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Document type:
Zeitschriftenaufsatz 
Author(s):
Rueck, M.; Garlyyev, B.; Mayr, F.; Bandarenka, A.S.; Gagliardi, A. 
Title:
Oxygen Reduction Activities of Strained Platinum Core-Shell Electrocatalysts Predicted by Machine Learning 
Abstract:
Core-shell nanocatalyst activities are chiefly controlled by bimetallic material composition, shell thickness, and nanoparticle size. We present a machine learning framework predicting strain with site-specific precision to rationalize how strain on Pt core-shell nanocatalysts can enhance oxygen reduction activities. Large compressive strain on Pt@Cu and Pt@Ni induces optimal mass activities at 1.9 nm nanoparticle size. It is predicted that bimetallic Pt@Au and Pt@Ag have best mass activities at...    »
 
Journal title:
J. Phys. Chem. Lett. 2020, 11, XXX, 1773-1780 2020-02 
Year:
2020 
Year / month:
2020-02 
Quarter:
1. Quartal 
Month:
Feb 
Pages contribution:
1-25 
Language:
en 
Publisher:
American Chemical Society ACS