电磁计算在飞机隐身设计中的应用及未来需求

随着飞机隐身技术的发展,对电磁计算提出了更高的要求,文中分析了国内外技术基础,梳理了电磁计算在飞机雷达隐身设计中的切入点和应用点,阐述了设计过程中利用电磁仿真手段重点开展的分析研究内容.在此基础上,分析了目前电磁计算在飞机隐身设计领域存在的技术难点以及未来技术需求,并结合飞机研制工程经验,指出未来电磁计算将重点突破超电大尺寸目标快速计算、隐身结构材料仿真等问题.     

低压电缆在谐波环境下的阻抗特性研究

电缆广泛用于低压配电网中,研究低压配电系统中电力电缆的谐波特性十分重要。基于电路理论对电缆在谐波环境下的电阻和电抗计算方法进行分析,提出了在谐波频率下求解电缆全矩阵阻抗的实验测算方法,并探究不同参数对电缆电阻和电抗的影响。对电缆谐波阻抗进行实验测算并与公式计算结果进行对比,结果表明:电缆电阻会随谐波次数的增加而增大,而电缆电感则随谐波次数的增加而减小,电缆谐波阻抗近似计算公式对于单芯电缆和多芯电缆分别具有不同的准确精度,论文研究成果对电缆特性研究具有指导意义。     

The Growing Impact of Micro/Nanomaterial‐Based Systems in Precision Oncology: Translating “Multiomics” Technologies

The field of precision oncology is rapidly progressing toward integrated “multiomics” analysis of multiple molecular species (such as DNA, RNA, or proteins) to provide a more complete profile of tumor heterogeneity. Micro/nanomaterial‐based systems, which leverage the unique properties of miniature materials, are currently well positioned to expand beyond rudimentary biomarker detection toward multiomics signature analysis. To enable clinical translation, the rational design and implementation of miniaturized systems should be driven by the unique clinical challenges present at various crucial cancer stages. This review features micro/nanomaterial‐based systems that are robustly tested on real patient samples for molecular biomarker detection at i) initial cancer screening and/or diagnosis, ii) cancer prognosis and risk stratification, and iii) longitudinal treatment/recurrence monitoring. Furthermore, this review discusses the use of micro/nanomaterials to facilitate sample preparation for different molecular biomarker species. Finally, this review deliberates on the recent paradigm shift of micro/nanomaterial‐based system innovation toward integrated multiomics cancer signature analysis and puts forth insights and perspectives on existing challenges. It is anticipated that this review could stimulate the propagation of new concepts and approaches to kick‐start a new generation of clinically translational technologies that capitalize on multiomics cancer signatures.     

2D Material Enabled Offset‐Patterning with Atomic Resolution

Atomic‐precision patterning at large scale is a central requirement for nanotechnology and future electronics that is hindered by the limitations of lithographical techniques. Historically, imperfections of the fabrication tools have been compensated by multi‐patterning using sequential lithography processes. The realization of nanometer‐scale features from much larger patterns through offset stacking of atomically thin masks is demonstrated. A unique mutual stabilization effect between two graphene layers produces atomically abrupt transitions that selectively expose single‐layer covered regions. Bilayer regions, on the other hand, protect the underlying substrate from removal for several hours permitting transfer of atomic thickness variations into lateral features in various semiconductors. Nanoscopic offsets between two 2D materials layers could be introduced through bottom‐up and top‐down approaches, opening up new routes for high‐resolution patterning. A self‐aligned templating approach yields nanometer‐wide bilayer graphene nanoribbons with macroscopic length that produces high‐aspect‐ratio silicon nanowalls. Moreover, offset‐transfer of lithographically patterned graphene layers enables multipatterning of large arrays of semiconductor features whose resolution is not limited by the employed lithography and could reach <10 nm feature size. The results open up a new route to combining design flexibility with unprecedented resolution at large scale.     

