Center-Environment Feature Model for Machine Learning Study of Spinel Oxides Based on First-Principles Computations-Reference-Cited by-同舟云学术

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Center-Environment Feature Model for Machine Learning Study of Spinel Oxides Based on First-Principles Computations

Published:2020-12-17 Issue:52 Volume:124 Page:28458-28468
ISSN:1932-7447
Container-title:The Journal of Physical Chemistry C
language:en
Short-container-title:J. Phys. Chem. C

Author:

Li Yihang¹,Xiao Bin¹,Tang Yuchao²,Liu Fu²,Wang Xiaomeng²,Yan Feinan³,Liu Yi¹²^ORCID

Affiliation:

1. Materials Genome Institute, Shanghai University, Shanghai 200444, China

2. Department of Physics, College of Science, Shanghai University, Shanghai 200444, China

3. Department of Physics, College of Science, University of Shanghai for Science and Technology, Shanghai 200093, China

Funder

Ministry of Science and Technology of the People's Republic of China

National Natural Science Foundation of China

Publisher

American Chemical Society (ACS)

Subject

Surfaces, Coatings and Films,Physical and Theoretical Chemistry,General Energy,Electronic, Optical and Magnetic Materials

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jpcc.0c06958

Reference65 articles.

1. Lattice Parameters and Stability of the Spinel Compounds in Relation to the Ionic Radii and Electronegativities of Constituting Chemical Elements

2. Structure of Spinel

3. Electrode properties of a spinel family, AFe2O4 (A = Co, Ni, Cu), as new cathode for solid oxide fuel cells

4. Application of spinel ferrite nanoparticles in water and wastewater treatment: A review

5. Spinel photocatalysts for environmental remediation, hydrogen generation, CO2 reduction and photoelectrochemical water splitting

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