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This article, based on OMI data products, utilizes spatial distribution, ozone-sensitive control areas, Pearson correlation methods, and the Ben-MAP model to study the changes in ozone column concentration from 2018 to 2022, along with the influencing factors and the health of populations exposed to ozone. The findings suggest a spatial variation in the ozone column concentration within the study area, with an increasing trend observed from west to east and from south to north. Over time, the ozone column concentration exhibits an initial increase followed by a subsequent decrease, with the peak concentration observed in 2019 at 37.45 DU and the nadir recorded in 2022 at 33.10 DU. The monthly mean distribution exhibits an inverted V-shaped pattern during the warm season from April to September, with a peak in July (46.71 DU) and a trough in April (35.29 DU). The Hetao Plain Oasis area is primarily a NOx control area in sensitive control areas. The concentrations of O3 and precursor HCHO exhibited significant positive correlations with vegetation index and air temperature, while showing significant negative correlations with wind speed and air pressure. The precursor NO2, in contrast, exhibited a significant negative correlation with both the vegetation index and relative humidity. Based on the ground-based monitoring sites and analysis of human health benefits, the study area witnessed 1944.45 deaths attributed to warm season O3 exposure in 2018, with a subsequent reduction in premature deaths by 149.7, 588.2, and 231.75 for the years 2019 to 2021 respectively when compared to the baseline year. In 2021, the observed decrease in warm-season O3 concentration within that region compared to 2018 resulted in a significant reduction, leading to the prevention of 126 premature deaths.
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Monitoramento Ambiental , Ozônio , Humanos , Mortalidade Prematura , Ozônio/toxicidade , Estações do Ano , TemperaturaRESUMO
Climate change and air pollution are one of the global environmental problems. It is significant to grasp the air pollution situation of Western Europe in recent 10 years for its or the global pollution control. Based on the OMI tropospheric nitrogen dioxide (NO2) column density data, the spatial and temporal distribution characteristics, variation trend, transmission path, and influencing factors of NO2 in 15 countries in Western Europe from 2011 to 2022 are discussed in this paper. Meanwhile, the annual average spatial and temporal distribution in 2023 is predicted by the random forest (RF) model. The results showed that (1) the 12-year spatial distribution map showed an increasing trend from southwest to northeast, with the border area of the Netherlands and Germany and Milan as two high-value areas, and the overall trend over time was that the high-concentration area gradually shrank, the low-concentration area gradually expanded, and the annual average concentration gradually decreased. (2) The inter-month trend presents a "U" shape, with the mean NO2 pollution ranking in winter > autumn > spring > summer. (3) Natural factors are one of the reasons affecting NO2; for instance, NO2 pollution has a strong positive correlation with the lifted index, relative humidity, and wind speed and a moderately strong negative correlation with precipitable water and air temperature. (4) Exogenous atmospheric transport is another important factor affecting the change of NO2 pollution in Western Europe. The HYSPLIT model is used to analyze the backward trajectory of Milan, Italy, and Nijmegen, Netherlands, in the four seasons of 2022. Both are mainly influenced by westerly airflows, and therefore, the transport effect in the atmosphere brings air pollutants from westerly regions in the atmosphere.
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Poluentes Atmosféricos , Poluição do Ar , Dióxido de Nitrogênio/análise , Monitoramento Ambiental/métodos , Poluição do Ar/análise , Poluentes Atmosféricos/análise , Europa (Continente) , Material Particulado/análise , China , Estações do AnoRESUMO
The failure of bearings can have a significant negative impact on the safe operation of equipment. Recently, deep learning has become one of the focuses of RUL prediction due to its potent scalability and nonlinear fitting ability. The supervised learning process in deep learning requires a significant quantity of labeled data, but data labeling can be expensive and time-consuming. Cotraining is a semisupervised learning method that reduces the quantity of required labeled data through exploiting available unlabeled data in supervised learning to boost accuracy. This paper innovatively proposes a cotraining-based approach for RUL prediction. A CNN and an LSTM were cotrained on large amounts of unlabeled data to obtain a health indicator (HI), then the monitoring data were entered into the HI and the RUL prediction was realized. The effectiveness of the proposed approach was compared and analyzed against individual CNN and LSTM and the stacking networks SAE+LSTM and CNN+LSTM in the existing literature using RMSE and MAPE values on a PHM 2012 dataset. The results demonstrate that the RMSE and MAPE value of the proposed approach are superior to individual CNN and LSTM, and the RMSE value of the proposed approach is 54.72, which is significantly lower than SAE+LSTM (137.12), and close to CNN+LSTM (49.36). The proposed approach has also been tested successfully on a real-world task and thus has strong application value.