Temperature‐Mediated Engineering of Graphdiyne Framework Enabling High‐Performance Potassium Storage

Graphdiyne (GDY), an emerging type of carbon allotropes, possesses fascinating electrical, chemical, and mechanical properties to readily spark energy applications in the realm of Li‐ion and Na‐ion batteries. Nevertheless, rational design of GDY architectures targeting advanced K‐ion storage has rarely been reported to date. Herein, the first example of synthesizing GDY frameworks in a scalable fashion to realize superb potassium storage for high‐performance K‐ion battery (KIB) anodes is showcased. To begin with, first principles calculations provide theoretical guidances for analyzing the intrinsic potassium storage capability of GDY. Meanwhile, the specific capacity is predicted to be as high as 620 mAh g^?1, which is considerably augmented as compared with graphite (278 mAh g^?1). Experimental tests then reveal that prepared GDY framework indeed harvests excellent electrochemical performance as a KIB anode, achieving high specific capacity (≈505 mAh g^?1 at 50 mA g^?1), outstanding rate performance (150 mAh g^?1 at 5000 mA g^?1) and favorable cycling stability (a high capacity retention of over 90% after 2000 cycles at 1000 mA g^?1). Furthermore, kinetic analysis reveals that capacitive effect mainly accounts for the K‐ion storage, with operando Raman spectroscopy/ex situ X‐ray photoelectron spectroscopy identifying good electrochemical reversibility of GDY.     

特高压交流电力线路仿真模型的创建

特高压电力线路运行特性不同于一般高压电力线路,进行特高压交流电力线路特性研究需要创建电力线路仿真模型。文章以均匀传输线理论为基础,对特高压电力线路4个参数进行分析,得出特高压交流电力线路单位长度电导G0表达式,推导得出特高压交流电力线路考虑分布参数特性的数学模型,并在Matlab仿真软件平台创建仿真模型,为特高压长距离电力线路运行特性研究奠定基础。     

d维(t,n)门限量子同态加密算法的设计与仿真

量子同态加密对量子态密文直接进行同态评估计算,而不是将密文解密之后再进行计算.基于相位和状态变换的d维通用酉算子,提出了一种d维（t,n）门限量子同态加密算法.在该算法中,客户端将量子态密文传送给n个服务器中的t个,这t个服务器生成评估子密钥,运行评估算法对量子态密文执行同态计算.客户端对解密之后的量子态执行CNOT门操作,t+1个粒子的聚合值就是评估算法对量子态明文计算之后的结果.该算法使用Shamir（t,n）门限机制隐藏了评估密钥,保护了客户端的隐私数据.从理论上证明了算法的正确性,各个阶段操作过程的仿真实现进一步验证了算法的正确性.     

基于区域分解的大规模并行有限元快速算法

区域分解方法是近来发展迅速的有限元求解方法之一.基于有限元区域分解方法以及多重网格的思想,我们研究了自适应求解以及离散扫频快速算法,并采用自主研发的高性能计算并行框架,将基于区域分解的大规模并行有限元快速算法进行了实现,并行规模能够扩展到数万CPU 核.我们在文中将展示程序的核心架构,以及如何采用多重网格算法的思想实现有效的粗网格校正技术,从而实现有限元线性系统的多次快速求解,加速自适应求解和离散扫频.最后,对算法进行了准确性验证以及大规模并行测试.     

基于BP神经网络的高精度本地多基准时钟合成算法研究

解决基于单个原子钟的系统频率准确度难以突破10^-12量级,基于多基准时钟合成算法的系统无法同时显著改善时钟的长期稳定性和短期稳定性,难以满足未来诸多领域超高精度时钟同步需求的问题,本文将多基准时钟合成算法和神经网络算法相结合,提出一种基于误差逆传播算法神经网络（BP神经网络）的本地多基准时钟合成算法,可以同时改善时钟源的短期和长期稳定性.     

基于U-NET网络的消防红外图像的人体检测算法

针对消防红外图像分辨率差、对比度低、信噪比低、视觉效果模糊、人体姿态复杂,多障碍物遮蔽、人体姿态不完整等特点。本文提出了一种基于U-Net网络的消防红外图像的人体检测算法,通过该算法解决了消防场景中人体姿态复杂,多障碍物遮蔽,人体形态不完整的困难。同时对比于传统目标检测算法以及YOLO v3算法,本文提出的算法在消防红外图像的人体检测上无论是检测的精度还是运算的实时性上都有大幅的提升。