电爆炸箔断路开关的理论和实验研究

 采用金属箔电爆炸过程的二维数值计算模型，对含电爆炸金属箔断路开关的电感储能脉冲功率调节系统进行了数值计算。以此为基础，研制出了一种低电感型的电爆炸箔断路开关，并以4μF/75kV脉冲电容器组作为初级能源，13Ω电阻作为负载进行实验研究。研究结果表明：在负载上可获得约250kV，脉宽大于400ns的脉冲电压。     

Electrostatic Interactions Leading to Hierarchical Interpenetrating Electroconductive Networks in Silicon Anodes for Fast Lithium Storage

Recently, the frequency of combining MXene, which has unique properties such as metal-level conductivity and large specific surface area, with silicon to achieve excellent electrochemical performance has increased considerably. There is no doubt that the introduction of MXene can improve the conductivity of silicon and the cycling stability of electrodes after elaborate structure design. However, most exhaustive contacts can only improve the electrode conductivity on the plane. Herein, a MXene@Si/CNTs (HIEN-MSC) composite with hierarchical interpenetrating electroconductive networks has been synthesized by electrostatic self-assembly. In this process, the CNTs are first combined with silicon nanoparticles and then assembled with MXene nanosheets. Inserting CNTs into silicon nanoparticles can not only reduce the latter‘s agglomeration, but also immobilizes them on the three-dimensional conductive framework composed of CNTs and MXene nanosheets. Therefore, the HIEN-MSC electrode shows superior rate performance (high reversible capacity of 280 mA h⁻¹ even tested at 10 A g⁻¹), cycling stability (stable reversible capacity of 547 mA h g⁻¹ after 200 cycles at 1 A g⁻¹) and applicability (a high reversible capacity of 101 mA h g⁻¹ after 50 cycles when assembled with NCM622 into a full cell). These results may provide new insights for other electrodes with excellent rate performance and long-cycle stability.     

生物分子自组装的仿生叶绿体:光酶催化反应及燃料合成

正自然界经过上亿年的演变,已经进化出许多精巧的结构来完成复杂的功能。叶绿体就是自然界进化出的太阳能利用的高级系统。它具有分级组织的结构,能将太阳能转化为稳定的化学能。具体而言,捕光单元和电子传递链排布在类囊体膜上,后者堆叠形成基粒,其上的光催化反应可以与基质中的酶催化反应偶联起来~1。目前,人们已经制备出许多分级组织的光催化体系~2。然而,上述制备过程大多需要高温和有机溶剂,这限制     

Analysis of financial stock markets through multidimensional scaling based on information measures

In this paper, a novel multidimensional scaling (MDS) based on information measures method is proposed to analyze financial stock markets. In order to examine the effectiveness of this method, we applied it to the classification of two types of artificial series, the logistic map model and the cubic map model, as well as stock time series. Moreover, the traditional MDS using Euclidean dissimilarity is also provided as a reference for comparisons. The results show that the MDS based on information measures can give us more detailed, exact and clearer information on the classification of simulation series and stock time series than the MDS using Euclidean dissimilarity. In addition, the proposed graphical method may also assist in the construction of multivariate econometric models.     

Boron-iron nanochains for selective electrocatalytic reduction of nitrate

The electrocatalysis of nitrate reduction reaction(NRR) has been considered to be a promising nitrate removal technology.Developing a highly effective iron-based electrocatalyst is an essential challenge for NRR.Herein,boron-iron nanochains(B-Fe NCs) as efficient NRR catalysts were prepared via a facile lowcost and scalable method.The Fe/B ratio of the B-Fe NCs-x can be elaborately adjusted to optimize the NRR catalytic performance.Due to the electron transfer from boron to metal,the metal-metal bonds are weakened and the electron density near the metal atom centers are rearranged,which are favor of the conversion from NO_3~-into N_2.Moreover,the well-crosslinked chain-like architectures benefit the mass/electron transport to boost the exposure of abundant catalytic active sites.Laboratory experiments demonstrated that the optimized B-Fe NCs catalyst exhibits superior intrinsic electrocatalytic NRR activity of high nitrate conversion(～80%),ultrahigh nitrogen selectivity(～99%) and excellent long-term reactivity in the mixed electrolyte system(0.02 mol/L NaCl and 0.02 mol/L Na_2 SO_4 mixed electrolyte),and the electrocatalytic activity of the material shows poor performance at low chloride ion concentration(Nitrate conversion of ～61 % and nitrogen selectivity of ～57% in 0.005 mol/L NaCl and 0.035 mol/L Na_2 SO_4 mixed electrolyte).This study provides a broad application prospect for further exploring the highefficiency and low-cost iron-based functional nanostructures for electrocatalytic nitrate reduction.     

Cu∶CdS纳米晶的绿色合成、结构及光谱性质研究

本文利用一种绿色合成工艺,采用巯基乙酸作为配体,在水溶液中成功合成了水溶性的Cu∶CdS纳米晶。利用X射线衍射分析(XRD)、傅里叶变换红外光谱(FT-IR)、场发射扫描电镜显微分析(FE-SEM)、能量色散X射线谱(EDX)、紫外可见(UV-Vis)吸收光谱对样品的晶体学性质、结构、形貌、成分、吸收光谱性质进行了系统的研究。着重研究了掺杂浓度对Cu∶CdS纳米晶的晶体学性质及吸收光谱的影响。结果表明:合成的Cu∶CdS纳米晶为立方相,通过谢乐公式估算的平均晶粒尺寸约为2 nm;随着掺杂浓度的增加,产物的晶胞参数也逐渐增大,表明Cu离子已经掺入到CdS纳米晶中,该发现与EDX结果相吻合。FT-IR红外光谱发现,配体巯基乙酸成功包覆在纳米晶的表面。UV-vis吸收谱表明,掺杂后的Cu∶CdS纳米晶的吸收峰向长波长方向移动。这种红移主要是Cu离子在CdS纳米晶中的掺杂而形成电子能级跃迁所致。     

简单方法制备与表征新颖复合凝胶及表面微结构——由科研成果转化的化学综合实验

材料表面的微结构会赋予材料独特的性能，水凝胶在生物医学领域有广泛的应用前景。采用紫外光刻蚀法创新性地实现了复合凝胶的制备和凝胶表面图案化微结构的构筑一步完成；通过原子力显微镜和光学显微镜的表征，复合凝胶聚N-异丙基丙烯酰胺/聚乙二醇二丙烯酸酯兼具了温敏性能与图案化微结构的新颖性能结构特征。本实验有助于培养学生的创新意识，激发学生的学习兴趣以及未来从事科研的兴趣。     

Effect of deuteron density distribution on the deduction of screening potential from the D(d,p)T reaction in Be metals

The D(d,p)T reaction in Be metal environments has been measured to investigate the electron screening effect in metals in an energy region of from 5.5 keV to 10 keV in a center of mass system(CMS)at a temperature of 121 K.The depth distribution of deuteron density in Be metals has an impact on the observed reaction yields.A model of deuteron density distribution in metal has been proposed to obtain the original yields.A screening energy of(116±46)eV has been obtained with the assumed deuteron density distribution model.     

关于完全完备分配格上矩阵相对于特征值的特征向量

借助于伪补和矩阵的幂序列研究了完全完备分配格上矩阵相对于特征值的特征向量的计算方法,利用特征向量的性质证明了最大特征向量的计算公式,并给出了一般特征向量的计算方法.