A diffusion model for cyclic voltammetry with nanostructured electrode surfaces
Date of Award
2014
Degree Name
M.S. in Chemical Engineering
Department
Department of Chemical and Materials Engineering
Advisor/Chair
Advisor: Kevin J. Myers
Abstract
Claims made by literature use models that do not account for mass transport that is likely to affect the cyclic voltammetric response of nanostructured electrodes. This response is generally assumed to be electrocatalytic in nature. Recent research has suggested that mass transfer must have a combined effect on the increased current reported in cyclic voltammetry, however, no model exists that sheds light on these effects. As nanostructured electrodes have become standard for numerous applications, it would be to the benefit of these applications that a more fundamental understanding exists.Fundamental transport is applied to semi-infinite and thin-layer diffusion regions to estimate the corresponding diffusivities. The derivation parallels the previous work by Nicholson and thin layer diffusion theorized by Streeter. The model fits voltammetric data from common redox reactions whose bulk diffusivities and electron rate transfer parameters are readily accepted in literature. The results estimate an effective thin layer diffusivity lower than the bulk diffusivity due to the nature of hindered pore diffusion. The diffusion model more accurately describes the diffusion conditions that occur as a result of nanomodified electrode structures, and can be used to optimize an electrode structure to maximize its electrochemical efficiency.
Keywords
Nanostructured materials Surfaces, Thin films Electric properties, Electrodes Design and construction, Mathematics, Materials Science, Chemical Engineering, cyclic voltammetry, diffusion model, nanomodified electrodes, reversible kinetics, electrochemistry
Rights Statement
Copyright © 2014, author
Recommended Citation
Brubaker, Joel Patrick, "A diffusion model for cyclic voltammetry with nanostructured electrode surfaces" (2014). Graduate Theses and Dissertations. 763.
https://ecommons.udayton.edu/graduate_theses/763