First-principles database driven computational neural network approach to the discovery of active ternary nanocatalysts for oxygen reduction reaction

2018 ◽  
Vol 20 (38) ◽  
pp. 24539-24544 ◽  
Author(s):  
Joonhee Kang ◽  
Seung Hyo Noh ◽  
Jeemin Hwang ◽  
Hoje Chun ◽  
Hansung Kim ◽  
...  
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Oxygen Reduction Reaction ◽  
Electrochemical Properties ◽  
Oxygen Reduction ◽  
First Principles ◽  
Reduction Reaction ◽  
Network Approach ◽  
Neural Network Approach

An elegant machine-learning-based algorithm was applied to study the thermo-electrochemical properties of ternary nanocatalysts for oxygen reduction reaction (ORR).

scholarly journals Oxygen reduction on zirconium-stabilized-PdO surfaces: a first-principles study

RSC Advances ◽  
2017 ◽  
Vol 7 (65) ◽  
pp. 41057-41062 ◽  
Author(s):  
Xiaofeng Yang ◽  
Zongbao Li ◽  
Xinyu Li ◽  
Ao Wang ◽  
Lichao Jia ◽  
...  
Keyword(s):  
Oxygen Reduction Reaction ◽  
Oxygen Reduction ◽  
First Principles ◽  
Relative Stability ◽  
Reduction Reaction ◽  
First Principles Calculations ◽  
First Principles Study

The oxygen reduction reaction properties on PdO and Zr-doped PdO surfaces, and the relative stability of the concerned surfaces, have been studied by first-principles calculations.

O2 and H2O2 transformation steps for the oxygen reduction reaction catalyzed by graphitic nitrogen-doped carbon nanotubes in acidic electrolyte from first principles calculations

2015 ◽  
Vol 17 (34) ◽  
pp. 21950-21959 ◽  
Author(s):  
Yuhang Li ◽  
Guoyu Zhong ◽  
Hao Yu ◽  
Hongjuan Wang ◽  
Feng Peng
Keyword(s):  
Carbon Nanotubes ◽  
Oxygen Reduction Reaction ◽  
Oxygen Reduction ◽  
First Principles ◽  
Reduction Reaction ◽  
First Principles Calculations ◽  
Nitrogen Doped ◽  
Acidic Electrolyte ◽  
Nitrogen Doped Carbon ◽  
Mixed Mechanism

DFT calculations reveal a mixed mechanism for the oxygen reduction reaction catalyzed by nitrogen-doped carbon nanotubes in acidic electrolyte.

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