The performance of any electrocatalytic material can be determined by fabricating the material into electrodes and measuring the current density as a function of overpotential, ideally under standardised conditions [4, 5]. While the overpotential at a certain current density is the only parameter required to determine if the developed electrocatalytic material has any practical relevance, in most cases it is also useful to understand why the material has the observed electrocatalytic performance. This understanding can then (in theory) be used to either design better electrocatalytic materials or enhance the underlying theory of the electrode reactions of interest. Such understanding may come from electrochemical techniques like cyclic voltammetry and electrochemical impedance spectroscopy, or in-situ spectroscopic or structural analysis of the electrocatalytic material, or by fitting experimental data to microkinetic models.
Given that electrocatalytic reactions are multi-step processes [6], understanding how electrode performance is related to the surface coverage of reaction intermediates and the rate determining step is critical in designing better electrocatalysts. However as the reaction intermediates during the hydrogen and oxygen evolution reactions are similar to species within the electrolyte (e.g. adsorbed H, OH, O), directly quantifying these surface bound intermediates by spectroscopy is difficult [7]. Microkinetic models avoid this challenge by allowing the simulation of steady-state or dynamic electrode behavior for a given set of kinetic parameters. This approach was successfully used in some of the earliest work on the hydrogen and oxygen evolution reactions by showing that the reaction mechanism and rate determining steps can be differentiated by measuring the Tafel slope and reaction order with respect to pH [8, 9]. More recent work shows that these microkinetic models can also discover unexpected behaviour such as non-Tafel-like polarisation curves [10, 11].
In the present work, the simulation of steady-state polarization curves and chronoamperometry hydrogen and oxygen evolution reactions following standard reaction mechanisms is discussed. These simulations show that under some conditions, unexpected Tafel slopes can be observed and that multiple sets of kinetic parameters can result in almost identical polarisation curves. The latter clearly highlights the difficultly in determining kinetic parameters from steady-state experimental data. To address this, we show how the simulation of dynamic electrode behaviour can be used to differentiate between sets of kinetic parameters.
References:
- J. Greeley, T.F. Jaramillo, J. Bonde, I. Chorkendorff, and J.K. Nørskov, Nature Materials, 2006. 5(11): p. 909-13.
- G.M. Whitesides and G.W. Crabtree, Science, 2007. 315(5813): p. 796-798.
- Z.W. Seh, et al., Science, 2017. 355(6321).
- C.C.L. McCrory, S. Jung, J.C. Peters, and T.F. Jaramillo, Journal of the American Chemical Society, 2013. 135(45): p. 16977-16987.
- Y. Garsany, J. Ge, J. St-Pierre, R. Rocheleau, and K.E. Swider-Lyons, Journal of the Electrochemical Society, 2014. 161(5): p. F628-F640.
- M.T.M. Koper, Journal of Electroanalytical Chemistry, 2011. 660(2): p. 254-260.
- M. Markiewicz, C. Zalitis, and A. Kucernak, Electrochimica Acta, 2015. 179: p. 126-136.
- J.O.M. Bockris and E.C. Potter, Journal of the Electrochemical Society, 1952. 99(4): p. 169-186.
- J.O.M. Bockris, The Journal of Chemical Physics, 1956. 24(4): p. 817-827.
- A.T. Marshall and L. Vaisson-Béthune, Electrochemistry Communications, 2015. 61: p. 23-26.
- M.R. Gennero de Chialvo and A.C. Chialvo, Electrochimica Acta, 1998. 44(5): p. 841-851.