Ruichen Shen, Tianpei He, Sailing Yao, Yun Zhang, Tianhuan Peng, Weihong Tan, Na Chen, Quan Yuan
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Defect Regulation Strategy of Porous Persistent Phosphors for Multiple and Dynamic Information Encryption
Optical encryption technologies based on persistent luminescence material have currently drawn increasing attention due to the distinctive and long-lived optical properties, which enable multi-dimensional and dynamic optical information encryption to improve the security level. However, the controlled synthesis of persistent phosphors remains largely unexplored and it is still a great challenge to regulate the structure for optical properties optimization, which inevitably sets significant limitations on the practical application of persistent luminescent materials. Herein, a controlled synthesis method is proposed based on defect structure regulation and a series of porous persistent phosphors is obtained with different luminous intensities, lifetime, and wavelengths. By simply using diverse templates during the sol–gel process, the oxygen vacancy defects structures are successfully regulated to improve the optical properties. Additionally, the obtained series of porous Al2O3 are utilized for multi-color and dynamic optical information encryption to increase the security level. Overall, the proposed defect regulation strategy in this work is expected to provide a general and facile method for optimizing the optical properties of persistent luminescent materials, paving new ways for broadening their applications in multi-dimensional and dynamic information encryption.
Small MethodsMaterials Science-General Materials Science
CiteScore
17.40
自引率
1.60%
发文量
347
期刊介绍:
Small Methods is a multidisciplinary journal that publishes groundbreaking research on methods relevant to nano- and microscale research. It welcomes contributions from the fields of materials science, biomedical science, chemistry, and physics, showcasing the latest advancements in experimental techniques.
With a notable 2022 Impact Factor of 12.4 (Journal Citation Reports, Clarivate Analytics, 2023), Small Methods is recognized for its significant impact on the scientific community.
The online ISSN for Small Methods is 2366-9608.