(521eb) Are Microkinetic Predictions of (Electrocatalytic) Dynamic Rate Enhancement Robust to Errors in Scaling Relations?

Cost-competitive production of sustainable fuels and chemicals requires the discovery of higher-performance catalysts, among other challenges. One proposed strategy for enhancing catalyst activity is programmable catalysis, in which temporal modulation of catalysts is predicted to promote reaction rates above that of a so-called static catalyst. Several microkinetic analyses by our group and others, including both thermocatalytic^[1,2] and electrocatalytic^[3] reactions, have predicted varying degrees of rate enhancement; the exact performance depends on the specific system under investigation. However, it is unclear how uncertainty in the model parameters propagates into the predicted performance of these programmable catalysts. In this work, we investigate how uncertainty in thermodynamic and kinetic scaling relations impacts the predicted rate enhancement of electrocatalytic series reactions. We quantify this uncertainty impact using a distributed evaluation of local sensitivity analysis (DELSA),^[4] where the parameter space is determined from a review of electrocatalytic activation energies reported in the literature and sampled quasi-randomly. We compare our results to those of static (thermo)catalysts, for which uncertainties in rate predictions can span several orders of magnitude,^[5] and identify cases where programmable electrocatalysts significantly enhance rates. Finally, we note that incorporation of parameter uncertainty in microkinetic models of electrocatalysis is especially important because the activation barriers of such reactions are not as well understood as thermochemistry due to the additional complexities of modeling electrochemical systems.

[1] ACS Catal. 2019, 9, 6929.

[2] Sci. Adv. 2022, 8, eabl6576.

[3] Chem Catalysis 2022, 2, 3497.

[4] AIChE J. 2022, 68, e17653.

[5] J. Catal. 2016, 338, 273.