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Combining computational and experimental methods is a powerful approach, but these are not always directly comparable. This Perspective discusses the relationship between experimental measurements and theoretical calculations in electrocatalysis and aims to enhance the connections between the two.
Reliable testing of fuel cell and electrolyser catalysts is crucial for comparison between studies. This Perspective discusses the differences between rotating disk electrode (RDE) and membrane electrode assembly (MEA) testing of electrocatalysts, and identifies where RDE can be useful and when MEA is more appropriate to study activity and stability under realistic conditions.
Most applications of machine learning in catalysis use black-box models to predict physical properties, but extracting meaningful physical insights from them is challenging. This Perspective discusses machine learning approaches for heterogeneous catalysis and classifies them in terms of their interpretability.
