OER composition optimisation of AuIrOsPdPtReRhRu

In this paper, the OER performance of the AuIrOsPdPtReRhRu composition space was investigated by using an experimental data set of 349 nanoparticles to construct a machine learning model. Density functional theory (DFT) calculations of the IrOsPdPtRhRu subspace were performed to provide a complementary theoretical model. Comparison of the two models gives insights into the contributions of the individual elements to the OER activity.

DOI: To be provided

Optimised DFT structures and scripts used to analyse the results can be retrieved here