The role of co-adsorbed O2 on the catalytic reduction of NO with C2H5OH on the surface of Pt(3 3 2)

The influence of pre-dosed O₂ on the catalytic reduction of NO with ¹³C₂H₅OH on the surface of stepped Pt(3 3 2) was investigated using Fourier transform infra red reflection-absorption spectroscopy (FTIR-RAS) and thermal desorption spectroscopy (TDS). We show that the oxidation of ¹³C₂H₅OH with O₂ is a very effective reaction, occurring at 150 K and giving rise to acetate. The presence of NO does not lead to any evident oxidation of ¹³C₂H₅OH irrespective of the annealing temperature. For the case of O₂ + ¹³C₂H₅OH + NO co-adlayers, oxidation of ¹³C₂H₅OH also takes place at 150 K. However, no new surface species that are supposed to be an intermediate for the production of N₂ are detected.The influence of O₂ on the production and desorption of N₂ is intimately related to both O₂ and ¹³C₂H₅OH coverage. The presence of pre-dosed O₂ does not greatly promote N₂ desorption. In fact, N₂ desorption is suppressed quantitatively with increasing O₂ coverage, after which unreacted, or left-over O atoms appear and remain on steps. It is concluded that the presence of pre-dosed O₂ does not play a role of activating reactants in the catalytic reduction of NO with ¹³C₂H₅OH on the surface of Pt(3 3 2).     

基于视感知特征的多光谱高保真降维方法研究

为解决多光谱数据在降维压缩过程中的颜色精度保持问题,提出一种基于人眼视觉感知特征的多光谱数据高保真降维压缩方法(VPCM)。研究首先依据人眼视觉响应的非线性解析特征,成功构建了同时综合人眼光谱特征与色度特征的变换函数,并通过进一步构造的优化函数对其进行修正,以针对不同的样本集找到最佳变换方向,而后利用修正后的视觉特征变换函数对光谱样本集进行空间变换(Γ(S)=C),然后利用主成分分析方法对经视觉特征函数变换后样本集光谱数据进行降维压缩处理,并通过逆变换重构出样本集光谱数据(Γ-1(C)=^S),进行降维评价。实验选取四类具有典型代表性的数据集作为测试样本,分别以D50/2°条件下的CIELab色差和75组典型照明光源(钨丝灯、荧光灯和LED灯)下的平均同色异谱指数(MMI)作为色度主要评价指标,同时对比了Lab-PQR和2-XYZ两种较为先进的光谱降维算法。实验结果为VPCM方法的MMI值最小,其次是LabPQR,而2-XYZ的表现较差;VPCM方法在75组光源下对四组样本集的平均重构色差ΔEab也为最小,且最大样本平均色差及方差均要小于其他两种方法;VPCM方法的重构光谱精度介于Lab-PQR和2-XYZ之间,Lab-PQR的重构光谱精度最高。实验结果显示新方法色度压缩精度整体优于对比的两种方法,在变换参考条件下具有良好的色差稳定性,能够较好的应用于多光谱数据色度高保真压缩。     

Yolk–Shell‐Structured Cu/Fe@γ‐Fe2O3 Nanoparticles Loaded Graphitic Porous Carbon for the Oxygen Reduction Reaction

Core–shell Cu/γ‐Fe₂O₃@C and yolk–shell‐structured Cu/Fe@γ‐Fe₂O₃@C particles are prepared by a facile synthesis method using copper oxide as template particles, resorcinol‐formaldehyde as the carbon precursor, and iron nitrate solution as the iron source via pyrolysis. With increasing carbonization temperature and time, solid γ‐Fe₂O₃ cores are formed and then transformed into Fe@γ‐Fe₂O₃ yolk–shell‐structured particles via Ostwald ripening under nitrogen gas flow. The composition variations are studied, and the formation mechanism is proposed for the generation of the hollow and yolk–shell‐structured metal and metal oxides. Moreover, highly graphitic carbons can be obtained by etching the metal and metal oxide nanoparticles through an acid treatment. The electrocatalytic activity for oxygen reduction reaction is investigated on Cu/γ‐Fe₂O₃@C, Cu/Fe@γ‐Fe₂O₃@C, and graphitic carbons, indicating comparable or even superior performance to other Fe‐based nanocatalysts.     

Simulation methodology — An introduction for queueing theorists

Simulation is a widely used methodology for queueing systems. Its superficial simplicity hides a number of pitfalls which are not all as well known as they should be. In particular simulation experiments need careful design and analysis as well as good presentations of the results. Even the elements of simulation such as the generation of arrival and service times have a chequered history with major problems lying undiscovered for 20 years. On the other hand, good simulation practice can offer much more than is commonly realized.     

Highly Strong Interaction between Fe/Fe3C Nanoparticles and N-Doped Carbon toward Enhanced Oxygen Reduction Reaction Performance

Transition metal compounds anchored on N-doped carbon (NC) show intrinsic activity and stability for oxygen reduction reaction (ORR). However, the interaction between the transition metal compounds and NC still needs to be strengthened for electron transfer at the compounds/carbon interface. Herein, Fe/Fe₃C hybrid nanoparticles encapsulated into N-doped carbon (Fe@NC) are used as high-performance ORR catalysts. Benefiting from the strong interaction at Fe/Fe₃C nanoparticles/NC interface, the electrons can transfer from Fe/Fe₃C hybrid nanoparticles to NC, redistributing the electron density of active sites and promoting the ORR process. The as-synthesized Fe@NC exhibits outstanding ORR catalytic activity with an onset potential of 1.01 V and a half-wave potential of 0.92 V in alkaline media. It also shows prominent cycling stability and tolerance to methanol crossover, superior to Pt/C catalyst. The theoretical analysis reveals that the Fe nanoparticles have regulated the electron distributions at the heterojunction interface. The Gibbs free energy diagrams for ORR illustrate that the rate-determining step is the conversion of OH* to OH⁻. In situ Raman spectra give evidence of O-containing intermediates to prove the ORR process.     

充水管道声分隔片消声性能研究Ⅰ.理论分析

本文对在充水管道中加入声分隔片的消声结构的消声性能进行了理论研究,用模式匹配法计算了有限和蔗声分隔片的传递损失和功率反射系数。研究结果表明,声分隔片的消声效果优于通常所采用在管壁加吸声衬怪的结构,并且其功率反射系数很小。     

A relational perspective of attribute reduction in rough set-based data analysis

Attribute reduction is very important in rough set-based data analysis (RSDA) because it can be used to simplify the induced decision rules without reducing the classification accuracy. The notion of reduct plays a key role in rough set-based attribute reduction. In rough set theory, a reduct is generally defined as a minimal subset of attributes that can classify the same domain of objects as unambiguously as the original set of attributes. Nevertheless, from a relational perspective, RSDA relies on a kind of dependency principle. That is, the relationship between the class labels of a pair of objects depends on component-wise comparison of their condition attributes. The larger the number of condition attributes compared, the greater the probability that the dependency will hold. Thus, elimination of condition attributes may cause more object pairs to violate the dependency principle. Based on this observation, a reduct can be defined alternatively as a minimal subset of attributes that does not increase the number of objects violating the dependency principle. While the alternative definition coincides with the original one in ordinary RSDA, it is more easily generalized to cases of fuzzy RSDA and relational data analysis.