Active learning-based framework for optimal reaction mechanism selection from microkinetic modeling: a case study of electrocatalytic oxygen reduction reaction on carbon nanotubes

2020 ◽  
Vol 22 (8) ◽  
pp. 4581-4591
Author(s):  
Aleksandr A. Kurilovich ◽  
Caleb T. Alexander ◽  
Egor M. Pazhetnov ◽  
Keith J. Stevenson

Our quantitative framework demonstrates that model parameters uncertainty treatment is crucial to select an optimal model for available experimental data.

2019 ◽  
Vol 3 (8) ◽  
pp. 1951-1956 ◽  
Author(s):  
Rongtao Hu ◽  
Fenfa Yao ◽  
Chuxin Wu ◽  
Chuanhong Jin ◽  
Lunhui Guan

Single-walled carbon nanotubes co-modified with interior filling of phosphomolybdic acid and successive exterior oxidation (O-HPMO@SWCNTs) possess better two-electron oxygen reduction reaction performance than the HPMO-filled SWCNTs, oxidized SWCNTs or pristine SWCNTs.


2016 ◽  
Vol 190 ◽  
pp. 49-56 ◽  
Author(s):  
Guoyu Zhong ◽  
Hongjuan Wang ◽  
Hao Yu ◽  
Haihui Wang ◽  
Feng Peng

2021 ◽  
Vol 6 (4) ◽  
pp. 726-746
Author(s):  
Cristhian A. Fonseca Benítez ◽  
Vanina A. Mazzieri ◽  
Carlos R. Vera ◽  
Viviana M. Benitez ◽  
Carlos L. Pieck

The selective hydrogenation of oleic acid to oleyl alcohol over a Rh(1 wt%)–Sn(4 wt%)–B/Al2O3 catalyst was studied. A comprehensive set of experimental data was used for elucidating the reaction mechanism.


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