Continuous Synthesis and Processing of Covalent Organic Frameworks in a Flow Reactor
Safiya Khalil1, Abdullah Alazmi1, Guanhui Gao2
1Department of Chemical and Biomolecular Engineering, Rice University, MS-362, 6100 Main Street, Houston, Texas 77005, United States.
Continuous flow synthesis enables scalable production of covalent organic frameworks (COFs). This method yields high-purity COFs in diverse forms, demonstrating superior photocatalytic activity for pollutant degradation.
Area of Science:
- Materials Science
- Chemical Engineering
- Nanotechnology
Background:
- Covalent organic frameworks (COFs) are typically synthesized via energy-intensive batch solvothermal methods, leading to limitations in scalability and processing.
- These synthetic challenges hinder the widespread adoption and commercialization of COFs for various applications.
Purpose of the Study:
- To develop a scalable and efficient method for continuous synthesis and processing of COFs.
- To produce COFs with controlled morphology and high crystallinity.
- To evaluate the performance of flow-synthesized COFs in a practical application, such as photocatalysis.
Main Methods:
- Utilized a flow microreactor for continuous synthesis of imine- and hydrazone-linked COFs.
- Controlled key COF formation stages including nanoparticle growth, self-assembly, and precipitation.
- Characterized the resulting COFs for crystallinity, porosity, and macroscopic structure.
Main Results:
- Achieved unprecedented COF productivities up to 61,111 kg m⁻³ day⁻¹.
- Successfully produced highly crystalline and porous COFs in versatile macroscopic forms (monoliths, membranes, prints, packed beds).
- Demonstrated superior photocatalytic degradation of perfluorooctanoic acid (PFOA) using flow-synthesized COFs compared to batch analogues and TiO₂.
Conclusions:
- Flow microreactor technology offers a scalable and efficient route for COF synthesis and processing.
- Flow-synthesized COFs exhibit excellent properties and performance, particularly in photocatalysis.
- This approach overcomes limitations of traditional batch methods, paving the way for broader COF applications.
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