Search Results (2,531)

Conductive filaments for Material Extrusion Additive Manufacturing (MEX) can enable low-cost fabrication of functional parts with embedded electrical features. However, systematic studies on process-dependent electrical properties like apparent resistivity and repeatability are limited, and the post-printing stability of the electrical response is not commonly addressed. This study evaluates the influence of printing temperature, printing speed and layer height on the apparent resistivity, specimen-to-specimen repeatability and time-dependent drift of a commercial carbon black-filled conductive PLA filament (ProtoPasta). The novelty of the study consists of evaluating not only the initial apparent resistivity, but also the repeatability between specimens and the post-print drift of apparent resistivity over a 0–50 h interval. The filament was investigated using three printing temperatures (210–230 °C), two printing speeds (60–80 mm/s) and three layer heights (0.2–0.4 mm), with three replicates per configuration. Apparent resistivity ranged between 0.156 and 0.205 kΩ·mm at t0 and between 0.162 and 0.222 kΩ·mm at t50. Multifactorial ANOVA and main-effects analyses showed that the printing temperature was the main factor affecting mean apparent resistivity at both t0 and t50. Higher temperature reduced apparent resistivity, most likely due to improved polymer flow, inter-bead/inter-layer bonding and conductive-network continuity. Printing speed had no significant main effect on the mean apparent resistivity or drift within the tested range. Repeatability depended on the parameter configuration and measurement time, with variability increasing after 24 h and then becoming mainly dependent on layer height. Drift analysis showed a significant main effect of layer height and a significant layer height × temperature interaction, with the largest increase at 0.3 mm. These results show that parameter selection for conductive MEX parts should consider both the initial resistivity level and post-print stability over time. Full article

Coal spontaneous combustion in gob areas is a major disaster endangering safe production in underground coal mines, and accurate prediction of carbon monoxide (CO), the core signature gas of coal oxidation, is critical for early warning and targeted prevention of mine fire disasters. However, CO concentration in gob areas is governed by complex gas–solid thermal–chemical multi-field coupling, presenting strong nonlinear characteristics. Traditional numerical methods suffer from prohibitive computational cost, purely data-driven models have inherent black-box defects, and conventional Physics-Informed Neural Networks (PINNs) require explicit full governing equations, which are hard to establish for such complex systems. This paper first proposes a Physics-Informed Modified Kolmogorov–Arnold Network (PIM-KAN), which deeply integrates domain physical knowledge with KAN architecture via a physics encoding layer, a residual-modified KAN layer, a multi-physics attention mechanism, and a multi-term physical consistency constraint framework. Experiments on 3125 real coal mine field samples show that the PIM-KAN achieves R² = 0.9965 and RMSE = 0.9290 ppm, reducing RMSE by 19.5% compared with MLP, and outperforming all baseline models. Ablation studies confirm the significant contribution of each innovation module, and attention weight analysis is highly consistent with Arrhenius reaction kinetics, verifying its superior prediction accuracy, physical consistency and intrinsic interpretability. Full article

Surface stain contamination poses a critical barrier to the automated, high-precision fiber identification required for industrial-scale waste textile recycling. In this study, a dataset comprising 120 physical specimens (yielding 1200 regions of interest, ROIs) across 12 contamination categories was constructed by contaminating cotton, polyester, and poly-cotton blend textiles with carbon black, protein, and oil stains. The spectral interference effects of stains—including baseline drift and spectral overlapping induced by physical shielding and chemical absorption—were systematically analyzed. To identify the optimal classification pipeline, three mathematical preprocessing methods (First Derivative, FD; Standard Normal Variate, SNV; and Multiplicative Scatter Correction, MSC) were evaluated alongside Support Vector Machine (SVM) and One-Dimensional Convolutional Neural Network (1D-CNN) models. Results show that among the SVM-based pipelines, the FD-SVM model effectively resolves overlapping absorption peaks, achieved an average accuracy of 98.17% ± 1.33%, but remains highly dependent on mathematical preprocessing. In contrast, the 1D-CNN model employing a progressive stacking architecture of multi-scale convolutional kernels attains a highly robust mean accuracy of 99.58% ± 0.56% under a strict specimen-level 10-fold cross-validation. It achieves this by directly utilizing radiometrically calibrated raw spectra, thereby effectively bypassing manual spectral feature engineering. These findings demonstrate that Hyperspectral Imaging coupled with end-to-end deep learning provides a feasible and industrially deployable solution for simultaneous stain detection and fiber identification in waste textile sorting. Full article

