Exploring pathways for the development of novel electroctalysts for energy conversion

Die Doktorarbeit befasst sich der Erschließung von multinären Metall-Legierungen als Katalysatoren für elektrochemische Reaktionen mit Fokus auf der Sauerstoffreduktion. Zunächst wurden Methoden zur Fixierung einzelner Nanopartikel (NP) auf Nanoelektroden sowie eine Normierungsmethode entwickelt, die unterschiedliche Mengen an immobilisierten NPs kompensiert und somit einen Vergleich der Aktivität ermöglicht. Damit konnte eine edelmetallfreie Legierung mit vergleichbarer Aktivität zum Benchmark-Pt-Katalysator identifiziert werden, was durch einen Hochentropieffekt und einer dadurch bedingten komplexen Mischkristall-Festphase begründet werden konnte. Diese neue Katalysatorklasse wurde hinsichtlich ihrer Potentiale für die Elektrokatalyse bewertet und die zugrundeliegenden Konzepte wurden erschlossen. Das daraus gewonnene Verständnis konnte genutzt werden, um Richtlinien für systematische Optimierung der katalytischen Eigenschaften solcher Legierungen zu entwickeln

Calibrating SECCM measurements by means of a nanoelectrode ruler

Scanning electrochemical cell microscopy (SECCM) is increasingly applied to determine the intrinsic catalytic activity of single electrocatalyst particle. This is especially feasible if the catalyst nanoparticles are large enough that they can be found and counted in post-SECCM scanning electron microscopy images. Evidently, this becomes impossible for very small nanoparticles and hence, a catalytic current measured in one landing zone of the SECCM droplet cannot be correlated to the exact number of catalyst particles. We show, that by introducing a ruler method employing a carbon nanoelectrode decorated with a countable number of the same catalyst particles from which the catalytic activity can be determined, the activity determined using SECCM from many spots can be converted in the intrinsic catalytic activity of a certain number of catalyst nanoparticles

Design of complex solid‐solution electrocatalysts by correlating configuration, adsorption energy distribution patterns, and activity curves

Complex solid‐solution electrocatalysts (also referred to as high‐entropy alloy) are gaining increasing interest owing to their promising properties which were only recently discovered. With the capability of forming complex single‐phase solid solutions from five or more constituents, they offer unique capabilities of fine‐tuning adsorption energies. However, the elemental complexity within the crystal structure and its effect on electrocatalytic properties is poorly understood. We discuss how addition or replacement of elements affect the adsorption energy distribution pattern and how this impacts the shape and activity of catalytic response curves. We highlight the implications of these conceptual findings on improved screening of new catalyst configurations and illustrate this strategy based on the discovery and experimental evaluation of several highly active complex solid solution nanoparticle catalysts for the oxygen reduction reaction in alkaline media

Unravelling composition-activity-stability trends in high entropy alloy electrocatalysts by using a data‐guided combinatorial synthesis strategy and computational modeling

High entropy alloys (HEA) comprise a huge search space for new electrocatalysts. Next to element combinations, the optimization of the chemical composition is essential for tuning HEA to specific catalytic processes. Simulations of electrocatalytic activity can guide experimental efforts. Yet, the currently available underlying model assumptions do not necessarily align with experimental evidence. To study deviations of theoretical models and experimental data requires statistically relevant datasets. Here, a combinatorial strategy for acquiring large experimental datasets of multi-dimensional composition spaces is presented. Ru–Rh–Pd–Ir–Pt is studied as an exemplary, highly relevant HEA system. Systematic comparison with computed electrochemical activity enables the study of deviations from theoretical model assumptions for compositionally complex solid solutions in the experiment. The results suggest that the experimentally obtained distribution of surface atoms deviates from the ideal distribution of atoms in the model. Leveraging both advanced simulation and large experimental data enables the estimation of electrocatalytic activity and solid-solution stability trends in the 5D composition space of the HEA system. A perspective on future directions for the development of active and stable HEA catalysts is outlined