Theoretical and experimental study on the fluidity performance of hard-to-fluidize carbon nanotubes-based CO2 capture sorbents

Carbon nanotubes-based materials have been identified as promising sorbents for efficient CO2 capture in fluidized beds, suffering from insufficient contact with CO2 for the high-level CO2 capture capacity. This study focuses on promoting the fluidizability of hard-to-fluidize pure and synthesized silica-coated amine-functionalized carbon nanotubes. The novel synthesized sorbent presents a superior sorption capacity of about 25 times higher than pure carbon nanotubes during 5 consecutive adsorption/regeneration cycles. The low-cost fluidizable-SiO2 nanoparticles are used as assistant material to improve the fluidity of carbon nanotubes-based sorbents. Results reveal that a minimum amount of 7.5 and 5 wt% SiO2 nanoparticles are required to achieve an agglomerate particulate fluidization behavior for pure and synthesized carbon nanotubes, respectively. Pure carbon nanotubes + 7.5 wt% SiO2 and synthesized carbon nanotubes + 5 wt% SiO2 indicates an agglomerate particulate fluidization characteristic, including the high-level bed expansion ratio, low minimum fluidization velocity (1.5 and 1.6 cms−1), high Richardson—Zaki n index (5.2 and 5.3 > 5), and low Π value (83.2 and 84.8 < 100, respectively). Chemical modification of carbon nanotubes causes not only enhanced CO2 uptake capacity but also decreases the required amount of silica additive to reach a homogeneous fluidization behavior for synthesized carbon nanotubes sorbent. [Figure not available: see fulltext.]

Bibliographic Details

Main Authors:	Nobarzad, Mahsa Javidi, Tahmasebpoor, Maryam, Heidari, Mohammad, Pevida García, Covadonga
Other Authors:	Pevida García, Covadonga [0000-0002-4662-8448]
Format:	artículo biblioteca
Language:	English
Published:	Springer Nature 2022-05-18
Subjects:	CNT-based sorbents, CO2 capture, SiO2 fluidization, nanoparticles, fluidized bed reactors,
Online Access:	http://hdl.handle.net/10261/278316 https://api.elsevier.com/content/abstract/scopus_id/85130300810
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