Exploring covalent organic frameworks for H2S+CO2 separation from natural gas using efficient computational approaches

吸附 共价键 天然气 真空摆动吸附 金属有机骨架 共价有机骨架 多孔性 气体分离 化学 化学工程 材料科学 变压吸附 有机化学 生物化学 工程类
作者
Gokhan Onder Aksu,İlknur Eruçar,Zeynep Pınar Haşlak,Seda Keskın
出处
期刊:Journal of CO2 utilization [Elsevier]
卷期号:62: 102077-102077 被引量:4
标识
DOI:10.1016/j.jcou.2022.102077
摘要

Covalent organic frameworks (COFs) are emerged as strong adsorbent candidates for industrial gas separation applications due to their highly porous structures. In this work, we explored H2S+CO2 capture potentials of synthesized and computer-generated COFs from a natural gas mixture using an efficient, multi-level computational screening approach. We computed the adsorption data of a six-component natural gas mixture, CH4/C2H6/CO2/C3H8/H2S/H2O, for 580 synthesized COFs by performing Grand Canonical Monte Carlo (GCMC) simulations under industrially relevant conditions. H2S+CO2 selectivities and working capacities of COFs were computed to be 0.4–12.4 (0.2–8.5) and 0.01–5.36 (0.04–2.5) mol/kg at pressure-swing adsorption (vacuum-swing adsorption) condition. NPN-3 was identified as the best performing COF due to the competitive adsorption of H2S+CO2 over C2H6 and C3H8 as revealed by density functional theory (DFT) calculations. Structural (pore sizes, porosities, and topologies) and chemical properties (linker units and heats of gas adsorption) of the best-performing synthesized COFs were used to efficiently screen the very large number of hypothetical COFs (hypoCOFs). Results showed that isosteric heats of adsorption can be used to discover high performing hypoCOFs for H2S+CO2 separation from natural gas. Finally, we compared COFs, hypoCOFs, zeolites, carbon nanotubes, metal organic frameworks (MOFs) and concluded that several synthesized and computer-generated COFs can outperform traditional adsorbents in terms of H2S+CO2 selectivities. Our results provide molecular-level insights about the potential of COFs for natural gas purification and direct the design and development of new COF materials with high H2S+CO2 selectivities.

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
大幅提高文件上传限制,最高150M (2024-4-1)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
酸奶泡泡完成签到 ,获得积分10
4秒前
认真莆完成签到,获得积分10
4秒前
Fuchen完成签到,获得积分10
6秒前
小猪熊完成签到 ,获得积分10
11秒前
bkagyin应助金甲狮王采纳,获得10
11秒前
俊逸沛菡完成签到 ,获得积分10
13秒前
xiaozhang完成签到 ,获得积分10
15秒前
你爸完成签到 ,获得积分10
19秒前
21秒前
程程完成签到,获得积分10
26秒前
zhdjj完成签到 ,获得积分10
26秒前
金甲狮王发布了新的文献求助10
27秒前
鹏826完成签到 ,获得积分10
28秒前
DTiverson完成签到,获得积分10
29秒前
苏子轩完成签到 ,获得积分10
36秒前
山城完成签到 ,获得积分10
38秒前
火龙果完成签到,获得积分10
39秒前
星海完成签到,获得积分10
39秒前
gjww完成签到,获得积分0
40秒前
飘文献完成签到,获得积分10
41秒前
无名花生完成签到 ,获得积分10
42秒前
Andy完成签到 ,获得积分10
47秒前
一程完成签到 ,获得积分10
48秒前
wwww娟娟完成签到 ,获得积分10
49秒前
牟稀应助jinyu采纳,获得30
49秒前
Judy完成签到 ,获得积分10
50秒前
orixero应助vivian采纳,获得10
55秒前
洛尘完成签到,获得积分10
57秒前
ywsss完成签到,获得积分10
57秒前
xinxin完成签到 ,获得积分10
58秒前
11完成签到 ,获得积分10
1分钟前
小猪佩奇完成签到,获得积分10
1分钟前
1分钟前
赘婿应助牟稀采纳,获得10
1分钟前
顺利雪糕完成签到,获得积分10
1分钟前
JamesPei应助科研通管家采纳,获得10
1分钟前
酷波er应助科研通管家采纳,获得10
1分钟前
小蘑菇应助科研通管家采纳,获得10
1分钟前
烟花应助科研通管家采纳,获得10
1分钟前
上官若男应助科研通管家采纳,获得10
1分钟前
高分求助中
Teaching Social and Emotional Learning in Physical Education 900
Boris Pesce - Gli impiegati della Fiat dal 1955 al 1999 un percorso nella memoria 500
Chinese-English Translation Lexicon Version 3.0 500
Recherches Ethnographiques sue les Yao dans la Chine du Sud 500
Two-sample Mendelian randomization analysis reveals causal relationships between blood lipids and venous thromboembolism 500
[Lambert-Eaton syndrome without calcium channel autoantibodies] 460
Aspect and Predication: The Semantics of Argument Structure 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 有机化学 工程类 生物化学 纳米技术 物理 内科学 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 电极 光电子学 量子力学
热门帖子
关注 科研通微信公众号,转发送积分 2396595
求助须知:如何正确求助?哪些是违规求助? 2098746
关于积分的说明 5289432
捐赠科研通 1826225
什么是DOI,文献DOI怎么找? 910523
版权声明 560007
科研通“疑难数据库(出版商)”最低求助积分说明 486633