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Redes Neurais de ComputaçãoRESUMO
Nanoparticle-functionalized 2D material networks are promising for a wide range of applications, but in situ formation of nanoparticles is commonly challenged by rapid growth. Here, we demonstrate controlled synthesis of small and dispersed iron oxide nanoparticles on reduced graphene oxide (rGO) networks through rapid localized heating with microwaves with low-cost iron nitrate as the precursor. The strong coupling of the microwave radiation with the rGO network rapidly heats the network locally to decompose the iron nitrate and generate iron oxide nanoparticles, while cessation of microwaves leads to rapid cooling to minimize crystal growth. Small changes in the microwave reaction time (<1 min) led to very large changes in the iron oxide morphology. The solid-state microwave syntheses produced narrower nanoparticle size distribution than conventional heating. These results illustrate the potential of solid-state microwave syntheses to control the nanoparticle size on 2D materials through rapid localized heating under the microwave process conditions, which should be extendable to a variety of transition metal oxide-rGO systems.
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Microwave heating provides an efficient method to rapidly heat materials through interaction of microwaves with the media. Here, we demonstrate the rapid synthesis of mesoporous cobalt oxide films through the heating of the silicon substrate by microwaves. A non-sol-gel approach based on cobalt nitrate-citric acid complex cooperative assembly with a poly[methoxy poly(ethylene glycol)methacrylate]-block-poly(butyl acrylate) (PMPEGMA-b-PBA) block copolymer was used to fabricate the cobalt oxide through a cobalt carbonate intermediate. The time required to convert cobalt carbonate to cobalt oxide with the full removal of the PMPEGMA-b-PBA template can be decreased by two orders of magnitude with microwaves in comparison to standard heating in a furnace at 350 °C. At the highest microwave power examined (1500 W), this can be accomplished within 2 s, while >5 min is required at 350 °C in a furnace. At a microwave power of <400 W, there is insufficient energy to induce the transition from carbonate to oxide, but even at only 420 W, the oxide can be formed within 26 s. The rapid heating by the microwaves tends to increase the crystallinity and mean crystal size of the cobalt oxide within the mesoporous films. Despite the growth of larger average crystals, the pore size and porosity tend to be larger when the film is processed using microwaves. Higher microwave power leads to larger average crystals and average pore size. These results suggest that rapid processing to crystallize frameworks in mesoporous materials may allow for highly crystalline frameworks without loss of the templated mesostructure.
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Block copolymer templating enables the generation of well-defined pore sizes and geometries in a wide variety of frameworks, typically through evaporation-induced self-assembly (EISA). Here, we systematically modulate the solvent quality with mixtures of tetrahydrofuran-ethanol (THF-EtOH) to manipulate the unimer/micelle ratio in the precursor solution to explore how the associated solution structure influences the final pore morphology. A bottlebrush block copolymer (BBCP) with poly(ethylene oxide) and poly(t-butyl acrylate) side chains was used as the template for pore formation. Irrespective of the solvent composition, a bimodal pore size distribution was obtained with mesopores templated by small aggregates of the BBCP unimers (potentially low aggregation number micelles) and macropores templated by large self-assembled BBCP micelles. The morphology and pore characteristics of the metal oxide films were dependent on the THF-EtOH composition. Interestingly, an intermediate solvent composition where the volume of micelles is approximately half the volume of unimers (in the precursor solution) leads to the best ordering of micelle-templated pores and also the maximum porosity in the films. The micelle/unimer ratios in the precursor solutions do not correspond directly to the bimodal pore distribution in the metal oxide films, which we attribute to kinetically trapped assembly of the BBCP at a low THF content. The increased critical micelle concentration at high THF composition leads to changes in the unimer/micelle ratio during solvent evaporation. These results appear to be universal for a number of metal oxides (cobalt, magnesium, and zinc) with the porosity maximized at a THF/EtOH ratio of 3:1. These results suggest the potential for enhancements in the porosity of block copolymer-templated films by EISA methods through judicious solvent selection.
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The cooperative assembly of functional precursors with block copolymers (BCPs) is a powerful, general route to fabricate ordered mesoporous materials, but the precise tuning of the mesopore size generally requires trial and error to obtain the correct BCP template or appropriate swelling agent. Here, we demonstrate the ability to effectively modulate both expansion and contraction of the ordered cylindrical mesopores relative to those obtained from cooperatively assembled Pluronic F127, resol, and tetraethylorthosilicate. The two key physical parameters for the swelling agents are their hydrophobicity, as quantified by the octanol-water partition coefficient (Kow), and Hansen solubility parameters that describe the interactions of the solvent with the different components of the BCP template. Four low volatility solvents are examined that span a wide Kow with up to 90 wt % solvent relative to the Pluronic F127. Glycerol triacetate (Kow < 1) can decrease the average mesopore size from 5.9 to 4.8 nm due to segmental screening of the interactions in the Pluronic F127 to decrease chain stretching at intermediate loadings. A modest increase in mesopore size to 8.1 nm can be achieved with trimethylbenzene (TMB, Kow = 3.42). Dioctyl phthalate (DOP), which is slightly more hydrophobic (Kow = 8.1), is more effective than TMB at expanding the pore size (maximum: 13.5 nm) without loss of ordered structure. A more hydrophobic solvent, tris (2-ethylhexyl) trimellitate (Kow = 12.5), is less effective at increasing the pore size (maximum: 8.2 nm). The Hansen solubility parameters for DOP most closely match those of the hydrophobic segment in the Pluronic F217 template. We attribute this similarity, which is related to the solvent quality, to the improved efficacy of DOP in increasing the pore size. These results illustrate that both the Hansen solubility parameters (relative to the hydrophobic segment of the template) and relative hydrophobicity of the swelling agent determine the obtainable pore sizes in cooperatively assembled ordered mesoporous materials.
