Photoluminescence Color Prediction for Eu3+‐Doped Perovskite Red Phosphors Using Machine Learning
Takahito Otsuka,
Ryohei Oka,
Masayuki Karasuyama
et al.
Abstract:Currently, data‐driven approaches for exploring novel materials are garnering significant attention with the expectation of accelerating material development cycles and understanding materials from various aspects. This short article presents a supervised prediction model for the emission intensity ratio of 5D0–7F2 and 5D0–7F1 transition of Eu3+ ions, called an “asymmetry ratio”, which determines the color purity of the red region of Eu3+ photoluminescence in perovskite phosphors. The model is developed using … Show more
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