High-Performance Iridium-Molybdenum Oxide Electrocatalysts for Water Oxidation in Acid: Bayesian Optimization Discovery and Experimental Testing.

Ir oxides are costly and scarce catalysts for oxygen evolution reaction (OER) in acid. There has been extensive interest in developing alternatives that are either Ir-free or require smaller amounts of Ir to drive the reactions at acceptable rates. One design strategy is to identify Ir-based mixed oxides that achieve similar performance while requiring smaller amounts of Ir. The obstacle to this strategy has been a very large phase space of the Ir-based mixed metal oxides, in terms of the metals combined with Ir and the different crystallographic structures of the mixed oxides, which prevents a thorough exploration of possible materials. In this work, we developed a workflow that uses machine-learning-aided Bayesian optimization in combination with density functional theory to make the exploration of this phase space plausible. This screening identified Mo as a promising dopant for forming acid-tolerant Ir-based oxides for the OER. We synthesized and characterized the Ir-Mo mixed oxides in the form of thin-film electrocatalysts with a known surface area. We show that these mixed oxides exhibited overpotentials ∼30 mV lower than a pure Ir control while maintaining 24% lower Ir dissolution rates than the Ir control. These findings suggest that Mo is a promising dopant and highlight the promise of machine learning to guide the experimental exploration and optimization of catalytic materials.

Substituent Impact on Quinoxaline Performance and Degradation in Redox Flow Batteries.

Aqueous redox flow batteries (RFBs) are attractive candidates for low-cost, grid-scale storage of energy from renewable sources. Quinoxaline derivatives represent a promising but underexplored class of charge-storing materials on account of poor chemical stability in prior studies (with capacity fade rates >20%/day). Here, we establish that 2,3-dimethylquinoxaline-6-carboxylic acid (DMeQUIC) is vulnerable to tautomerization in its reduced form under alkaline conditions. We obtain kinetic rate constants for tautomerization by applying Bayesian inference to ultraviolet-visible spectroscopic data from operating flow cells and show that these rate constants quantitatively account for capacity fade measured in cycled cells. We use density functional theory (DFT) modeling to identify structural and chemical predictors of tautomerization resistance and demonstrate that they qualitatively explain stability trends for several commercially available and synthesized derivatives. Among these, quinoxaline-2-carboxylic acid shows a dramatic increase in stability over DMeQUIC and does not exhibit capacity fade in mixed symmetric cell cycling. The molecular design principles identified in this work set the stage for further development of quinoxalines in practical, aqueous organic RFBs.

Theoretical Investigation of the Potential-Dependent CO Adsorption on Copper Electrodes.

Despite the importance of CO adsorption in many electrocatalytic reaction mechanisms, there has been little investigation of the dependence of the free energy of CO adsorption on the applied potential. Herein, we report on the potential-dependent adsorption of CO on Cu electrodes using a grand-canonical density functional theory approach. We demonstrate that, within the working potential range of electrocatalytic CO2 reduction on Cu(111) and Cu(100), the CO adsorption strength can change by over 0.1 eV. Our analyses explain the potential dependence through an interfacial capacitance loss upon CO adsorption as well as orbital relaxation induced by the electrode potential. Via sensitivity analysis with respect to two electrolyte model parameters (solvent dielectric constant and Debye screening length), we find that the surface excess charge density is a useful descriptor of the CO adsorption free energy.