Topological Engineering of Perylene Diimide-Based Metallacycles through Multicomponent Self-Assembly for Fluorescence Sensing of Picric Acid

Abstract The rational construction of discrete supramolecular architectures with controlled topological complexity remains a significant challenge in coordination-driven self-assembly. Herein, we report a modular multicomponent self-assembly strategy for the construction of a homologous series of perylene diimide (PDI)-based fluorescent metallacycles with progressively increasing structural complexity. By simply varying the geometry and connectivity of auxiliary carboxylate ligands, discrete monocyclic, bicyclic, and tricyclic metallacycles were successfully assembled and characterized by nuclear magnetic resonance spectroscopy, electrospray ionization mass spectrometry, and single-crystal X-ray diffraction. Photophysical and frontier-orbital analyses reveal that these metallacycles retain strong PDI-centered absorption and high fluorescence quantum yields of 69.5–81.4%, while the tricyclic metallacycle displays a distinct donor–acceptor-type orbital separation. Furthermore, these metallacycles exhibited efficient fluorescence sensing toward picric acid, with the tricyclic metallacycle showing the highest sensitivity with a detection limit of 2.3 μmol/L. This work demonstrates that topological engineering through multicomponent coordination-driven self-assembly provides an effective strategy for developing structurally sophisticated fluorescent supramolecular sensors.

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Journal
The Journal of Physical Chemistry B
Published
2026-09-10
DOI
https://doi.org/10.1021/acs.jpcb.6c04747
Primary Topic
Supramolecular Chemistry and Complexes
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article
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Topological Engineering of Perylene Diimide-Based Metallacycles through Multicomponent Self-Assembly for Fluorescence Sensing of Picric Acid

Haonan Peng, Zhaohui Wang, Mingming Zhang, Shijin Jian et al.
The Journal of Physical Chemistry B
Supramolecular Chemistry and Complexes
article

Topological Engineering of Perylene Diimide-Based Metallacycles through Multicomponent Self-Assembly for Fluorescence Sensing of Picric Acid

Haonan Peng, Zhaohui Wang, Mingming Zhang, Shijin Jian, Yali Hou, Yingjie Li
article en

Abstract

Abstract The rational construction of discrete supramolecular architectures with controlled topological complexity remains a significant challenge in coordination-driven self-assembly. Herein, we report a modular multicomponent self-assembly strategy for the construction of a homologous series of perylene diimide (PDI)-based fluorescent metallacycles with progressively increasing structural complexity. By simply varying the geometry and connectivity of auxiliary carboxylate ligands, discrete monocyclic, bicyclic, and tricyclic metallacycles were successfully assembled and characterized by nuclear magnetic resonance spectroscopy, electrospray ionization mass spectrometry, and single-crystal X-ray diffraction. Photophysical and frontier-orbital analyses reveal that these metallacycles retain strong PDI-centered absorption and high fluorescence quantum yields of 69.5–81.4%, while the tricyclic metallacycle displays a distinct donor–acceptor-type orbital separation. Furthermore, these metallacycles exhibited efficient fluorescence sensing toward picric acid, with the tricyclic metallacycle showing the highest sensitivity with a detection limit of 2.3 μmol/L. This work demonstrates that topological engineering through multicomponent coordination-driven self-assembly provides an effective strategy for developing structurally sophisticated fluorescent supramolecular sensors.

The Journal of Physical Chemistry B
Xi'an Jiaotong University (CN), Shaanxi Normal University (CN), Tsinghua University (CN)
Industry, innovation and infrastructure
Openalex Percentile: Top 20%
Supramolecular Chemistry and Complexes
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Topological Engineering of Perylene Diimide-Based Metallacycles through Multicomponent Self-Assembly for Fluorescence Sensing of Picric Acid — Haonan Peng, Zhaohui Wang, et al. · The Journal of Physical Chemistry B (2026) | TGRS Research Map | TGRS