Flexible Polydimethylsiloxane Composite with Multi-Scale Conductive Network for Ultra-Strong Electromagnetic Interference Protection

Highly conductive polymer composites(CPCs) with excellent mechanical flexibility are ideal materials for designing excellent electromagnetic interference(EMI) shielding materials,which can be used for the electromagnetic interference protection of flexible electronic devices.It is extremely urgent to fabricate ultra-strong EMI shielding CPCs with efficient conductive networks.In this paper,a novel silver-plated polylactide short fiber(Ag@PL ASF,AAF) was fabricated and was integrated with carbon nanotubes(CNT) to construct a multi-scale conductive network in polydimethylsiloxane(PDMS) matrix.The multi-scale conductive network endowed the flexible PDMS/AAF/CNT composite with excellent electrical conductivity of 440 S m-1and ultra-strong EMI shielding effectiveness(EMI SE) of up to 113 dB,containing only 5.0 vol% of AAF and 3.0 vol% of CNT(11.1wt% conductive filler content).Due to its excellent flexibility,the composite still showed 94% and 90% retention rates of EMI SE even after subjected to a simulated aging strategy(60℃ for 7 days) and 10,000 bending-releasing cycles.This strategy provides an important guidance for designing excellent EMI shielding materials to protect the workspace,environment and sensitive circuits against radiation for flexible electronic devices.

Identification of denatured and normal biological tissues based on compressed sensing and refined composite multi-scale fuzzy entropy during high intensity focused ultrasound treatment

In high intensity focused ultrasound(HIFU)treatment,it is crucial to accurately identify denatured and normal biological tissues.In this paper,a novel method based on compressed sensing(CS)and refined composite multi-scale fuzzy entropy(RCMFE)is proposed.First,CS is used to denoise the HIFU echo signals.Then the multi-scale fuzzy entropy(MFE)and RCMFE of the denoised HIFU echo signals are calculated.This study analyzed 90 cases of HIFU echo signals,including 45 cases in normal status and 45 cases in denatured status,and the results show that although both MFE and RCMFE can be used to identify denatured tissues,the intra-class distance of RCMFE on each scale factor is smaller than MFE,and the inter-class distance is larger than MFE.Compared with MFE,RCMFE can calculate the complexity of the signal more accurately and improve the stability,compactness,and separability.When RCMFE is selected as the characteristic parameter,the RCMFE difference between denatured and normal biological tissues is more evident than that of MFE,which helps doctors evaluate the treatment effect more accurately.When the scale factor is selected as 16,the best distinguishing effect can be obtained.

Concurrent multi-scale design optimization of composite frame structures using the Heaviside penalization of discrete material model

This paper deals with the concurrent multi-scale optimization design of frame structure composed of glass or carbon fiber reinforced polymer laminates. In the composite frame structure, the fiber winding angle at the micro-material scale and the geometrical parameter of components of the frame in the macro-structural scale are introduced as the independent variables on the two geometrical scales. Considering manufacturing requirements, discrete fiber winding angles are specified for the micro design variable. The improved Heaviside penalization discrete material optimization interpolation scheme has been applied to achieve the discrete optimization design of the fiber winding angle. An optimization model based on the minimum structural compliance and the specified fiber material volume constraint has been established. The sensitivity information about the two geometrical scales design variables are also deduced considering the characteristics of discrete fiber winding angles. The optimization results of the fiber winding angle or the macro structural topology on the two single geometrical scales, together with the concurrent two-scale optimization, is separately studied and compared in the paper. Numerical examples in the paper show that the concurrent multi-scale optimization can further explore the coupling effect between the macro-structure and micro-material of the composite to achieve an ultralight design of the composite frame structure. The novel two geometrical scales optimization model provides a new opportunity for the design of composite structure in aerospace and other industries.

Multi-Scale Damage Model for Quasi-Brittle Composite Materials

In the present paper,a hierarchical multi-scale method is developed for the nonlinear analysis of composite materials undergoing heterogeneity and damage.Starting from the homogenization theory,the energy equivalence between scales is developed.Then accompanied with the energy based damage model,the multi-scale damage evolutions are resolved by homogenizing the energy scalar over the meso-cell.The macroscopic behaviors described by the multi-scale damage evolutions represent the mesoscopic heterogeneity and damage of the composites.A rather simple structure made from particle reinforced composite materials is developed as a numerical example.The agreement between the fullscale simulating results and the multi-scale simulating results demonstrates the capacity of the proposed model to simulate nonlinear behaviors of quasi-brittle composite materials within the multi-scale framework.

