JOURNAL ARTICLE

Ionic Covalent Organic Frameworks Consisting of Tetraborate Nodes and Flexible Linkers.

  • Published In: Angewandte Chemie International Edition, 2024, v. 63, n. 42. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Wayment, Lacey J.; Huang, Shaofeng; Chen, Hongxuan; Lei, Zepeng; Ley, Ashley; Lee, Se‐Hee; Zhang, Wei 3 of 3

Abstract

Covalent organic frameworks (COFs) have emerged as versatile materials with many applications, such as carbon capture, molecular separation, catalysis, and energy storage. Traditionally, flexible building blocks have been avoided due to their potential to disrupt ordered structures. Recent studies have demonstrated the intriguing properties and enhanced structural diversity achievable with flexible components by judicious selection of building blocks. This study presents a novel series of ionic COFs (ICOFs) consisting of tetraborate nodes and flexible linkers. These ICOFs use borohydrides to irreversibly deprotonate the alcohol monomers to achieve a high degree of polymerization. Structural analysis confirms the dia topologies. Reticulation is explored using various monomers and metal counterions. Also, these frameworks exhibit excellent stability in alcohols and coordinating solvents. The materials have been tested as single‐ion conductive solid‐state electrolytes. ICOF‐203‐Li displays one of the lowest activation energies reported for ion conduction. This tetraborate chemistry is anticipated to facilitate further structural diversity and functionality in crystalline polymers. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Angewandte Chemie International Edition. 2024/10, Vol. 63, Issue 42, p1
  • Document Type:Article
  • Subject Area:Geology
  • Publication Date:2024
  • ISSN:1433-7851
  • DOI:10.1002/anie.202410816
  • Accession Number:180150669
  • 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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