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Data-Driven Photoluminescence Tuning in Eu2+-Doped Phosphors
journal contribution
posted on 2020-07-02, 18:03 authored by Shunqi Lai, Ming Zhao, Jianwei Qiao, Maxim S. Molokeev, Zhiguo XiaDiscovery
of rare earth phosphors has generally relied on the chemical
intuition and time-intensive trial-and-error synthesis; therefore,
finding new materials assisted by data-driven computations is urgent.
Herein, we utilize a regression model to predict the emission wavelengths
of Eu2+-doped phosphors by revealing the relationships
between the crystal structure and luminescence property. The emission
wavelengths of [Rb(1–x)K(x)]3LuSi2O7:Eu2+ (0 ≤ x ≤ 1) phosphors, as examples for the data-driven
photoluminescence tuning, are successfully predicted on the basis
of the existing data of only eight systems, also consistent with the
experimental results. These phosphors can be excited by blue light
and exhibit broad-band red and near-infrared emission ranging from
619 to 737 nm. These findings in Eu2+-doped silicate phosphors
indicate that data-driven computations through the regression mode
would have bright application in discovering novel phosphors with
a target emission wavelengths.