Dataset - Accelerating Combinatorial Electrocatalyst Discovery with Bayesian Optimization: A Case Study in the Quaternary System Ni-Pd-Pt-Ru for the Oxygen Evolution Reaction

This dataset contains the compositional and electrochemical characterization data used in the study on Bayesian optimization for high-throughput electrocatalyst discovery in the quaternary Ni-Pd-Pt-Ru system. The dataset includes: Composition maps of all 12 materials libraries, acquired by energy-dispersive X-ray spectroscopy Linear sweep voltammograms (LSVs) for all compositions of the materials libraries for the oxygen evolution reaction, acquired by alkaline scanning droplet cell measurements Activity maps of all materials libraries extracted by taking the current density at a potential of 1.7 V vs. the reversible hydrogen electrode LSVs and activities of thin films of the single elements Ni, Pd, Pt, Ru 3D rotating animations of the quaternary composition space plots shown in the publication A Jupyter notebook for plotting the data and replicating the Gaussian process predictions shown in the publication [UPDATE] Upon request of the reviewers, the .csv files with the compositions as well as the activities were combined into a single file for convenience and Jupyter notebook for plotting and replicating the findings of the paper was added. The script depends on numpy and pandas for data loading, matplotlib and colorcet for visualization, and gpflow and scipy for the Gaussian process predictions.