Fast Face Detection with Multi-Scale Window Search Free from Image Resizing Using SGI Features

Face detection is applied to many tasks such as auto focus control, surveillance, user interface, and face recognition. Processing speed and detection accuracy of the face detection have been improved continuously. This paper describes a novel method of fast face detection with multi-scale window search free from image resizing. We adopt statistics of gradient images (SGI) as image features and append an overlapping cell array to improve detection accuracy. The SGI feature is scale invariant and insensitive to small difference of pixel value. These characteristics enable the multi-scale window search without image resizing. Experimental results show that processing speed of our method is 3.66 times faster than a conventional method, adopting HOG features combined to an SVM classifier, without accuracy degradation.

Multi-scale Modeling and Finite Element Analyses of Thermal Conductivity of 3D C/SiC Composites Fabricating by Flexible-Oriented Woven Process

Thermal conductivity is one of the most significant criterion of three-dimensional carbon fiber-reinforced SiC matrix composites(3D C/SiC).Represent volume element(RVE)models of microscale,void/matrix and mesoscale proposed in this work are used to simulate the thermal conductivity behaviors of the 3D C/SiC composites.An entirely new process is introduced to weave the preform with three-dimensional orthogonal architecture.The 3D steady-state analysis step is created for assessing the thermal conductivity behaviors of the composites by applying periodic temperature boundary conditions.Three RVE models of cuboid,hexagonal and fiber random distribution are respectively developed to comparatively study the influence of fiber package pattern on the thermal conductivities at the microscale.Besides,the effect of void morphology on the thermal conductivity of the matrix is analyzed by the void/matrix models.The prediction results at the mesoscale correspond closely to the experimental values.The effect of the porosities and fiber volume fractions on the thermal conductivities is also taken into consideration.The multi-scale models mentioned in this paper can be used to predict the thermal conductivity behaviors of other composites with complex structures.

Research on quantum well intermixing of 680 nm AlGaInP/GaInP semiconductor lasers induced by composited Si-Si_(3)N_(4) dielectric layer

The optical catastrophic damage that usually occurs at the cavity surface of semiconductor lasers has become the main bottleneck affecting the improvement of laser output power and long-term reliability.To improve the output power of 680 nm AlGaInP/GaInP quantum well red semiconductor lasers,Si-Si_(3)N_(4)composited dielectric layers are used to induce its quantum wells to be intermixed at the cavity surface to make a non-absorption window.Si with a thickness of 100 nm and Si_(3)N_(4)with a thickness of 100 nm were grown on the surface of the epitaxial wafer by magnetron sputtering and PECVD as diffusion source and driving source,respectively.Compared with traditional Si impurity induced quantum well intermixing,this paper realizes the blue shift of 54.8 nm in the nonabsorbent window region at a lower annealing temperature of 600 ℃ and annealing time of 10 min.Under this annealing condition,the wavelength of the gain luminescence region basically does not shift to short wavelength,and the surface morphology of the whole epitaxial wafer remains fine after annealing.The application of this process condition can reduce the difficulty of production and save cost,which provides an effective method for upcoming fabrication.

Elastic Predictions of 3D Orthogonal Woven Composites Using Micro/meso-scale Repeated Unit Cell Models

This presentation predicts the elastic properties of three-dimensional(3D)orthogonal woven composite(3DOWC)by finite element analysis based on micro/meso repeated unit cell(RUC)models.First,the properties of fiber yarn are obtained by analysis on a micro-scale RUC model assuming fibers in a hexagonal distribution pattern in the polymer matrix.Then a full thickness meso-scale RUC model including weft yarns,warp yarns,Z-yarns and pure resin zones is established and full stiffness matrix of the 3DOWC including the in-plane and flexural constants are predicted.For thick 3DOWC with large number of weft,warp layers,an alternative analysis method is proposed in which an inner meso-RUC and a surface meso-RUC are established,respectively.Then the properties of 3DOWC are deduced based on laminate theory and properties of the inner and surface layers.The predicted results by the above two alternative methods are in good experimental agreement.

