A Flexible Theory for Catalysis: Learning Alkaline Oxygen Reduction on Complex Solid Solutions within the Ag-Pd-Pt-Ru Composition Space.

Compositionally complex materials such as high-entropy alloys and oxides have the potential to be efficient platforms for catalyst discovery because of the vast chemical space spanned by these novel materials. Identifying the composition of the most active catalyst materials, however, requires unraveling the descriptor-activity relationship, as experimentally screening the multitude of possible element ratios quickly becomes a daunting task. In this work, we show that inferred adsorption energy distributions of *OH and *O on complex solid solution surfaces within the space spanned by the system Ag-Pd-Pt-Ru are coupled to the experimentally observed electrocatalytic performance for the oxygen reduction reaction. In total, the catalytic activity of 1582 alloy compositions is predicted with a cross-validated mean absolute error of 0.042 mA/cm2 by applying a theory-derived model with only two adjustable parameters. Trends in the discrepancies between predicted electrochemical performance values of the model and the measured values on thin film surfaces subsequently provide insight into the alloys' surface compositions during reaction conditions. Bridging this gap between computationally modeled and experimentally observed catalytic activities, not only reveals insight into the underlying theory of catalysis but also takes a step closer to realizing exploration and exploitation of high-entropy materials.

Scalable Synthesis of Multi-Metal Electrocatalyst Powders and Electrodes and their Application for Oxygen Evolution and Water Splitting.

Multi-metal electrocatalysts provide nearly unlimited catalytic possibilities arising from synergistic element interactions. We propose a polymer/metal precursor spraying technique that can easily be adapted to produce a large variety of compositional different multi-metal catalyst materials. To demonstrate this, 11 catalysts were synthesized, characterized, and investigated for the oxygen evolution reaction (OER). Further investigation of the most active OER catalyst, namely CoNiFeMoCr, revealed a polycrystalline structure, and operando Raman measurements indicate that multiple active sites are participating in the reaction. Moreover, Ni foam-supported CoNiFeMoCr electrodes were developed and applied for water splitting in flow-through electrolysis cells with electrolyte gaps and in zero-gap membrane electrode assembly (MEA) configurations. The proposed alkaline MEA-type electrolyzers reached up to 3 A cm-2 , and 24 h measurements demonstrated no loss of current density of 1 A cm-2 .

Acidic Hydrogen Evolution Electrocatalysis at High-Entropy Alloys Correlates with its Composition-Dependent Potential of Zero Charge.

The vast possibilities in the elemental combinations of high-entropy alloys (HEAs) make it essential to discover activity descriptors for establishing rational electrocatalyst design principles. Despite the increasing attention on the potential of zero charge (PZC) of hydrogen evolution reaction (HER) electrocatalyst, neither the PZC of HEAs nor the impact of the PZC on the HER activity at HEAs has been described. Here, we use scanning electrochemical cell microscopy (SECCM) to determine the PZC and the HER activities of various elemental compositions of a Pt-Pd-Ru-Ir-Ag thin-film HEA materials library (HEA-ML) with high statistical reliability. Interestingly, the PZC of Pt-Pd-Ru-Ir-Ag is linearly correlated with its composition-weighted average work function. The HER current density in acidic media positively correlates with the PZC, which can be explained by the preconcentration of H+ in the electrical double layer at potentials negative of the PZC.

Bayesian Optimization of High-Entropy Alloy Compositions for Electrocatalytic Oxygen Reduction*.

Active, selective and stable catalysts are imperative for sustainable energy conversion, and engineering materials with such properties are highly desired. High-entropy alloys (HEAs) offer a vast compositional space for tuning such properties. Too vast, however, to traverse without the proper tools. Here, we report the use of Bayesian optimization on a model based on density functional theory (DFT) to predict the most active compositions for the electrochemical oxygen reduction reaction (ORR) with the least possible number of sampled compositions for the two HEAs Ag-Ir-Pd-Pt-Ru and Ir-Pd-Pt-Rh-Ru. The discovered optima are then scrutinized with DFT and subjected to experimental validation where optimal catalytic activities are verified for Ag-Pd, Ir-Pt, and Pd-Ru binary alloys. This study offers insight into the number of experiments needed for optimizing the vast compositional space of multimetallic alloys which has been determined to be on the order of 50 for ORR on these HEAs.

Complex-Solid-Solution Electrocatalyst Discovery by Computational Prediction and High-Throughput Experimentation*.

