The modification of the carbon paste electrode (CPE) with the amphiphile hexadecyl sulfonic acid (sodium salt) has permitted the development of a stable and anal>Tically useful functionalized electrode. The electrochemical characterization of the modified electrode (potential range, background current, stability) has been investigated by cyclic voltammetry in aqueous media with different buffer compositions and in hydro-organic media and the results compared favorably with the conventional carbon paste electrode. The characterization of the sulfonated functionalities and their influence in the electrode behavior has been pointed out using linear scan and adsorptive voltammetry by studying two model compounds: promethazine and ascorbic acid. The marked influence of the pH, ionic strength, and nature of the buffer cation on the shape (potential and intensity) of the voltammetric curves confirmed the structure of the modified electrode interface, i.e., electrode bearing strong cation exchange functionalities. Scanning electron microscopy and optical microscopic observations of the CPE and modified CPE showed a higher density of graphite particles not covered by liquid paraffin at the latter.

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The hexadeqlsulfonic acid (sodium salt) modified carbon paste electrode (HDSNa-CPE) has been studied in batch and flowing systems, and its analytical performance has been established in comparison with a conventional carbon paste electrode (CPE). Amperornet?, linear scan, and preconcentration voltammetry have been used for the investigation of several analytes of pharmacological interest. Because of the presence of surface hnctionalities, markedly different electrode responses have been observed at the HDSNa-CPE depending on the nature (hydrophobicity and charge) of the investigated molecule. The HDSNa-CPE showed, in linear scan voltammetry and for all the species investigated. higher responses compared to the CPE. The HDSNa-CPE showed important current enhancements in voltammetric analysis of hydrophobic organic cations in acidic media and at low ionic strength.

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The aim of this work was to develop an effective quantitative relationship model using support vector machines for the synthesis of phosphocalcic hydroxyapatite by precipitation from a calcium carbonate solution and a phosphoric acid solution. The model was created using a set of factors consisting of the pH of the reaction solution, the Ca/P molar ratio of the reagents, the reaction time and the initial concentration of calcium. Previous studies modelled these relationships using different classification techniques. In this paper, a novel approach based on support vector machines (SVMs) is introduced. This latter approach yields the best result compared to polynomial regression (PR), linear regression (LR) and artificial neural networks (ANN). In addition, the contribution of each descriptor is evaluated. Thus, the proposed method can be successfully used to predict the Ca/P analysis directly from the considered factors.

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