CO into less harmful CO₂ is an effective strategy to reduce these emissions. In this study, we investigated the catalytic performance of platinum (Pt) single atoms doped on C₃N monolayers with various vacancy defects, including single carbon (C_V) and nitrogen (N_V) vacancies, using density functional theory (DFT) calculations. Our results demonstrate that Pt@N_V-C₃N exhibited the most favorable catalytic properties, with the highest O₂ adsorption energy (−3.07 eV). This performance significantly outperforms Pt atoms doped at other vacancies. It can be attributed to the strong binding between Pt and nitrogen vacancies, which contributes to its excellent resistance to Pt aggregation. CO oxidation on Pt@N_V-C₃N proceeds via the Eley–Rideal (ER2) mechanism with a low activation barrier of 0.41 eV for the rate-determining step, indicating high catalytic efficiency at low temperatures. These findings suggest that Pt@N_V-C₃N is a promising candidate for CO oxidation, contributing to developing cost-effective and environmentally sustainable catalysts. The strong binding of Pt atoms to the nitrogen vacancies prevents aggregation, ensuring the stability and durability of the catalyst. The kinetic modeling further revealed that the ER2 mechanism offers the highest reaction rate constants over a wide temperature range (273–700 K). The low activation energy barrier also facilitates CO oxidation at lower temperatures, addressing critical challenges in automotive and industrial pollution control. This study provides valuable theoretical insights for designing advanced single-atom catalysts for environmental remediation applications. Full article

In this paper, the accuracy of basic and advanced spiral inductor models for gallium nitride (GaN) integrated inductors is evaluated. Specifically, the experimental measurements of geometrically scaled circular spiral inductors, fabricated in a radio frequency (RF) GaN-on silicon technology, are exploited to estimate the errors of two lumped geometrically scalable models, i.e., a simple π-model with seven components and an advanced model with thirteen components. The comparison is performed by using either the standard performance parameters, such as inductance (L), quality factor (Q-factor), and self-resonance frequency (SRF), or the two-port scattering parameters (S-parameters). The comparison reveals that despite a higher complexity, the developed advanced model achieves a significant reduction in SRF percentage errors in a wide range of geometrical parameters, while enabling an accurate estimation of two-port S-parameters. Indeed, the correct evaluation of both SRF and two-port S-parameters is crucial to exploit the model in an actual circuit design environment by properly setting the inductor geometrical parameters to optimize RF performance. Full article

Sin Nombre virus (SNV) is the main causative agent of hantavirus cardiopulmonary syndrome (HCPS) in North America. SNV is transmitted via environmental biological aerosols (bioaerosols) produced by infected deer mice (Peromyscus maniculatus). It is similar to other viruses that have environmental transmission routes rather than a person-to-person transmission route, such as avian influenza (e.g., H5N1) and Lassa fever. Despite the lack of person-to-person transmission, these viruses cause a significant public health and economic burden. However, due to the lack of targeted pharmaceutical preventatives and therapeutics, the recommended approach to prevent SNV infections is to avoid locations that have a combination of low foot traffic, receive minimal natural sunlight, and where P. maniculatus may be found nesting. Consequently, gaining insight into the SNV bioaerosol decay profile is fundamental to the prevention of SNV infections. The Biological Aerosol Reaction Chamber (Bio-ARC) is a flow-through system designed to rapidly expose bioaerosols to environmental conditions (ozone, simulated solar radiation (SSR), humidity, and other gas phase species at stable temperatures) and determine the sensitivity of those particles to simulated ambient conditions. Using this system, we examined the bioaerosol stability of SNV. The virus was found to be susceptible to both simulated solar radiation and ozone under the tested conditions. Comparisons of decay between the virus aerosolized in residual media and in a mouse bedding matrix showed similar results. This study indicates that SNV aerosol particles are susceptible to inactivation by solar radiation and ozone, both of which could be implemented as effective control measures to prevent disease in locations where SNV is endemic. Full article

