Virus and bacterial removal ability of TiO2 nanowire-based self-supported hybrid membranes

Development and application of hybrid membranes containing multi-component materials are increasing day by day in the fields of environmental protection and water treatment. In this research, the efficiency of titania nanowire (TiO₂ NW)-based self-supported hybrid membranes was investigated in the removal of Escherichia coli (E. coli) bacteria and MS2 bacteriophages from contaminated water mimicking the microorganism suspension. Furthermore, toxicology tests on the as-prepared membranes were also performed. TiO₂ NWs were coated with iron(III) oxide (Fe₂O₃) and copper(II) oxide (CuO) nanoparticles, respectively, and cellulose was used as reinforcement material. It was found that, the functionalisation strongly affected the MS2 removal ability of as-prepared membranes, which can be due to the electrostatic interactions between the surface of hybrid membrane and the bacteriophages. The most efficient removal (greater than or equal to 99.99%) was obtained with the TiO₂ NW-CuO-cellulose membrane at pH 7.0. The fabricated hybrid membranes were characterized by micro computed tomography (μCT), Raman spectroscopy, Fourier transform infrared spectroscopy (FT-IR), dynamic light scattering (DLS), contact angle measurement and inductively coupled optical emission spectrometry (ICP-OES) techniques. This study shows a simple route of the usage of novel and effective inorganic nanowire-based hybrid membranes for bacteria and virus removal, providing new pathways in the field of water filtration technologies.     

Experimental analysis and thermodynamic modelling of Nitroxynil solubility in pure solvent and binary solvent

Nitroxynil(NIT) is a commonly used anti-liver fluke drug for cattle and sheep, Its solubility is closely related to its preparation. In this work, the molar solubility of NIT in nine pure solvents (methanol, ethanol, 1,2-propanediolethyl, isopropanol, ethyl acetate, acetonitrile, n-butanol, phemethylol) and two kinds of binary mixtures with different ratio(ethanol + phemethylol; ethanol + acetonitrile) was determined by shake flask method over the temperature from 278.15 ～ 323.15 K at atmosphere pressure. Results show that the solubility of NIT in all tested solvents was increased with raised temperature. In mono-solvents, the mole fraction solubility of NIT was highest in phemethylol and the solubility order is: phemethylol > acetonitrile > ethyl acetate > methanol > n-butanol > ethanol > 1,2-propanediolethyl > isopropanol > water. In binary solvents, the mole fraction solubility increased with increasing ratio of phemethylol/acetonitrile. In mono-solvents, the modified Apelblat equation, λh equation, Van't Hoff model were applied to correlate the solubility data. In binary solvents, the modified Apelblat equation, λh equation, GSM model and Jouyban-Acree model were to correlate the solubility data. Solubility order of NIT in nine pure solvent and two binary solvent systems were analysed by using the Hansen solubility parameter (HSP). Activity coefficient was to access the solute–solvent molecular interactions. In addition, the dissolution of NIT is an endothermic and entropy-friendly process, since thermodynamic parameters such as enthalpy, entropy, and apparent standard Gibbs free energy are all greater than zero. The results will supply some essential data on recrystallization process, purification and formulation development of NIT in pharmaceutical applications.     

Reaction parameters influence on the catalytic performance of copper-silica aerogel in the methanol steam reforming

Steam reforming of methanol was carried out on the copper-silica aerogel catalyst.The effects of reaction temperature,feed rate,water to methanol molar ratio and carrier gas flowrate on the H_2 production rate and CO selectivity were investigated.M ethanol conversion was increased considerably in the range of about 240-300,after which it increased at a slightly lower rate.The used feed flowrate,steam to methanol molar ratio and carrier gas flowwere 1.2-9.0 m L/h,1.2-5.0 and 20-80 m L/min,respectively.Reducing the feed flowrate increased the H_2 production rate.It was found that an increase in the water to methanol ratio and decreasing the carrier gas flowrate slightly increases the H2production rate.Increasing the water to methanol ratio causes the lowest temperature in which CO formation was observed to rise,so that for the ratio of 5.0 no CO formation was detected in temperatures lower than 375℃.In all conditions,by approaching the complete conversion,increasing the main product concentration,increasing the temperature and contact time,and decreasing the steam to methanol ratio,the CO selectivity was increased.These results suggested that CO was formed as a secondary product through reverse water-gas shift reaction and did not participate in the methanol steam reforming reaction mechanism.     