Research on Fixture's Effect on Properties of Single-Shear Bolt Jointed Composite Laminates Structure

The testing on the bearing strength of single-shear bolt jointed composite laminates structure is done.And the effect of the fixture on the testing results is analyzed. Then a macro-micro multi-scale analytical model combined with the improved"Generalized Method of Cells( GMC) "is developed,which is used to predict the macro bearing strength and to characterize the micro constitute material failure of the bolt jointed composite laminates structure. Both the contact conditions at the bolt/hole boundary and the contact conditions at the specimen/fixture boundary,progressive damage,and the material properties degradation are all taken account into the analytical model. Thus,the numerical simulation results agree well with the experimental results.Finally,the effect of the fixture on the testing results is characterized. The results show that the incomplete contaction between the fixture and the specimen or the lack of the lateral constraint on the specimen will affect the limited bearing strength and the offset bearing strength of the bolt jointed composite laminates structure. In addition,the lower support rigid of the fixture will affect the rigid of the bolt jointed composite laminates structure.

BPA可逆热敏变色复合材料制备方法及其应用研究进展

综述了BPA可逆热敏变色材料的制备及其应用,以及复配法、无机包覆法、微胶囊法、湿成膜法和近年来的2,6-单取代双酚A复合膜新方法,并分析了2,6-单取代法中膜结晶相变与二醛、酚醛树脂及胶种的关系。2,6-单取代双酚A线型或芳香酚醛树脂及其复合膜有机体系的设计与研究将进一步推动该类材料在具有可调的迟滞响应相变智能窗口,超低温变色敏感性、变色深度、稳定性,环境友好型合成树脂及塑料及实验教学等方面的应用。

Zn杂质诱导GaInP/AlGaInP红光半导体激光器量子阱混杂的研究

在GaAs基GaInP/AlGaInP单量子阱结构外延片上分别使用磁控溅射设备生长ZnO薄膜和等离子增强化学气相沉积设备生长SiO2薄膜,以ZnO介质层作为Zn杂质诱导源,采用固态扩Zn的方式对激光器进行选择性区域诱导以制备非吸收窗口来提高器件的腔面光学灾变损伤阈值,从而提高半导体激光器的输出功率和长期可靠性。在580~680℃、20~60 min退火条件下对Zn杂质诱导量子阱混杂展开研究,实验发现,ZnO/SiO2或ZnO/Si3N4复合介质层的采用比单一Zn介质层的杂质诱导蓝移量大,且在680℃、30 min的条件下获得了最大55 nm的蓝移量。分析结果表明,介质层所施加的压应变会将外延片表面GaAs层中Ga原子析出,促使Zn原子进入外延层中以诱导量子阱混杂。通过测量光致发光光谱发现发光强度并没有明显下降,可为后期器件制作提供借鉴。

聚醚醚酮的黏度特性及其复合材料加工工艺窗口研究

为了探究聚醚醚酮(Poly-ether-ether-ketone,PEEK)的黏度特性,为PEEK基复合材料制备工艺的设计提供参考,采用旋转流变仪考察在一定剪切速率下温度和时间对PEEK黏度的影响,创建PEEK熔体的黏度模型,模拟在有氧条件下PEEK熔体的黏度与时间和温度的关系。结果表明:在653.15~673.15 K温度范围内,随着测试时间的增加,PEEK熔体的黏度先降低后升高,表明PEEK熔体存在由下降到增大的临界黏度,到达临界黏度的时间与温度成反比例关系。构建的模型能预测在有氧条件下PEEK熔体的黏度随温度时间的变化趋势,由此可确立加工工艺窗口,从而为PEEK基复合材料生产中的加工工艺设计提供依据。

