Coal fly ash, the main industrial waste in coal-fired power plants generated during the coal combustion, usually re-utilized as raw materials in construction industry. However, a lot of unburned ...carbons are contained in raw fly ash, which not only decreasing the strength of fly ash concrete but also causing a huge waste of the resources. Separation of unburned carbon from fly ash is an efficient way to achieve a higher efficiency in the utilization of waste fly ash and greater economic and environmental benefits. This review highlights current methods for separating unburned carbon from fly ash, such as sieving, gravity separation, electrostatic separation, froth flotation, and oil agglomeration. The mineralogy features of unburned carbon affecting the separation efficiency are also presented. This review is closed with a brief discussion on the future research directions addressing different problems related to the recovery of unburned carbon.
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Hazardous chemicals have their own intrinsic properties such as explosive, flammable, corrosive, toxicity, and radioactivity, which will lead to great threats and substantial security risks in the ...transportation, application and storage processes. Problems, if possibly arisen in the transportation and management processes, may cause a major accident. We have to fight through some troubles in the whole process. For this purpose, the paper designs and implements a chemical logistics supervision and forewarning system based on the Internet of Things (IoT) cloud computing, which integrates IoT technology to collect, merge and transmit geographical location information and operation conditions for chemical supply chain such as storage and distribution, environmental parameters for hazardous chemicals, monitor and analyze the transportation route safety and driver operation status. This is a real-time surveillance over the whole logistics chain for hazardous chemicals. Here analyze and aggregate the parameter thresholds of the feature elements that lead the hazardous chemicals logistics to accidents. When the platform detects there is a parameter that reaches the critical threshold, the system automatically issues a warning signal according to the preset forewarning decision program, and then takes measures for level-to-level troubleshooting against it, thereby realizing the monitoring and forewarning on the hazardous chemicals logistics. It is proved by the test that the function modules on the platform all fill the bill for the design and implementation. Given the above, this platform can well apply to monitoring and early warning for hazardous chemicals logistics.
Spaceborne synthetic aperture radar (SAR) is an advanced microwave imaging technology that provides all-weather and all-day target information. However, as spaceborne SAR resolution improves, ...traditional echo signal models based on airborne SAR design become inadequate due to the curved orbit, Earth rotation, and increased propagation distance. In this study, we propose an accurate range model for high-resolution spaceborne SAR by analyzing motion trajectory and Doppler parameters from the perspective of the space geometry of spaceborne SAR. We evaluate the accuracy of existing range models and propose an advanced equivalent squint range model (AESRM) that accurately fits the actual range history and compensates for high-order term errors by introducing third-order and fourth-order error terms while maintaining the simplicity of the traditional model. The proposed AESRM's concise two-dimensional frequency spectrum form facilitates the design of imaging algorithms. Point target simulations confirm the effectiveness of the proposed AESRM, demonstrating significant improvements in fitting accuracy for range histories characterized by nonlinear trajectories. The developed AESRM provides a robust foundation for designing imaging algorithms and enables higher resolution and more accurate radar imaging.
The organic-inorganic hybrid Sn-based perovskite has attracted extensive attention because of its more suitable band gap and environmentally friendly characteristics, but the natural oxidization of ...Sn2+ makes for unsatisfactory illumination stability and efficiency in solar cells. Here, we successfully proved that the synergistical introduction of phenylhydrazine cation (PhNHNH3+) and halogen anions (Cl– and Br–) could substantially improve the illumination stability of FASnI3 (FA stands for NH2CH = NH2+) through the combination of experiments and theoretical calculations. The resultant device achieved a power conversion efficiency of 13.4% (certified 12.4%) with striking long-term durability; i.e., the optimized device maintained 82% of the original efficiency over 330 h under AM1.5G one-sun illumination. This method provides a universal way for improving the illumination stability and efficiency of Sn-based perovskites.
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•13.4% is, so far, the highest PCE in lead-free perovskite solar cells•Coordinate control suppressed phase segregation•Film shows smooth and large grains with reduced defects•Device exhibits excellent shelf and illumination stability
Sn-based perovskite solar cells (PSCs) have been recognized as one of the most promising solutions to the toxicity of lead (Pb)-based cells. However, Sn4+ caused by oxidation during device preparation and application causes severe deterioration of the efficiency and stability of the device. Here, we demonstrated that the synergistical introduction of reducing phenylhydrazine cation (PhNHNH3+) and halide anions (Cl− and Br−) into the FASnI3 (FA stands for NH2CH = NH2+) perovskite film can greatly improve the efficiency and stability of the device. As a result, the champion device showed a power conversion efficiency of 13.4% with an invert p-i-n structure. Moreover, the unencapsulated device possessed excellent stability, maintaining 91% and 82% of the initial efficiency upon storage in a glove box at room temperature for over 4,800 h and under continuous illumination for over 330 h, respectively. These results provide new insights for the further exploration of Sn-based PSCs with regard to high efficiency and long-term durability.