Fine particulate matter (PM_2.5) composition, rather than mass alone, plays a critical role in determining toxicity and health impact. This study examined short-term associations between daily PM_2.5 constituents—black carbon (BC), nitrate (NO₃⁻), ammonium (NH₄⁺), and trace elements—and cardiopulmonary hospital admissions in Makkah, Saudi Arabia. Twelve months of constituent data from the Alharam monitoring site were linked to Herra hospital admissions for cardiovascular (CVD) and pulmonary diseases, stratified by visit type, age, and sex. Negative-binomial generalized linear models estimated adjusted relative risks (aRRs) per interquartile range increase in each constituent, controlling for meteorology, seasonality, and temporal trends. Mean PM_2.5 was 113.6 µg/m³; BC, sulfur, NO₃⁻, and NH₄⁺ dominated the fine fraction. Crustal elements were strongly intercorrelated (r > 0.9), while BC, lead (Pb), and nickel (Ni) showed moderate correlations (r ≈ 0.4–0.6), suggesting shared anthropogenic origins. BC increased CVD emergency/outpatient visits by 18% (aRR = 1.18; 95% CI: 1.08–1.29) and inpatient admissions by 25% (aRR = 1.25; 95% CI: 1.07–1.46). Ni and sulfur were also significant predictors; crustal elements were not. Multi-pollutant models confirmed BC and Pb as independent predictors (aRR = 1.19; 95% CI: 1.02–1.38). Effects were strongest among older adults aged 45–65 at lag 0–2 days. These findings highlight the need for emission controls targeting traffic and industrial combustion sources. Full article

This study provides the first comprehensive assessment of microplastic (MP) contamination within oyster bed ecosystems of the Kingdom of Bahrain. Sediment, water, and oyster samples were collected from six sites representing diverse environmental conditions. Raman spectroscopy identified the presence of 12 distinct polymer types, with polypropylene (PP), polyurethane (PU), poly(ethylene terephthalate)/diamine/multi-walled carbon nanotube (PET/diamine/MWCNT), and fluorinated ethylene propylene (FEP) being the most prevalent. MPs occurred predominantly as fragments, films, and pellets, with black being the most common color across all matrices. MP abundances ranged from 750 to 1850 MPs/kg dry weight in sediments, 2100–9600 MPs/L in water, and 1.78–5.25 MPs/individual in oysters, with particles (<50 µm) most frequent in oyster tissues. Although spatial variation was evident across regions, detected polymers included types associated with known ecotoxicological risks. No significant correlation was observed between sediment grain size and MP abundance, suggesting that additional hydrodynamic or anthropogenic factors may influence MP distribution. Overall, this study provides critical baseline data on MP contamination in Bahrain’s marine environments and highlights the need for continued monitoring to assess potential risks to marine ecosystems and seafood safety. It also contributes to the limited understanding of MPs in the Arabian Gulf, informing future monitoring, conservation and policy initiatives that support long-term environmental sustainability. Full article

This study investigated the effects of different straw return practices—no-tillage with straw mulching (SM), shallow tillage with straw incorporation (SS), and deep tillage with straw incorporation (DS)—on the content and structural characteristics of soil water-soluble organic carbon (WSOC) under a maize–soybean rotation in the black soil region in the Northeast of China. Compared with SM, SS and DS increased WSOC content by 39.0% and 28.8% in the 0~20 cm layer (p < 0.05), and by 28.4% and 8.5% in the 20–40 cm layer, respectively. Deep tillage combined with straw return reduced the WSOC/SOC ratio. The DS treatment exhibited the highest levels under maize straw incorporation, while SM treatment showed the highest levels under soybean straw incorporation. Spectral indices in both maize and soybean seasons—including the fluorescence index (FI, ranging from 1.53 to 1.57 in the maize season and from 1.53 to 1.67 in the soybean season), biological index (BIX, ranging from 0.84 to 1.79 in the maize season and from 0.61 to 0.74 in the soybean season), and humification index (HIX, ranging from 0.51 to 0.79 in the maize season and from 0.84 to 0.97 in the soybean season)—collectively indicated that WSOC predominantly consisted of microbially processed organic matter with a low degree of humification. PARAFAC modeling resolved two fluorescent components in maize season: C1 (humic acid-like substances, accounting for 34.8–54.9%) and C2 (Tryptophan-like substance, accounting for 45.1–65.2%), and two components in the soybean season: C1 (humic-like substances, 51.0–53.7%), and C2 (Fulvic acid-like substance 46.3–49.0%). Overall, deep straw return promotes soil humification but increases the structural complexity of WSOC. This systematic investigation provides mechanistic insights into how straw return practices regulate the quantity and quality of labile carbon pools in agricultural ecosystems over time. Full article

