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Self‐Assembled Bent Perylenediimides.

  • Published In: Angewandte Chemie International Edition, 2025, v. 64, n. 6. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Wang, Rui; Qian, Baiyang; Xu, Yuchuan; Zhao, Di; Chen, Qiqi; Wei, Yifei; Zhang, Cankun; Liang, WanZhen; Jiang, Yun‐Bao; Zhang, Hui‐Jun; Lin, Jianbin 3 of 3

Abstract

The properties of π‐functional materials are predominantly influenced by both their molecular structures and interactions between π‐systems. Recent advancements have focused on modifying the geometry or topology of π‐molecules from planar to nonplanar conformations to tailor molecular properties. However, the interactions among nonplanar π‐molecules remain largely unexplored, likely due to the significant reduction in contact surfaces arising from their curved structures. Herein, we investigated the electro‐optical properties and π‐stacking behaviors of a series of bent perylenediimides (B‐PDIs) with gradual changes in bending angles, achieved by altering the lengths of linear alkyl chains connecting the two nitrogen positions of each PDI. Curvature‐dependent self‐assembly of these bent PDIs is observed, which is primarily driven by dipole‐dipole interactions rather than dispersion forces. More importantly, fine‐tuning intermolecular coupling through bending enables excited‐state symmetry‐breaking charge separation in [n]B‐PDIs (n = 16, 12) in the crystalline solid state. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Angewandte Chemie International Edition. 2025/02, Vol. 64, Issue 6, p1
  • Document Type:Article
  • Subject Area:Physics
  • Publication Date:2025
  • ISSN:1433-7851
  • DOI:10.1002/anie.202421871
  • Accession Number:183986378
  • 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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