All-solid-state potentiometric sensors for ascorbic acid by using a screen-printed compatible solid contact

The development of all-solid-state potentiometric ion selective electrodes for monitoring of ascorbic acid, by using a screen-printed compatible solid contact is described. The applied methodology is based on the use of PVC membrane modified with some firstly-tested ionophores (triphenyltin(IV)chloride, triphenyltin(IV)hydroxide and palmitoyl-l-ascorbic acid) and a novel one synthesized in our laboratory (dibutyltin(IV) diascorbate). Synthesis protocol and some preliminary identification studies are given. A conductive graphite-based polymer thick film ink was used as an internal solid contact between the graphite electrode and the PVC membrane. The presence and the nature of the solid contact (plain or doped with lanthanum 2,6-dichlorophenolindophenol (DCPI)) seem to enhance the analytical performance of the electrodes in terms of sensitivity, dynamic range, and response time. The analytical performance of the constructed electrodes was evaluated with potentiometry, constant-current chronopotentiometry and electrochemical impedance spectroscopy (EIS). The interference effect of various compounds was also tested. The potential response of the optimized Ph₃SnCl-based electrode was linear against ascorbic acid concentration range 0.005-5.0 mM. The applicability of the proposed sensors in real samples was also tested. The detection limit was 0.002 mM ascorbic acid (50 mM phosphate, pH 5 in 50 mM KCl). The slope of the electrodes was super-Nernstian and pH dependent, indicating a mechanism involving a combination of charge transfer and ion exchange processes. Fabrication of screen-printed ascorbate ISEs has also been demonstrated.     

Novel disposable bismuth-sputtered electrodes for the determination of trace metals by stripping voltammetry

This work describes a novel type of bismuth electrode for stripping voltammetry based on coating a silicon substrate with a thin bismuth film by means of sputtering. The bismuth-based sensors were characterized by optical methods (scanning electron microscopy (SEM), atomic force microscopy (AFM) and X-ray diffraction (XRD)) and as well as by linear sweep voltammetry. Subsequently, the electrodes were tested for the detection of low concentrations of trace metals (Cd(II), Pb(II) and Ni(II)) by stripping voltammetry. Well-formed stripping peaks were observed for trace concentrations of the target analytes demonstrating “proof-of-principle” for these sensors. This type of electrochemical device, utilizing thin-film technology for the formation of the bismuth film, holds promise for future applications in trace metal analysis.     

Artificial Neural Networks in water analysis: Theory and applications

Artificial Neural Networks (ANNs) have seen an explosion of interest over the last two decades and have been successfully applied in all fields of chemistry and particularly in analytical chemistry. Inspired from biological systems and originated from the perceptron, i.e. a program unit that learns concepts, ANNs are capable of gradual learning over time and modelling extremely complex functions. In addition to the traditional multivariate chemometric techniques, ANNs are often applied for prediction, clustering, classification, modelling of a property, process control, procedural optimisation and/or regression of the obtained data. This paper aims at presenting the most common network architectures such as Multi-layer Perceptrons (MLPs), Radial Basis Function (RBF) and Kohonen's self-organisations maps (SOM). Moreover, back-propagation (BP), the most widespread algorithm used today and its modifications, such as quick-propagation (QP) and Delta-bar-Delta, are also discussed. All architectures correlate input variables to output variables through non-linear, weighted, parameterised functions, called neurons. In addition, various training algorithms have been developed in order to minimise the prediction error made by the network. The applications of ANNs in water analysis and water quality assessment are also reviewed. Most of the ANNs works are focused on modelling and parameters prediction. In the case of water quality assessment, extended predictive models are constructed and optimised, while variables correlation and significance is usually estimated in the framework of the predictive or classifier models. On the contrary, ANNs models are not frequently used for clustering/classification purposes, although they seem to be an effective tool. ANNs proved to be a powerful, yet often complementary, tool for water quality assessment, prediction and classification.     

微乳液的热力学性质 I: 芳烃类的侧链链长对微乳液热力学函数影响

本文研究以非离子型表面活性剂-正辛醇-水-芳烃类所组成的微乳液, 探讨醇从油相转移到界面相时的自由能变化, 以及温度对自由能的影响。计算出熵和焓的变化, 发现在实验范围内, 上述热力学函数的对数值与芳烃侧链的碳原子数(n)呈线性关系。这些关系式对微乳液的构成和稳定性的讨论是重要的, 还对几种芳烃异构体所构成的微乳液的热力学函数进行了实验和讨论。     

Natural examples of -complete sets in analysis

The purpose of this paper is to show that given any non-negative real number , the set of entire functions whose order is equal to is -complete, and the set of all sequences of entire functions whose orders converge to is -complete.

     

Identifying the underlying structure and dynamic interactions in a voting network

We analyse the structure and behaviour of a specific voting network using a dynamic structure-based methodology which draws on Q-Analysis and social network theory. Our empirical focus is on the Eurovision Song Contest over a period of 20 years. For a multicultural contest of this kind, one of the key questions is how the quality of a song is judged and how voting groups emerge. We investigate structures that may identify the winner based purely on the topology of the network. This provides a basic framework to identify what the characteristics associated with becoming a winner are, and may help to establish a homogenous criterion for subjective measures such as quality. Further, we measure the importance of voting cliques, and present a dynamic model based on a changing multidimensional measure of connectivity in order to reveal the formation of emerging community structure within the contest. Finally, we study the dynamic behaviour exhibited by the network in order to understand the clustering of voting preferences and the relationship between local and global properties.     

抗坏血酸和尿酸在甘氨酸-壳聚糖修饰玻碳电极上的电化学行为及测定

制备了甘氨酸-壳聚糖复合膜修饰玻碳电极(Gly-CTS/GCE),研究了抗坏血酸(AA)和尿酸(UA)在该修饰电极上的电化学行为。结果表明在pH=5.59的磷酸盐缓冲溶液中,AA、UA在Gly-CTS/GCE上均产生灵敏的不可逆氧化峰,其峰电流与浓度在一定范围内呈良好的线性关系。对AA和UA混合溶液平行测定7次,相对标准偏差分别为4.6%、2.9%,表明该电极重现性和稳定性良好。AA、UA在Gly-CTS/GCE电极上的氧化峰峰电位相差340mV,据此可实现对二者的同时检测,并可应用于实际样品测定。     

Why Restricted Additive Schwarz Converges Faster than Additive Schwarz

Recently a variant of the additive Schwarz (AS) preconditioner, the restricted additive Schwarz (RAS) preconditioner has been introduced, and numerical experiments showed that RAS converges faster and requires less communication than AS. We show in this paper how RAS, which is defined at the matrix level, can be interpreted as an iteration at the continuous level of the underlying problem. This interpretation reveals why RAS converges faster than classical AS.This revised version was published online in October 2005 with corrections to the Cover Date.