模板组装Fe纳米线阵列及其微结构

铝在硫酸溶液中经直流阳极氧化,得到多孔铝阳极氧化膜(AAO). 以AAO膜为模板,通过交流电沉积的方法,在AAO模板孔内成功组装了Fe纳米线.TEM分析表明,Fe纳米线的长度约为2.5 μm,其长度分布十分均匀；粗细均匀,直径约为25 nm. XRD实验分析证实,所制备的Fe纳米线为α-Fe.选区电子衍射（SAED）实验分析表明,α-Fe纳米线具有单晶结构.     

Effect of brain lesions on [3H]ohmefentanyl binding site densities in the rat striatum and substantia nigra.

We have recently demonstrated that [3H]ohmefentanyl, a non-peptidergic opioid ligand which was suggested to cross the blood brain barrier in contrast to other peptidergic opioid ligands, bound not only to mu opioid receptor sites but also to sigma sites. In order to examine whether [3H]ohmefentanyl can be used as a marker for mu sites, we investigated the effects of brain lesions on [3H]ohmefentanyl binding site densities, as compared with [3H][D-Ala2, MePhe4, Gly-ol5]enkephalin ([3H]DAGO), a selective mu ligand. These binding site densities were measured by quantitative autoradiography in the rat striatum and substantia nigra, two brain structures known to contain a high density of mu receptors, following lesions of the nigro-striatal dopaminergic pathway and striatal intrinsic neurons. Following unilateral nigral lesion with 6-hydroxydopamine, [3H]ohmefentanyl binding site densities were decreased in the patches (-35%) and matrix (-20%) of the ipsilateral striatum and in the lesioned substantia nigra pars compacta (-49%). Unilateral striatal lesion with quinolinic acid induced 72%, 61% and 50% decreases in [3H]ohmefentanyl binding in the patches and matrix of the lesioned striatum and in the ipsilateral substantia nigra pars reticulata, respectively. Similar results were obtained in the binding of [3H]DAGO. Indeed, a significant linear correlation was observed between [3H]ohmefentanyl and [3H]DAGO binding site densities. Therefore, mu opioid receptors may be mainly located on intrinsic neurons in the striatum, dopaminergic cell bodies in the substantia nigra pars compacta and nerve terminals of striatal efferents in the substantia nigra pars reticulata.(ABSTRACT TRUNCATED AT 250 WORDS)     

All-Visible-Light Triggered Photoswitch of Dithienylethene Derivatives with Molecular Conformation Changes Excess 5 Å

Developing new all-visible-light driven fluorescent molecular switches has attracted much interests due to their important application prospects in materials science and life science. Herein, three novel all-visible-light triggered fluorescent molecular photoswitches ( 2P3 , 4F , and 4Cl ) are designed and prepared, which are realized by prolonging π-conjugation length with aggregated-induced emission units. These photoswitches show reversible photochromic and fluorescent switching in dilute solutions and films under 420 nm and 560 nm irradiations. Meanwhile, upon alternating irradiations with 450 nm/560 nm light, effective photochromic and fluorescent switching in powder states are also achieved. More interestingly, two distinct conformations with different photochromic abilities can be altered by solvents polarity. The size difference of the two conformations is over 5 Å in the vertical direction which is one of the largest changes among photochromic molecules based on dithienylethene. The accompanying conformational changes are analysed to understand the relationship between solvent characteristics and crystal structure, as well as the intermolecular interaction in solid state for all-visible-light triggered photoswitching molecules.     

Inorganic Filler Enhanced Formation of Stable Inorganic-Rich Solid Electrolyte Interphase for High Performance Lithium Metal Batteries

Lithium metal (LM) is a promising anode material for next generation lithium ion based electrochemical energy storage devices. Critical issues of unstable solid electrolyte interphases (SEIs) and dendrite growth however still impede its practical applications. Herein, a composite gel polymer electrolyte (GPE), formed through in situ polymerization of pentaerythritol tetraacrylate with fumed silica fillers, is developed to achieve high performance lithium metal batteries (LMBs). As evidenced theoretically and experimentally, the presence of SiO₂ not only accelerates Li⁺ transport but also regulates Li⁺ solvation sheath structures, thus facilitating fast kinetics and formation of stable LiF-rich interphase and achieving uniform Li depositions to suppress Li dendrite growth. The composite GPE-based Li||Cu half-cells and Li||Li symmetrical cells display high Coulombic efficiency (CE) of 90.3% after 450 cycles and maintain stability over 960 h at 3 mA cm⁻² and 3 mAh cm⁻², respectively. In addition, Li||LiFePO₄ full-cells with a LM anode of limited Li supply of 4 mAh cm⁻² achieve capacity retention of 68.5% after 700 cycles at 0.5 C (1 C = 170 mA g⁻¹). Especially, when further applied in anode-free LMBs, the carbon cloth||LiFePO₄ full-cell exhibits excellent cycling stability with an average CE of 99.94% and capacity retention of 90.3% at the 160th cycle at 0.5 C.     

