SYNTHESIS OF CONDUCTIVE POLYANILINE VIA OXIDATION BY MnO2

A unique process of chemical oxidation polymerization of aniline using manganese dioxide (MnO2) as the oxidizing agent in an aqueous medium is described. The reaction between aniline and MnO2 follows a mechanism by which the organic monomer is oxidized while the metal oxide undergoes reductive dissolution. The effects of the amount of oxidizing agent and aniline, pH and temperature of the reactive system, type of acid on the yield and conductivity of polyaniline are discussed. The resulting polyaniline was characterized by [R and UV-Vis spectrometry. Polyaniline with a conductivity of 12.5 S/cm was obtained using 0.033 tool of aniline oxidized by 0.023 tool MnO2 in the presence of 100 mL of 2.7 mol/L HCI at 25℃ for 4 h.     

Effect of Organic Ligands Used in Sol-Gel Process on the Formation of Mullite

The preparation of mullite by the sol-gel method using organic polydentate ligands and the effect of the raw materials and organic polydentate ligands on the formation of mullite were investigated. Two series of samples were prepared using tetraethoxyorthosilicate (TEOS) and aluminum nitrate nonahydrate, or dibutoxyethylacetoacetatoaluminum (Al(OBu)₂(AcAcEt)) as the silica and alumina sources, respectively, and using ethylene glycol (EG), 1,3-propanediol (PD), 1,3-butanediol (BD), 2-methyl-2, 4-pentanediol (MPD), diethlene glycol monoethyl ether (DEME) and ethoxyethanol as the ligands. When the alumina source was aluminum nitrate nonahydrate, mullite was apt to appear in the order of EG>PD>MPD. When Al(OBu)₂(AcAcEt) was the alumina source, the tendency toward the appearance of mullite crystalline phase was EG>BD>DEME>MPD. Between the two alumina sources, aluminum nitrate nonahydrate gave mullite much easier than Al(OBu)₂(AcAcEt). These relationships were discussed from the viewpoints of the coordination ability of the ligands and the miscibility between the silica and alumina.     

Optimisation of stir bar sorptive extraction for the analysis of volatile phenols in wines

An easy, fast and reliable analytical method is proposed for the determination of the concentration of volatile phenols (ethyl- and vinylphenols) in wines. The novel stir bar sorptive extraction (SBSE) technique is employed, following a simple and fast procedure that allows 15 samples to be extracted simultaneously using very small sample volume. Extracts are desorbed in a thermodesorption system (TDS) coupled on-line to a gas chromatograph-mass spectrometry system. The SBSE offers better recovery and linear regression coefficient (r2) for the four volatile phenols than solid-phase extraction (SPE). The mass spectrometric detection in selected ion monitoring mode contributes to the lower detection limit and good sensibility obtained with this method.     

Cooled internal reflection element for infrared chemical sensing of volatile to semi-volatile organic compounds in the headspace of aqueous solutions

In this study, the cooling effect was applied to an evanescent wave type infrared (IR) chemical sensing method to effectively trap volatile organic compounds (VOCs), which have been absorbed in the hydrophobic film coated around the internal reflection element (IRE). The detection of VOCs in aqueous solutions was taken in the headspace of the aqueous solution. This method eliminates the long-term instability of hydrophobic film soaked in an aqueous solution and the potential spectral interference caused by the matrix of the aqueous solution. Thermal energy has been applied to the aqueous solution to assist in the evaporation of VOCs out of the aqueous matrix. By applying a cooling system to the IRE, the excess thermal energy can be removed leading to more stable IR signals. After examination of organic compounds with vapour pressure (P_v) ranging from 0.017 to 150 Torr, significant differences were found between IR signals from cooled and un-cooled systems. Because the thermal conductivity of the IRE used in IR detection is typically low; the efficiency in removing the thermal energy is limited. By heating the aqueous solutions to different temperatures, the IR signals showed that the sample temperature was limited to around 80 °C. The IR signal determination results for five different volatility organic compounds indicated that the optimal heating temperature was not necessary to match with the volatilities of organic compounds in cooling system. The linear regression coefficient (R²) of the standard curve for sample concentrations in the range 5-200 μg ml⁻¹ was generally higher than 0.991 and the detection limit was around a few hundred ng ml⁻¹, which was two to three times lower than that of un-cooled system.     

Enzymes in Organic Synthesis: Application to the Problems of Carbohydrate Recognition (Part 1)

Carbohydrates on cell surfaces are information molecules. Although only seven or eight monosaccharides are commonly used as building blocks in mammalian systems, the multifunctionality of these monomers can lead to the assembly of an immense variety of complex structures. Millions of different tetrasaccharide structures, for example, can be constructed from this small number of building blocks, if branching, the stereochemistry of glycosidic linkages, and the modification of hydroxyl and amino groups are taken into consideration. Oligosaccharides therefore represent an effective class of biomolecules that code for a vast amount of information required in various biological recognition processes, such as intercellular communication, signal transduction, cell adhesion, infection, cell differentiation, development and metastasis. The pace of development of pharmaceuticals based on carbohydrates has, however, been slower than that based on other classes of biomolecules. Part of the reason is the lack of technologies for the study of complex carbohydrates. There is no method to amplify oligosaccharides for sequence analysis. There is no machine available for automated synthesis of oligosaccharides. In addition, the possibly poor bioavailability and difficulties in the large-scale synthesis of carbohydrates have undoubtedly contributed to this slow pace. The enzymatic and chemoenzymatic methods, especially those based on aldolases and glycosyltransferases, described here appear to be useful for the synthesis of mono- and oligosaccaharides and related molecules. Further advances in glycobiology will probably lead to the development of new technologies for the study of carbohydrate recognition and for the synthesis of bioactive carbohydrates and mimetics to control the recognition processes.     