While the association between criteria air pollutants and sleep duration is well-documented, evidence on the impact of fine particulate matter (PM_2.5) chemical components on sleep remains limited. This study investigated the effects of intermediate- (6-month) and long-term (2-year) exposure to PM_2.5 and its five major components—black carbon (BC), organic matter (OM), sulfate (SO₄²⁻), nitrate (NO₃⁻), and ammonium (NH₄⁺)—on nocturnal sleep and daytime napping duration. We included 19,505 participants aged ≥ 45 years from the China Health and Retirement Longitudinal Study (CHARLS, 2011–2018). Residential PM_2.5 and component concentrations were estimated via the Tracking Air Pollution in China dataset, and sleep data were collected through self-reported questionnaires. Linear mixed-effects models and quantile-based g-computation (qgcomp) were used to assess single- and multi-pollutant effects. Results showed that both intermediate- and long-term exposure to PM_2.5 components was associated with shorter nocturnal sleep and longer daytime napping. Subgroup analyses revealed greater susceptibility among rural residents, solid fuel users, and individuals without pensions. These findings emphasize the need for component-specific PM_2.5 control strategies and targeted public health interventions to reduce sleep-related health inequalities, especially in socioeconomically disadvantaged populations. Full article

Soil micro- and nanoplastic contamination is escalating globally, yet its potential to interfere with routine agrochemical analyses remains poorly quantified. Standard operating procedures (SOPs) were calibrated for natural soil matrices and may not account for synthetic, carbon-rich polymers. This controlled model study quantified the analytical sensitivity of FAO/GLOSOLAN/ISO standard procedures to polystyrene nanoparticle (50 nm) contamination across a 0–0.5% (w/w) gradient in a Luvic Chernozem. Key parameters—pH, soil carbon, total nitrogen (TN), cation exchange capacity (CEC), and clay fraction—were measured following standardized protocols. The Walkley–Black method exhibited a strong dose-dependent increase in measured SOC (r = 0.93), reflecting systematic overestimation due to dichromate co-oxidation of polymer matrix, likely facilitated by exothermic heating above polystyrene’s glass transition temperature. The Dumas method showed moderate correlation (r = 0.59) but higher replicate variability driven by small aliquot size and heterogeneous nanoparticle distribution. The pH measurements displayed non-linear responses and elevated variability at low doses, whereas TN, CEC, and clay content remained statistically stable. These findings demonstrate that nanoplastic contamination can introduce significant analytical artifacts in oxidation-based SOC determinations, potentially leading to misinterpretation of soil carbon trends. Given the single-soil, single-polymer design, results represent a system-specific proof of analytical vulnerability rather than a universally quantified bias. Laboratories analyzing potentially contaminated soils should exercise caution with wet-oxidation SOC data, and broader SOP revisions must await multi-soil, multi-polymer validation campaigns. Full article

Intermetallic compounds represent a highly promising class of materials for catalytic applications due to their tuneable structure, composition, and electronic properties. In this study, we report a series of carbon black-supported intermetallic Pt-Te and Pt-Zn nanoparticles synthesized via a novel and facile direct vapour–solid approach. Their catalytic performance toward the oxygen reduction reaction (ORR) in alkaline media was systematically investigated. Incorporation of Te or Zn into Pt/C significantly enhanced the intrinsic activity, as reflected by an increase in the limiting current density from −2.11 mA cm⁻² for Pt/C to up to −2.94 mA cm⁻² for Pt-Zn and −2.85 mA cm⁻² for Pt-Te systems, while maintaining similar half-wave potentials of 0.79 V vs. RHE and onset potentials around 0.90 V vs. RHE. This work provides a direct comparison of two intermetallic systems prepared under identical conditions, demonstrating how composition and crystal structure determine the catalytic activity and selectivity in the ORR. Full article