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Crystal orientation in semi-crystalline polymers tends to enhance their performance, such as increased yield strength and modulus, along the orientation direction. Zone annealing (ZA) orients the crystal lamellae through a sharp temperature gradient that effectively directs the crystal growth, but the sweep rate (VZA) of this gradient significantly impacts the extent of crystal orientation. Here, we demonstrate rotational zone annealing (RZA) as an efficient method to elucidate the influence of VZA on the crystal morphology of thin films in a single experiment using isotactic poly(1-butene), PB-1, as a model semi-crystalline polymer. These RZA results are confirmed using standard, serial linear ZA to tune the structure from an almost unidirectional oriented morphology to weakly oriented spherulites. The overall crystallinity is only modestly changed in comparison to isothermal crystallization (maximum of 55% from ZA vs. 48% for isothermal crystallization). However, the average grain size increases and the spherulites become anisotropic from ZA. Due to these structural changes, the Young's modulus of the oriented films, both parallel and perpendicular to the spherulite orientation direction, is significantly increased by ZA. The modulus does become anisotropic after ZA due to the directionality in the crystal structure, with more than a threefold increase in the modulus parallel to the orientation direction for the highest oriented film in comparison to the modulus from isothermal crystallization. RZA enables rapid identification of conditions to maximize orientation of crystals in thin polymer films, which could find utility in determining conditions to improve crystallinity and performance in organic electronics.
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Device applications of shape memory polymers demand diverse shape changing geometries, which are currently limited to non-omnidirectional movement. This restriction originates from traditional thermomechanical programming methods such as uniaxial, biaxial stretching, bending, or compression. A solvent-modulated programming method is reported to achieve an omnidirectional shape memory behavior. The method utilizes freeze drying of hydrogels of polyethylene glycol networks with a melting transition temperature around 50 °C in their dry state. Such a process creates temporarily fixed macroporosity, which collapses upon heating, leading to significant omnidirectional shrinkage. These shrunken materials can swell in water to form hydrogels again and the omnidirectional programming and recovery can be repeated. The fixity ratio (R f ) and recovery ratio (R r ) can be maintained at 90% and 98% respectively upon shape memory multicycling. The maximum linear recoverable strain, as limited by the maximum swelling, is ≈90%. Amongst various application potentials, one can envision the fabrication of multiphase composites by taking advantages of the omnidirectional shrinkage from a porous polymer to a denser structure.
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Hidrogéis/química , Polietilenoglicóis/química , Liofilização , Tamanho da Partícula , Porosidade , Propriedades de SuperfícieRESUMO
With a significant number of mechanical products approaching the retirement phase, the batch recycling of discarded mechanical parts necessitates a preliminary assessment of their surface condition. However, the presence of surface rust poses a challenge to defect identification. Therefore, this paper proposes a method for detecting heavily rusted surface defects based on an improved YOLOv8n network. In the Backbone, the C2f-DBB module of re-parameterized deep feature extraction was introduced, and the attention module was designed to improve the accuracy of information extraction. In the Neck part, a Bi-Afpn multiscale feature fusion strategy is designed to facilitate information exchange between features at different scales. Finally, Focal-CIoU is employed as the bounding box loss function to enhance the network's localization performance and accuracy for defects. Experimentally, it is proved that the improved network in this paper improves the Recall, Precision, and mAP0.5 by 1.2%, 2.1%, and 1.9%, respectively, on the original basis, which is better than other network models.
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In order to study the ecological and atmospheric recovery of the Hexi Corridor region, this paper analyzes the migration changes of land use characteristics and utilizes multivariate data and BenMAP-CE software to study the pollution characteristics of ozone and its precursors and the impact on human health in the Hexi Corridor region. The results showed that the increase of cultivated land area in the Hexi Corridor mainly originated from grassland. The MDA8-O3 concentrations met the primary and secondary standards of the Ambient Air Quality Standards on 43% and 99% of the days, respectively. NO2 showed a negative weekend effect with O3, and HCHO was opposite to it. Temperature, barometric pressure, and vegetation were highly correlated with O3-NO2-HCHO. Ozone pollution in the study area caused about 60% of all-cause premature deaths due to cardiovascular diseases. The study suggests that controlling exogenous transport in Wuwei City during the high ozone period (except August) is mainly dominated by the west and northwest, and that synergistic management of VOCs and NOx emissions can reduce O3 pollution and, consequently, reduce the risk to human health.
