A rational study of transduction mechanisms of different materials for all solid contact-ISEs

Author:

Hashem Heba M.,Abdallah A. B.

Abstract

AbstractThe new era of solid contact ion selective electrodes (SC-ISEs) miniaturized design has received an extensive amount of concern. Because it eliminated the requirement for ongoing internal solution composition optimization and created a two-phase system with stronger detection limitations. Herein, the determination of venlafaxine HCl is based on a comparison study between different ion- to electron transduction materials (such as; multiwalled carbon nanotubes (MWCNTs), polyaniline (PANi), and ferrocene) and illustrating their mechanisms in their applied sensors. Their different electrochemical features (such as bulk resistance (Rb**), double-layer capacitance (Cdl), geometric capacitance (Cg), and specific capacitance (Cp)) were evaluated and discussed by using the Electrochemical Impedance Spectroscopy (EIS), Chronopotentiometry (CP), and Cyclic Voltammetry (CV) experiments. The results indicated that each transducer's influence on the proposed sensor's electrochemical characteristics is determined by their unique chemical and physical properties. The electrochemical features vary for different solid contact materials used in transduction mechanisms. The results confirm that the MWCNT sensor revealed the best electrochemical behavior with the potentiometric response of a near-Nernestian slope of 56.1 ± 0.8 mV/decade with detection limits of 3.8 × 10−6 mol/L (r2 = 0.999) and a low potential drift (∆E/∆t) of 34.6 µV/s. Also, the selectivity study was performed in the presence of different interfering species either in single or complex matrices. This demonstrates excellent selectivity, stability, conductivity, and reliability as a VEN-TPB ion pair sensor for accurately measuring VEN in its various formulations. The proposed method was compared to HPLC reported technique and confirmed no significant difference between them. So, the proposed sensors fulfill their solutions' demand features for VEN appraisal.

Funder

Mansoura University

Publisher

Springer Science and Business Media LLC

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