Dual-Phasic Carbon with Co Single Atoms and Nanoparticles as a Bifunctional Oxygen Electrocatalyst for Rechargeable Zn–Air Batteries

The great interest in rechargeable Zn–air batteries (ZABs) arouses extensive research on low-cost, high-active, and durable bifunctional electrocatalysts to boost the sluggish oxygen reduction reaction (ORR) and oxygen evolution reaction (OER). It remains a great challenge to simultaneously host high-active and independent ORR and OER sites in a single catalyst. Herein a dual-phasic carbon nanoarchitecture consisting of a single-atom phase for the ORR and nanosized phase for the OER is proposed. Specifically, single Co atoms supported on carbon nanotubes (single-atom phase) and nanosized Co encapsulated in zeolitic-imidazole-framework-derived carbon polyhedron (nanosized phase) are integrated together via carbon nanotube bridges. The obtained dual-phasic carbon catalyst shows a small overpotential difference of 0.74 V between OER potential at 10 mA cm⁻² and ORR half-wave potential. The ZAB based on the bifunctional catalyst demonstrates a large power density of 172 mW cm⁻². Furthermore, it shows a small charge-discharge potential gap of 0.51 V at 5 mA cm⁻² and outstanding discharge-charge cycling durability. This study provides a feasible design concept to achieve multifunctional catalysts and promotes the development of rechargeable ZABs.     

Multifunctional Superelastic Cellulose Nanofibrils Aerogel by Dual Ice-Templating Assembly

A superelastic aerogel with fast shape recovery performance from large compressive strain is highly desired for numerous applications such as thermal insulation in clothing, high-sensitive sensors, and oil contaminant removal. Fabrication of superelastic cellulose nanofibrils (CNF) aerogels is challenging as the CNF can assemble into non-elastic sheet-like cell walls. Here, a dual ice-templating assembly (DITA) strategy is proposed that can control the assembly of CNF into sub-micrometer fibers by extremely low temperature freezing (–196 °C), which can further assemble into an elastic aerogel with interconnected sub-micron fibers by freezer freezing (−20 °C) and freeze drying. The CNF aerogel from the DITA process demonstrates isotropic superelastic behavior that can recover from over 80% compressive strain along both longitudinal and cross-sectional directions, even in an extremely cold liquid nitrogen environment. The elastic CNF aerogel can be easily modified by chemical vapor deposition of organosilane, demonstrating superhydrophobicity (164° water contact angle), high liquid absorption (489 g g⁻¹ of chloroform absorption capacity), self-cleaning, thermal insulating (0.023 W (mK)⁻¹), and infrared shielding properties. This new DITA strategy provides a facile design of superelastic aerogels from bio-based nanomaterials, and the derived high performance multifunctional elastic aerogel is expected to be useful for a wide-range of applications.     

结合JND模型的交叉验证深度图质量评价方法

针对在3D视频(3DV)和自由视点视频(FVV)中传统的 图像质量评价方法不适用于深度图的问题,本文从人类视觉感知特性出发,提出一 种新的深度图 质量评估算法。首先进行交叉验证,得到待评价深度图的差值图;然后提取遮挡掩膜,去除 被遮挡的像素 点;再根据人类视觉特性,考虑背景亮度掩蔽、纹理掩蔽和边缘敏感性等因素,应用恰可察 觉失真(JND)模 型得到每个像素点的误差可视阈值;最后计算错误像素率作为度量指标评价深度图的质量 。实验结果表 明,本文提出的算法能够准确地检测错误像素,所提出的度量指标与全参考度量指标的相关 系数的平均值 为0.833,最高达到0.933,与合成虚拟视点均 方误差的相关系数的平均值为0.857,最高达 到0.928。     

