Machine-Learning Methods Enable Exhaustive Searches for Active Bimetallic Facets and Reveal Active Site Motifs for CO2 Reduction | Center for Interface Science and Catalysis

Authors:

Zachary Ulissi, Michael Tang, Jianping Xiao, Xinyan Liu, Daniel A Torelli, Mohammadreza Karamad, Kyle Cummins, Christopher Hahn, Nathan S Lewis, Thomas F Jaramillo, Karen Chan, Jens K Norskov

Year of publication:

2017

Journal:

ACS Catalysis

Research Areas:

Synthetic fuels and chemicals, System scaling relations, Artificial photosynthesis, Electrocatalysis, Electrochemical fuels

Funding sources:

JCAP