(27e) High-Permeance Polymer-Functionalized Graphene Membranes That Surpass the Postcombustion Carbon Capture Target | AIChE

(27e) High-Permeance Polymer-Functionalized Graphene Membranes That Surpass the Postcombustion Carbon Capture Target

Authors 

Agrawal, K. V. - Presenter, École Polytechnique Fédérale De Lausanne (EPFL)
He, G., École Polytechnique Fédérale de Lausanne (EPFL)
Postcombustion carbon capture using high-performance CO2-selective membranes has been identified as one of the most energy-efficient routes for reducing CO2 emissions [1-3]. However, the capture performance, especially the permeance of the state-of-the-art membranes needs to be significantly increased to further improve the appeal of membranes for postconbustion capture, and importantingly, reduce the needed membrane area for separation because the capital cost of the membrane modules scales inversely with the permeance. Currently, with the exception of Polaris second generation membranes from Membrane Technology Research which yields a CO2 permeance of 2000 GPU, there is no membrane technology that reaches the CO2 permeance significantly higher than 1000 GPU, while maintaining a separation factor of 20 or above in the humid flue gas conditions. In this presentation, I will report a new class of sub-20-nm-thick organic-inorganic hybrid membranes, which we call as SPONG, comprising of nanoporous single-layer-graphene with a high porosity (up to 18.5%), functionalized with CO2-phillic polymeric chains [4]. The hybrid membranes yield CO2 permeance sixfold larger (6290 GPU) than the performance target while separating the CO2/N2 mixture mimicking flue gas streams with a separation factor well within the target. Overall, we report a number of membranes that yield CO2 permeance up to 11790 GPU and CO2/N2 mixture separation factor up to 57.2. The hybrid membrane is conducive for scale-up because of its facile preparation involving simple coating steps.

References

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  2. Rao, A. B. & Rubin, E. S. Sci. Technol. 36, 4467–4475 (2002).
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  4. He, G., Huang, S., Villalobos, L. F., Zhao, J., Mensi, M., Oveisi, E., Rezaei, M., Agrawal, K. V. Submitted, under review (2019).