JOURNAL ARTICLE

Rational Design of Porous Organic Framework (POF) for Efficient Conversion of CO2 to Cyclic Carbonates and 2‐Oxazolidinones at Atmospheric Pressure Conditions.

  • Published In: Chemistry - An Asian Journal, 2025, v. 20, n. 8. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Parihar, Vaibhav; Kumar, Bharat; Singh, Gulshan; Nagaraja, C. M. 3 of 3

Abstract

Carbon dioxide (CO2) capture and its subsequent catalytic fixation into usable compounds represent a potential approach for addressing the energy problem and the implications of global warming. Hence, it is necessary to develop effective catalytic systems required for the transformation of CO2 into valuable chemicals/fuels. Herein, we rationally designed a hydroxyl‐functionalized porous organic framework (OH‐POF) consisting of both acidic (OH) as well as basic N sites for the transformation of CO2 using epoxides for the production of cyclic carbonates (CCs), a useful commodity chemical under environmental‐friendly, metal/solvent/co‐catalyst‐free conditions. Moreover, OH‐POF was post‐synthetically modified to anchor non‐noble metal, Zn(II) to generate Zn‐POF and further explored it for the efficient functionalization of CO2 with propargylic amines to generate valuable bioactive 2‐oxazolidinones. Significantly, both OH‐POF and Zn‐POF demonstrated exceptional reusability with catalytic efficacy retained across numerous cycles of use. Notably, this study showcases a green and sustainable process for utilization of CO2 under environmentally favorable ambient conditions into two highly valuable compounds, viz cyclic carbonates and 2‐oxazolidinones. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Chemistry - An Asian Journal. 2025/04, Vol. 20, Issue 8, p1
  • Document Type:Article
  • Subject Area:Chemistry
  • Publication Date:2025
  • ISSN:1861-4728
  • DOI:10.1002/asia.202401546
  • Accession Number:184574074
  • Copyright Statement:Copyright of Chemistry - An Asian Journal 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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