Complex solid solutions ("high entropy alloys"), comprising five or more principal elements, promise a paradigm change in electrocatalysis due to the availability of millions of different active sites with unique arrangements of multiple elements directly neighbouring a binding site. Thus, strong electronic and geometric effects are induced, which are known as effective tools to tune activity. With the example of the oxygen reduction reaction, we show that by utilising a data-driven discovery cycle, the multidimensionality challenge raised by this catalyst class can be mastered. Iteratively refined computational models predict activity trends around which continuous composition-spread thin-film libraries are synthesised. High-throughput characterisation datasets are then used as input for refinement of the model. The refined model correctly predicts activity maxima of the exemplary model system Ag-Ir-Pd-Pt-Ru. The method can identify optimal complex-solid-solution materials for electrocatalytic reactions in an unprecedented manner.

Long-Range SECCM Enables High-Throughput Electrochemical Screening of High Entropy Alloy Electrocatalysts at Up-To-Industrial Current Densities.

High-entropy alloys (HEAs), especially in the form of compositional complex solid solutions (CCSS), have gained attention in the field of electrocatalysis. However, exploring their vast composition space concerning their electrocatalytic properties imposes significant challenges. Scanning electrochemical cell microscopy (SECCM) offers high-speed electrochemical analysis on surface areas with a lateral resolution down to tens of nm. However, high-precision piezo positioners often used for the motion of the tip limit the area of SECCM scans to the motion range of the piezo positioners which is typically a few tens of microns. To bridge this experimental gap, the study proposes a long-range SECCM system with a rapid gas-exchange environmental cell for high-throughput electrochemical characterization of 100 mm diameter HEA thin-film material libraries (ML) obtained by combinatorial co-sputtering. Due to the gas-liquid interface at the positioned SECCM droplet on the sample, high-throughput evaluation under industrial current density conditions becomes feasible. This allows the direct correlation between electrocatalytic activity and material composition with high statistical reliability. The multidimensional data obtained accelerates materials discovery, development, and optimization.

Discovery of High-Entropy Oxide Electrocatalysts: From Thin-Film Material Libraries to Particles.

Discovery of new high-entropy electrocatalysts requires testing of hundreds to thousands of possible compositions, which can be addressed most efficiently by high-throughput experimentation on thin-film material libraries. Since the conditions for high-throughput measurements ("screening") differ from more standardized methods, it is frequently a concern whether the findings from screening can be transferred to the commonly used particulate catalysts. We demonstrate the successful transfer of results from thin-film material libraries to particles of Cantor alloy oxide (Co-Cr-Fe-Mn-Ni)3O4. The chemical compositions of the libraries, all single-phase spinels, cover a wide compositional range of (Cr8.1-28.0Mn11.6-28.4Fe10.6-39.0Co11.4-36.7Ni13.5-31.4)37.7±0.6O62.3±0.6, with composition-dependent lattice constant values ranging from 0.826 to 0.851 nm. Electrochemical screening of the libraries for the oxygen evolution reaction (OER) identifies (Cr24.6±1.4Mn15.7±2.0Fe16.9±1.8Co26.1±1.9Ni16.6±1.7)37.8±0.8O62.2±1.2 as the most active composition, exhibiting an overpotential of 0.36 V at a current density of 1 mA cm-2. This "hit" in the library was subsequently synthesized in the form of particles with the same composition and crystal structure using an aerosol-based synthesis strategy. The similar OER activity of the most active thin-film composition and the derived catalyst particles validates the proposed approach of accelerated discovery of novel catalysts by screening of thin-film libraries.

Tuning Light-Driven Water Oxidation Efficiency of Molybdenum-Doped BiVO4 by Means of Multicomposite Catalysts Containing Nickel, Iron, and Chromium Oxides.

Mo-doped BiVO4 has emerged as a promising material for photoelectrodes for photoelectrochemical water splitting, however, still shows a limited efficiency for light-driven water oxidation. We present the influence of an oxygen-evolution catalyst composed of Ni, Fe, and Cr oxides on the activity of Mo:BiVO4 photoanodes. The photoanodes are prepared by spray-coating, enabling compositional and thickness gradients of the incorporated catalyst. Two different configurations are evaluated, namely with the catalyst embedded into the Mo:BiVO4 film or deposited on top of it. Both configurations provide a significantly different impact on the photoelectrocatalytic efficiency. Structural characterisation of the materials by means of SEM, TEM and XRD as well as the photoelectrocatalytic activity investigated by means of an optical scanning droplet cell and in situ detection of oxygen using scanning photoelectrochemical microscopy are presented.