Interpretable Machine Learning Models for Practical Antimonate Electrocatalyst Performance
Shyam Deo(SLAC National Accelerator Laboratory), Johannes Voss(SLAC National Accelerator Laboratory), Lingze Wei(SLAC National Accelerator Laboratory), Kirsten T. Winther(SLAC National Accelerator Laboratory), Ishaan Singh(SLAC National Accelerator Laboratory), José A. Zamora Zeledón(SLAC National Accelerator Laboratory), Jesse Matthews(SLAC National Accelerator Laboratory), Gaurav A. Kamat(SLAC National Accelerator Laboratory), McKenzie A. Hubert(SLAC National Accelerator Laboratory), Thomas F. Jaramillo(Stanford University), Melissa E. Kreider(National Laboratory of the Rockies), Frank Abild‐Pedersen(SLAC National Accelerator Laboratory), Nathaniel Keyes(SLAC National Accelerator Laboratory), Michaela Burke Stevens(SLAC National Accelerator Laboratory)
Cited by 4
Related Papers
Combining theory and experiment in electrocatalysis: Insights into materials design
|Science|2017|11.6k
Promoter Effects of Alkali Metal Cations on the Electrochemical Reduction of Carbon Dioxide
|Journal of the American Chemical Society|2017|1.1k
Benchmarking nanoparticulate metal oxide electrocatalysts for the alkaline water oxidation reaction
|Journal of Materials Chemistry A|2015|581