Electrochemical and surfaced-enhanced Raman spectroscopic investigation of CO and SCN- adsorbed on Au(core)-Pt(shell) nanoparticles supported on GC electrodes

Core-shell Au-Pt nanoparticles were synthesized by using a seed growth method and characterized by transmission electron microscopy, X-ray diffraction, and UV-vis spectroscopy. Au(core)-Pt(shell)/GC electrodes were prepared by drop-coating the nanoparticles on clean glassy carbon (GC) surfaces, and their electrochemical behavior in 0.5 M H2SO4 revealed that coating of the Au core by the Pt shell is complete. The electrooxidation of carbon monoxide and methanol on the Au(core)-Pt(shell)/GC was also examined, and the results are similar to those obtained on a bulk Pt electrode. High quality surface-enhanced Raman scattering (SERS) spectra of both adsorbed CO and thiocyanate were observed on the Au(core)-Pt(shell)/GC electrodes. The potential-dependent SERS features resemble those obtained on electrochemically roughened bulk Pt or Pt thin films deposited on roughened Au electrodes. For thiocyanate, the C-N stretching frequency increases with the applied potential, yielding two distinctly different dnu(CN)/dE. From -0.8 to -0.2 V, the dnu(CN)/dE is ca. 50 cm(-1)/V, whereas it is 90 cm(-1)/V above 0 V. The bandwidth along with the band intensity increases sharply above 0 V. At the low-frequency region, Pt-NCS stretching mode at 350 cm(-1) was observed at the potentials from -0.8 to 0 V, whereas the Pt-SCN mode at 280 cm(-1) was largely absent until around 0 V and became dominant at more positive potentials. These potential-dependent spectral transitions were attributed to the adsorption orientation switch from N-bound dominant at the negative potential region to S-bound at more positive potentials. The origin of the SERS activity of the particles is briefly discussed. The study demonstrates a new method of obtaining high quality SERS on Pt-group transition metals, with the possibility of tuning SERS activity by varying the core size and the shell thickness.     

Infrared (1.2-1.6 microm) luminescence in Cr4+:Yb3Al5O12 single crystal with 940 nm diode pumping

Infrared (1.2-1.6 microm) luminescence in a ytterbium aluminium garnet (YbAG) crystal, doped with Cr (0.05at.%) ions, was investigated under CW laser diode pumping (lambda=940 nm). The Cr4+ emission band was observed with its peak at 1.34 microm and measured to be about 1.3 times with respect to Yb3+ IR luminescence (lambda=1.03 microm). We demonstrate that for the excitation wavelength of 940 nm Yb3+ ions act as sensitizers of the 3B2(3T2)-3B1(3A2) emission of Cr4+ ions. This crystal is promising as a high-efficient system for tunable laser (1.2-1.6 microm) output.     

Synthesis and magnetic properties of the one-dimensional linear chain structure cyano-bridged complex [Cu(teta)(H2O)2][Cu(teta) Fe(CN)6]ClO4·2H2O (teta=5,7,7,12,14,14-hexamethyl-1,4,8,11-tetraazacylotetradecane)

Reaction of either K₃[Fe(CN)₆] or K₄[Fe(CN)₆] with a macrocyclic Cu^II complex, [Cu(teta)](ClO₄)₂ (teta = 5,7,7,12,14,14-hexamethyl-1,4,8,11-tetraazacylotetradecane), in aqueous solution gave the same product as shown by spectroscopic and physicochemical characterisation. The crystal structure of the complex shows that it is a one-dimensional linear chain type heterobinuclear Fe^III–Cu^II polymer. The unit is composed of a [Cu(teta)(H₂O)₂]²⁺ cationic complex, a Fe^III–Cu^II alternate linear chain unit, a ClO ₄ ^– ion and four water molecules. The Cu atom is coordinated in a distorted octahedral arrangement by four nitrogen atoms from one teta ligand and two nitrogen atoms of the bridging cyanide groups. The Cu—N bond distances involving the cyanide bridges, 2.522(7) and 2.608(7)Å, respectively, indicate weak antiferromagnetic interactions between the Fe^III and Cu^II atoms.     

大环分子衍生物在人工跨膜离子通道领域中的研究进展

大环分子如环糊精、冠醚等因具备独特的空腔结构,能够通过主-客体相互作用实现对分子、离子的特异性识别,因此常被应用于人工跨膜离子传输系统的研究和开发.与天然的通道蛋白相比,大环分子具有价格低廉、性质稳定、结构易于修饰和功能化等诸多优点,因而备受科研工作者们的关注.本综述详细介绍了大环分子在人工离子通道领域中的研究进展,按...     

