Mixed matrix membranes based on carbon quantum dots with enhanced CO2 capture performances

Abstract

Abstract Mixed matrix membranes (MMMs) can more readily surpass the Robeson upper bound by combining the complementary advantages of organic and inorganic membranes. However, these membranes inevitably suffer from nanoparticle agglomeration and the resulting non-selective interfacial defects, which significantly deteriorate their carbon dioxide (CO2) separation performance. Furthermore, particle aggregation poses considerable challenges for fabricating thin-film nanocomposite (TFN) membranes. In this study, CQDs rich in amino and oxygen-containing functional groups were synthesized via a one-step method and used to fabricate MMMs for CO2 separation. The small size of 0D carbon quantum dots (CQDs) enables their uniform dispersion in casting solutions, effectively preventing filler aggregation-induced degradation of CO2 separation performance. Meanwhile, the addition of CQDs altered the disorder and hydrophilicity of Pebax 1657, significantly improving its CO2 capture performance. With a feed pressure of 6 bar, the CO2 permeability of the CQDs-Pebax 1657 membrane reached 248.3 Barrer, with a CO2/N2 selectivity of 78.1 (close to the 2019 Robeson upper bound). TFN membranes have been also developed, CO2 permeance of 248.4 GPU and CO2/N2 separation factor of 56.2 was documented. Under 100% relative humidity conditions, the CO2 permeance was improved to 345.9 GPU, and the CO2/N2 separation factor was 64.2, outperforming most other Pebax-based membranes. The obtained membranes also exhibited good stability performances in a 72 h of continuous test, denoting that CQDs can be considered an ideal nano additives to effectively enhance membrane CO2 capture permeances.

Supplementary files

Article information

Article type
Paper
Submitted
16 Apr 2025
Accepted
24 Jul 2025
First published
25 Jul 2025

J. Mater. Chem. A, 2025, Accepted Manuscript

Mixed matrix membranes based on carbon quantum dots with enhanced CO2 capture performances

L. Shi, J. Wei, Y. Wu, Z. Qin, M. Deng, J. Song, Y. Wang, L. Yang, L. Yao, W. Jiang, J. Zheng and Z. Dai, J. Mater. Chem. A, 2025, Accepted Manuscript , DOI: 10.1039/D5TA03016A

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