journal article·2024-10Open access

Multiscale Scrutinizing Ion Storage Kinetics in Hollow Ni‐Mn Prussian Blue Analogues for Enhanced Capacitive Deionization

Adekunle Adedapo Obisanya, Liang Ma, Jinkang Liu, Tianshuo Yang, Zhibin Ren, Xinyi Tan, Faming Gao, Jianren Wang

Advanced Functional Materials· Volume 34· Issue 44

Abstract

Abstract Prussian blue analogues (PBAs) are a class of promising materials for capacitive deionization. However, the kinetic mismatch between their slow ion storage rate and the demand from short‐time desalination severely limits their desalination performance. Here, a group of structure‐tuneable Ni‐Mn PBAs have been developed by a combination strategy of surface‐protected chemical etching and Ostwald ripening to study their ion storage kinetics. Treating them as demos, the characterizations and investigations, e.g., in situ XRD in a three‐electrode system, dynamic impedance, finite element simulation, and DFT calculations etc., reveal that the slow ion diffusion caused by the severe agglomeration of the nanoparticles and the unsuitable lattice parameter controls the final desalination behavior. Therefore, the correspondingly optimized sample (HC‐t) possessing a microscale hollow structure, nanoscale shell thickness, and expanded lattice, displays a fast ion storage kinetics with the ratio of surface‐controlled current as high as 82% at a scan rate of 20 mV s−1. Consequently, it delivers an impressive desalination capacity of 120.8 mg g−1 (2.06 mmol g−1 Na+) with a fast average desalination rate of 0.25 mg g−1 s−1 (0.004 mmol g−1 s−1) at 1.2 V, competitive with those reported in the literature. Moreover, the elucidation of the structure‐performance correlation provides valuable insights for the development and design of next‐generation PBAs for capacitive deionization (CDI).
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Research context

OpenAlex topics: Membrane-based Ion Separation Techniques · Advancements in Battery Materials · Advanced Battery Materials and Technologies

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Hebei Key Laboratory of Applied Chemistry School of Environmental and Chemical Engineering Yanshan University No. 438 Hebei Street Qinhuangdao 066004 China

State Key Laboratory of Metastable Materials Science & Technology and Key Laboratory for Microstructural Material Physics of Hebei Province School of Science Yanshan University Qinhuangdao 066004 China

Funding

National Natural Science Foundation of China · Hebei Province Science and Technology Support Program · China Sponsorship Council · Natural Science Foundation of Hebei Province

References (60)

Show source-provided references
1. 10.1039/D2EE03530H10.1039/D2EE03530H ↗
2. 10.1016/j.cej.2023.14542110.1016/j.cej.2023.145421 ↗
3. 10.1016/j.watres.2018.11.06410.1016/j.watres.2018.11.064 ↗
4. Wang H. · Coord. Chem. Rev. · 2024 · 510
5. 10.1021/jacs.3c0175510.1021/jacs.3c01755 ↗
6. 10.1039/C7NR03579A10.1039/C7NR03579A ↗
7. 10.1021/acsami.0c2006710.1021/acsami.0c20067 ↗
8. 10.1021/acs.est.2c0158610.1021/acs.est.2c01586 ↗
9. 10.1007/s40820-021-00700-910.1007/s40820-021-00700-9 ↗
10. 10.1103/PhysRevLett.91.10610210.1103/PhysRevLett.91.106102 ↗
11. 10.1021/acsami.6b1088410.1021/acsami.6b10884 ↗
12. 10.1002/adma.20170682510.1002/adma.201706825 ↗
13. 10.1039/D2QI01068B10.1039/D2QI01068B ↗
14. 10.1002/adfm.20200697010.1002/adfm.202006970 ↗
15. 10.1016/j.nanoen.2022.10742410.1016/j.nanoen.2022.107424 ↗
16. 10.1016/j.joule.2018.07.01710.1016/j.joule.2018.07.017 ↗
17. 10.1038/ncomms628010.1038/ncomms6280 ↗
18. 10.1016/j.jcis.2022.10.14010.1016/j.jcis.2022.10.140 ↗
19. 10.1002/adfm.20220412610.1002/adfm.202204126 ↗
20. 10.1002/cssc.20200156210.1002/cssc.202001562 ↗
21. Liu T. · Sci. Adv. · 2020 · 6
22. 10.1039/D2CC06460J10.1039/D2CC06460J ↗
23. 10.1039/C8TA12433G10.1039/C8TA12433G ↗
24. 10.1016/j.pmatsci.2021.10091110.1016/j.pmatsci.2021.100911 ↗
25. Yu S. · Nano · 2018 · 13 · 11
26. 10.1002/jrs.536610.1002/jrs.5366 ↗
27. 10.1143/APEX.2.08500110.1143/APEX.2.085001 ↗
28. 10.1002/adma.20190740410.1002/adma.201907404 ↗
29. 10.1002/smll.20180124610.1002/smll.201801246 ↗
30. 10.1002/adfm.20190875410.1002/adfm.201908754 ↗
31. 10.1002/aenm.20190300610.1002/aenm.201903006 ↗
32. Wang S. · Small · 2022 · 18
33. 10.1002/anie.20120685410.1002/anie.201206854 ↗
34. 10.1002/adfm.20160430710.1002/adfm.201604307 ↗
35. 10.1002/smll.20230038410.1002/smll.202300384 ↗
36. 10.1002/adfm.20211172710.1002/adfm.202111727 ↗
37. 10.1016/j.desal.2022.11562210.1016/j.desal.2022.115622 ↗
38. 10.1039/D0SE00610F10.1039/D0SE00610F ↗
39. 10.1021/jp074464w10.1021/jp074464w ↗
40. 10.1016/j.electacta.2023.14218310.1016/j.electacta.2023.142183 ↗
41. 10.1016/j.cej.2023.14321610.1016/j.cej.2023.143216 ↗
42. 10.1016/j.desal.2022.11630510.1016/j.desal.2022.116305 ↗
43. 10.1016/j.seppur.2022.12048310.1016/j.seppur.2022.120483 ↗
44. 10.1016/j.apsusc.2023.15692610.1016/j.apsusc.2023.156926 ↗
45. 10.1016/j.seppur.2023.12515510.1016/j.seppur.2023.125155 ↗
46. 10.1016/j.seppur.2023.12389910.1016/j.seppur.2023.123899 ↗
47. 10.1016/j.jcis.2023.04.00710.1016/j.jcis.2023.04.007 ↗
48. 10.1016/j.desal.2019.11407810.1016/j.desal.2019.114078 ↗
49. 10.1021/acs.est.8b0485810.1021/acs.est.8b04858 ↗
50. 2022
51. 10.1039/D1RA03785D10.1039/D1RA03785D ↗
52. 10.1016/j.est.2021.10365410.1016/j.est.2021.103654 ↗
53. 10.1016/j.electacta.2018.05.13610.1016/j.electacta.2018.05.136 ↗
54. 10.1021/acsmeasuresciau.2c0007010.1021/acsmeasuresciau.2c00070 ↗
55. 10.1016/j.electacta.2018.04.14910.1016/j.electacta.2018.04.149 ↗
56. 10.1149/1.356142710.1149/1.3561427 ↗
57. 10.1002/adfm.20180640510.1002/adfm.201806405 ↗
58. 10.1021/cm504091z10.1021/cm504091z ↗
59. 10.1103/PhysRevB.54.1116910.1103/PhysRevB.54.11169 ↗
60. 10.1016/0039-6028(94)00731-410.1016/0039-6028(94)00731-4 ↗