Development of 3D-Printed Polymer-Zeolite Composite Monoliths for Gas Separation

Abstract

Organic-inorganic materials have emerged as promising candidates for use in various gas separation processes due to the beneficial synergistic effect of both constituents. Herein, we report a novel and facile approach for fabrication of composite monoliths consisting of Torlon polymer and 13X and 5A zeolites via 3D printing technique for the removal of CO₂ from flue gas. The physical and structural properties of 3D-printed composite monoliths were systematically evaluated and compared with their pristine powders. The formation of monoliths was facilitated through nonsolvent-induced phase separation technique. By the incorporation of ∼31 wt% zeolite particles into the polymer matrix, the obtained monoliths displayed CO₂ capture capacities proportional to the zeolite loading. Most importantly, both 3D-printed Torlon-zeolite monoliths exhibited high compressive strengths of approximately 210 MPa, which was significantly higher than that of 3D-printed zeolite monoliths developed in our previous work. These results demonstrate the superiority of polymer-zeolite composite monoliths, formulated by 3D printing technique as robust structures with outstanding mechanical integrity and comparable adsorption capacity for various adsorption-based gas separation processes. The printing strategy reported herein can be easily extended to other organic-inorganic composite materials with different polymers and inorganic particles.

Department(s)

Chemical and Biochemical Engineering

Comments

This work was financially supported by the NASA-EPSCoR (NNX15AK38A).

Keywords and Phrases

Carbon Dioxide; Compressive Strength; Organic Polymers; Organic-Inorganic Materials; Phase Separation; Zeolites; 3-D Printing; Adsorption Capacities; CO2 Capture; Composite Monoliths; Gas Separation Process; Mechanical Integrity; Nonsolvent-Induced Phase Separation; Organic-Inorganic Composite; 3D Printers; Torlon Polymer

International Standard Serial Number (ISSN)

1385-8947

Document Type

Article - Journal

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2018 Elsevier, All rights reserved.

Publication Date

01 Sep 2018

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