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.
Optimised DFT structures and scripts used to analyse the results can be retrieved here
Experimental data and scripts used to analyse the data can be downloaded here