光电耦合器件低频噪声特性与可靠性老化研究

在宽的输入偏置电流范围条件下,开展了光电耦合器件低频噪声特性测试与功率老化和高温老化的可靠性试验研究。结果表明,光电耦合器件的低频噪声主要是内部光敏晶体管1/f噪声,并随输入偏置电流的增大呈现先增大后减小的规律,这与器件的工作状态密切相关。功率老化试验后,高输入偏置电流条件下的低频噪声有所增大,这归因于电应力诱发的有源区缺陷。高温老化试验后,整个器件线性工作区条件下的低频噪声都明显增大,说明温度应力能够更多地激发器件内部的缺陷。相对于1/f噪声幅度参量,低频噪声宽带噪声电压参量可以更灵敏准确地进行器件可靠性表征。     

基于液体直接冷却的薄片固体激光器研究

详细研究了直接液体冷却薄片固体激光器的关键技 术,主要包括增益模块内流道结构的设 计、薄片增益介质的装夹方式的选择等。从流场的流动状态和 流道换热能力的角度出发分析了增益模块内流道结构的设计;对比分析了采用 “软装夹” 和“硬装夹”对增益 介质热应力和增益介质所能承受最大抽运功率的不同影响,计算结果表明,采用“软装夹” 增益介质所能承受 的抽运功率大约是“硬装夹”的8倍。最终,基于课题组所研制的1kW量级直接液体冷却薄 片固体激光器对其关键技术进行分析总结。     

一种基于模式识别的光纤通信系统故障诊断方法

为了改善光纤通信系统故障诊断效果,设计了一种基于模式识别的光纤通信系统故障诊断模型。首先提取光纤通信系统故障诊断的特征向量,然后采用模式识别技术中的最小二乘支持向量机构建光纤通信系统故障诊断分类器,最后采用具体光纤通信系统故障诊断实例对模型性能进行测试。结果表明,设计模型的光纤通信系统故障诊断率超过90%,诊断效率较传统系统改善明显,且故障误诊率明显低于对比模型。     

基于卷积神经网络迁移学习的飞机目标识别

飞机目标识别是地面情报系统的一项重要关键技术。近年来火热的深度学习方法,如卷积神经网络,展现出对于图像识别任务的优越性能。但是,训练卷积神经网络需要大量的带标签样本以估计规模庞大的模型参数,因而限制了其在雷达目标识别领域中的应用。针对飞机目标识别中的小样本问题,文中引入适用于有限数据场景的迁移学习技术,预先在其他大样本高分辨距离像数据上训练一个初始卷积神经网络模型,再结合当前飞机目标识别任务调优模型参数。在实测数据上的实验结果显示,与仅使用卷积神经网络的方法相比,所提方法可显著提升识别准确率,验证了方法的有效性。     

S波段35W GaN功率MMIC

报道了一款采用两级拓扑结构的2～4 GHz宽带高功率单片微波功率放大器芯片.放大器采用了微带结构,并使用电抗匹配进行设计,重点在于宽带功率效率平坦化设计.经匹配优化后放大器在2～4 GHz整个频带内脉冲输出功率大于35 W,小信号增益达到22 dB,在2.4 GHz频点处峰值输出功率达到40 W,对应的功率附加效率为3...     

基于时域有限差分法舰载活动设备电磁场分析

舰载活动设备产生的电磁干扰因无法采用传统的舰船消磁技术消除而需准确评估。以舰载火炮为例,采用时域有限差分法分析了舰载火炮在姿态改变时的电磁场特性变化。为提高建模精度,引入平均电参数对金属设备进行建模。通过坐标变换,提出了修正的差分方程对金属设备与Yee网格不重合的边缘部分进行模型修正。通过算例对比验证了算法的有效性。仿真结果表明：舰载火炮在姿态改变时电场有0.6~3.8 V/m的变化,磁场有0.0016~0.01 A/m的变化,这类电磁场变化对舰船电磁兼容性的影响不容忽视。     

基于覆盖网络的应用层选播服务的设计与研究

针对网络层的选播通信存在着可扩展性和无状态服务等根本问题,在现有的应用层选播研究基础上,提出了一种基于覆盖网络的应用层选播的结构,并把这种结构从代理节点的部署和链路的选取上进行求解,并通过实验对此拓扑结构进行了验证.