The low-energy excitations of SrTiO 3 (001), a large-bandgap oxide perovskite, are dominated by phonons and phonon polaritons. At the surface they couple to dipole-active surface phonon polaritons that are bound to...

Descriptors link basic physicochemical parameters that characterize the materials and the environment to the catalytic performance. Traditionally, descriptors are rooted in mechanistic understanding of elementary surface reactions gained from surface...

Electrocatalytic reactions often involve several steps and intermediates, along with changes in the catalyst structure and chemistry under reaction conditions, making their mechanistic understanding very challenging. As a way to...

Understanding how activation energies and entropies vary with electrode potential is central to interpreting electrocatalytic kinetics, yet temperature-dependent analyses often yield apparent “compensation effects” whose physical origin remains debated. Here,...

Multi-metallic alloys such as high entropy alloys (HEAs) span an extensive compositional space, potentially offering materials with enhanced activity and stability for various catalytic reactions. However, experimentally identifying the optimal composition within this vast compositional space poses significant challenges. In this study, we present a medium-throughput approach to screen the composition–activity correlation of electrodeposited multi-metallic and HEA nanoparticles. We apply the approach for exploring the Pd–Ag–Au composition subspace for the alkaline Oxygen Reduction Reaction (ORR). The Pd–Ag–Au alloy nanoparticles were synthesized electrochemically, characterized and evaluated for the ORR using a rotating disk electrode (RDE) setup. From 107 individual measurements, a composition–activity correlation model was constructed using Gaussian Process Regression (GPR), pinpointing the optimal composition around Pd85Ag1Au14. The experimental results are then compared to theoretical predictions based on the well-established descriptor approach utilizing density functional theory (DFT) calculations. While some discrepancies exist, the experimental DFT-derived models show partial overlap, validating the utility of computational screening for multi-metallic systems. This work provides valuable insights for the efficient screening of multi-metallic catalysts for catalytic applications and exemplifies advanced pathways on how to compare and analyze experimental data to simulations based on well-defined hypotheses.

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