Metal–Organic Gel Leading to Customized Magnetic‑Coupling Engineering in Carbon Aerogels for Excellent Radar Stealth and Thermal Insulation Performances

Metal–organic gel(MOG)derived composites are promising multi-functional materials due to their alterable composition,identifiable chemical homogeneity,tunable shape,and porous structure.Herein,stable metal–organic hydrogels are prepared by regulating the complexation effect,solution polarity and curing speed.Meanwhile,collagen peptide is used to facilitate the fabrication of a porous aerogel with excellent physical properties as well as the homogeneous dispersion of magnetic particles during calcination.Subsequently,two kinds of heterometallic magnetic coupling systems are obtained through the application of Kirkendall effect.FeCo/nitrogen-doped carbon(NC)aerogel demonstrates an ultra-strong microwave absorption of−85 dB at an ultra-low loading of 5%.After reducing the time taken by atom shifting,a FeCo/Fe3O4/NC aerogel containing virus-shaped particles is obtained,which achieves an ultra-broad absorption of 7.44 GHz at an ultra-thin thickness of 1.59 mm due to the coupling effect offered by dual-soft-magnetic particles.Furthermore,both aerogels show excellent thermal insulation property,and their outstanding radar stealth performances in J-20 aircraft are confirmed by computer simulation technology.The formation mechanism of MOG is also discussed along with the thermal insulation and electromagnetic wave absorption mechanism of the aerogels,which will enable the development and application of novel and lightweight stealth coatings.

Many-Objective Optimization-Based Task Scheduling in Hybrid Cloud Environments

Due to the security and scalability features of hybrid cloud architecture,it can bettermeet the diverse requirements of users for cloud services.And a reasonable resource allocation solution is the key to adequately utilize the hybrid cloud.However,most previous studies have not comprehensively optimized the performance of hybrid cloud task scheduling,even ignoring the conflicts between its security privacy features and other requirements.Based on the above problems,a many-objective hybrid cloud task scheduling optimization model(HCTSO)is constructed combining risk rate,resource utilization,total cost,and task completion time.Meanwhile,an opposition-based learning knee point-driven many-objective evolutionary algorithm(OBL-KnEA)is proposed to improve the performance of model solving.The algorithm uses opposition-based learning to generate initial populations for faster convergence.Furthermore,a perturbation-based multipoint crossover operator and a dynamic range mutation operator are designed to extend the search range.By comparing the experiments with other excellent algorithms on HCTSO,OBL-KnEA achieves excellent results in terms of evaluation metrics,initial populations,and model optimization effects.

Effects of Nitrogen Concentration on Microstructure and Antibacterial Property of Copper-Bearing Austenite Stainless Steels

Austenite antibacterial stainless steels have been found to have wide applications in hospitals and food industries. In recent years epsilon copper precipitation in antibacterial stainless steels has obtained much research interest due to its antibacterial action. The objective of this study was to determine the effects of nitrogen concentration on the precipitation of epsilon copper and antibacterial property. Two kinds of austenite antibacterial stainless steels containing copper and different nitrogen concentration （0.02 and 0.08 wt pct, respectively） were prepared and the microstructures were characterized by a combination of electron microscopy and thermodynamic analysis. A mathematical expression was deduced to predict the effect of nitrogen concentration on the activity coefficient of copper, In（fCu/f^0cu）=0.53524＋4.11xN-0.48x^2N. Higher nitrogen was found to increase the free energy difference of copper concentration distribution between precipitation phase and austenite matrix, stimulate the aggregation of copper atoms from austenite, increase the precipitation amount and consequently enhance the antibacterial property of steel.

Precipitation of Epsilon Copper in Ferrite Antibacterial Stainless Steel

The precipitation of epsilon copper at 1023 K ageing in ferrite antibacterial stainless steel was investigated by a combination of electron microscopy and micro-Vickers hardness measurement. The results show that epsilon copper precipitation occurs within 90 s, Complex multilayer structure confirmed as twins and stacking faults on {111}ε-Cu planes was observed in the precipitates. The precipitates grow by the lengthwise enlargement of a set of parallel layers, having [111]ε-Cu and [112]ε-Cu preferred growth orientations. The volume fraction of precipitates f formed within 120 min can be predicted by a modified Avrami equation （In1/1-f= kt ＋ b）. Simultaneously, substituent atom clusters with a size of 5-10 nm was found to occur in the solution and cause matrix strain. The precipitate morphology and distribution on the surface of ferrite antibacterial stainless steel are associated with surface crystallographic orientation of the matrix. The precipitates are predominantly located within the ferrite grains of 〈110〉 orientation. The precipitates located on {111}α-Fe surface planes have sphere or ellipse shape.

基于高维多目标优化的多无人机协同航迹规划

随着无人机应用领域的增多,多无人机协同航迹规划问题变得愈发重要.然而,现存的多无人机协同航迹规划问题大多将多个目标加权转换为单目标问题进行优化,为减少多目标加权的主观性,本文提出一种基于高维多目标优化的多无人机协同航迹规划模型,此模型可以同时优化多无人机航迹距离代价、多无人机航迹威胁代价、多无人机航迹能耗代价,以及多无人机协同性能.同时,为提高高维多目标优化算法在解决此模型时的性能,提出一种基于个体评估交叉策略的NSGA-Ⅲ算法(NSGAⅢ-ICO),可以根据算法运行代数综合评估个体优劣并指导种群交叉操作.仿真结果证明,此模型可以有效地提供多无人机协同航迹,且通过与其他高维多目标优化算法的比较,可以证明此改进算法可以有效地提高多无人机协同航迹规划的多种性能.

Discharge inventory of pharmaceuticals and personal care products in Beijing,China

Pharmaceuticals and personal care products(PPCPs)are emerging environmental contaminants,whose potential risk for the ecological environment has caused wide attention in recent years.In China,quite a large amount of PPCPs were annually emitted into the environment.Their existence in different matrix has been reported frequently,including river water,sediment and soil.However,the contribution from different sources was seldom reported and still unclear in China.Wastewater treatment plant(WWTP)was usually considered to be the main source to the urban river,but livestock and aquaculture farms were also reported as significant pollution sources of PPCPs due to poor environmental management in China.This study summarized environmental discharges of different PPCPs from various sources and obtained the discharge data through different environment media in Beijing,the statistical source of PPCPs was analyzed in detail.The sources comprised WWTPs,excess sludge,hospital wastewater,municipal untreated wastewater,aquaculture wastewater and landfill leachate.This article helps understand the general situation and the potential risk of PPCPs in Beijing.