Simulation Studies on Improved Separation of Helium and Helium Isotopes by Strain Modulated r-N-GY Monolayer Nanostructure
Source abstract
Abstract
Acquiring helium gas (He) via membrane separation technology is deemed a prospective and benign approach to mitigate the He shortage crisis. This study demonstrates, through theoretical means, that the recently synthesized r -N-GY nanostructure can serve as a semi-permeable membrane for highly efficient separation of He and its isotopes. Our simulation results clearly reveal that the r -N-GY monolayer exhibits an excellent selectivity in separating He from natural gas molecules, with a selectivity exceeding 10 8 toward He over other impurities. Additionally, the He permeance reaches 1.1 × 10 –5 mol s –1 m –2 Pa –1, surpassing the industrial standard by 4 orders of magnitude. We further demonstrate that the application of tensile strain can effectively regulate He permeance. For instance, the application of 8% strain along the armchair (AC) direction results in the substantial reduction in the energy barrier for gas molecules passing through the r -N-GY monolayer, leading to a two-order-of-magnitude increase in He permeation rate compared to that of the unstrained case, while still maintaining ultra-high He/Ne and He/N 2 selectivity (10 3 and 10 15, respectively). Moreover, there is a marked enhancement for the quantum sieving of 3 He/ 4 He upon application of 8% tensile strain along AC direction, thus offering a promising strategy for both He and 3 He isotope separation. Therefore, this study suggests a high performance and strain-tunable nanostructure candidate with great promise in He and He isotope purification that can constitute the ultimate functions of nanomaterials in semi-permeable membrane technique.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Superconductivity in MgB2 and Alloys · Superconducting Materials and Applications · Quantum, superfluid, helium dynamics
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Physics, Shandong University, Jinan 250100, Shandong, China
Funding
Taishan Scholar Foundation of Shandong Province · National Natural Science Foundation of China · Natural Science Foundation of Shandong Province
References (76)
Show source-provided references
1. 10.1038/485573a10.1038/485573a ↗
2. 10.1109/tasc.2013.224463310.1109/tasc.2013.2244633 ↗
3. 10.1016/j.egyr.2022.01.08710.1016/j.egyr.2022.01.087 ↗
4. 10.1016/j.resourpol.2009.10.00210.1016/j.resourpol.2009.10.002 ↗
5. 10.1016/j.jngse.2016.06.03010.1016/j.jngse.2016.06.030 ↗
6. 10.1260/0263-6174.32.1.4910.1260/0263-6174.32.1.49 ↗
7. 10.1016/j.fuproc.2020.10646410.1016/j.fuproc.2020.106464 ↗
8. 10.1016/j.seppur.2016.12.02010.1016/j.seppur.2016.12.020 ↗
9. 10.1016/j.memsci.2008.04.03010.1016/j.memsci.2008.04.030 ↗
10. 10.1021/jp302498d10.1021/jp302498d ↗
11. 10.1016/j.carbon.2015.08.01310.1016/j.carbon.2015.08.013 ↗
12. 10.1016/j.pmatsci.2011.03.00310.1016/j.pmatsci.2011.03.003 ↗
13. 10.1016/j.pmatsci.2012.03.00210.1016/j.pmatsci.2012.03.002 ↗
14. 10.1038/nnano.2012.16210.1038/nnano.2012.162 ↗
15. 10.1039/c4cs00423j10.1039/c4cs00423j ↗
16. 10.1039/c5ta05700k10.1039/c5ta05700k ↗
17. 10.1038/srep1995210.1038/srep19952 ↗
