Enhanced Electrochemical Sensor for Electrocatalytic Glucose Analysis in Orange Juices and Milk by the Integration of the Electron-Withdrawing Substituents on Graphene/Glassy Carbon Electrode.

In this work, a novel electrochemical sensor was developed by electron-withdrawing substituent modification of 1-phenyl-3-methyl-4-(4-fluorobenzoyl)-5-pyrazolone on a graphene-modified glassy carbon electrode (HPMpFP-graphene/GCE) for glucose detection. The results of characterizations using a scanning electron microscope, Fourier transform infrared spectroscopy, Raman spectroscopy, and nuclear magnetic resonance spectroscopy showed the successful fabrication of HPMpFP-graphene nanocomposite, which served as an electroactive probe for glucose detection. The electron transfer ability of HPMpFBP-graphene/GCE has been successfully revealed using cyclic voltammetry and electrochemical impedance spectroscopy results. The good electrochemical performance was shown by well-defined peak currents of square wave voltammetry under various parameters, including pH, HPMpFP and graphene composition, and scan rate effect. A high electrochemically evaluated surface area using chronoamperometry suggested that the present glucose detection response was intensified. The chronoamperometry results at a work potential of 0.4 V presented a wide linear range of 1 × 103-90 µM and 88-1 µM with 0.74 µM (S/N = 3) as the detection limit. An acceptable recovery has been revealed in the real sample analysis. The electrochemical sensing behaviour of the composite indicates that it may be a promising candidate for a glucose sensor and it significantly extends the range of applications in the electrochemical field.

Carboxymethyl Cellulose Hydrogel Based Formulations of Zinc Hydroxide Nitrate-Sodium Dodecylsulphate-Bispyribac Nanocomposite: Advancements in Controlled Release Formulation of Herbicide.

The usefulness of carboxymethyl cellulose (CMC) as a matrix material in enhancing the controlled release formulations of bispyribac (BP) herbicide from the interlayer gallery of zinc hydroxide nitratesodium dodecylsulphate-bispyribac (ZHN-SDS-BP) nanocomposite was investigated. The CMC coated nanocomposite, ZHN-SDS-BP-CMC was characterised using several instruments for the determination of its physicochemical properties. The release rates of the BP were measured using a UV spectrophotometer, and the aqueous solutions containing PO3-4 , SO2-4 and Cl- were selected as release media in the release studies so as to mimic the real conditions of environmental soil. Significant release time delays, triggered by the gelation forming ability and hygroscopic nature of CMC, were observed in all release media, and the release processes were found to behave in a concentration-dependent manner in all release media. Fitting the release data into several kinetic models demonstrated that release in aqueous solutions of Na3PO4 and Na2SO4 was governed by pseudo second order processes, whereas the release in an aqueous NaCl solution was governed by the parabolic diffusion kinetic model. The potential of CMC in prolonging the release of BP from ZHN-SDS-BP-CMC can potentially help in reducing the pollution resulting from the overuse of pesticides.

Spatial and temporal air quality pattern recognition using environmetric techniques: a case study in Malaysia.

The objective of this study is to identify spatial and temporal patterns in the air quality at three selected Malaysian air monitoring stations based on an eleven-year database (January 2000-December 2010). Four statistical methods, Discriminant Analysis (DA), Hierarchical Agglomerative Cluster Analysis (HACA), Principal Component Analysis (PCA) and Artificial Neural Networks (ANNs), were selected to analyze the datasets of five air quality parameters, namely: SO2, NO2, O3, CO and particulate matter with a diameter size of below 10 µm (PM10). The three selected air monitoring stations share the characteristic of being located in highly urbanized areas and are surrounded by a number of industries. The DA results show that spatial characterizations allow successful discrimination between the three stations, while HACA shows the temporal pattern from the monthly and yearly factor analysis which correlates with severe haze episodes that have happened in this country at certain periods of time. The PCA results show that the major source of air pollution is mostly due to the combustion of fossil fuel in motor vehicles and industrial activities. The spatial pattern recognition (S-ANN) results show a better prediction performance in discriminating between the regions, with an excellent percentage of correct classification compared to DA. This study presents the necessity and usefulness of environmetric techniques for the interpretation of large datasets aiming to obtain better information about air quality patterns based on spatial and temporal characterizations at the selected air monitoring stations.