journal article·2018-06

Sacrificing trap density to achieve short-delay and high-contrast mechanoluminescence for stress imaging

Jun-Cheng Zhang, Xin-Hua Fan, Xu Yan, Feng Xia, Weijin Kong, Yun-Ze Long, Xusheng Wang

Acta Materialia· Volume 152
Publisher page

Abstract

Abstract Trap-controlled mechanoluminescence (ML) enables the direct observation of stress concentration of load-bearing objects through imaging the ML distribution, showing numerous prospects in stress detection, bio-imaging and optical displays. However, the applications of trap-controlled ML materials universally require long-time delay to fade the noise of symbiotic persistent luminescence (PersL) in order to achieve high-contrast ML images. In view of the difficulty to solve the PersL problem through individually eliminating the PersL traps, herein we propose a novel strategy of sacrificing trap density which decreases PersL and ML traps as a whole. By employing Sr2+ substitution to decrease the trap density of Ca2Nb2O7:Pr3+, we identify a novel composition of (Ca0.5Sr0.5)2Nb2O7:Pr3+ displaying short-delay and high-contrast ML images, and evaluate its practicability through a 2-dimensional in-situ imaging experiment of dynamic stress distribution. The underlying mechanism is ascribed to the greater decrease ratio of PersL intensity than ML intensity as a result of the larger detrapping rate of traps due to stress (leading to ML) than that due to thermal energy (PersL). Furthermore, multi-spectral investigations of (Ca,Sr)2Nb2O7:Pr3+ system reveal a distinctive electron transition process co-regulated by trap levels, charge transfer state and crystal field. The proposed strategy and the associated phosphors are expected to initiate the reconstruction of PersL-type ML materials and bring important implications for real-world stress imaging.
Source: openaire · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Luminescence Properties of Advanced Materials · Luminescence and Fluorescent Materials · bioluminescence and chemiluminescence research

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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