多源中高分辨率影像协同下时间合成窗口对农作物识别的影响

【背景】中高空间分辨率(≤30 m)影像是在耕地破碎、种植结构复杂的中国南方开展农作物遥感识别研究的重要数据。然而,要克服中高分辨率传感器重访周期较长以及南方多云雨天气的影响,对影像进行时间窗口合成以协同使用多源中高分辨率遥感数据,是获取时空连续农作物制图结果的必要保障。由于不同卫星影像获取的周期不同,且不同农作物物候季相节律存在较大差异,如何选择影像合成时间窗口是农作物准确识别的关键前提。【目的】通过探究影像合成时间窗口对于农作物识别的影响机制,为大尺度复杂农作物种植结构制图提供重要参考依据。【方法】以农作物类型多样且云雨天气频繁的湖北省江汉平原为研究区,通过协同Landsat-8和Sentinel-2A/2B卫星影像,设置7种时间合成窗口(15、20、25、30、40、50和60 d)情景,分别从影像的覆盖度、不同农作物时序光谱特征以及不同农作物分类精度等角度,深入分析影像时间合成窗口对农作物遥感识别的影响。【结果】在影像20 d时间合成窗口的情景下,江汉平原农作物(冬油菜、冬小麦、水稻、稻虾田和其他作物)的总体分类精度最高,为93.13%。对比而言,在影像较短时间合成窗口(如15d)的情景下,时间序列密集但高质量影像覆盖度较低,农作物总体分类精度较低(90.91%);而在影像较长时间合成窗口(如60 d)的情景下,影像覆盖度高但时间序列稀疏,导致农作物识别的关键物候信息丢失,降低了总体分类精度(86.06%)。此外,不同农作物的识别效果受影像时间合成窗口的影响程度不同,依次为其他作物>冬油菜>水稻>冬小麦>稻虾田。其他作物类内时序光谱特征变异性较大,因此对时间窗口极其敏感。油菜准确识别的关键物候期为开花期,该时期长度较短,影像合成时间超过30 d会极大降低其识别效果,主要体现为与小麦的混淆。区分稻虾田与单季稻的关键物候期为稻虾田的稻闲季淹水期,其持续时间较长,受时间合成窗口影响较小。【结论】影像时间合成窗口20d时可兼顾高质量影像覆盖度和捕获农作物识别的关键物候特征,但不同作物识别的最优时间合成窗口受到作物关键物候期影响。研究结果可为多源中高分辨率影像协同下时间合成窗口的选择提供理论参考和方法支撑,进而有效服务于宏观尺度农作物高精度遥感制图研究。

Multi-scale collaborative design method for macroscopic thermal optimization and mesoscopic woven structure of hypersonic vehicle's TOCMC leading edge

A new thermal protection design method for hypersonic vehicle's leading edge is proposed, which can effectively reduce temperature of the leading edge without additional cooling measures. This method reduces the leading-edge's temperature by the multi-scale collaborative design of the macroscopic thermal optimization and the mesoscopic woven structures of Three-dimensional Orthogonal Woven Ceramic Matrix Composites(TOCMC). The macroscopic thermal optimization is achieved by designing different mesoscopic woven structures in different regions to create combined heat transfer channels to dredge the heat. The combined heat transfer channel is macroscopically represented by the anisotropic thermal conductivity of TOCMC. The thermal optimization multiple linear regression model is established to optimize the heat transport channel, which predicts Theoretical Optimal Thermal Conductivity Configuration(TOTCC) in different regions to achieve the lowest leading-edge temperature. The function-oriented mesostructure design method is invented to design the corresponding mesostructure of TOCMC according to the TOTCC, which consists of universal thermal conductivity prediction formulas for TOCMC. These universal formulas are firstly derived based on the thermal resistance network method, which is verified by experiments with an error of 6.25%. The results show that the collaborative design method can effectively reduce the leading edge temperature by about 12.8% without adding cooling measures.

Multi-scale thermodynamic analysis method for 2D SiC/SiC composite turbine guide vanes

Ceramic Matrix Composite （CMC） turbine guide vanes possess multi-scale stress and strain with inhomogeneity at the microscopic scale. Given that the macroscopic distribution cannot reflect the microscopic stress fluctuation, the macroscopic method fails to meet the requirements of stress and strain analysis of CMC turbine guide vanes. Furthermore, the complete thermodynamic properties of 2D woven SiC/SiC-CMC cannot be obtained through experimentation, Accordingly, a method to calculate the thermodynamic properties of CMC and analyze multi-scale stress and strain of the turbine guide vanes should be established. In this study, the multi-scale thermodynamic analysis is investigated. The thermodynamic properties of Chemical Vapor Infiltration （CVI） pro- cessed SiC/SiC-CMC are predicted by a Representative Volume Element （RVE） model with porosity, leading to the result that the relative error between the calculated in-plane tensile modulus and the experimental value is 4.2%. The macroscopic response of a guide vane under given conditions is predicted. The relative error between the predicted strain on the trailing edge and the experimental value is 9.7%. The calculation of the stress distribution of micro-scale RVE shows that the maximum value of microscopic stress, which is located in the interlayer matrix, is more than 1.5 times that of macroscopic stress in the same direction and the microscopic stress distribution of the interlayer matrix is related to the pore distribution of the composite.