Reaction-bonded SiC (RBSC) ceramics exhibit limited hydrothermal corrosion resistance due to the presence of residual silicon. This study presents a strategy to enhance the corrosion resistance of RBSC through homogeneous incorporation of MoSi₂ and concurrent reduction in residual silicon content. Three material systems were fabricated via reactive melt infiltration: conventional RBSC with a SiC/C preform (SC), a SiC–MoSi₂ composite incorporating commercial Mo₂C powder via physical mixing (MC), and a SiC–MoSi₂ composite derived from a Mo₂C/C precursor synthesized by a molten salt method (MS). The Mo₂C/C composite synthesized at 1150 °C exhibited fine, uniformly distributed Mo₂C particles coated on carbon black, contrasting with the agglomerated distribution in commercial Mo₂C mixtures. During reactive sintering at 1600 °C, Mo₂C reacted with molten Si to form MoSi₂, reducing residual Si content. Sample MS achieved the lowest residual Si (8.77 ± 0.45 vol.%), followed by MC (12.43 ± 0.86 vol.%) and SC (19.17 ± 1.01 vol.%). All samples achieved near-full densification (open porosity < 0.1%), with bulk densities of 2.96 ± 0.05, 3.03 ± 0.03, and 3.07 ± 0.03 g/cm³ for SC, MC, and MS, respectively. Microstructurally, MS displayed homogeneous MoSi₂ dispersion, while MC showed partial MoSi₂ aggregation, and SC contained continuous residual Si regions. Hydrothermal corrosion tests at 345 °C and 15 MPa for 9 days demonstrated that corrosion resistance followed the order MS > MC > SC. After 9 days, weight loss was 22.3970 ± 1.2059 mg/cm² (SC), 17.6370 ± 0.8266 mg/cm² (MC), and 15.4347 ± 0.7807 mg/cm² (MS), with corrosion depths of 393.17 ± 27.46, 267.40 ± 24.44, and 224.60 ± 25.13 μm, respectively. The enhanced performance of MS arises from two synergistic factors: reduced residual Si minimizes large corrosion pores, while uniform distribution of MoSi₂ facilitates the formation of a stable, dissolution-resistant composite oxide layer composed of MoO₃ and SiO₂, in which MoO₃ restrains excessive dissolution of SiO₂ through a pinning effect. These findings demonstrate that combining residual Si reduction with homogeneous MoSi₂ incorporation via molten salt-synthesized precursors offers an effective strategy for improving hydrothermal corrosion resistance of reaction-bonded SiC-based materials for applications in high-temperature and high-pressure aqueous environments such as nuclear water reactors. Full article

This study investigated the influence of hydrocarbon feedstock composition evolved from slow pyrolysis of polypropylene (PP) and polystyrene (PS) and plasma gas flow rate on the carbon black and hydrogen production yields and quality. The temperature distribution and feedstock flow within the carbon black formation zone with plasma were supplementarily modeled using computational fluid dynamics. TG-FTIR-GC/MS was employed to analyze thermal degradation patterns of plastics and to estimate the composition of volatile intermediates of plastics’ slow pyrolysis. Produced CB was characterized, encompassing physical, structural, and compositional properties using thermogravimetric analysis, CHNS analysis, scanning electron microscopy–energy dispersive spectroscopy, transmission electron microscopy, Brunauer-Emmett-Teller, and Raman spectroscopy. The results revealed that both feedstocks yield CB with comparable structural characteristics; however, PS-derived (aromatic-rich) volatiles produce significantly higher CB yields, whereas PP-derived (aliphatic) volatiles favor hydrogen formation. Differences in carbon structure were also observed, with PP-derived CB exhibiting a higher degree of graphitic ordering compared to the more disordered CB obtained from PS. The optimal flow rate of plasma gas was identified as 6.1 L/min. Increasing the flow rate to 7.2 L/min led to reduced conversion efficiency for PP-derived long-chain hydrocarbons. Overall, the findings demonstrate the potential of this approach for the co-production of high-quality carbon black and hydrogen from plastic waste. Full article

To investigate the effects of water-saving irrigation and different straw retention methods on soil CH₄ and N₂O emissions from paddy fields in cold regions and their potential underlying mechanisms, a field experiment was conducted in Qing’an City, Heilongjiang Province. Two water management regimes were set, combined with four straw retention treatments. The static chamber-gas chromatography method was used to monitor CH₄ and N₂O emission fluxes during the entire rice growth period. Meanwhile, soil pH, oxidation–reduction potential (Eh), dissolved oxygen (DO), and dynamic changes in carbon and nitrogen substrates were measured, and the global warming potential (GWP) and greenhouse gas emission intensity (GHGI) were comprehensively evaluated. The results showed that controlled irrigation significantly increased soil dissolved oxygen content and oxidation–reduction potential. Compared with conventional flooding irrigation, total CH₄ emission decreased by more than 50%, while N₂O emission increased by 1.5–2.5 times, exhibiting an obvious divergent correlation with the two gas emission fluxes. Among different straw retention methods, organic fertilizer returning and direct straw returning significantly promoted CH₄ emission by supplying easily decomposable organic carbon. In contrast, biochar, due to its stable carbon structure and favorable pore properties, inhibited CH₄ emission without significantly stimulating N₂O emission. The treatment of controlled irrigation combined with biochar returning (CB) achieved the lowest global warming potential and greenhouse gas emission intensity at 7230.82 kg CO₂-eq/hm² and 0.8054 kg CO₂-eq/kg, respectively, while maintaining high rice yield. Path analysis based on soil physicochemical properties and emission fluxes further revealed that Eh and DO were significantly negatively correlated with CH₄ emission but positively correlated with N₂O emission. Path inference from flux and substrate data indicated that carbon and nitrogen availability were the key factors limiting the denitrification process. In conclusion, the combined application of controlled irrigation and biochar returning can realize the synergistic effect of stable yield and emission reduction in cold-region paddy fields by improving soil aeration and regulating the transformation of carbon and nitrogen substrates, providing a scientific basis for establishing a green and low-carbon rice production technology system for black soil in cold regions. Full article

