globalchange  > 影响、适应和脆弱性
DOI: 10.1016/j.jcou.2017.07.022
Scopus记录号: 2-s2.0-85028082820
论文题名:
Fluorine-rich carbon nanoscrolls for CO2/CO (C2H2) adsorptive separation
作者: Li X.; Xue Q.; Chang X.; Zhu L.; Zheng H.
刊名: Journal of CO2 Utilization
ISSN: 22129820
出版年: 2017
卷: 21
起始页码: 429
结束页码: 435
语种: 英语
英文关键词: Adsorption energy ; Carbon nanoscrolls ; CO2 capture ; Fluorine doping ; Grand canonical Monte Carlo calculations
Scopus关键词: Adsorption ; Fluorine ; Gas adsorption ; Molecules ; Monte Carlo methods ; Adsorption energies ; Carbon nanoscrolls ; CO2 capture ; Fluorine doping ; Grand canonical Monte carlo ; Carbon dioxide
英文摘要: Carbon nanoscrolls have shown great potential in gas adsorption and storage. In this paper, a feasible method for synthesizing one-sided fluorine doped carbon nanoscroll (F-CNS) is proposed, and the adsorption behavior of CO2, CO and C2H2 on one-sided F-CNS has been firstly investigated via Grand Canonical Monte Carlo calculations. It is demonstrated that the one-sided F-CNS possesses outstanding CO2 uptake with good CO2/CO and CO2/C2H2 selectivity compared with pristine CNS. Specially, at 300 K and 1 bar, one-sided F-CNS shows a CO2 uptake of 68.87 mmol/mol and CO uptake of 12.09 mmol/mol, which is much higher than those of CO2 (16.6 mmol/mol) and CO (6.02 mmol/mol) for pristine CNS. Furthermore, our results demonstrate that the excellent selective CO2 adsorption capacity of one-sided F-CNS is owing to its stronger interactions with CO2 molecules than CO and C2H2 molecules. Our research suggests that one-sided F-CNS is a promising candidate for high selective CO2 capture.
Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/52663
Appears in Collections:影响、适应和脆弱性

Files in This Item:

There are no files associated with this item.


Recommended Citation:
Li X.,Xue Q.,Chang X.,et al. Fluorine-rich carbon nanoscrolls for CO2/CO (C2H2) adsorptive separation[J]. Journal of CO2 Utilization,2017-01-01,21
Service
Recommend this item
Sava as my favorate item
Show this item's statistics
Export Endnote File
Google Scholar
Similar articles in Google Scholar
[Li X.]'s Articles
[Xue Q.]'s Articles
[Chang X.]'s Articles
百度学术
Similar articles in Baidu Scholar
[Li X.]'s Articles
[Xue Q.]'s Articles
[Chang X.]'s Articles
CSDL cross search
Similar articles in CSDL Cross Search
[Li X.]‘s Articles
[Xue Q.]‘s Articles
[Chang X.]‘s Articles
Related Copyright Policies
Null
收藏/分享
所有评论 (0)
暂无评论
 

Items in IR are protected by copyright, with all rights reserved, unless otherwise indicated.