Sn-based perovskite solar cells (PSCs) have been recognized as one of the most promising solutions to toxic lead (Pb)-based cells. However, the easy oxidation of Sn2+ to Sn4+ limits the power conversion efficiency (PCE) and stability of Sn-based PSCs. Here, we reduced phenylhydrazine (PhNHNH3+) and halide (Cl− and Br−) ions and successfully improved the efficiency and stability of FASnI3 solar cells. The champion device showed a recorded PCE of 13.4% with excellent storage and illumination stabilities.
A desirable microenvironment is essential for wound healing, in which an ideal moisture content is one of the most important factors. The fundamental function and requirement for wound dressings is ...to keep the wound at an optimal moisture. Here, we prepared serial polyurethane (PU) membrane dressings with graded water vapor transmission rates (WVTRs), and the optimal WVTR of the dressing for wound healing was identified by both in vitro and in vivo studies. It was found that the dressing with a WVTR of 2028.3 ± 237.8 g/m(2)·24 h was able to maintain an optimal moisture content for the proliferation and regular function of epidermal cells and fibroblasts in a three-dimensional culture model. Moreover, the dressing with this optimal WTVR was found to be able to promote wound healing in a mouse skin wound model. Our finds may be helpful in the design of wound dressing for wound regeneration in the future.
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•Gray water footprint and carrying capacity coefficient were applied.•The coupling evolution was analyzed by combining a physical and statistical model.•Based on the present ...situation, different development scenarios were predicted.
Being a crucial focal point of China's regional development, green development is a novel concept for the coordinated development of the environment and social economy. Therefore, elucidation of the relationship between the aforementioned factors is scientifically necessary to achieve regional green sustainability. Based on the theory of the gray water footprint and physical and statistical models, this study aims to analyze, evaluate, and predict the spatiotemporal dynamics of the coupling evolution between the water environment and social economy in the Yangtze River Economic Belt to provide a scientific reference for exploring basic laws of coordinated development, identifying influencing factors, and formulating management strategies. The results showed that: (1) from 2003 to 2017, the carrying capacity coefficients of the gray water footprint (i.e., the KCOD, KNH3-N, and KTP, except for KTN) decreased over time, as shown by a decreasing trend in the degree of the coupling coordination, which was observed from the east to the west; (2) the coupling coordination degree showed a decreasing trend from the east to the west at the spatial level and an increasing trend from 2003 to 2017 at the temporal level; and (3) the optimal scenario was green development (Plan IV) and the overall coordination degree improved. In addition, corresponding policy recommendations were proposed. The research results are scientifically significant and present a theoretical reference for the coordinated and sustainable development of the regional ecological environment and social economy.
Precipitation can lead to significant leaching of heavy metals from abandoned tailings，resulting in a decline in the quality of the surrounding environment. This study aimed to simulate and quantify ...the migration patterns and fate of heavy metals in tailings caused by precipitation in various environmental media (tailings, air, water, soil, and sediments) using leaching tests, source apportionment, and a fugacity model. Results revealed that the average contents of Cd, Cu, As, Pb, Zn, and Cr in the un-weathered tailings were 3.43, 495.56, 160.70, 138.94, 536.57, and 69.52 mg/kg, respectively. The ecological risk factors in the tailings as well as in sediments and soils, were in the following order: Cd >Cu >As >Pb >Zn >Cr. A fugacity model based on the mass-balance methods was established, achieving a good agreement between simulation and measured values. The total amounts of Cd, Cu, As, Pb, and Zn leached from abandoned tailings over the 30-year evaluation period were estimated to be 1.09, 62.44, 0.16, 0.94, and 102.12 t, respectively. Soil and sediments are important reservoirs for heavy metals. The sum of the As, Cd, Cu, Pb, and Zn storage capacities in the soil and sediment accounted for 77.28%, 75.63%, 73.94%, 69.39%, and 57.80% of the total storage capacity, respectively. This study could provide the means for the establishment of a targeted pollution control plan, a guide for restoration projects, and will aid in controlling pollution risk and improving the surrounding environment.
