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鈥?4鈥?/sup> Proce

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• 作者：Graham P. Morris ; Alexandr N. Simonov ; Elena A. Mashkina ; Rafel Bordas ; Kathryn Gillow ; Ruth E. Baker ; David J. Gavaghan ; Alan M. Bond
• 刊名：Analytical Chemistry
• 出版年：2013
• 出版时间：December 17, 2013
• 年：2013
• 卷：85
• 期：24
• 页码：11780-11787
• 全文大小：345K
• 年卷期：v.85,no.24(December 17, 2013)
• ISSN：1520-6882

文摘

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鈥?4鈥?/sup> 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), 伪 (charge transfer coefficient), R_u (uncompensated resistance), and C_dl (double layer capacitance). The automated method of analysis employed time domain optimization and Bayesian statistics. This and all other methods assumed the Butler鈥揤olmer model applies for electron transfer kinetics, planar diffusion for mass transport, Ohm鈥檚 Law for R_u, and a potential-independent C_dl 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鈥搕heory comparisons. Remarkable consistency of parameter evaluation was achieved, although the fully automated time domain method provided consistently higher 伪 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鈥?4鈥?/sup> process, but remarkably, all fit the quasi-reversible model satisfactorily.}