Abstract
In this work, we proposed multi-scale screening, which employs both molecular and process-level methods, to identify high-performing MOFs for energy-efficient separation of SF6 and N2 mixture. Grand canonical Monte Carlo (GCMC) simulations were combined with ideal adsorption process simulation to computationally screen 2890 metal–organic frameworks (MOFs) for adsorptive separation of SF6/N2. More than 150 high-performing MOFs were identified based on the GCMC simulations at the pressure and vacuum swing conditions, and subsequently evaluated using the ideal adsorption process simulation. 78 out of 86 MOFs selected for the VSA conditions were able to achieve the 90% target purity level of SF6, but 62 top-performing MOFs selected for the PSA condition could not reach the purity level with a single train PSA configuration. Cascade PSA configuration was proposed and adopted to improve the purity level. We also investigated the effect of vacuum pump and compressor efficiency on the energy consumption of the process. We found that the top-performing MOFs were able to achieve the 90% purity-level of SF6 with 0.10–0.4 and 0.5–1.4 MJ per kg of SF6 for VSA and PSA processes, respectively. Finally, the process-level performance of top-performing MFOs (HKST-1, UiO-67) was evaluated on the basis of the experimental isotherms obtained from the literature, and compared with the other materials reported in the literature (MIL-100(Fe), UiO-66, and zeolite-13X). We found that the results based on the experimental isotherms are in qualitative agreement with the results based on the simulated isotherms.
Original language | English |
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Article number | 131787 |
Journal | Chemical Engineering Journal |
Volume | 426 |
DOIs | |
Publication status | Published - 2021 Dec 15 |
Bibliographical note
Funding Information:Jaehoon Cha and Seongbin Ga contributed equally. This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSTI) (No. 2020R1C1C1010373). This research was also supported by Korea Electric Power Corporation (Grant number: R21X001-4). Authors thank the computational time provided by KISTI (KSC-2021-CRE-0066). Authors also thank Prof. Tae-Hyun Bae (KAIST) and Chong Yang for kindly providing the isotherm data for HKUST-1.
Funding Information:
Jaehoon Cha and Seongbin Ga contributed equally. This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSTI) (No. 2020R1C1C1010373 ). This research was also supported by Korea Electric Power Corporation (Grant number: R21X001-4 ). Authors thank the computational time provided by KISTI (KSC-2021-CRE-0066). Authors also thank Prof. Tae-Hyun Bae (KAIST) and Chong Yang for kindly providing the isotherm data for HKUST-1.
Publisher Copyright:
© 2021 Elsevier B.V.
All Science Journal Classification (ASJC) codes
- Chemistry(all)
- Environmental Chemistry
- Chemical Engineering(all)
- Industrial and Manufacturing Engineering