Vertical GaN P-i-N diodes exhibit excellent high-voltage performance, fast switching speed, and low conduction losses, making them highly attractive for power applications. However, their breakdown voltage is severely constrained by electric field crowding at device edges. Using silvaco tcad (2019) tools, this work systematically evaluates multiple edge termination techniques, including deep-etched mesa, beveled mesa, and field-plate configurations with both vertical and inclined mesa structures. We present an optimized multi-drift-layer GaN P-i-N diode incorporating field-plate termination and analyze its electrical performance in detail. This study covers forward conduction characteristics including on-state voltage, on-resistance, and their temperature dependence, reverse breakdown behavior examining voltage capability and electric field distribution under different temperatures, and switching performance addressing both forward recovery phenomena, i.e., voltage overshoot and carrier injection dynamics, and reverse recovery characteristics including peak current and recovery time. The comprehensive analysis offers practical design guidelines for developing high-performance GaN power devices. Full article

Background: Allergic rhinitis (AR) is a prevalent allergic disorder characterized by a complex pathogenesis. Drawing on traditional Chinese medicine theory and contemporary pharmacological principles, this study developed an inhalation-based herbal formulation, ZHW, to explore a novel non-invasive therapeutic approach. Objective: To investigate the therapeutic effects of ZHW on AR and elucidate its underlying mechanisms and potential targets through an integrated analysis of network pharmacology and proteomics. Materials and Methods: The volatile components of ZHW were analyzed by gas chromatography–mass spectrometry (GC-MS). The mouse model of AR was induced by OVA sensitization. The therapeutic efficacy of ZHW was assessed based on nasal symptom scores, histopathological examination, and inflammatory cytokine levels. Furthermore, the underlying mechanisms and potential targets of ZHW were investigated through integrated network pharmacology and proteomics analyses. Results: GC-MS analysis identified 39 bioactive compounds in ZHW. Inhalation treatment with ZHW demonstrated significant anti-allergic effects in OVA-sensitized mice, as evidenced by (1) reduced sneezing frequency and nasal rubbing behaviors; (2) decreased serum levels of IL-4, histamine, and OVA-specific IgE; (3) attenuated IL-4 concentrations in both nasal lavage fluid and lung tissue; (4) diminished nasal mucosal thickening; and (5) suppression of inflammatory cell infiltration. Integrated network pharmacology and proteomics analyses indicated that ZHW’s therapeutic effects were mediated through the modulation of multiple pathways, including the PI3K-Akt signaling pathway, the B cell receptor signaling pathway, oxidative phosphorylation, and the FcεRI signaling pathway. Key molecular targets involved Rac1, MAPK1, and SYK. Molecular docking simulations revealed strong binding affinities between ZHW’s primary bioactive constituents (linalool, levomenthol, linoleic acid, Linoelaidic acid, and n-Valeric acid cis-3-hexenyl ester) and these target proteins. Conclusions: The herbal formulation ZHW demonstrates significant efficacy in alleviating allergic rhinitis symptoms through multi-target modulation of key signaling pathways, including PI3K-Akt- and FcεRI-mediated inflammatory responses. These findings substantiate ZHW’s therapeutic potential as a novel, non-invasive treatment for AR and provide a strong basis for the development of new AR therapies. Future clinical development will require systematic safety evaluation to ensure optimal therapeutic outcomes. Full article

Gallium nitride (GaN) enhancement-mode high-electron-mobility transistors ( E-HEMTs) deliver superior performance compared to traditional silicon (Si) and silicon carbide (SiC) counterparts. Their faster switching speeds, lower on-state resistances, and higher operating frequencies enable more efficient and compact power converters. However, their integration into high-power applications is limited by critical reliability concerns, particularly regarding their short-circuit (SC) withstand capability and overvoltage (OV) resilience. GaN devices typically exhibit SC withstand times of only a few hundred nanoseconds, needing ultrafast protection circuits, which conventional desaturation (DESAT) methods cannot adequately provide. Furthermore, their high switching transients increase the risk of false activation events. The lack of avalanche capability and the dynamic nature of GaN breakdown voltage exacerbate issues related to OV stress during fault conditions. Although SC-related behaviour in GaN devices has been previously studied, a focused and comprehensive review of protection strategies tailored to GaN technology remains lacking. This paper fills that gap by providing an in-depth analysis of SC and OV failure phenomena, coupled with a critical evaluation of current and next-generation protection schemes suitable for GaN-based high-power converters. Full article