Conservation tillage has an influence on the cultivation and sustainable utilization of farmland. However, the microbial mechanism driving soil nutrient cycling in conservation tillage and its regulation pathway remain unclear. Based on a positioning experiment in black soil areas, this study systematically compared the effects of no-tillage (NT) and moldboard tillage (MT) combined with different straw returning amounts (straw non-returning, NS; straw half-returning, HS; straw full-returning, TS) on the composition of soil carbon (C), nitrogen (N) and phosphorus (P) and focused on the role of microbial community structure succession and functional changes in soil nutrient cycling. Microbial community remodeling driven by tillage measures was mainly regulated by C and N components. Bacterial modules 2 and 4 and fungal modules 1 and 2 were key for regulating the C, N and P cycle, of which 87 bacteria and 45 fungi taxa represented the core driving microorganisms. The total amount of no-tillage straw return reduced the formation and accumulation of labile organic carbon fractions by enriching yeast-like fungi and inhibiting the expression of complex organic matter decomposition genes. Tillage mainly promoted the accumulation of labile organic carbon fractions and nutrient release by regulating the bacterial community, while no-tillage straw returning promoted the accumulation of total organic carbon and organic nitrogen fixation by promoting the fungal community. This study revealed the biological pathway of conservation tillage that drives soil nutrient cycling by regulating key microbial communities. It also provides a microbiological basis for sustainable soil management in black soil areas. Full article

The polymer–filler interphase in filled elastomers is often represented by a single thickness, obscuring internal heterogeneity. Coupling coarse-grained molecular dynamics with dynamic mechanical analysis of EPDM/carbon-black compounds, we resolve a bimodal bound-rubber layer with a dense inner zone set by surface adsorption and a looser outer zone sustained by chain connectivity. Heating contracts the outer zone about twice as strongly as the inner zone (outer: 26.5%, 95% confidence interval 17.4–34.8%; inner: 13.3%). Per-layer mean-squared displacement analysis shows a modest mobility gradient between the 1–2 nm outer zone and the bulk. Dynamic mechanical analysis at 120–140 °C shows a flatter reinforcement factor at higher temperature, consistent with interphase-linked thermal contraction. Lengthening the chain at fixed filler loading markedly enlarges the bridging fraction and the cumulative excess thickness, signaling a transition from adsorption-limited to connectivity-limited reinforcement. These results show that a single interphase boundary can miss a dynamically active outer zone relevant to reinforcement and thermal aging in filled elastomers. Full article

Simultaneous quantification of ascorbic acid, dopamine, and uric acid is crucial for clinical diagnostics. Here, an electrochemical sensor was developed by modifying a glassy carbon electrode with a ternary composite of multi-walled carbon nanotubes, graphene, and Vulcan XC72 carbon black via a simple mixing method. The synergistic interaction of these carbon materials significantly increases the electroactive surface area and introduces defect-driven catalytic sites, enhancing electron transfer kinetics. The sensor enables interference-free simultaneous detection, exhibiting linear ranges of 100–1000 μM ascorbic acid, 5–50 μM dopamine, and 10–100 μM uric acid with sensitivities of 0.044, 0.47, and 0.95 μA μM⁻¹, respectively, and corresponding limits of detection of 34.1, 4.23, and 11.1 μM. The platform also demonstrated excellent stability, reproducibility, and anti-interference performance, with satisfactory recoveries in human urine samples. These results highlight the ternary composite sensor as a reliable and practical tool for multiplexed monitoring in complex physiological matrices. Full article