In Silico Screening of Metal-organic Frameworks for Water Harvesting

被引:11
作者
Wang, Yi-Ming [1 ]
Datar, Archit [2 ,3 ]
Xu, Zhi-Xun [1 ]
Lin, Li-Chiang [1 ,3 ]
机构
[1] Natl Taiwan Univ, Dept Chem Engn, Taipei 10617, Taiwan
[2] Celanese Corp, Technol & Innovat, Wilmington, DE 19803 USA
[3] Ohio State Univ, William G Lowrie Dept Chem & Biomol Engn, Columbus, OH 43210 USA
关键词
FLASH DISTILLATION; METHANE STORAGE; CARBON-CAPTURE; FORCE-FIELD; ADSORPTION; CHEMISTRY; DESALINATION; DISCOVERY; UIO-66; AIR;
D O I
10.1021/acs.jpcc.3c05868
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
The increasingly limited availability of fresh water has become one of the most prominent challenges of our time, and therefore, producing clean water from unconventional sources is of urgent importance. Water harvesting, a process that utilizes changes in the pressure and temperature to capture atmospheric water, has recently drawn considerable attention. In this study, by employing state-of-the-art Monte Carlo simulations, a large-scale study of similar to 12,000 metal-organic frameworks (MOFs) included in the Computational-Ready Experimental (CoRE) MOF database is conducted for their potential in water harvesting. The outcomes herein identify hundreds of promising adsorbents that can deliver a greater amount of fresh water per adsorption-desorption cycle than current state-of-the-art adsorbents. Analyses on such large amounts of computational data have also shed light on the structure-property relationships. Overall, the results obtained herein offer significant insights into the future development of MOFs as water adsorbents to harvest atmospheric water.
引用
收藏
页码:384 / 395
页数:12
相关论文
共 67 条
[1]   Reticular Chemistry in Action: A Hydrolytically Stable MOF Capturing Twice Its Weight in Adsorbed Water [J].
Abtab, Sk Md Towsif ;
Alezi, Dalal ;
Bhatt, Prashant M. ;
Shkurenko, Aleksander ;
Belmabkhout, Youssef ;
Aggarwal, Himanshu ;
Weselinski, Lukasz J. ;
Alsadun, Norah ;
Samin, Umer ;
Hedhili, Mohamed Nejib ;
Eddaoudi, Mohamed .
CHEM, 2018, 4 (01) :94-105
[2]   Computational development of the nanoporous materials genome [J].
Boyd, Peter G. ;
Lee, Yongjin ;
Smit, Berend .
NATURE REVIEWS MATERIALS, 2017, 2 (08)
[3]   Machine Learning-Aided Computational Study of Metal-Organic Frameworks for Sour Gas Sweetening [J].
Cho, Eun Hyun ;
Deng, Xuepeng ;
Zou, Changlong ;
Lin, Li-Chiang .
JOURNAL OF PHYSICAL CHEMISTRY C, 2020, 124 (50) :27580-27591
[4]   Computational discovery of nanoporous materials for energy- and environment-related applications [J].
Cho, Eun Hyun ;
Lyu, Qiang ;
Lin, Li-Chiang .
MOLECULAR SIMULATION, 2019, 45 (14-15) :1122-1147
[5]   Role of Structural Defects in the Water Adsorption Properties of MOF-801 [J].
Choi, Jongwon ;
Lin, Li-Chiang ;
Grossman, Jeffrey C. .
JOURNAL OF PHYSICAL CHEMISTRY C, 2018, 122 (10) :5545-5552
[6]   Advances, Updates, and Analytics for the Computation-Ready, Experimental Metal-Organic Framework Database: CoRE MOF 2019 [J].
Chung, Yongchul G. ;
Haldoupis, Emmanuel ;
Bucior, Benjamin J. ;
Haranczyk, Maciej ;
Lee, Seulchan ;
Zhang, Hongda ;
Vogiatzis, Konstantinos D. ;
Milisavljevic, Marija ;
Ling, Sanliang ;
Camp, Jeffrey S. ;
Slater, Ben ;
Siepmann, J. Ilja ;
Sholl, David S. ;
Snurr, Randall Q. .
JOURNAL OF CHEMICAL AND ENGINEERING DATA, 2019, 64 (12) :5985-5998
[7]   Computation-Ready, Experimental Metal-Organic Frameworks: A Tool To Enable High-Throughput Screening of Nanoporous Crystals [J].
Chung, Yongchul G. ;
Camp, Jeffrey ;
Haranczyk, Maciej ;
Sikora, Benjamin J. ;
Bury, Wojciech ;
Krungleviciute, Vaiva ;
Yildirim, Taner ;
Farha, Omar K. ;
Sholl, David S. ;
Snurr, Randall Q. .
CHEMISTRY OF MATERIALS, 2014, 26 (21) :6185-6192
[8]   Industrial applications of metal-organic frameworks [J].
Czaja, Alexander U. ;
Trukhan, Natalia ;
Mueller, Ulrich .
CHEMICAL SOCIETY REVIEWS, 2009, 38 (05) :1284-1293
[9]   Responses to the comments on "Monte Carlo simulations for water adsorption in porous materials: Best practices and new insights" [J].
Datar, Archit ;
Witman, Matthew ;
Lin, Li-Chiang .
AICHE JOURNAL, 2022, 68 (08)
[10]   Monte Carlo simulations for water adsorption in porous materials: Best practices and new insights [J].
Datar, Archit ;
Witman, Matthew ;
Lin, Li-Chiang .
AICHE JOURNAL, 2021, 67 (12)