Extension of dc transient techniques to reactions with a potential dependent charge transfer coefficient
✍ Scribed by Z. Nagy; G.K. Leaf; M. Minkoff; R.H. Land
- Publisher
- Elsevier Science
- Year
- 1988
- Tongue
- English
- Weight
- 480 KB
- Volume
- 33
- Category
- Article
- ISSN
- 0013-4686
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✦ Synopsis
The evaluation of data from dc transient measurements invariably involves comparison of the experimental results with the predictions of a theoretical model. In the past, these models were usually based on the Butler-Volmer equation, with the assumption that the charge transfer coeflicient (0~) is constant. The Marcus theory of charge transfer predicts a linear variation of OL with electrode potential; therefore, it is important to examine the problems in the use of the dc relaxation techniques caused by a potential dependent a, and to examine possible ways to detect and to overcome these problems. An error analysis was carried out, and it was concluded that the dc transient techniques cannot be used for the measurement of kmerrcs of electrode reactions if the charge transfer coefficient of the reaction is potential dependent and the potential excursion during the transient is large enough to cause an appreciable variation of a, unless the potential dependence of OL is explicitly included in the data evaluation model. While this effect is self explanatory for those transient techniques where the potential is not the controlled variable (eg, galvanostatic and coulostatic techniques), large errors can also occur for the potentiostatic techniques (where the potential is the controlled variable) ifthe reaction is fast and the uncompensated solution resistance is large. It was also shown that an all numerical data evaluation method based on multidimensional, non-linear, least squares curve fitting calculations coupled with a numerical differential equation solver routine can extend the usefulness of the dc relaxation techniques to reactions having a potential dependent charge transfer coefficient provided a functional dependence of OL on the potential can be included in the data evaluation model.