Adaptive impulsive synchronization of uncertain delayed chaotic system with full unknown parameters via discrete‐time drive signals

This article investigates the adaptive impulsive synchronization of delayed chaotic system with full unknown parameters. Aiming at this problem, we propose a new adaptive strategy, in which both the adaptive–impulsive controller and the parameters adaptive laws are designed via the discrete‐time signals from the drive system. The corresponding theoretical proof is given to guarantee the effectiveness of the proposed strategy. Moreover, the concrete adaptive strategies are achieved for delayed Hopfield neural network, optical Ikeda system and the well‐known delayed Lü chaotic system. As expected, numerical simulations show the effectiveness of the proposed strategy. This method has potential applications in parameters estimation, secure communication, and cryptanalysis when only discrete signals are transmitted in communication channel. © 2014 Wiley Periodicals, Inc. Complexity 21: 43–51, 2016     

Robust stability analysis of stochastic neural networks with Markovian jumping parameters and probabilistic time‐varying delays

This article discusses the issue of robust stability analysis for a class of Markovian jumping stochastic neural networks (NNs) with probabilistic time‐varying delays. The jumping parameters are represented as a continuous‐time discrete‐state Markov chain. Using the stochastic stability theory, properties of Brownian motion, the information of probabilistic time‐varying delay, the generalized Ito's formula, and linear matrix inequality (LMI) technique, some novel sufficient conditions are obtained to guarantee the stochastical stability of the given NNs. In particular, the activation functions considered in this article are reasonably general in view of the fact that they may depend on Markovian jump parameters and they are more general than those usual Lipschitz conditions. The main features of this article are described in the following: first one is that, based on generalized Finsler lemma, some improved delay‐dependent stability criteria are established and the second one is that the nonlinear stochastic perturbation acting on the system satisfies a class of Lipschitz linear growth conditions. By resorting to the Lyapunov–Krasovskii stability theory and the stochastic analysis tools, sufficient stability conditions are established using an efficient LMI approach. Finally, two numerical examples and its simulations are given to demonstrate the usefulness and effectiveness of the proposed results. © 2014 Wiley Periodicals, Inc. Complexity 21: 59–72, 2016     

3DSEM++: Adaptive and intelligent 3D SEM surface reconstruction

Structural analysis of microscopic objects is a longstanding topic in several scientific disciplines, such as biological, mechanical, and materials sciences. The scanning electron microscope (SEM), as a promising imaging equipment has been around for decades to determine the surface properties (e.g., compositions or geometries) of specimens by achieving increased magnification, contrast, and resolution greater than one nanometer. Whereas SEM micrographs still remain two-dimensional (2D), many research and educational questions truly require knowledge and facts about their three-dimensional (3D) structures. 3D surface reconstruction from SEM images leads to remarkable understanding of microscopic surfaces, allowing informative and qualitative visualization of the samples being investigated. In this contribution, we integrate several computational technologies including machine learning, contrario methodology, and epipolar geometry to design and develop a novel and efficient method called 3DSEM++ for multi-view 3D SEM surface reconstruction in an adaptive and intelligent fashion. The experiments which have been performed on real and synthetic data assert the approach is able to reach a significant precision to both SEM extrinsic calibration and its 3D surface modeling.     

内嵌富勒烯[M@C_(70)](M=Li,Na,K,Be,Mg,Ca)与[Mg(H_2O)_6]~(2+)相互作用的密度泛函理论研究

使用密度泛函理论方法,对内嵌多种碱金属及碱土金属原子(M=Li,Na,K,Be,Mg,Ca)的富勒烯C70与水合Mg(II)离子之间的相互作用进行了理论研究.首先对各原子(M=Li,Na,K,Be,Mg,Ca)嵌入C70后的形成能进行了讨论,之后计算了[M@C70]各体系与[Mg(H_2O)6]2~+的相互作用能,并采用自然键轨道理论(NBO)研究了电荷转移的情况,最后进行了电子密度拓扑分析.结果表明,内嵌原子半径越大,[M@C70]各体系的热力学稳定性就越高,转移至[Mg(H_2O)6]2~+的电荷也随之增加,二者之间的相互作用属于闭壳层相互作用及共价作用.     

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利用Matlab语言将EFIT程序反演计算过程进行优化整合,简化了程序操作步骤,并增加了对计算结果的分析与存储功能。利用整合后的 EFIT 程序,计算分析了 J-TXET 装置放电过程中等离子体磁场位形和其它参数的演变,绘制了等离子体压强剖面图、等离子体电流密度和安全因子分布等磁面信息的重建结果。此外,还将反演结果与软X射线测算数据进行比对。结果表明,改善后的EFIT程序能够初步满足对实验放电的反演计算分析要求,为J-TXET装置的放电控制和运行提供重要的参考数据。     

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在对国内外液态锂回路研究综述的基础上,重点介绍了四川大学流动液态锂回路的研究进展。为开展等离子体与流动自由液态锂表面相互作用的研究而设计了该回路,其目标是：(1)获得稳定、均匀的流动自由液态锂表面;(2)研究等离子体辐照下液态锂的蒸发、溅射以及氢、氢同位素和氦在液态锂中的滞留行为;(3)研究等离子体辐照下液态锂与结构材料的相容性。系统包括液态锂循环部分和直线高密度等离子体发生装置。