The efficient simultaneous removal of NO_x and CO from sintering flue gas under low-temperature conditions (110–180 °C) in iron and steel enterprises remains a significant challenge in the field of environmental catalysis. In this study, we present an innovative strategy to enhance the performance of CuSmTi catalysts through silver modification, yielding a bifunctional system capable of oxygen structure regulation and demonstrating superior activity for the combined NH₃-SCR and CO oxidation reactions under low-temperature, oxygen-rich conditions. The modified AgCuSmTi catalyst achieves complete NO conversion at 150 °C, representing a 50 °C reduction compared to the unmodified CuSmTi catalyst (T_100% = 200 °C). Moreover, the catalyst exhibits over 90% N₂ selectivity across a broad temperature range of 150–300 °C, while achieving full CO oxidation at 175 °C. A series of characterization techniques, including XRD, Raman spectroscopy, N₂ adsorption, XPS, and O₂-TPD, were employed to elucidate the Ag-Cu interaction. These modifications effectively optimize the surface physical structure, modulate the distribution of acid sites, increase the proportion of Lewis acid sites, and enhance the activity of lattice oxygen species. As a result, they effectively promote the adsorption and activation of reactants, as well as electron transfer between active species, thereby significantly enhancing the low-temperature performance of the catalyst. Furthermore, in situ DRIFTS investigations reveal the reaction mechanisms involved in NH₃-SCR and CO oxidation over the Ag-modified CuSmTi catalyst. The NH₃-SCR process predominantly follows the L-H mechanism, with partial contribution from the E-R mechanism, whereas CO oxidation proceeds via the MvK mechanism. This work demonstrates that Ag modification is an effective approach for enhancing the low-temperature performance of CuSmTi-based catalysts, offering a promising technical solution for the simultaneous control of NO_x and CO emissions in industrial flue gases. Full article

The eGaN HEMT power devices face serious crosstalk problems when applied to high-frequency bridge circuits, thereby limiting the switching performance of these devices. To address this issue, a gate driver is proposed in this paper that can suppress both positive and negative crosstalk of eGaN HEMT power devices, offering the advantages of simple control and easy integration. The basic idea is to suppress positive crosstalk by constructing a negative voltage capacitor, and to suppress negative crosstalk by reducing the impedance of the gate loop. To verify the capability of the proposed gate driver, double-pulse and synchronous Buck test platforms are constructed. The experimental results clearly demonstrate that the proposed gate driver reduces the positive and negative crosstalk spikes by 2.03 V and 1.54 V, respectively, ensuring that the positive and negative crosstalk spikes fall within a safe operating range. Additionally, the turn-off speed of the device is enhanced, leading to a reduction in switching loss. Full article

The initial surface reaction of gallium nitride (GaN) grown by atomic layer deposition (GaN-ALD) was investigated using density functional theory (DFT) calculations. Trimethylgallium (TMG) and ammonia (NH₃) were used as gallium (Ga) and nitrogen (N) precursors, respectively. DFT calculations at the B3LYP/6-311+G(2d,p) and 6-31G(d) levels were performed to compute relative energies and optimize chemical structures, respectively. TMG adsorption on Si₁₅H₁₈–(NH₂)₂ and Si₁₅H₂₀=(NH)₂ clusters was modeled, where –NH₂ and =NH surface species served as adsorption sites. The reaction mechanisms in the adsorption and nitridation steps were investigated. The results showed that TMG can adsorb on both surface adsorption sites. In the initial adsorption stage, TMG adsorbs onto =NH- and –NH₂-terminated Si(100) surfaces with activation energies of 1.11 and 2.00 eV, respectively, indicating that the =NH site is more reactive. During subsequent NH3 adsorption, NH₃ adsorbs onto the residual TMG on the =NH- and –NH₂-terminated surfaces with activation energies of approximately 2.00 ± 0.02 eV. The reaction pathways indicate that NH₃ adsorbs via similar mechanisms on both surfaces, resulting in comparable nitridation kinetics. Furthermore, this study suggests that highly reactive NH₂⁻ species generated in the gas phase from ionized NH₃ may help reduce the process temperature in the GaN-ALD process. Full article