区块链电子存证系统的设计与实现

文中介绍了区块链技术在电子证据存证方面的应用。通过将需要的电子证据以交易的形式记录下来,并明确记录时间戳,然后将记录存储在节点账本中。利用分布式数据存储技术完成电子存证过程,区块链技术可以实现不可篡改的信息存取和交换,有效保证电子数据的安全性和可信性。文中还探讨了区块链技术在降低处理电子证据时的技术风险和存储成本以及其对司法机构的协助作用。     

温循条件下电源模块的瞬态热力耦合研究及优化

针对电源模块在温度循环条件下工作的可靠性问题,以典型电源模块为研究对象,基于有限元分析软件建立温循条件下电源模块的瞬态温度分布模型和电源模块的瞬态热力耦合模型,着重分析芯片、玻璃绝缘子等易损区域。在此基础上以玻璃绝缘子的最大热应力和芯片的最高温度为优化目标,对电源模块进行遗传算法优化设计。结果表明,相比其他研究直接施加热载荷条件,采用瞬态热力耦合所得电源模块结果更准确,芯片温度为86.03℃,玻璃绝缘子的热应力为61.27 MPa。经过遗传算法优化的芯片温度为81.85℃,玻璃绝缘子的热应力为37.05 MPa,满足可靠性要求。证明遗传算法与仿真结合,可有效提高产品设计的可靠性。     

皮秒激光烧蚀7075铝合金数值模拟与实验研究北大核心CSCD

为了解超快激光与材料相互作用的机理,优化激光金属烧蚀能力,以达到理想的烧蚀效果,本文在二维轴对称模型中引入了适用于超快激光烧蚀的双温模型,模拟了皮秒激光对于以7075铝合金为代表的低熔点合金的烧蚀行为。通过更改皮秒激光的功率密度和冲击次数,确定皮秒激光各参数对于7075铝合金的影响并与实验结果相对照。结果表明,激光烧蚀的深度小于通过双温模型计算出的金属熔化温度层,同时激光的烧蚀深度与激光密度线性相关,当烧蚀深度大于一定数值时,激光烧蚀深度几乎不随着烧蚀次数的增加而增大。     

谐振器加载石墨烯的双通带可调滤波衰减器设计

石墨烯材料在微波段的阻抗可控特性是其最有价值的应用特性之一。文中首次分析了石墨烯对微带 多模谐振的影响机理,提出了一种集成滤波衰减功能为一体的灵活可控器件。首先,对不同位置加载石墨烯的微带双 模谐振器进行了严格的等效电路建模,通过奇偶模分析法及输入导纳参数计算,探究了双模谐振受石墨烯阻抗及其加 载位置的影响,明晰了石墨烯材料对微波谐振器的影响。随后设计了动态可调的滤波衰减器并阐述了石墨烯材料在谐 波控制上的潜在应用点。最后,采用不同尺寸的双模谐振器进行石墨烯加载并完成双通带幅度独立可控的滤波衰减器 的设计,仿真与实测结果吻合良好,验证了阻抗可控石墨烯材料在可调微波衰减类器件上的应用前景。     

基于拓扑链路识别的光网络流量数据合成算法

基于深度学习的光网络流量诊断与预测等场景中,由于保密等原因,光链路的流量数据采集和存储工作受限。针对数据量少而无法支撑深度学习的问题,文章提出了一种基于拓扑链路识别的光网络流量数据合成算法,其核心思想是在生成对抗网络框架下,联合基于光网络拓扑的条件生成模型和基于光网络流量的数据合成模型,以自监督的方式合成指定光链路的流量数据。仿真结果表明,所提算法合成的光网络流量数据在自相关系数指标上与真实数据接近且使得基于全连接神经网络的流量预测模型准确率达到95%以上。