Promising oxygen storage capacity of equimolar high entropy transition metal oxide (MgCoNiCuZn)O

2021 ◽  
pp. 130635
Author(s):  
G. Ranga Rao ◽  
Mohamed Mukthar Ali ◽  
Somasree Roychowdhury ◽  
Lakshmi Prasad
Keyword(s):  
Transition Metal ◽  
Metal Oxide ◽  
Storage Capacity ◽  
Transition Metal Oxide ◽  
Oxygen Storage Capacity ◽  
Oxygen Storage ◽  
High Entropy

Mn3O4 doped with highly dispersed Zr species: a new non-noble metal oxide with enhanced activity for three-way catalysis

2016 ◽  
Vol 40 (12) ◽  
pp. 10108-10115 ◽  
Author(s):  
Genyuan Zhao ◽  
Jing Li ◽  
Wenshuang Zhu ◽  
Xueqin Ma ◽  
Yonghua Guo ◽  
...  
Keyword(s):  
Metal Oxide ◽  
Manganese Oxide ◽  
Noble Metal ◽  
Storage Capacity ◽  
Catalytic Properties ◽  
Oxygen Storage Capacity ◽  
Oxide Catalysts ◽  
Oxygen Storage ◽  
Highly Dispersed ◽  
Three Way Catalysis

Herein, we demonstrate the influence of zirconium species on promoting the oxygen storage capacity and three-way catalytic properties of zirconium-manganese oxide catalysts.

Influence of transition metal electronegativity on the oxygen storage capacity of perovskite oxides

2016 ◽  
Vol 52 (68) ◽  
pp. 10369-10372 ◽  
Author(s):  
Lu Liu ◽  
Daniel D. Taylor ◽  
Efrain E. Rodriguez ◽  
Michael R. Zachariah
Keyword(s):  
Transition Metal ◽  
Storage Capacity ◽  
Oxygen Storage Capacity ◽  
Perovskite Oxides ◽  
Oxygen Storage ◽  
Chemical Looping Combustion ◽  
Chemical Looping ◽  
Oxygen Carriers ◽  
Practical Development ◽  
Selection Of

The selection of highly efficient oxygen carriers (OCs) is a key step necessary for the practical development of chemical looping combustion (CLC).

Extra storage capacity in transition metal oxide lithium-ion batteries revealed by in situ magnetometry

2020 ◽  
Vol 20 (1) ◽  
pp. 76-83 ◽  
Author(s):  
Qiang Li ◽  
Hongsen Li ◽  
Qingtao Xia ◽  
Zhengqiang Hu ◽  
Yue Zhu ◽  
...  
Keyword(s):  
Transition Metal ◽  
Metal Oxide ◽  
Lithium Ion Batteries ◽  
Storage Capacity ◽  
Lithium Ion ◽  
Transition Metal Oxide ◽  
In Situ Magnetometry

Lateral-size control of exfoliated transition-metal–oxide 2D materials by machine learning on small data

Nanoscale ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 3853-3859
Author(s):  
Ryosuke Mizuguchi ◽  
Yasuhiko Igarashi ◽  
Hiroaki Imai ◽  
Yuya Oaki
Keyword(s):  
Machine Learning ◽  
Transition Metal ◽  
Metal Oxide ◽  
2D Materials ◽  
Size Control ◽  
Transition Metal Oxide ◽  
Small Data ◽  
Lateral Size

Lateral sizes of the exfoliated transition-metal–oxide nanosheets were predicted and controlled by the assistance of machine learning. 

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