Presentation Information
[19p-C601-6]Text mining and machine learning of Eu valence states in phosphor materials
〇Yukinori Koyama1, Naoto Hirosaki1, Yukako Kohriki1, Takashi Takeda1 (1.NIMS)
Keywords:
phosphor,machine learning,text mining
Europium is one of the elements that have been widely investigated as luminescent centers of phosphor materials. The doped europium can have divalent and trivalent states in the host crystals. Since the luminescence mechanism is different for divalent and trivalent europium, it is essential to select host compounds that achieve the desired valence state. However, the valence state of europium in the host crystal is not obvious. Therefore, we extracted information on the valence of europium in phosphor materials from the literature and performed machine learning of the valence states in the host compounds.