Voltammetric Thin-Layer Ionophore-Based Films: Part 1. Experimental Evidence and Numerical Simulations
| Autor: | Dajing Yuan, Eric Bakker, Gastón A. Crespo, Maria Cuartero |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
chemistry.chemical_classification
Stripping (chemistry) Chemistry 010401 analytical chemistry Potentiometric titration Analytical chemistry Ionophore 02 engineering and technology Polymer 021001 nanoscience & nanotechnology Electrochemistry 01 natural sciences 0104 chemical sciences Analytical Chemistry Ion Membrane ddc:540 Potentiometric sensor 0210 nano-technology |
| Zdroj: | Analytical Chemistry, Vol. 89, No 1 (2017) pp. 586-594 |
| ISSN: | 1520-6882 0003-2700 |
| Popis: | Voltammetric thin layer (~200 nm) ionophore-based polymeric films have recently emerged as a promising approach to acquire multi-ion information about the sample, in analogy to performing multiple potentiometric measurements with individual membranes. They behave under two different regimes that depend on the ion concentration. A thin layer control (no mass transport limitation of the polymer film or solution) is identified for ion concentrations higher than 10 µM in which case the peak potential serves as the readout signal in analogy to a potentiometric sensor. On the other hand, ion transfer at lower concentrations is chiefly controlled by diffusional mass transport from the solution to the sensing film, resulting in an increase of peak current with ion concentration. This concentration range is suitable for electrochemical ion transfer stripping analysis. The transition between the two mentioned scenarios is here explored experimentally using a silver selective membrane as a highly selective proof-of-concept under different conditions (variation of ion concentration in the sample from 0.1 µM to 1 mM, scan rate from 25 to 200 mV s-1, and angular frequency from 100 to 6400 rpm). Apart from experimental evidence, a numerical simulation is developed that considers an idealized conducting polymer behavior and permits one to predict experimental behavior under diffusion or thin layer control. |
| Databáze: | OpenAIRE |
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