JOURNAL ARTICLE
Transitioning Room‐Temperature Phosphorescence from Solid States to Aqueous Phases via a Cyclic Peptide‐Based Supramolecular Scaffold.
Published In: Angewandte Chemie International Edition, 2025, v. 64, n. 11. P. 1 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Feng, Ruicong; Yan, Xianjia; Sang, Yufeng; Liu, Xindi; Luo, Zhi; Xie, Zhenhua; Ke, Yubin; Song, Qiao 3 of 3
Abstract
Aqueous room‐temperature phosphorescence (RTP) materials have garnered considerable attention for their significant potential across various applications such as bioimaging, sensing, and encryption. However, establishing a universally applicable method for achieving aqueous RTP remains a substantial challenge. Herein, we present a versatile supramolecular strategy to transition RTP from solid states to aqueous phases. By leveraging a cyclic peptide‐based supramolecular scaffold, we have developed a noncovalent approach to molecularly disperse diverse organic phosphors within its rigid hydrophobic microdomain in water, yielding a series of aqueous RTP materials. Moreover, high‐performance supramolecular phosphorescence resonance energy transfer (PRET) systems have been constructed. Through the facile co‐assembly of a fluorescent acceptor with the existing RTP system, these PRET systems exhibit high energy transfer efficiencies (>80 %), red‐shifted afterglow emission (520–790 nm), ultralarge Stokes shifts (up to 450 nm), and improved photoluminescence quantum yields (6.1–30.7 %). This study not only provides a general strategy for constructing aqueous RTP materials from existing phosphors, but also facilitates the creation of PRET systems featuring color‐tunable afterglow emission. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Angewandte Chemie International Edition. 2025/03, Vol. 64, Issue 11, p1
- Document Type:Article
- Subject Area:Physics
- Publication Date:2025
- ISSN:1433-7851
- DOI:10.1002/anie.202421729
- Accession Number:183986944
- Copyright Statement:Copyright of Angewandte Chemie International Edition is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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