fig11

High-entropy alloy catalysts: high-throughput and machine learning-driven design

Figure 11. New research strategy for HEA catalysts. HT experimental and theoretical methods are used to generate comprehensive databases of HEA catalysts. Highly transferable and accurate ML models are explored to analyze databases and predict optimal HEA catalysts. New insights into active centers and new catalytic mechanisms and descriptors are expected to be developed on the basis of HT techniques and ML models. Finally, high-performance HEA catalysts will be rationally designed, promoting the development of catalysis. Reproduced with permission[25]. Copyright 2022, Elsevier. CE: counter electrode; RE: reference electrode; WE: working electrode; HEA: high-entropy alloy; HT: high-throughput; ML: machine learning.

Journal of Materials Informatics
ISSN 2770-372X (Online)
Follow Us

Portico

All published articles are preserved here permanently:

https://www.portico.org/publishers/oae/

Portico

All published articles are preserved here permanently:

https://www.portico.org/publishers/oae/