Prediction of soil organic carbon partition coefficients by soil column liquid chromatography

To avoid the limitation of the widely used prediction methods of soil organic carbon partition coefficients (KOC) from hydrophobic parameters, e.g., the n-octanol/water partition coefficients (KOW) and the reversed phase high performance liquid chromatographic (RP-HPLC) retention factors, the soil column liquid chromatographic (SCLC) method was developed for KOC prediction. The real soils were used as the packing materials of RP-HPLC columns, and the correlations between the retention factors of organic compounds on soil columns (ksoil) and KOC measured by batch equilibrium method were studied. Good correlations were achieved between ksoil and KOC for three types of soils with different properties. All the square of the correlation coefficients (R2) of the linear regression between log ksoil and log KOC were higher than 0.89 with standard deviations of less than 0.21. In addition, the prediction of KOC from KOW and the RP-HPLC retention factors on cyanopropyl (CN) stationary phase (kCN) was comparatively evaluated for the three types of soils. The results show that the prediction of KOC from kCN and KOW is only applicable to some specific types of soils. The results obtained in the present study proved that the SCLC method is appropriate for the KOC prediction for different types of soils, however the applicability of using hydrophobic parameters to predict KOC largely depends on the properties of soil concerned.     

SNAP-tag蛋白标签技术与荧光分析法在蛋白原位分析中的联合应用

为将生物体内微观的蛋白行为可视化并以宏观信号呈现出来对蛋白进行实时、动态分析，借助SNAP-tag蛋白标签技术与有机小分子荧光染料，构建了一系列用于活细胞内实时监测目标蛋白的免洗荧光探针。标签蛋白SNAP-tag能够特异性识别探针中的苄基鸟嘌呤，从而使目标蛋白共价连接上荧光团（萘酰亚胺），携带上荧光信使。此外，由于萘酰亚胺从水环境中被牵引至SNAP-tag蛋白的疏水空腔，其荧光信号呈现出2~13倍的增强。通过SNAP-tag标签蛋白与目标蛋白的融合，该荧光探针实现了对活细胞内线粒体蛋白CoX8A及核内蛋白H2B特异性识别，在免洗条件下完成了对目标蛋白的实时追踪及原位分析。     

Optimization of the Microwave-Assisted Saponification and Extraction of Organic Pollutants from Marine Biota Using Experimental Design and Artificial Neural Networks

Several improvements in sample pretreatment for the determination of organic pollutants (i.e. n-alkanes, polycyclic aromatic hydrocarbons, PAHs) in marine biota (mussels) are presented. The use of liquid nitrogen and homogenization of the samples are shown to be an alternative to the time consuming liophilization step required for the analysis of biota samples. Microwave-assisted hydrolysis and extraction are combined to isolate organic pollutants (19 n-alkanes and 27 PAHs) from biota matrices. Experimental design (ED) and artificial neural networks (ANNs) were used to optimize the experimental conditions. NIST-CRM 2978 was used to test the validity of the developed method which shows a good agreement with certified values.     

Complexation of Ni, Cu, Zn, and Cd by DOC in some metal-impacted freshwater lakes: a comparison of approaches using electrochemical determination of free-metal-ion and labile complexes and a computer speciation model, WHAM V and VI

Complexation of Ni(II), Cu(II), Zn(II), and Cd(II) by dissolved organic carbon (DOC) in some freshwater lakes in Rouyn-Noranda, Québec, Canada, where they were impacted by effluents from a nearby copper smelter, was measured by kinetic and equilibrium methods using cathodic and anodic stripping voltammetry. The measured free-metal-ion and labile metal-complex concentrations were compared with the predictions made by a widely-used computer speciation model, the Windermere Humic Aqueous Model (WHAM): WHAM V and its improved version WHAM VI. If it is assumed that 65% of the DOC is “active”, i.e. behaving as isolated humic substances such as fulvic acid, both versions of WHAM are able to predict the labile and free-metal-ion concentrations of Ni, Zn, and Cd reasonably well; however, both underestimate the free-copper-ion concentration by one to two orders of magnitude. WHAM VI is generally better than or equal to WHAM V for successfully predicting most of the free-metal-ion concentrations. The modelled competition by Al(III) and Fe(III) in the lake surface waters showed that in most cases Cu(II) was most affected by this competition. WHAM VI predicts a larger effect from the Al(III) and Fe(III) competition than does WHAM V.