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Poluentes Atmosféricos , Poluição do Ar , Monitoramento Ambiental , Ozônio , Ozônio/análise , Humanos , Compostos Orgânicos Voláteis/análise , China , Óxidos de Nitrogênio/análiseRESUMO
Core-shell (Ni@Ag) particles are aligned through the thickness of a poly(dimethylsiloxane) (PDMS) film using a magnetic field in a continuous roll-to-roll process. The alignment of the particles dramatically decreases the percolation threshold for electrical conductivity through the thickness of the film by nearly an order of magnitude from 28 vol % without the field to ≈1 vol % with a 52 mT magnetic field during curing. However, the magnetic forces lead to rough surface topography for intermediate Ni@Ag loadings, but confining the Ni@Ag/PDMS composite by a glass constraint provides a smooth surface. This difference in geometry changes the morphology of the vertically aligned "chains" of Ni@Ag particles where the chains are more aggregated when the film is unconstrained. As the Ni@Ag concentration is decreased below 3.6% for the constrained film, breaks in the aligned particles evident from X-ray tomography lead to pressure sensitive resistance across that film with a large decrease in resistance above a threshold pressure. The threshold pressure is demonstrated to be controllable from ≈15 to ≈290 kPa through the loading of aligned Ni@Ag in the PDMS, but this threshold pressure decreases on cyclic loading. These magnetically aligned composites represent a facile route to mechanically responsive films that could be used in a variety of applications where cyclic loading above and below the threshold pressure is not required, such as disposable pressure sensors for ensuring reliability of products through transportation and embedded structural health monitoring for identifying critical displacements.
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Net-shape manufacture of customizable objects through three-dimensional (3D) printing offers tremendous promise for personalization to improve the fit, performance, and comfort associated with devices and tools used in our daily lives. However, the application of 3D printing in structural objects has been limited by their poor mechanical performance that manifests from the layer-by-layer process by which the part is produced. Here, this interfacial weakness is overcome using a structured, core-shell polymer filament where a polycarbonate (PC) core solidifies quickly to define the shape, whereas an olefin ionomer shell contains functionality (crystallinity and ionic) that strengthen the interface between the printed layers. This structured filament leads to improved dimensional accuracy and impact resistance in comparison to the individual components. The impact resistance from structured filaments containing 45 vol % shell can exceed 800 J/m. The origins of this improved impact resistance are probed using X-ray microcomputed tomography. Energy is dissipated by delamination of the shell from PC near the crack tip, whereas PC remains intact to provide stability to the part after impact. This structured filament provides tremendous improvements in the critical properties for manufacture and represents a major leap forward in the impact properties obtainable for 3D-printed parts.
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Emergent lithium-ion (Li+) batteries commonly rely on nanostructuring of the active electrode materials to decrease the Li+ ion diffusion path length and to accommodate the strains associated with the insertion and de-insertion of Li+, but in many cases these nanostructures evolve during electrochemical charging-discharging. This change in the nanostructure can adversely impact performance, and challenges remain regarding how to control these changes from the perspective of morphological design. In order to address these questions, operando grazing-incidence small-angle X-ray scattering and X-ray diffraction (GISAXS/GIXD) were used to assess the structural evolution of a family of model ordered mesoporous NiCo2O4 anode films during battery operation. The pore dimensions were systematically varied and appear to impact the stability of the ordered nanostructure during the cycling. For the anodes with small mesopores (≈9 nm), the ordered nanostructure collapses during the first two charge-discharge cycles, as determined from GISAXS. This collapse is accompanied by irreversible Li-ion insertion within the oxide framework, determined from GIXD and irreversible capacity loss. Conversely, anodes with larger ordered mesopores (17-28 nm) mostly maintained their nanostructure through the first two cycles with reversible Li-ion insertion. During the second cycle, there was a small additional deformation of the mesostructure. This preservation of the ordered structure lead to significant improvement in capacity retention during these first two cycles; however, a gradual loss in the ordered nanostructure from continuing deformation of the ordered structure during additional charge-discharge cycles leads to capacity decay in battery performance. These multiscale operando measurements provide insight into how changes at the atomic scale (lithium insertion and de-insertion) are translated to the nanostructure during battery operation. Moreover, small changes in the nanostructure can build up to significant morphological transformations that adversely impact battery performance through multiple charge-discharge cycles.