Oxygen vacancies in self-assemblies of ceria nanoparticles

2014 ◽  
Vol 2 (43) ◽  
pp. 18329-18338 ◽  
Author(s):  
Mahasin Alam Sk ◽  
Sergey M. Kozlov ◽  
Kok Hwa Lim ◽  
Annapaola Migani ◽  
Konstantin M. Neyman
Keyword(s):  
Oxygen Vacancy ◽  
Formation Energy ◽  
Oxygen Vacancies ◽  
Vacancy Formation Energy ◽  
Vacancy Formation ◽  
Ceria Nanoparticles ◽  
Oxygen Vacancy Formation ◽  
Noticeable Reduction

The corner Ce atoms are essential for a noticeable reduction of the oxygen vacancy formation energy, Ef(Ovac), in nanostructured CeO2.

scholarly journals Surface Oxygen Vacancy Formation Energy Calculations in 34 Orientations of β-Ga2O3 and θ-Al2O3

2020 ◽  
Vol 124 (19) ◽  
pp. 10509-10522 ◽  
Author(s):  
Yoyo Hinuma ◽  
Takashi Kamachi ◽  
Nobutsugu Hamamoto ◽  
Motoshi Takao ◽  
Takashi Toyao ◽  
...  
Keyword(s):  
Oxygen Vacancy ◽  
Formation Energy ◽  
Vacancy Formation Energy ◽  
Vacancy Formation ◽  
Surface Oxygen ◽  
Energy Calculations ◽  
Surface Oxygen Vacancy ◽  
Oxygen Vacancy Formation

Oxygen vacancy formation energy in Pd-doped ceria: A DFT+U study

2007 ◽  
Vol 127 (7) ◽  
pp. 074704 ◽  
Author(s):  
Zongxian Yang ◽  
Gaixia Luo ◽  
Zhansheng Lu ◽  
Kersti Hermansson
Keyword(s):  
Oxygen Vacancy ◽  
Formation Energy ◽  
Vacancy Formation Energy ◽  
Vacancy Formation ◽  
Doped Ceria ◽  
Oxygen Vacancy Formation

scholarly journals Trends in C–O and N–O bond scission on rutile oxides described using oxygen vacancy formation energies

2020 ◽  
Vol 11 (16) ◽  
pp. 4119-4124
Author(s):  
Hai-Yan Su ◽  
Xiufang Ma ◽  
Keju Sun ◽  
Chenghua Sun ◽  
Yongjun Xu ◽  
...  
Keyword(s):  
Oxygen Vacancy ◽  
Formation Energy ◽  
Vacancy Formation Energy ◽  
Vacancy Formation ◽  
Oxygen Vacancy Formation ◽  
Bond Scission ◽  
Formation Energies

Oxygen vacancy formation energy is a simple and accurate descriptor for C–O and N–O bond scissions on 3d-rutile oxides.

Data-driven machine learning model for the prediction of oxygen vacancy formation energy of metal oxide materials

2021 ◽  
Author(s):  
Zhongyu Wan ◽  
Quan-De Wang ◽  
Dongchang Liu ◽  
Jinhu Liang
Keyword(s):  
Machine Learning ◽  
Oxygen Vacancy ◽  
Formation Energy ◽  
Vacancy Formation Energy ◽  
Data Driven ◽  
Vacancy Formation ◽  
Oxide Materials ◽  
Machine Learning Model ◽  
Oxygen Vacancy Formation ◽  
Key Parameter

Metal oxides are widely used in the fields of chemistry, physics and materials. Oxygen vacancy formation energy is a key parameter to describe the chemical, mechanical, and thermodynamic properties of...

Formation of oxygen vacancies in Li2FeSiO4: first-principles calculations

2021 ◽  
Vol 23 (36) ◽  
pp. 20444-20452
Author(s):  
Lihong Zhang ◽  
Shunqing Wu ◽  
Jianwei Shuai ◽  
Zhufeng Hou ◽  
Zizhong Zhu
Keyword(s):  
Oxygen Vacancy ◽  
First Principles ◽  
Formation Energy ◽  
Oxygen Vacancies ◽  
Vacancy Formation Energy ◽  
Vacancy Formation ◽  
First Principles Calculations ◽  
Temperature And Pressure

The oxygen vacancy (left panel) and the vacancy formation energy as a function of temperature and pressure (right panel).

Interfacial Structure and Point Defects in Ceria/Zirconia Superlattices

2006 ◽  
Vol 972 ◽  
Author(s):  
Michael Dyer ◽  
Anter El-Azab ◽  
Fei Gao
Keyword(s):  
Oxygen Vacancy ◽  
Formation Energy ◽  
Dislocation Core ◽  
Vacancy Formation Energy ◽  
Interfacial Structure ◽  
Dynamics Simulation ◽  
Vacancy Formation ◽  
Superlattice Structure ◽  
Oxygen Vacancy Formation ◽  
The Impact

AbstractWe report the results of a molecular dynamics simulation study aiming to understand the interfacial structure in ceria/zirconia superlattices and the impact of the interfaces on the energies of oxygen vacancy formation and Gd ion substitution in ceria and zirconia layers of the superlattice structure. It is found that the semi-coherent interface is characterized by misfit dislocations, paired at approximately 3-4 nm, with stacking-fault-like region in between, which agrees with the TEM observations. It is also found that the vacancy formation energy and the Gd substitution energy vary as a function of distance from the interface in the individual layers, and that these energies depend on the layer thickness. In addition, the simulations showed that the defect energy variations across the thickness of the ceria and zirconia layers are consistent with the XPS data for composition profile in the superlattice structure. Finally, in the semi-coherent superlattice structure, the formation energy of oxygen vacancies and the Gd substitution energy are found to depend on the position of these defects relative to the interfacial dislocation core. In particular, the oxygen vacancy formation energy is found to be negative close to the dislocation core, indicating that vacancy concentration will increase in such regions allowing for high conduction parallel to the interface.

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