Domain Adaptation with Data Uncertainty Measure Based on Evidence Theory

Domain adaptation aims to learn a classifier for a target domain task by using related labeled data from the source domain. Because source domain data and target domain task may be mismatched, there is an uncertainty of source domain data with respect to the target domain task. Ignoring the uncertainty may lead to models with unreliable and suboptimal classification results for the target domain task. However, most previous works focus on reducing the gap in data distribution between the source and target domains. They do not consider the uncertainty of source domain data about the target domain task and cannot apply the uncertainty to learn an adaptive classifier. Aimed at this problem, we revisit the domain adaptation from source domain data uncertainty based on evidence theory and thereby devise an adaptive classifier with the uncertainty measure. Based on evidence theory, we first design an evidence net to estimate the uncertainty of source domain data about the target domain task. Second, we design a general loss function with the uncertainty measure for the adaptive classifier and extend the loss function to support vector machine. Finally, numerical experiments on simulation datasets and real-world applications are given to comprehensively demonstrate the effectiveness of the adaptive classifier with the uncertainty measure.     

HO2非均相摄取系数的测量与参数化

HO2自由基与环境大气气溶胶的非均相反应是HO2自由基的重要汇之一,对大气氧化能力有重要影响,对大气颗粒物的物化性质等进一步产生影响.HO2的非均相反应过程的定量描述对不同地区大气氧化性与臭氧生成能力等问题的探求具有重要意义.目前不同研究小组测量的摄取系数可相差3到5个数量级,深入探究不同条件下不同种类气溶胶对HO2自...     

Nickel-catalyzed cross-electrophile allylation of vinyl bromides and the modification of anti-tumour natural medicine β-elemene

Herein, we present a facile and efficient allylation method via Ni-catalyzed cross-electrophile coupling of readily available allylic acetates with a variety of substituted alkenyl bromides using zinc as the terminal reductant. This Ni-catalyzed modular approach displays excellent functional group tolerance and a broad substrate scope, which the creation of a series of 1,4-dienes including several structurally complex natural products and pharmaceutical motifs. Moreover, the coupling strategy has the potential to realize enantiomeric control. The practicality of this transformation is demonstrated through the potent modification of the naturally antitumor active molecule β-elemene.

Herein, we present a facile and efficient allylation method via Ni-catalyzed cross-electrophile coupling of readily available allylic acetates with a variety of substituted alkenyl bromides using zinc as the terminal reductant.     

Three-Way Decision Models Based on Ideal Relations in Multi-Attribute Decision-Making

In recent years, research on applications of three-way decision (e.g., TWD) has attracted the attention of many scholars. In this paper, we combine TWD with multi-attribute decision-making (MADM). First, we utilize the essential idea of TOPSIS in MADM theory to propose a pair of new ideal relation models based on TWD, namely, the three-way ideal superiority model and the three-way ideal inferiority model. Second, in order to reduce errors caused by the subjectivity of decision-makers, we develop two new methods to calculate the state sets for the two proposed ideal relation models. Third, we employ aggregate relative loss functions to calculate the thresholds of each object, divide all objects into three different territories and sort all objects. Then, we use a concrete example of building appearance selection to verify the rationality and feasibility of our proposed models. Furthermore, we apply comparative analysis, Spearman’s rank correlation analysis and experiment analysis to illustrate the consistency and superiority of our methods.     

Joint Detection of Community and Structural Hole Spanner of Networks in Hyperbolic Space

Community detection and structural hole spanner (the node bridging different communities) identification, revealing the mesoscopic and microscopic structural properties of complex networks, have drawn much attention in recent years. As the determinant of mesoscopic structure, communities and structural hole spanners discover the clustering and hierarchy of networks, which has a key impact on transmission phenomena such as epidemic transmission, information diffusion, etc. However, most existing studies address the two tasks independently, which ignores the structural correlation between mesoscale and microscale and suffers from high computational costs. In this article, we propose an algorithm for simultaneously detecting communities and structural hole spanners via hyperbolic embedding (SDHE). Specifically, we first embed networks into a hyperbolic plane, in which, the angular distribution of the nodes reveals community structures of the embedded network. Then, we analyze the critical gap to detect communities and the angular region where structural hole spanners may exist. Finally, we identify structural hole spanners via two-step connectivity. Experimental results on synthetic networks and real networks demonstrate the effectiveness of our proposed algorithm compared with several state-of-the-art methods.