Amino-Functionalized Microporous MOFs for Capturing Greenhouse Gases CF4 and NF3 with Record Selectivity
Source abstract
Abstract
The capture and separation of fluorinated gases (F-gases) from N2 has the potential to not only reduce greenhouse gas emissions but also provide economic benefits for the semiconductor industry. In this work, two Ni-based metal–organic frameworks (MOFs), Ni-MOF (Ni(ina)2, ina = isonicotinic acid) and amine-functionalized NH2–Ni-MOF (Ni(3-ain)2, 3-ain = 3-aminoisonicotinic acid), were constructed for capturing F-gases (CF4 and NF3). At ambient conditions, both materials exhibit very high CF4 sorption capacities (2.92 mmol g–1 for Ni-MOF and 2.69 mmol g–1 for NH2–Ni-MOF). In addition, NH2–Ni-MOF exhibited a record selectivity of 46.3 for the CF4/N2 mixture at 298 K and 100 kPa, surpassing all benchmark adsorbents, including Ni-MOF (34.7). The kinetic adsorption tests demonstrated that Ni-MOF and NH2–Ni-MOF performed well for CF4/N2 and NF3/N2 mixtures. According to grand canonical Monte Carlo (GCMC) simulations, CF4 or NF3 interacts with NH2–Ni-MOF by multiple van der Waals interactions, resulting in stronger interaction than N2. More importantly, dynamic breakthrough experiments verified the practical separation potential of the two materials for CF4/N2 and NF3/N2 mixtures.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Metal-Organic Frameworks: Synthesis and Applications · Inorganic Fluorides and Related Compounds · Carbon Dioxide Capture Technologies
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Chemical Engineering and Technology, Xi’an Jiaotong University, Xi’an 710049, China
Funding
National Natural Science Foundation of China · Shanxi Province
References (40)
Show source-provided references
1. 10.1162/daed_a_0191610.1162/daed_a_01916 ↗
2. 10.1021/ie051227b10.1021/ie051227b ↗
3. 10.1116/1.498392210.1116/1.4983922 ↗
4. 10.1021/es980547210.1021/es9805472 ↗
5. 10.1080/1943815100362141710.1080/19438151003621417 ↗
6. 10.1038/nclimate175810.1038/nclimate1758 ↗
7. 10.1016/j.rser.2021.11075910.1016/j.rser.2021.110759 ↗
8. 10.1016/j.cej.2020.12657710.1016/j.cej.2020.126577 ↗
9. 10.1002/aic.1231210.1002/aic.12312 ↗
10. 10.1627/jpi.62.21110.1627/jpi.62.211 ↗
11. 10.1016/0376-7388(93)E0128-710.1016/0376-7388(93)E0128-7 ↗
12. Kim H. · Membr.J. · 2012 · 22 · 201
13. 10.1126/science.abi728110.1126/science.abi7281 ↗
14. 10.1038/s41586-021-03627-810.1038/s41586-021-03627-8 ↗
15. 10.1039/b802426j10.1039/b802426j ↗
16. Yang R. T. · 200310.1002/047144409X ↗
17. 10.1023/A:101127701816210.1023/A:1011277018162 ↗
18. 10.1016/j.jhazmat.2010.02.00310.1016/j.jhazmat.2010.02.003 ↗
19. 10.1021/acs.iecr.1c0066210.1021/acs.iecr.1c00662 ↗
20. 10.1021/acs.chemmater.1c0113910.1021/acs.chemmater.1c01139 ↗
21. 10.1016/j.micromeso.2021.11154810.1016/j.micromeso.2021.111548 ↗
22. 10.1016/j.cej.2022.13536410.1016/j.cej.2022.135364 ↗
23. 10.1002/ange.20220101710.1002/ange.202201017 ↗
24. 10.1016/j.cej.2018.01.12910.1016/j.cej.2018.01.129 ↗
25. 10.1016/j.seppur.2022.12105910.1016/j.seppur.2022.121059 ↗
26. 10.1021/acs.macromol.1c0241310.1021/acs.macromol.1c02413 ↗
27. 10.1016/j.chempr.2019.10.01210.1016/j.chempr.2019.10.012 ↗
28. 10.1126/science.aat058610.1126/science.aat0586 ↗
29. 10.1002/adma.20200260310.1002/adma.202002603 ↗
30. 10.1016/j.micromeso.2012.02.02110.1016/j.micromeso.2012.02.021 ↗
31. 10.1021/jacs.1c1097310.1021/jacs.1c10973 ↗
32. 10.1039/C8QI01404C10.1039/C8QI01404C ↗
33. 10.1007/s40843-019-9427-510.1007/s40843-019-9427-5 ↗
34. 10.1021/jacs.6b1045510.1021/jacs.6b10455 ↗
35. 10.1021/acs.chemmater.1c0189210.1021/acs.chemmater.1c01892 ↗
36. 10.1016/j.cej.2016.11.10210.1016/j.cej.2016.11.102 ↗
37. 10.1021/acsami.2c1005010.1021/acsami.2c10050 ↗
38. 10.1002/adma.20220229010.1002/adma.202202290 ↗
39. 10.1021/acs.langmuir.2c0109810.1021/acs.langmuir.2c01098 ↗
40. 10.1016/j.gce.2022.04.00610.1016/j.gce.2022.04.006 ↗