Prediction and exploration of emission wavelength (or energy) of luminescent materials based on machine learning DOI
X. Shi, Xin Zhong,

Wei Liu

et al.

Journal of Luminescence, Journal Year: 2024, Volume and Issue: 279, P. 121024 - 121024

Published: Dec. 10, 2024

Language: Английский

Self-recoverable broadband near infrared mechanoluminescence from BaGa12O19:Cr3+ by multi-site occupation strategy DOI
Xuesong Wang, Yao Xiao, Puxian Xiong

et al.

Materials Horizons, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 1, 2025

Near infrared mechanoluminescence (NIR-ML) materials have attracted the attention of researchers due to their unique advantages, such as high resistance bright-field interference and higher penetration depth into biological tissues. However, reported NIR-ML are mainly rare-ion-activated narrow-band emitters. In this work, we report a material BaGa12O19:Cr3+ by solid state reaction method. Broad NIR ML (650-1000 nm) is observed at lower force loads (12 N), which based on Cr3+ ion's multi-lattice site occupation. After heat treatment 573 K for 20 min, still maintains 84.4% its intensity. Furthermore, intensity also significantly improved after UV pre-irradiation. Due defective piezoelectric photonic effect, has great self-recoverable properties even in absence sunlight irradiation. Finally, rate reached 66.97% tissues, suggests potential prospects biostress detection towards bio-imaging applications.

Language: Английский

Citations

0

Prediction and exploration of emission wavelength (or energy) of luminescent materials based on machine learning DOI
X. Shi, Xin Zhong,

Wei Liu

et al.

Journal of Luminescence, Journal Year: 2024, Volume and Issue: 279, P. 121024 - 121024

Published: Dec. 10, 2024

Language: Английский

Citations

0