Maximal predictability approach for identifying the right descriptors for electrocatalytic reactions

Density Functional Theory (DFT) calculations are being routinely used to identify new material candidates that approach activity near fundamental limits imposed by thermodynamics or scaling relations. DFT calculations have finite uncertainty and this raises an issue related to the ability to delineate materials that possess high activity. With the development of error estimation capabilities in DFT, there is an urgent need to propagate uncertainty through activity prediction models. In this work, we demonstrate a rigorous approach to propagate uncertainty within thermodynamic activity models. This maps the calculated activity into a probability distribution, and can be used to calculate the expectation value of the distribution, termed as the expected activity. We prove that the ability to distinguish materials increases with reducing uncertainty. We define a quantity, prediction efficiency, which provides a precise measure of the ability to distinguish the activity of materials for a reaction scheme over an activity range. We demonstrate the framework for 4 important electrochemical reactions, hydrogen evolution, chlorine evolution, oxygen reduction and oxygen evolution. We argue that future studies should utilize the expected activity and prediction efficiency to improve the likelihood of identifying material candidates that can possess high activity.Comment: 17 pages, 6 figures; 17 pages of Supporting Informatio

Quantifying Confidence in DFT Predicted Surface Pourbaix Diagrams of Transition Metal Electrode-Electrolyte Interfaces

Density Functional Theory (DFT) calculations have been widely used to predict the activity of catalysts based on the free energies of reaction intermediates. The incorporation of the state of the catalyst surface under the electrochemical operating conditions while constructing the free energy diagram is crucial, without which even trends in activity predictions could be imprecisely captured. Surface Pourbaix diagrams indicate the surface state as a function of the pH and the potential. In this work, we utilize error-estimation capabilities within the BEEF-vdW exchange correlation functional as an ensemble approach to propagate the uncertainty associated with the adsorption energetics in the construction of Pourbaix diagrams. Within this approach, surface-transition phase boundaries are no longer sharp and are therefore associated with a finite width. We determine the surface phase diagram for several transition metals under reaction conditions and electrode potentials relevant for the Oxygen Reduction Reaction (ORR). We observe that our surface phase predictions for most predominant species are in good agreement with cyclic voltammetry experiments and prior DFT studies. We use the OH$^*$ intermediate for comparing adsorption characteristics on Pt(111), Pt(100), Pd(111), Ir(111), Rh(111), and Ru(0001) since it has been shown to have a higher prediction efficiency relative to O$^*$, and find the trend Ru>Rh>Ir>Pt>Pd for (111) metal facets, where Ru binds OH$^*$ the strongest. We robustly predict the likely surface phase as a function of reaction conditions by associating c-values to quantifying the confidence in predictions within the Pourbaix diagram. We define a confidence quantifying metric using which certain experimentally observed surface phases and peak assignments can be better rationalized.Comment: 21 pages, 8 figures and Supporting Informatio

Universality in Nonaqueous Alkali Oxygen Reduction on Metal Surfaces: Implications for Li−O₂ and Na−O₂ Batteries

Nonaqueous metal–oxygen batteries, particularly lithium–oxygen and sodium–oxygen, have emerged as possible high energy density alternatives to Li-ion batteries that could address the limited driving range issues faced by electric vehicles. Many fundamental questions remain unanswered, including the origin of the differences in the discharge product formed, i.e., Li₂O₂ versus Li₂O in Li–O₂ batteries and NaO₂ versus Na₂O₂ in Na–O₂ batteries. In this Letter, we analyze the role of the electrode (electrocatalyst) in determining the selectivity of the discharge product through a tuning of the nucleation overpotential for a given electrolyte. On the basis of a thermodynamic analysis using density functional theory calculations, we demonstrate that the free energy of adsorbed LiO₂^* is a descriptor determining the nucleation overpotential for the formation of lithium peroxide, Li₂O₂, the primary discharge product in Li–O₂ batteries. Our analysis suggests that Au(100), Ag(111), and Au(111) are capable of nucleating Li₂O₂ with very low overpotentials. We also show that the free energy of adsorbed NaO₂^* is a descriptor determining the nucleation rate for sodium superoxide, NaO₂, the primary discharge product in Na–O₂ batteries. We explore trends in selectivity between 2e^– and 4e^– oxygen reduction for nucleating Li₂O₂ and Li₂O, respectively, and show that to a first approximation, the selectivity can be determined by a single descriptor, the free energy of adsorbed LiO₂^*. This is due to the existence of linear scaling between LiO₂^* and LiO* similar to that observed for OOH* and OH* for aqueous oxygen reduction. This analysis shows that for all materials that possess low nucleation overpotentials, the nucleation overpotential for 2e^– oxygen reduction is smaller than that for the 4e^– oxygen reduction. In the case of Na–O₂, we find that the trends in selectivity between nucleating NaO₂ and Na₂O₂ are determined by the free energy of adsorbed NaO₂^* and the reorganization energy associated with sodium-ion coupled electron transfer. This analysis provides a rational basis for the selection of the electrode (electrocatalyst) for tuning the nucleation and thereby potentially controlling the discharge product

