Discovery of highly radon-selective metal-organic frameworks through high-throughput computational screening and experimental validation

被引:0
|
作者
Park, Wanje [1 ]
Oh, Kwang Hyun [1 ]
Lee, Dongil [3 ]
Kim, Seo-Yul [1 ,2 ]
Bae, Youn-Sang [1 ]
机构
[1] Department of Chemical and Biomolecular Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul,03722, Korea, Republic of
[2] School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta,GA,30332, United States
[3] R&D Center, LX Hausys, 30, Magokjungang 10-ro, Gangseo-gu, Seoul,07796, Korea, Republic of
来源
关键词
This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIT). (No. 2022R1A2B5B02002577; No; 2020R1A5A1019131);
D O I
暂无
中图分类号
学科分类号
摘要
A highly radon (Rn)-selective adsorbent is essential for the capture of radon from indoor air. Here, an aluminum-based metal–organic framework (MOF), Al-NDC, was identified as a highly Rn-selective adsorbent via high-throughput screening of 4,951 MOFs in the Computation-Ready, Experimental (CoRE) MOF database. Notably, Al-NDC experimentally demonstrated an excellent Rn removal rate (52 %) – more than twice that of the activated carbon benchmarks (25 %) – while also exhibiting excellent hydrothermal, chemical, and radioactive stabilities. Moreover, useful structure–property relationships were obtained from large-scale simulations. High crystal densities, low surface areas, small pore volumes, and small diameters of the largest cavity were found to favor the selective capture of radon. Interestingly, channel-like pores of a size appropriate to fit one to two radon molecules (4.9–9.8 Å) were found to be most effective for selective radon capture. These findings provide key insights for the future development of Rn adsorbents. © 2022 Elsevier B.V.
引用
收藏
相关论文
共 50 条
  • [31] High-throughput screening of Metal-Organic frameworks for helium recovery from natural gas
    V. Grenev, Ivan
    Gavrilov, Vladimir Yu
    MICROPOROUS AND MESOPOROUS MATERIALS, 2024, 368
  • [32] Computation-Ready, Experimental Metal-Organic Frameworks: A Tool To Enable High-Throughput Screening of Nanoporous Crystals
    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
  • [33] Understanding the influence of secondary building units on the thermal conductivity of metal-organic frameworks via high-throughput computational screening
    Lin, Yuanchuang
    Cheng, Ruihuan
    Liang, Tiangui
    Wu, Weixiong
    Li, Song
    Li, Wei
    PHYSICAL CHEMISTRY CHEMICAL PHYSICS, 2023, 25 (47) : 32407 - 32415
  • [34] High-Throughput Computational Screening of Multivariate Metal-Organic Frameworks (MTV-MOFs) for CO2 Capture
    Li, Song
    Chung, Yongchul G.
    Simon, Cory M.
    Snurr, Randall Q.
    JOURNAL OF PHYSICAL CHEMISTRY LETTERS, 2017, 8 (24): : 6135 - 6141
  • [35] High-Throughput, Multiscale Computational Screening of Metal-Organic Frameworks for Xe/Kr Separation with Machine-Learned Parameters
    Zhao, Guobin
    Chen, Yu
    Chung, Yongchul G.
    INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, 2023, 62 (37) : 15176 - 15189
  • [36] Computational screening of hydrogen storage in experimental metal-organic frameworks
    Chung, Yongchul
    ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, 2017, 253
  • [37] From computational high-throughput screenings to the lab: taking metal-organic frameworks out of the computer
    Li, Aurelia
    Bueno-Perez, Rocio
    Madden, David
    Fairen-Jimenez, David
    CHEMICAL SCIENCE, 2022, 13 (27) : 7990 - 8002
  • [38] High-throughput computational screening of metal-organic framework membranes for upgrading of natural gas
    Qiao, Zhiwei
    Xu, Qisong
    Jiang, Jianwen
    JOURNAL OF MEMBRANE SCIENCE, 2018, 551 : 47 - 54
  • [39] Design of Metal-Organic Framework Templated Materials Using High-Throughput Computational Screening
    Ahmad, Momin
    Luo, Yi
    Woell, Christof
    Tsotsalas, Manuel
    Schug, Alexander
    MOLECULES, 2020, 25 (21):
  • [40] High-Throughput Computational Screening of Metal−Organic Frameworks for the Separation of Methane from Ethane and Propane
    Ponraj, Yadava Krishnan
    Borah, Bhaskarjyoti
    Journal of Physical Chemistry C, 2021, 125 (03): : 1839 - 1854