Diffusion coefficient of ions through graphene nanopores
Source abstract
Abstract
In this work, we investigate the transport of ions through graphene nanopores driven by concentration gradients through molecular dynamics simulations. The diffusion coefficients, D, of K+ and Cl− are computed for various pore sizes and porosities. It is found that D is sensitive to the pore size when the pore diameter is smaller than 3 nm. For relatively large pores, D remains largely independent of the pore size. The dependence of D on the porosity shows a near-linear relationship. The effects of pore size and porosity on the diffusion coefficient are caused by the free energy barrier at the pore due to the ion–pore molecular interactions and the dehydration of ions. A general scaling law for the diffusion coefficient is also proposed. The results in this work provide useful information for the design and fabrication of nanoporous structures for ion transport.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Nanopore and Nanochannel Transport Studies · Graphene research and applications · Fuel Cells and Related Materials
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Mechanical and Aerospace Engineering, The Hong Kong University of Science and Technology 1 , Clear Water Bay, Kowloon, Hong Kong
Sustainable Energy and Environment Thrust, The Hong Kong University of Science and Technology (Guangzhou) 2 , Guangzhou 511400, Guangdong, China
Department of Chemical Engineering, Massachusetts Institute of Technology 3 , Cambridge, Massachusetts 02139, USA
HKUST Shenzhen-Hong Kong Collaborative Innovation Research Institute 4 , Futian, Shenzhen, China
Funding
Research Grants Council, University Grants Committee · Hetao Shenzhen-Hong Kong Sci. Tech. Innovation Cooperation Zone
References (49)
Show source-provided references
1. J. Chromatogr. A · 2006 · 1137 · 25610.1016/j.chroma.2006.10.097 ↗
2. Joule · 2019 · 3 · 236410.1016/j.joule.2019.09.005 ↗
3. Chem. Soc. Rev. · 2010 · 39 · 90110.1039/b820556f ↗
4. Nanoscale · 2016 · 8 · 1952710.1039/c6nr06977k ↗
5. Anal. Chem. · 2002 · 74 · 141510.1021/ac011076w ↗
6. Nano Today · 2013 · 8 · 5610.1016/j.nantod.2012.12.008 ↗
7. Nano Lett. · 2010 · 10 · 316310.1021/nl102069z ↗
8. Phys. Chem. Chem. Phys. · 2021 · 23 · 1329210.1039/d1cp01733k ↗
9. 2011
10. Chem. Soc. Rev. · 2010 · 39 · 107310.1039/b909366b ↗
11. Electrophoresis · 2019 · 40 · 85910.1002/elps.201800465 ↗
12. Carbon · 2013 · 62 · 110.1016/j.carbon.2013.05.052 ↗
13. Nature · 2010 · 467 · 19010.1038/nature09379 ↗
14. Carbon · 2020 · 161 · 55010.1016/j.carbon.2020.01.100 ↗
15. Small · 2014 · 10 · 348010.1002/smll.201303202 ↗
16. Mater. Today · 2014 · 17 · 7710.1016/j.mattod.2014.01.021 ↗
17. Biosens. Bioelectron. · 2018 · 119 · 19110.1016/j.bios.2018.07.072 ↗
18. Annu. Rev. Fluid Mech. · 2021 · 53 · 37710.1146/annurev-fluid-071320-095958 ↗
19. Nat. Nanotechnol. · 2021 · 16 · 98910.1038/s41565-021-00933-0 ↗
20. J. Appl. Phys. · 2019 · 126 · 02490110.1063/1.5104309 ↗
21. Nat. Nanotechnol. · 2010 · 5 · 69710.1038/nnano.2010.198 ↗
22. Phys. Rev. Appl. · 2015 · 3 · 03400310.1103/physrevapplied.3.034003 ↗
23. Nano Lett. · 2012 · 12 · 411710.1021/nl301655d ↗
24. Nat. Biotechnol. · 2008 · 26 · 114610.1038/nbt.1495 ↗
25. Small · 2012 · 8 · 170110.1002/smll.201102056 ↗
26. J. Chem. Phys. · 2014 · 140 · 08470710.1063/1.4866643 ↗
27. RSC Adv. · 2019 · 9 · 2040210.1039/c9ra03025e ↗
28. Nanoscale · 2014 · 6 · 1066610.1039/c4nr01383b ↗
29. J. Phys. Chem. B · 2021 · 125 · 1125610.1021/acs.jpcb.1c06327 ↗
30. J. Membr. Sci. · 2021 · 620 · 11889210.1016/j.memsci.2020.118892 ↗
31. Langmuir · 2016 · 32 · 1377810.1021/acs.langmuir.6b03001 ↗
32. Fluid Phase Equilib. · 2019 · 489 · 2310.1016/j.fluid.2019.02.012 ↗
33. Matter · 2020 · 2 · 73510.1016/j.matt.2019.12.022 ↗
34. Comput. Phys. Commun. · 2022 · 271 · 10817110.1016/j.cpc.2021.108171 ↗
35. Phys. Rev. E · 2015 · 92 · 02301710.1103/physreve.92.023017 ↗
36. J. Phys. Chem. · 1987 · 91 · 626910.1021/j100308a038 ↗
37. Phys. Fluids · 2017 · 29 · 09200310.1063/1.4990093 ↗
38. J. Comput. Chem. · 1992 · 13 · 95210.1002/jcc.540130805 ↗
39. 2018
40. Phys. Rev. E · 2009 · 79 · 02631210.1103/PhysRevE.79.026312 ↗
41. J. Comput. Phys. · 1977 · 23 · 18710.1016/0021-9991(77)90121-8 ↗
42. J. Comput. Chem. · 1992 · 13 · 101110.1002/jcc.540130812 ↗
43. Struct. Chem. · 2020 · 31 · 29310.1007/s11224-019-01405-x ↗
44. Biophys. Chem. · 2006 · 124 · 25110.1016/j.bpc.2006.04.015 ↗
45. J. Chem. Educ. · 1984 · 61 · 49410.1021/ed061p494 ↗
46. Phys. Chem. Chem. Phys. · 2012 · 14 · 1163310.1039/c2cp41641g ↗
47. Sci. Adv. · 2020 · 6 · 4810.1126/sciadv.abd9045 ↗
48. J. Phys. Chem. B · 2008 · 112 · 902010.1021/jp8001614 ↗
49. Phys. Rev. B · 1993 · 48 · 1395910.1103/physrevb.48.13959 ↗