18. 10.1016/j.commatsci.2018.10.02210.1016/j.commatsci.2018.10.022 ↗
19. 10.1021/acsanm.9b0086210.1021/acsanm.9b00862 ↗
20. 10.1002/adts.20210032710.1002/adts.202100327 ↗
21. 10.1088/1361-6463/ac6e1110.1088/1361-6463/ac6e11 ↗
22. 10.1021/acsami.6b0065710.1021/acsami.6b00657 ↗
23. 10.1016/j.apsusc.2018.02.11110.1016/j.apsusc.2018.02.111 ↗
24. 10.1021/jp310186510.1021/jp3101865 ↗
25. 10.1021/jp510124e10.1021/jp510124e ↗
26. 10.1021/la403969g10.1021/la403969g ↗
27. 10.1016/j.spmi.2020.10647810.1016/j.spmi.2020.106478 ↗
28. 10.1039/d0cp00154f10.1039/d0cp00154f ↗
29. 10.3390/membranes1112092710.3390/membranes11120927 ↗
30. 10.1016/j.memsci.2017.02.01210.1016/j.memsci.2017.02.012 ↗
31. 10.1016/j.seppur.2019.04.03610.1016/j.seppur.2019.04.036 ↗
32. 10.1016/j.seppur.2022.12192710.1016/j.seppur.2022.121927 ↗
33. 10.1016/j.memsci.2022.12061410.1016/j.memsci.2022.120614 ↗
34. 10.1016/j.cjche.2021.09.00410.1016/j.cjche.2021.09.004 ↗
35. 10.1016/j.chemgeo.2017.11.02410.1016/j.chemgeo.2017.11.024 ↗
36. 10.3390/w1412194010.3390/w14121940 ↗
37. 10.1021/jz201504k10.1021/jz201504k ↗
38. 10.1021/acs.jpca.9b0667710.1021/acs.jpca.9b06677 ↗
39. 10.1039/d1cp02121d10.1039/d1cp02121d ↗
40. 10.1088/2043-6262/ac410810.1088/2043-6262/ac4108 ↗
41. 10.1039/d2cp01044e10.1039/d2cp01044e ↗
42. 10.1039/d0dt01855d10.1039/d0dt01855d ↗
43. 10.1016/j.mtphys.2019.10016410.1016/j.mtphys.2019.100164 ↗
44. 10.1016/j.carbon.2019.04.02410.1016/j.carbon.2019.04.024 ↗
45. 10.1039/d2ta04108a10.1039/d2ta04108a ↗
46. 10.1016/0927-0256(96)00008-010.1016/0927-0256(96)00008-0 ↗
47. 10.1103/physrevb.54.1116910.1103/physrevb.54.11169 ↗
48. 10.1103/physrevlett.77.386510.1103/physrevlett.77.3865 ↗
49. 10.1002/jcc.2049510.1002/jcc.20495 ↗
50. 10.1063/1.132967210.1063/1.1329672 ↗
51. 10.1063/1.487866410.1063/1.4878664 ↗
52. 10.1002/smll.20100112610.1002/smll.201001126 ↗
53. 10.1039/c6ta04456e10.1039/c6ta04456e ↗
54. 10.5185/amlett.2022.03170010.5185/amlett.2022.031700 ↗
55. 10.1021/acs.jpcc.7b0429810.1021/acs.jpcc.7b04298 ↗
56. 10.1021/ed077p52810.1021/ed077p528 ↗
57. 10.1038/s41598-017-01488-810.1038/s41598-017-01488-8 ↗
58. Hess B. · J. Chem. Theory Comput. · 2008 · 4 · 43510.1021/ct700301q ↗
59. 10.1093/bioinformatics/btt05510.1093/bioinformatics/btt055 ↗
60. 10.1016/j.softx.2015.06.00110.1016/j.softx.2015.06.001 ↗
61. 10.1021/ja00051a04010.1021/ja00051a040 ↗
62. 10.1002/jcc.2304910.1002/jcc.23049 ↗
63. Frisch, M. J.; Trucks, G.; Schlegel, H. B.; Scuseria, G. E.; Robb; Cheeseman, J. R.; Scalmani, G.; Barone, V.; Mennucci, B.; Petersson, G. A. Gaussian 09W. Revision A. 02, 2009;
64. 10.1063/1.240842010.1063/1.2408420 ↗
65. 10.1002/jcc.54013081210.1002/jcc.540130812 ↗
66. 10.1016/s0010-4655(00)00215-010.1016/s0010-4655(00)00215-0 ↗
67. 10.1007/s10853-017-1246-810.1007/s10853-017-1246-8 ↗
68. 10.1063/1.487343710.1063/1.4873437 ↗
69. 10.1063/1.487866410.1063/1.4878664 ↗
70. 10.1016/j.petrol.2012.06.01610.1016/j.petrol.2012.06.016 ↗
71. 10.1016/j.fuel.2011.12.07410.1016/j.fuel.2011.12.074 ↗
72. 10.1016/j.memsci.2016.07.06410.1016/j.memsci.2016.07.064 ↗
73. 10.1016/j.memsci.2006.04.04010.1016/j.memsci.2006.04.040 ↗
74. 10.1002/anie.20160043810.1002/anie.201600438 ↗
75. 10.1021/jz100748x10.1021/jz100748x ↗
76. 10.1021/acs.jpca.5b0848510.1021/acs.jpca.5b08485 ↗