Understanding Oxygen Anion Transport in Nb-Doped La0.7Sr0.3CoO3 Perovskite Materials

2021 ◽  
Vol MA2021-01 (46) ◽  
pp. 1842-1842
Author(s):  
Vicky Dhongde ◽  
Suddhasatwa Basu ◽  
Mohammad Ali Haider
Keyword(s):  
Anion Transport ◽  
Oxygen Anion ◽  
Perovskite Materials

Visualizing oxygen anion transport pathways in NdBaCo2O5+δ by in situ neutron diffraction

2013 ◽  
Vol 1 (9) ◽  
pp. 3091 ◽  
Author(s):  
Rosemary A. Cox-Galhotra ◽  
Ashfia Huq ◽  
Jason P. Hodges ◽  
Jung-Hyun Kim ◽  
Chengfei Yu ◽  
...  
Keyword(s):  
Neutron Diffraction ◽  
Anion Transport ◽  
Oxygen Anion ◽  
Transport Pathways ◽  
In Situ Neutron Diffraction

Oxygen vacancy localization and anisotropic oxygen anion transport in Sr1−xYxCoO3−δ (x = 0.1, 0.2) under solid oxide fuel cell cathode conditions

2018 ◽  
Vol 321 ◽  
pp. 34-42 ◽  
Author(s):  
Caterina Sarno ◽  
Tianrang Yang ◽  
Elisabetta Di Bartolomeo ◽  
Ashfia Huq ◽  
Kevin Huang ◽  
...  
Keyword(s):  
Fuel Cell ◽  
Oxygen Vacancy ◽  
Solid Oxide Fuel Cell ◽  
Anion Transport ◽  
Solid Oxide ◽  
Oxide Fuel ◽  
Oxygen Anion ◽  
Fuel Cell Cathode ◽  
Cell Cathode

Engineering Hybrid Perovskite Materials for Spectroscopic Sensing of Ionizing Radiation

2019 ◽  
Author(s):  
Eric Lukosi ◽  
Mahshid Ahmadi ◽  
Travis Smith ◽  
Ryan Tan ◽  
Bogdan Dryzhakov ◽  
...  
Keyword(s):  
Ionizing Radiation ◽  
Perovskite Materials ◽  
Hybrid Perovskite

Anharmonicity and Dielectric Properties in Hybrid and Inorganic Perovskite Materials used for Photovoltaics Applications

2017 ◽  
Author(s):  
Arthur Marronnier ◽  
Heejae Lee ◽  
Bernard Geffroy ◽  
Yvan Bonnassieux ◽  
Jacky Even ◽  
...  
Keyword(s):  
Dielectric Properties ◽  
Inorganic Perovskite ◽  
Perovskite Materials ◽  
Materials Used

scholarly journals Machine learning for perovskite materials design and discovery

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Qiuling Tao ◽  
Pengcheng Xu ◽  
Minjie Li ◽  
Wencong Lu
Keyword(s):  
Machine Learning ◽  
Technological Innovation ◽  
Future Development ◽  
Rational Design ◽  
Driving Forces ◽  
Scientific Progress ◽  
Double Perovskites ◽  
Perovskite Materials ◽  
Development Tendency ◽  
Development Prospects

AbstractThe development of materials is one of the driving forces to accelerate modern scientific progress and technological innovation. Machine learning (ML) technology is rapidly developed in many fields and opening blueprints for the discovery and rational design of materials. In this review, we retrospected the latest applications of ML in assisting perovskites discovery. First, the development tendency of ML in perovskite materials publications in recent years was organized and analyzed. Second, the workflow of ML in perovskites discovery was introduced. Then the applications of ML in various properties of inorganic perovskites, hybrid organic–inorganic perovskites and double perovskites were briefly reviewed. In the end, we put forward suggestions on the future development prospects of ML in the field of perovskite materials.

Sign in / Sign up

Export Citation Format

Share Document