Electrodeposition of polyaniline, poly(2-iodoaniline), and poly(aniline-co-2-iodoaniline) on steel surfaces and corrosion protection of steel

Polyaniline (PANi), poly(2-iodoaniline) (PIANi), and poly(aniline-co-2-iodoaniline) (co-PIANi) were synthesized using cyclic voltammetry in acetonitrile solution containing tetrabuthylammonium perchlorate (TBAP) and perchloric acid (HClO₄) on 304-stainless steel electrodes. Adherent and black polymer films were obtained on the electrodes. The structure and properties of these polymer films were characterized by FTIR and UV-vis spectroscopy and electrochemical method. The corrosion performance of PANi, PIANi, and co-PIANi coated electrodes were investigated in 0.5 M hydrochloric acid (HCl) solutions by potentiodynamic polarization technique, open circuit potential-time curves and electrochemical impedance spectroscopy, EIS. It was found that the PANi film could provide much better protection than PIANi, and co-PIANi and PANi films have barrier property as well as acting as passivator. On the other hand PIANi and co-PIANi films are acting as barrier coatings which were related with the prevention of cathodic reaction taking place at metal\electrolyte interface. EIS measurement shows that every coating gives protection efficiency of greater than 75% after 48 h of immersion time in corrosive test solution.     

Quadrupole relaxation enhancement and polarisation transfer in DMSO solution of [Bi(NO3)3(H2O)3]*18-crown-6 in solid state

ABSTRACT

¹H spin-lattice relaxation studies have been performed for pure [Bi(NO₃)₃(H₂O)₃]*18-crown-6 in powder and its solution in dimethyl sulfoxide (DMSO). The experiments have been carried out in the frequency range of 10?kHz–30?MHz and the temperature range of 240–277?K; at 277?K the solution is already frozen. The ¹H relaxation of pure [Bi(NO₃)₃(H₂O)₃]*18-crown-6 has been interpreted in terms of three dynamical processes. Quadrupole Relaxation Enhancement effects have been observed in the frozen DMSO solution of [Bi(NO₃)₃(H₂O)₃]*18-crown-6. The specific mechanisms of the ¹H spin-lattice relaxation enhancement have been discussed distinguishing between effects caused by time independent (residual) and fluctuating ¹H-²⁰⁹Bi dipole-dipole interactions.     

RLT-POS: Reformulation-Linearization Technique-based optimization software for solving polynomial programming problems

In this paper, we introduce a Reformulation-Linearization Technique-based open-source optimization software for solving polynomial programming problems (RLT-POS). We present algorithms and mechanisms that form the backbone of RLT-POS, including constraint filtering techniques, reduced RLT representations, and semidefinite cuts. When implemented individually, each model enhancement has been shown in previous papers to significantly improve the performance of the standard RLT procedure. However, the coordination between different model enhancement techniques becomes critical for an improved overall performance since special structures in the original formulation that work in favor of a particular technique might be lost after implementing some other model enhancement. More specifically, we discuss the coordination between (1) constraint elimination via filtering techniques and reduced RLT representations, and (2) semidefinite cuts for sparse problems. We present computational results using instances from the literature as well as randomly generated problems to demonstrate the improvement over a standard RLT implementation and to compare the performances of the software packages BARON, COUENNE, and SparsePOP with RLT-POS.     

The impact of an out‐of‐school STEM education program on students’ attitudes toward STEM and STEM careers

There is an increasing awareness of out‐of‐school program value in enhancing student interest and understanding of science, technology, engineering, and mathematics (STEM). This study examined the impact of an out‐of‐school STEM education program on student attitudes toward STEM disciplines and STEM careers. A STEM education program implemented at a public research university was designed to integrate STEM disciplines with hands‐on problem‐based activities. Design features included authentic learning contexts, engineering design processes, and content integration. Data sources included an attitude survey and interviews conducted with forty sixth grade middle school student participants. The analysis revealed significant differences between pre and posttests on student attitudes toward personal and social implications of STEM, science and engineering learning, and their relationship to STEM. Findings showed that the program contributed to students’ developing interest in STEM fields, and helped them make connections between schoolwork and daily lives. Recommendations for future research on out‐of‐school STEM education programs were discussed.     