Machine learning (ML) models are widely used to analyze the spatiotemporal impacts of agricultural practices on environmental sustainability, including the contribution to global greenhouse gas (GHG) emissions. Management practices, such as organic amendment applications, are critical pillars of Climate-smart agriculture (CSA) strategies that mitigate GHG emissions while maintaining adequate crop yields. This study investigated the critical threshold of soil moisture level associated with soil CO₂ emissions from organically amended plots using the classification and regression tree (CART) algorithm. Also, the study predicted the short-term soil CO₂ emissions from organically amended systems using soil moisture and weather variables (i.e., air temperature, relative humidity, and solar radiation) using multilinear regression (MLR) and generalized additive models (GAMs). The different organic amendments considered in this study are biochar (2268 and 4536 kg ha⁻¹) and chicken and dairy manure (0, 224, and 448 kg N/ha) under a sweet corn crop in the greater Houston area, Texas. The results of the CART analysis indicated a direct link between soil moisture level and the magnitude of CO₂ flux emission from the amended plots. A threshold of 0.103 m³m⁻³ was calculated for treatment amended by biochar level I (2268 kg ha⁻¹) and chicken manure at the N recommended rate (CXBX), indicating that if the soil moisture is less than the 0.103 m³m⁻³ threshold, then the median soil CO₂ emission is 142 kg ha⁻¹ d⁻¹. Furthermore, applying biochar at a rate of 4536 kg ha⁻¹ reduced the soil CO₂ emissions by 14.5% compared to the control plots. Additionally, the results demonstrate that GAMs outperformed MLR, exhibiting the highest performance under the combined effect of chicken and biochar. We conclude that quantifying soil moisture thresholds will provide valuable information for the sustainable mitigation of soil CO₂ emissions. Full article

Greenhouse gas (GHG) emissions evaluations from agroecosystems are critical, particularly as technology improves. Consistent GHG measurement methods are essential to the evaluation of GHG emissions. The objective of the study was to evaluate potential differences in gas-flux-determination (GFD) options and carbon dioxide (CO₂), methane (CH₄), and nitrous oxide (N₂O) fluxes and growing-season-long emissions estimates from furrow-irrigated cotton (Gossypium hirsutum) in southeast Arkansas. Four GFD methods were evaluated [i.e., linear (L) or exponential (E) regression models, with negative fluxes (WNF) included in the dataset or replacing negative fluxes (RNF)] over the 2024 growing season using a LI-COR field-portable chamber and gas analyzers. Exponential regression models were influenced by abnormal CO₂ and N₂O gas concentration data points, indicating the use of caution with E models. Season-long CH₄ emissions differed (p < 0.05) between the WNF (−0.51 kg ha⁻¹ season⁻¹ for L and−0.54 kg ha⁻¹ season⁻¹ for E) and RNF (0.01 kg ha⁻¹ season⁻¹ for L and E) GFD methods, concluding that RNF options over-estimate CH₄ emissions. Gas concentration measurements following chamber closure should remain under 300 s, with one concentration measurement obtained per second. The choice of GFD method needs careful consideration to result in accurate GHG fluxes and season-long emission estimates. Full article

