Unveiling the porosity effect of superbase ionic liquid-modified carbon sorbents in CO2 capture from air

被引:1
作者
Mokhtari-Nori, Narges [1 ]
Qiu, Liqi [1 ]
Song, Yanpei [2 ]
He, Lilin [3 ]
Ganesan, Arvind [2 ]
Ivanov, Alexander S. [2 ]
Wang, Qingju [1 ]
Wang, Tao [2 ]
Yang, Zhenzhen [2 ]
Dai, Sheng [1 ,2 ]
机构
[1] Univ Tennessee, Inst Adv Mat & Mfg, Dept Chem, Knoxville, TN 37996 USA
[2] Oak Ridge Natl Lab, Chem Sci Div, Oak Ridge, TN 37831 USA
[3] Oak Ridge Natl Lab, Neutron Scattering Div, Oak Ridge, TN 37831 USA
基金
美国国家科学基金会;
关键词
Ionic liquids; Direct air capture; Mesoporous carbon; Carbon dioxide; Porous adsorbents; SURFACE-AREA; POLYMERS; GAS; BET;
D O I
10.1016/j.mtener.2024.101693
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
Direct air capture (DAC) of CO2 represents one of the most promising technologies to achieve negative carbon emissions. In this work, the superbase ionic liquids (ILs)-modified carbon substrates were developed for DAC of CO2 by harnessing the strong CO2 binding capability of IL and the ordered porous channels of the carbon supports. Detailed porosity analysis revealed that the IL with an aromatic cation and an oxygenate anion preferred to fill the micropores, and a thin layer was created on the surface of the mesopores. Strong p-p interaction between the IL layer and the carbon surface was disclosed by wideangle X-ray scattering (WAXS) analysis, leading to enhanced thermal stability of the IL phase. For the same lL coating amount, the DAC of CO2 evaluation revealed that a larger mesopore size and pore volume in the carbon/IL composite materials led to higher CO2 uptake capacity by exposing more active sites to integrate CO2 from diluted sources. The thermodynamic analysis confirmed the critical role of IL coating in providing strong chemisorption sites and significantly improved selectivity to enrich the diluted CO2 from the air atmosphere. This work provides guidance on leveraging the scaffolds' surface properties and porosities of the scaffolds to optimize DAC of CO2 behavior. (c) 2024 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
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页数:7
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