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Microscale Combinatorial Libraries for the Discovery of High-Entropy Materials
Lars Banko1, Emmanuel Batsa Tetteh2, Aleksander Kostka3
1Materials Discovery and Interfaces, Institute for Materials, Faculty of Mechanical Engineering, Ruhr University Bochum, Universitätsstraße 150, D-44801, Bochum, Germany.
Advanced Materials (Deerfield Beach, Fla.)
|December 21, 2022
Summary
High-entropy alloys offer unique properties but are complex to study. This research uses microscale combinatorial libraries and high-throughput characterization to accelerate the discovery of advanced materials for electrocatalysis.
Area of Science:
- Materials Science
- Electrochemistry
- Nanotechnology
Background:
- Polyelemental material systems, particularly high-entropy alloys (HEAs), exhibit remarkable properties but face challenges in exploration due to vast combinatorial possibilities.
- Discovering novel HEAs with optimal properties for applications like electrocatalysis is hindered by traditional synthesis and characterization methods.
Purpose of the Study:
- To develop a high-throughput platform for exploring and optimizing polyelemental material systems, specifically high-entropy alloys.
- To accelerate the discovery of new HEAs with enhanced electrocatalytic activity for energy conversion reactions.
Main Methods:
- Co-sputtering combined with shadow masking to create microscale combinatorial libraries of thin-film composition spreads.
- Nanoscale scanning electrochemical cell microscopy for high-throughput characterization of thousands of HEA compositions.
- Electrocatalytic activity mapping for hydrogen evolution, oxygen evolution, and oxygen reduction reactions.
Main Results:
- Successfully generated microscale combinatorial libraries covering unprecedented compositional ranges of HEA systems.
- Identified activity optima in the Ru-Rh-Pd-Ir-Pt system for electrocatalytic reactions.
- Discovered active, noble-metal-lean compositions within the Co-Ni-Mo-Pd-Pt system.
Conclusions:
- The developed microlibrary approach serves as a holistic discovery platform for mastering the complexity of polyelemental systems.
- This method significantly accelerates the identification of high-performance HEAs for critical energy conversion applications.
