A Comparison of Fully Automated Methods of Data Analysis and Computer Assisted Heuristic Methods in an Electrode Kinetic Study of the Pathologically Variable [Fe(CN) 6 ] 3–/4– Process by AC Voltammetry

Type
Article

Authors
Morris, Graham P.
Simonov, Alexandr N.
Mashkina, Elena A.
Bordas, Rafel
Gillow, Kathryn
Baker, Ruth E.
Gavaghan, David J.
Bond, Alan M.

KAUST Grant Number
KUK-C1-013-04

Online Publication Date
2013-12-03

Print Publication Date
2013-12-17

Date
2013-12-03

Abstract
Fully automated and computer assisted heuristic data analysis approaches have been applied to a series of AC voltammetric experiments undertaken on the [Fe(CN)6]3-/4- process at a glassy carbon electrode in 3 M KCl aqueous electrolyte. The recovered parameters in all forms of data analysis encompass E0 (reversible potential), k0 (heterogeneous charge transfer rate constant at E0), α (charge transfer coefficient), Ru (uncompensated resistance), and Cdl (double layer capacitance). The automated method of analysis employed time domain optimization and Bayesian statistics. This and all other methods assumed the Butler-Volmer model applies for electron transfer kinetics, planar diffusion for mass transport, Ohm's Law for Ru, and a potential-independent Cdl model. Heuristic approaches utilize combinations of Fourier Transform filtering, sensitivity analysis, and simplex-based forms of optimization applied to resolved AC harmonics and rely on experimenter experience to assist in experiment-theory comparisons. Remarkable consistency of parameter evaluation was achieved, although the fully automated time domain method provided consistently higher α values than those based on frequency domain data analysis. The origin of this difference is that the implemented fully automated method requires a perfect model for the double layer capacitance. In contrast, the importance of imperfections in the double layer model is minimized when analysis is performed in the frequency domain. Substantial variation in k0 values was found by analysis of the 10 data sets for this highly surface-sensitive pathologically variable [Fe(CN) 6]3-/4- process, but remarkably, all fit the quasi-reversible model satisfactorily. © 2013 American Chemical Society.

Citation
Morris GP, Simonov AN, Mashkina EA, Bordas R, Gillow K, et al. (2013) A Comparison of Fully Automated Methods of Data Analysis and Computer Assisted Heuristic Methods in an Electrode Kinetic Study of the Pathologically Variable [Fe(CN) 6 ] 3–/4– Process by AC Voltammetry . Anal Chem 85: 11780–11787. Available: http://dx.doi.org/10.1021/ac4022105.

Acknowledgements
This publication is based on work supported by Award No. KUK-C1-013-04, made by King Abdullah University of Science and Technology (KAUST). Financial support from the Australian Research Council is also gratefully acknowledged. Authors are grateful to Mr. Blair Bethwaite (Monash eResearch Centre, Monash University, Australia), Dr. Jeff Tan (IBM Research, Melbourne, Australia), and Prof. David Abramson (University of Queensland, Australia) for their generous assistance with processing experimental data using Nimrod tools.

Publisher
American Chemical Society (ACS)

Journal
Analytical Chemistry

DOI
10.1021/ac4022105

PubMed ID
24160752

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