Gallium oxide (Ga₂O₃), as a wide-bandgap semiconductor material, is highly expected to find extensive applications in optoelectronic devices, high-power electronics, gas sensors, etc. However, the photoelectric properties of Ga₂O₃ still need to be improved before its devices become commercially viable. As is well known, doping is an effective method to modulate the various properties of semiconductor materials. In this study, Zn–N co-doped Ga₂O₃ films with various doping concentrations were grown in situ on sapphire substrates by atomic layer deposition (ALD) at 250 °C, followed by post-annealing at 900 °C. The post-annealed undoped Ga₂O₃ film showed a highly preferential orientation, whereas with the increase in Zn doping concentration, the preferential orientation of Ga₂O₃ films was deteriorated, turning it into an amorphous state. The surface roughness of the Ga₂O₃ thin films is largely affected by doping. As a result of post-annealing, the bandgaps of the Ga₂O₃ films can be modulated from 4.69 eV to 5.41 eV by controlling the Zn–N co-doping concentrations. When deposited under optimum conditions, high-quality Zn–N co-doped Ga₂O₃ films showed higher transmittance, a larger bandgap, and fewer defects compared with undoped ones. Full article

The incidence of fatal anaphylaxis is increasing, but there is still no recognized “golden standard” for forensic diagnosis. Due to its non-specific symptoms, especially cardiovascular symptoms without cutaneous changes, it can easily be misdiagnosed as acute myocardial infarction. Here, we established rat models (n = 12) of fatal anaphylaxis (FA), acute myocardial infarction (AMI), and coronary atherosclerosis with anaphylaxis (CAA). The untargeted metabolomics of plasma and 16S rRNA sequencing of fecal matter was performed, and a random forest was used to identify potential biomarkers. Three metabolites (tryptophan, trans-3-indole acrylic acid, and imidazole acetic acid) and three microbial genera (g_Prevotellaceae_Ga6A1_group, g_UCG_008, and g_Eubacterium_hallii_group) were identified as potential biomarkers for distinguishing anaphylaxis and non-anaphylaxis. The classification model of plasma metabolites showed a much better discriminatory performance than that of microbial genus, serum IgE, and tryptase. The performance of the microbial genera was superior to the serum IgE but inferior to the serum tryptase. Forensic samples of fatal anaphylaxis and non-anaphylaxis deaths (n = 12) were collected for untargeted metabolomics detection. The results showed that among the three identified metabolic biomarkers, tryptophan has better stability in cadaveric blood samples. Its diagnostic performance (AUC = 87.1528) was superior to serum IgE and tryptase, making it more suitable as a postmortem biomarker of fatal anaphylaxis. Full article

Polynitrogen compounds have broad applications in the field of high-energy materials, making the exploration of two-dimensional polynitride materials with both novel properties and practical utility a highly attractive research challenge. Through global structure search methods and first-principles theoretical calculations at the Perdew–Burke–Ernzerhof (PBE) level of density functional theory (DFT), the globally minimum-energy configuration of a novel planar BeN₃ monolayer (tetr-2D-BeN₃) is predicted. This material exhibits a planar quasi-isotropic structure containing pentagonal, hexagonal, and dodecagonal rings, as well as “S”-shaped N6 polymeric units, exhibiting a high energy density of 3.34 kJ·g⁻¹, excellent lattice dynamic stability and thermal stability, an indirect bandgap of 2.66 eV (HSE06), high carrier mobility, and ultraviolet light absorption capacity. In terms of mechanical properties, it shows a low in-plane Young’s stiffness of 52.3–52.9 N·m⁻¹ and a high in-plane Poisson’s ratio of 0.55–0.56, indicating superior flexibility. Furthermore, its porous structure endows it with remarkable selectivity for hydrogen (H₂) and argon (Ar) gas separation, achieving a maximum selectivity of up to 10²³ (He/Ar). Therefore, the tetr-2D-BeN₃ monolayer represents a multifunctional two-dimensional polynitrogen-based energetic material with potential applications in energetic materials, flexible semiconductor devices, ductile materials, ultraviolet photodetectors, and other fields, thereby expanding the design possibilities for polynitride materials. Full article