Surface Restructuring of Nickel Sulfide Generates Optimally Coordinated Active Sites for Oxygen Reduction Catalysis

The Ni₃S₂ bulk phase supports efficient oxygen reduction reaction (ORR) catalysis in pH neutral aqueous electrolytes. Here, we combine electrochemistry, surface spectroscopy, and high-resolution microscopy to show that Ni₃S₂ undergoes self-limiting oxidative surface restructuring under ORR conditions to form an amorphous surface film conformally coating the Ni₃S₂ crystallites. The surface film has a nominal NiS stoichiometry and is highly active for ORR catalysis. Density functional theory calculations suggest that, to a first approximation, the catalytic activity of nickel sulfides is determined by the Ni-S coordination numbers at surface-exposed sites through a simple geometric descriptor. In particular, Ni surface sites with three S nearest neighbors, formed via reconstruction of the Ni3S2 surface, provide an optimal energetic landscape for ORR catalysis. By providing a framework for understanding catalytic activity on reconstructed amorphous surface phases, the work enables the rational design of high-performance electrocatalysts based on kinetically labile, earth-abundant materials. In heterogeneous catalysis, only the surface of the active material is responsible for catalytic turnover. These surfaces often undergo dynamic changes that lead to altered structures and compositions relative to the bulk of the material. Thus, the development of improved catalysts requires a detailed understanding of these surface dynamics under the conditions of the reaction. Here, we uncover these dynamics on an earth-abundant catalyst, Ni₃S₂, that is highly active for the conversion of oxygen to water, the efficiency-limiting reaction in low-temperature fuel cells. We demonstrate that the surface of this material transforms into a disordered and active ∼2 nm NiS layer. We establish that the activity of materials of this type can be estimated by simply considering the number of S atoms directly bonded to the Ni active sites on the surface. This simple geometric descriptor enables the rational design of the disordered structures that persist on many catalytically active surfaces. Crystalline Ni₃S₂ oxygen reduction reaction (ORR) catalysts undergo oxidative surface reconstruction under catalytic conditions to generate an approximately 2 nm amorphous surface layer with NiS stoichiometry. DFT calculations establish a simple local coordination number based descriptor for ORR catalysis and suggest that Ni atoms surrounded by three S nearest neighbors display optimal activity. The surface reconstructed Ni₃S₂ exhibits similar ORR activity to electrodeposited amorphous NiS films.National Science Foundation (Awards CHE-1454060 and CBET-1554273

Reversible Alkaline Hydrogen Evolution and Oxidation Reactions Using Ni–Mo Catalysts Supported on Carbon

Unitized regenerative fuel cells based on hydroxide exchange membranes are attractive for long duration energy storage. This mode of operation depends on the ability to catalyze hydrogen evolution and oxidation reversibly, and ideally using nonprecious catalyst materials. Here we report the synthesis of Ni–Mo catalyst composites supported on oxidized Vulcan carbon (Ni–Mo/oC) and demonstrate their performance for reversible hydrogen evolution and oxidation. For the hydrogen evolution reaction, we observed mass-specific activities exceeding 80 mA/mg at 100 mV overpotential, and additional measurements using hydroxide exchange membrane electrode assemblies yielded full cell voltages that were only ~100 mV larger for Ni–Mo/oC cathodes compared to Pt–Ru/C at current densities exceeding 1 A/cm2. For hydrogen oxidation, Ni–Mo/oC films required <50 mV overpotential to achieve half the maximum anodic current density, but activity was limited by internal mass transfer and oxidative instability. Nonetheless, estimates of the mass-specific exchange current for Ni–Mo/oC from micropolarization measurements showed its hydrogen evolution/oxidation activity is within 1 order of magnitude of commercial Pt/C. Density functional theory calculations helped shed light on the high activity of Ni–Mo composites, where the addition of Mo leads to surface sites with weaker H-binding energies than pure Ni. These calculations further suggest that increasing the Mo content in the subsurface of the catalyst would result in still higher activity, but oxidative instability remains a significant impediment to high performance for hydrogen oxidation