A new stress-based multi-scale failure criterion of composites and its validation in open hole tension tests

A new stress-based multi-scale failure criterion is proposed based on a series of off-axis tension tests, and their corresponding fiber failure modes and matrix failure modes are determined at the microscopic level. It is a physical mechanism based, three-dimensional damage analysis criterion which takes into consideration the constituent properties on the macroscopic failure behavior of the composite laminates. A complete set of stress transformation, damage determination and evolution methods are established to realize the application of the multi-scale method in failure analysis. Open-hole tension（OHT） specimens of three material systems（CCF300/5228, CCF300/5428 and T700/5428） are tested according to ASTM standard D5766, and good agreements are found between the experimental results and the numerical predictions. It is found that fiber strength is a key factor influencing the ultimate strength of the laminates, while matrix failure alleviates the stress concentration around the hole. Different matchings of fiber and matrix result in different failure modes as well as ultimate strengths.

Development and Evaluation of Multiscale Fiber-reinforced Composite Powders for Powder-bed Fusion Process

The development of multiscale fiber-reinforced composite powders is an effective way to improve the mechanical properties and functionality of additively manufactured parts.Herein,a novel thermally induced precipitation process is proposed for preparing multiscale fiber-reinforced powders.A systematic evaluation was conducted to explore the main factors influencing powder morphology,powder flow,and microstructure.In the powder-forming mechanism,the polymer matrix is coated on the microfiber,and a film of carbon nanotubes covers the powder surface,which is promoted by heterogeneous nucleation.The composite powders comprised polyamide 12,carbon fiber(CF),and carbon nanotubes,which have been successfully applied in powder bed fusion processes including selective laser sintering(SLS).Smooth flow and powder deposition were observed,and the composite components obtained via SLS were well-fabricated using the optimized process parameters.A CF loading ratio of up to 66.7 wt%and homogeneous fiber distribution within the matrix were successfully achieved.

用于自适应调温辐射制冷智能窗户的双温度响应深共晶溶剂离子凝胶

构建具有自适应辐射制冷性能的双温度响应智能窗户以实现节能和隐私保护被认为具有很大的研究价值。我们提出了一种基于聚乙二醇基可聚合深共晶溶剂(PEG-PDES)聚合而成的双温度响应深共晶溶剂离子凝胶(DDESI),并应用于智能窗户。离子凝胶通过控制温度从低温(<20℃)到室温(20~40℃)再到高温(>40℃),实现了三阶段光学调制(不透明-透明-不透明),以实现节能和客户隐私保护的作用。它展示了具有竞争力的太阳能调制能力(ΔT_(sol)=80.69%)和透光率(T_(lum)=85.85%),以及可调节的低、高两个响应温度(T_(1)、T_(2))。该体系的T_(2)可以在较宽的温度范围内(40~70℃)实现透明-白色可逆的温度调节。同时,DDESI在中红外范围表现极高的发射率(>90%),且在高温下在太阳辐射范围极低的透过率(≈0%),使离子凝胶具有日间辐射效果并进一步提升热管理性能,在实践测试中能达到最高8℃降温作用。这项工作制备的自适应辐射制冷双温度响应深共晶溶剂离子凝胶为发展多功能智能窗户提供了新思路。

电磁透波功能复合材料的研究

介绍了电磁透波功能复合材料的应用环境及性能要求。综述了国内外相关研究领域的现状,展望了电磁透波功能复合材料的应用前景和研究重点。

木塑窗角的熔焊注塑复合连接试验

应用熔焊技术和注塑成型技术相结合的复合连接技术,对木塑窗进行了角部连接试验。木塑窗型材成分为60%的木粉(WF)、36%的聚乙烯(PE)和4%的马来酸酐接枝聚乙烯(MAPE)。复合连接试验由熔焊连接和注塑连接组成。通过对比不同焊接温度下的熔焊连接强度,选出进行注塑连接的最佳工艺参数,并应用Moldflow软件分析了复合连接的状况。研究结果表明熔焊注塑复合连接技术可以应用于木塑窗的角部连接问题,并且具有足够的强度。