Data-driven design of metal–organic frameworks for wet flue gas CO2 capture

烟气 金属有机骨架 纳米孔 吸附 背景(考古学) 限制 水槽(地理) 碳捕获和储存(时间表) 烟道 固碳 纳米技术 环境科学 工艺工程 废物管理 化学 材料科学 二氧化碳 有机化学 地质学 工程类 古生物学 地图学 气候变化 地理 海洋学 机械工程
作者
Peter G. Boyd,Arunraj Chidambaram,Enrique García-Díez,Christopher P. Ireland,Thomas D. Daff,Richard Bounds,Andrzej Gładysiak,Pascal Schouwink,Seyed Mohamad Moosavi,M. Mercedes Maroto‐Valer,Jeffrey A. Reimer,Jorge A. R. Navarro,Tom K. Woo,Susana García,Kyriakos C. Stylianou,Berend Smit
出处
期刊:Nature [Nature Portfolio]
卷期号:576 (7786): 253-256 被引量:864
标识
DOI:10.1038/s41586-019-1798-7
摘要

Limiting the increase of CO2 in the atmosphere is one of the largest challenges of our generation1. Because carbon capture and storage is one of the few viable technologies that can mitigate current CO2 emissions2, much effort is focused on developing solid adsorbents that can efficiently capture CO2 from flue gases emitted from anthropogenic sources3. One class of materials that has attracted considerable interest in this context is metal–organic frameworks (MOFs), in which the careful combination of organic ligands with metal-ion nodes can, in principle, give rise to innumerable structurally and chemically distinct nanoporous MOFs. However, many MOFs that are optimized for the separation of CO2 from nitrogen4–7 do not perform well when using realistic flue gas that contains water, because water competes with CO2 for the same adsorption sites and thereby causes the materials to lose their selectivity. Although flue gases can be dried, this renders the capture process prohibitively expensive8,9. Here we show that data mining of a computational screening library of over 300,000 MOFs can identify different classes of strong CO2-binding sites—which we term ‘adsorbaphores’—that endow MOFs with CO2/N2 selectivity that persists in wet flue gases. We subsequently synthesized two water-stable MOFs containing the most hydrophobic adsorbaphore, and found that their carbon-capture performance is not affected by water and outperforms that of some commercial materials. Testing the performance of these MOFs in an industrial setting and consideration of the full capture process—including the targeted CO2 sink, such as geological storage or serving as a carbon source for the chemical industry—will be necessary to identify the optimal separation material. Data mining of a computational library of metal–organic frameworks identifies motifs that bind CO2 sufficiently strongly and whose uptake is not affected by water, with application for the capture of CO2 from flue gases.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
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
zhangxh43发布了新的文献求助10
1秒前
1秒前
阿埃完成签到 ,获得积分10
1秒前
3秒前
4秒前
XZJ完成签到,获得积分10
4秒前
5秒前
6秒前
完美世界应助不倦采纳,获得10
6秒前
zhangxh43完成签到,获得积分20
7秒前
优雅的东完成签到,获得积分10
7秒前
Yukirin完成签到,获得积分10
8秒前
韦韦完成签到 ,获得积分10
8秒前
8秒前
lome发布了新的文献求助10
9秒前
majiayang发布了新的文献求助10
11秒前
hhud完成签到 ,获得积分10
12秒前
隐形曼青应助起名困难户采纳,获得10
12秒前
duxing完成签到,获得积分10
13秒前
14秒前
mojiali完成签到 ,获得积分10
14秒前
打野速度完成签到 ,获得积分10
15秒前
dde应助张sjb采纳,获得20
15秒前
16秒前
傲菡关注了科研通微信公众号
16秒前
贪玩的幻姬完成签到,获得积分10
16秒前
WSY完成签到 ,获得积分10
16秒前
能干的新筠完成签到,获得积分10
16秒前
wofos完成签到,获得积分10
17秒前
芃芃完成签到,获得积分10
17秒前
17秒前
sxw完成签到 ,获得积分10
17秒前
17秒前
隐形曼青应助任性的友桃采纳,获得10
18秒前
Snicolas完成签到,获得积分10
19秒前
jiah应助ljyx采纳,获得30
19秒前
科研通AI6.2应助高高从云采纳,获得10
20秒前
20秒前
20秒前
天天呼的海角完成签到,获得积分10
20秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Principles of town planning: translating concepts to applications 1000
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
核安全综合知识2024版 500
Photothermal Science and Techniques 500
Essentials of Carbohydrate Chemistry and Biochemistry, 4th Edition 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7716462
求助须知:如何正确求助?哪些是违规求助? 9271306
关于积分的说明 20085670
捐赠科研通 7292755
什么是DOI,文献DOI怎么找? 3298806
关于科研通互助平台的介绍 2452950
邀请新用户注册赠送积分活动 2306178