Electrifying Hydroformylation Catalysts Exposes Voltage-Driven C-C Bond Formation.

Electrochemical reactions can access a significant range of driving forces under operationally mild conditions and are thus envisioned to play a key role in decarbonizing chemical manufacturing. However, many reactions with well-established thermochemical precedents remain difficult to achieve electrochemically. For example, hydroformylation (thermo-HFN) is an industrially important reaction that couples olefins and carbon monoxide (CO) to make aldehydes. However, the electrochemical analogue of hydroformylation (electro-HFN), which uses protons and electrons instead of hydrogen gas, represents a complex C-C bond-forming reaction that is difficult to achieve at heterogeneous electrocatalysts. In this work, we import Rh-based thermo-HFN catalysts onto electrode surfaces to unlock electro-HFN reactivity. At mild conditions of room temperature and 5 bar CO, we achieve Faradaic efficiencies of up to 15% and turnover frequencies of up to 0.7 h-1. This electro-HFN rate is an order of magnitude greater than the corresponding thermo-HFN rate at the same catalyst, temperature, and pressure. Reaction kinetics and operando X-ray absorption spectroscopy provide evidence for an electro-HFN mechanism that involves distinct elementary steps relative to thermo-HFN. This work demonstrates a step-by-step experimental strategy for electrifying a well-studied thermochemical reaction to unveil a new electrocatalyst for a complex and underexplored electrochemical reaction.

Tuning Single-Atom Dopants on Manganese Oxide for Selective Electrocatalytic Cyclooctene Epoxidation.

Selective and efficient electrocatalysts are imperative for the successful deployment of electrochemistry toward synthetic applications. In this study, we used galvanic replacement reactions to synthesize iridium-decorated manganese oxide nanoparticles, which showed a cyclooctene epoxidation partial current density of 10.5 ± 2.8 mA/cm2 and a Faradaic efficiency of 46 ± 4%. Results from operando X-ray absorption spectroscopy suggest that manganese leaching from the nanoparticles during galvanic replacement introduces lattice vacancies that make the nanoparticles more susceptible to metal oxidation and catalyst reconstruction under an applied anodic potential. This results in an increased presence of electrophilic oxygen atoms on the catalyst surface during reaction conditions, which may contribute to the enhanced electrocatalytic activity toward cyclooctene epoxidation.

Electrochemical Modulation of Carbon Monoxide-Mediated Cell Signaling.

Despite the critical role played by carbon monoxide (CO) in physiological and pathological signaling events, current approaches to deliver this messenger molecule are often accompanied by off-target effects and offer limited control over release kinetics. To address these challenges, we develop an electrochemical approach that affords on-demand release of CO through reduction of carbon dioxide (CO2 ) dissolved in the extracellular space. Electrocatalytic generation of CO by cobalt phthalocyanine molecular catalysts modulates signaling pathways mediated by a CO receptor soluble guanylyl cyclase. Furthermore, by tuning the applied voltage during electrocatalysis, we explore the effect of the CO release kinetics on CO-dependent neuronal signaling. Finally, we integrate components of our electrochemical platform into microscale fibers to produce CO in a spatially-restricted manner and to activate signaling cascades in the targeted cells. By offering on-demand local synthesis of CO, our approach may facilitate the studies of physiological processes affected by this gaseous molecular messenger.

Bayesian data analysis reveals no preference for cardinal Tafel slopes in CO2 reduction electrocatalysis.

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.