RESUMEN
In electrocatalysis, mechanistic analysis of reaction rate data often relies on the linearization of relatively simple rate equations; this is the basis for typical Tafel and reactant order dependence analyses. However, for more complex reaction phenomena, such as surface coverage effects or mixed control, these common linearization strategies will yield incomplete or uninterpretable results. Cohesive kinetic analysis, which is often used in thermocatalysis and involves quantitative model fitting for data collected over a wide range of reaction conditions, requires more data but also provides a more robust strategy for interrogating reaction mechanisms. In this work, we report a robotic system that improves the experimental workflow for collecting electrochemical rate data by automating sequential testing of up to 10 electrochemical cells, where each cell can have a different electrode, electrolyte, gas-phase reactant composition, and applied voltage. We used this system to investigate the mechanism of carbon dioxide electroreduction to carbon monoxide at several immobilized metal tetrapyrroles. Specifically, at cobalt phthalocyanine (CoPc), cobalt tetraphenylporphyrin (CoTPP), and iron phthalocyanine (FePc), we see signatures of complex reaction mechanisms, where observed bicarbonate and CO2 order dependences change with applied potential. We illustrate how phenomena such as electrolyte poisoning and potential-dependent degrees of rate control can explain the observed kinetic behaviors. Our mechanistic analysis suggests that CoPc and CoTPP share a similar reaction mechanism, akin to one previously proposed, whereas the mechanism for FePc likely involves a species later in the catalytic cycle as the most abundant reactive intermediate. Our study illustrates that complex reaction mechanisms that are not amenable to common Tafel and order dependence analyses may be quite prevalent across this class of immobilized metal tetrapyrrole electrocatalysts.
RESUMEN
The Tafel slope is a key parameter often quoted to characterize the efficacy of an electrochemical catalyst. In this paper, we develop a Bayesian data analysis approach to estimate the Tafel slope from experimentally-measured current-voltage data. Our approach obviates the human intervention required by current literature practice for Tafel estimation, and provides robust, distributional uncertainty estimates. Using synthetic data, we illustrate how data insufficiency can unknowingly influence current fitting approaches, and how our approach allays these concerns. We apply our approach to conduct a comprehensive re-analysis of data from the CO2 reduction literature. This analysis reveals no systematic preference for Tafel slopes to cluster around certain "cardinal values" (e.g. 60 or 120 mV/decade). We hypothesize several plausible physical explanations for this observation, and discuss the implications of our finding for mechanistic analysis in electrochemical kinetic investigations.
RESUMEN
In this manuscript, we examine the role of image charge effects on the electrostatic potential fluctuations experienced by ionic species in the vicinity of an electrode surface. We combine simulation and theory to quantify these fluctuations and how they vary with distance from the electrode surface. We observe that the potential distribution narrows significantly for species within a few electrolyte screening lengths of the electrode. We attribute this narrowing to the effects of image charge fluctuations originating from the polarization response of the electrode. We show that the physical consequences of these image charge effects can be captured in the context of a simple analytical field theory with anti-symmetric boundary conditions. We contextualize these results by discussing their implications for rates of Marcus-like outer-sphere interfacial electron transfer.