•Heavy metal (HMs) leaching by precipitation degrades water, soil, and sediments.•A fugacity model was developed to simulate HMs migration in different environments.•HMs properties and environmental parameters determine HMs distribution and transport.•Our results can help establish a targeted pollution control plan.
Simulated raw data have become an essential tool for testing and assessing system parameters and imaging performance due to the high cost and limited availability of real raw data from spaceborne ...synthetic aperture radar (SAR). However, with increasing resolution and higher orbit altitudes, existing simulation methods fail to generate SAR simulated raw data that closely resemble real raw data. This is due to approximations such as curved orbits, “stop-and-go” assumption, and Earth’s rotation, among other factors. To overcome these challenges, this paper presents an accurate range model with a “nonstop-and-go” configuration for raw data simulation based on existing time-domain simulation methods. We model the SAR echo signal and establish a precise space geometry for spaceborne SAR. Additionally, we precisely identify the target illumination area based on elliptical beams through space coordinate transformation. Finally, the SAR raw data were accurately simulated using high-precision time-domain simulation methods. The accuracy of the proposed model was validated by comparing it with the traditional hyperbolic model and the curved orbit model with “stop-and-go” assumption through image processing of the generated raw data. Through the analysis of point target quality parameters, the errors of various parameters in our distance model compared with the other two models are within 1%. Furthermore, this simulation method can be adapted to simulate raw data of other modes and satellite orbits by adjusting beam control and satellite orbit parameters, respectively. The proposed simulation method demonstrated high accuracy and versatility, thereby providing a valuable contribution to the development of remote sensing technology.
Abstract The presence of surface defects in wire ropes (WR) may lead to potential safety hazards and performance degradation, necessitating timely detection and repair. Hence, this paper proposes a ...method for detecting surface defects in WR based on the deep learning models YOLOv8s and U-Net, aiming to identify surface defects in real-time and extract defect data, thereby enhancing the efficiency of surface defect detection. Firstly, the ECA attention mechanism is incorporated into the YOLOv8 algorithm to enhance detection performance, achieving real-time localization and identification of surface defects in WR. Secondly, in order to obtain detailed defect data, the U-Net semantic segmentation algorithm is employed for morphological segmentation of defects, thereby obtaining the contour features of surface defects. Finally, in conjunction with OpenCV technology, the segmentation results of the defects are quantified to extract data, obtaining parameters such as the area and perimeter of the surface defects in the WR. Experimental results demonstrate that the improved YOLOv8-ECA model exhibits good accuracy and robustness, with the model’s mAP@0.5 reaching 84.78%, an increase of 1.13% compared to the base model, an accuracy rate of 90.70%, and an FPS of 65. The U-Net model can efficiently perform segmentation processing on surface defects of WR, with an mIOU of 83.54% and an mPA of 90.78%. This method can rapidly, accurately, and specifically detect surface defects in WR, which is of significant importance in preventing industrial production safety accidents.
The outbreak of the COVID-19 and the Russia Ukraine war has had a great impact on the rice supply chain. Compared with other grain supply chains, rice supply chain has more complex structure and ...data. Using digital means to realize the dynamic supervision of rice supply chain is helpful to ensure the quality and safety of rice. This study aimed to build a dynamic supervision model suited to the circulation characteristics of the rice supply chain and implement contractualization, analysis, and verification. First, based on an analysis of key information in the supervision of the rice supply chain, we built a dynamic supervision model framework based on blockchain and smart contracts. Second, under the logical framework of a regulatory model, we custom designed three types of smart contracts: initialization smart contract, model-verification smart contract, and credit-evaluation smart contract. To implement the model, we combined an asymmetric encryption algorithm, virtual regret minimization algorithm, and multisource heterogeneous fusion algorithm. We then analyzed the feasibility of the algorithm and the model operation process. Finally, based on the dynamic supervision model and smart contract, a prototype system is designed for example verification. The results showed that the dynamic supervision model and prototype system could achieve the real-time management of the rice supply chain in terms of business information, hazard information, and personnel information. It could also achieve dynamic and credible supervision of the rice supply chain's entire life cycle at the information level. This new research is to apply information technology to the digital management of grain supply chain. It can strengthen the digital supervision of the agricultural product industry.
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