A One‐Dimensional Pyrazine Bridged Copper(II)‐Saccharinato Coordination Polymer

A one‐dimensional copper(II) complex {[Cu(sac)₂(μ‐pyz)(H₂O)]·H₂O}_n ( 1 ) (pyz = pyrazine, and sac = saccharinate) has been synthesized and characterized by elemental analysis, IR spectroscopy, thermal and single crystal X‐ray analyses. Complex 1 crystallizes in the triclinic space group . The [Cu(sac)₂(H₂O)] units are bridged by pyz leading to a one‐dimensional alternating chain in which the copper(II) ions exhibit a distorted square–pyramidal coordination of CuN₄O. The intradimer Cu···Cu distance is 6.881Å, while interdimer Cu···Cu distance is 7.066Å. The supramolecular interactions are mainly controlled by the sac anion and water molecules. The individual chains are linked by strong OW–H···O(sac) hydrogen bonds into a two‐dimensional layers, which are further arranged in a three‐dimensional supramolecular network by aromatic π(sac)···π(sac) stacking interactions and CH···π(pyz) interactions. Thermal analysis of complex 1 shows that the decompositions of the aqua, pyz and sac ligands are observed as distinct steps on the DTA and TG curves.     

A New HPLC Method with UV Detection for the Determination of Carnosol in Human Plasma and Application to a Pharmacokinetic Study

Chromatographia - This article aims to present a simple and sensitive, HPLC–UV method, which was developed to determine carnosol in human plasma samples. Chromatographic separation was...     

A robust alternative to the ratio estimator under non-normality

In sampling theory, the traditional ratio estimator is the most common estimator of the population mean when the correlation between study and auxiliary variables is positively high. We introduce a new ratio-type estimator based on the order statistics of a simple random sample. We show that this new estimator is considerably more efficient than the traditional ratio estimator under non-normality, and remarkably robust to data anomalies such as presence of outliers in data sets.     

Goldie Extending Modules

In this article, we define a module M to be 𝒢-extending if and only if for each X ≤ M there exists a direct summand D of M such that X ∩ D is essential in both X and D. We consider the decomposition theory for 𝒢-extending modules and give a characterization of the Abelian groups which are 𝒢-extending. In contrast to the charac-terization of extending Abelian groups, we obtain that all finitely generated Abelian groups are 𝒢-extending. We prove that a minimal cogenerator for 𝒢od-R is 𝒢-extending, but not, in general, extending. It is also shown that if M is (𝒢-) extending, then so is its rational hull. Examples are provided to illustrate and delimit the theory.     

New exploratory clustering tool

This paper describes a clustering method on three‐way arrays making use of an exploratory visualization approach. The aim of this study is to cluster samples in the object mode of a three‐way array, which is done using the scores (sample loadings) of a three‐way factor model, for example, a Tucker3 or a PARAFAC model. Further, tools are developed to explore and identify reasons for particular clusters by visually mining the data using the clustering results as guidance. We introduce a three‐way clustering tool and demonstrate our results on a metabolite profiling dataset. We explore how high performance liquid chromatography (HPLC) measurements of commercial extracts of St. John's wort (natural remedies for the treatment of mild to moderate depression) differ and which chemical compounds account for those differences. Using common distance measures, for example, Euclidean or Mahalanobis, on the scores of a three‐way model, we verify that we can capture the underlying clustering structure in the data. Beside this, by making use of the visualization approach, we are able to identify the variables playing a significant role in the extracted cluster structure. The suggested approach generalizes straightforwardly to higher‐order data and also to two‐way data. Copyright © 2007 John Wiley & Sons, Ltd.