LiGa5O8:Cr3+@PEG nanomaterials with near-infrared-persistent luminescence for bioimaging applications

Bioimaging is considered a convincing imaging method. The near-infrared Persistent Luminescence Nanoparticles(NIR PLNPS) have demonstrated great perspectives for application in the bioimaging field due to their unique optical properties. The high-temperature solid-phase(HT) methods cannot be used fo...

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Veröffentlicht in:Optical materials 2022-12, Vol.134, p.113157, Article 113157
Hauptverfasser: Wang, Yue, Wu, Shiran, Wu, Mengya, Lei, Weiyan, Yi shen, Li, Fengfeng
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Sprache:eng
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Zusammenfassung:Bioimaging is considered a convincing imaging method. The near-infrared Persistent Luminescence Nanoparticles(NIR PLNPS) have demonstrated great perspectives for application in the bioimaging field due to their unique optical properties. The high-temperature solid-phase(HT) methods cannot be used for bioimaging applications due to the existence of large particle size. On the other hand, the sol-gel (S-G) and the hydrothermal(Hy) methods can successfully prepare the LGO: Cr nanomaterials. In this work, a LiGa5O8:Cr3+(LGO: Cr) NIR PLNPS was prepared by S-G and Hy methods, and the employed nanomaterials were treated by PEG(Polyethylene glycol) modification to reduce the toxicity. The acquired results clearly show that the average particle size of the samples that were prepared by enforcing the S-G method is larger than that of the Hy method. However, their luminescence performance is better than that of the samples prepared by Hy method, and there are differences in trap characteristics. Synthetically, LGO: Cr@PEG(Hy) is suited for biological imaging due to its lower toxicity, and cell imaging by LGO: Cr@PEG(Hy)was successfully achieved. •LGO: Cr nanomaterials is synthesized by Sol-Gel and the hydrothermal methods.•The application of LGO: Cr in bioimaging is comprehensively studied from performance and particle size.•Toxicity is reduced by PEG modification and LGO: Cr @PEG is successfully used for bioimaging.
ISSN:0925-3467
1873-1252
DOI:10.1016/j.optmat.2022.113157