Prediction of emission energy of Cr 3+ in oxides based on first-principles calculations and machine learning

The first-principles calculations of the energies of the emission level ( 2 E g ) of Cr 3+ in 10 oxide crystals were performed using the first-principles configuration-interaction calculations. In order to improve the accuracy of the prediction, a machine learning model was created by using the resu...

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Bibliographic Details
Published in:IOP conference series. Materials Science and Engineering 2020-04, Vol.835 (1), p.12018
Main Authors: Hori, Tsubasa, Ogasawara, Kazuyoshi
Format: Article
Language:English
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Summary:The first-principles calculations of the energies of the emission level ( 2 E g ) of Cr 3+ in 10 oxide crystals were performed using the first-principles configuration-interaction calculations. In order to improve the accuracy of the prediction, a machine learning model was created by using the results of the first-principles calculations and the experimental 2 E g energies as the training data. The predicted values using this model showed good correlation with the experimental values, where the correlation coefficient is 0.92. The obtained predicted model indicated that the Cr 3d component of t 2g molecular orbital is the most important quantity for prediction of the 2 E g energy.
ISSN:1757-8981
1757-899X
DOI:10.1088/1757-899X/835/1/012018