Vascular System Inspired 3D Electrolyte Network for High Rate and High Mass Loading Graphene Supercapacitor
Source abstract
Abstract
Abstract High charge rate and high mass loading ability are of practical importance for high power and high volumetric performance supercapacitors but are always challenged by tortuous and sluggish ion diffusion in thick electrodes. Here, inspired by the hepatic vascular system, hierarchical 3D electrolyte networks are proposed to facilitate ion diffusion across laminar graphene films, resulting in a 14‐fold improved ion diffusion coefficient, better rate ability, and high mass loading ability for graphene supercapacitors. Such design enables graphene electrodes with high capacitance up to 236 F g−1, packing densities of 0.67–0.78 g cm−3 depending on structures; and core stack with 10 mg cm−2 mass loading exhibits a high energy density of 45.4 Wh L−1, which is among the state‐of‐the‐art graphene supercapacitors. This study provides a comprehensive investigation of structure‐related capacitive properties, guiding electrode design for high‐rate and high‐mass‐loading graphene supercapacitors. Moreover, such design also benefits solid‐state graphene supercapacitors by forming 3D gel electrolyte structures, which enable higher capacitance and better mechanical robustness, showing potential for flexible energy storage.
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Research context
OpenAlex topics: Supercapacitor Materials and Fabrication · Advanced battery technologies research · Advancements in Battery Materials
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Micro‐/Nano‐Technology Research Center State Key Laboratory for Manufacturing Systems Engineering Xi'an Jiaotong University Xi'an Shaanxi 710049 China
Frontier Institute of Science and Technology Xi'an Jiaotong University Xi'an Shaanxi 710049 China
The Key Laboratory of Biomedical Information Engineering of Ministry of Education School of Life Science and Technology Xi'an Jiaotong University Xi'an Shaanxi 710049 China
Funding
National Natural Science Foundation of China
References (57)
Show source-provided references
1. 10.1126/science.123908910.1126/science.1239089 ↗
2. 10.1038/s41560-020-0560-610.1038/s41560-020-0560-6 ↗
3. Zhang C. · Environ Sci · 2015 · 8 · 1390
4. 10.1126/science.121300310.1126/science.1213003 ↗
5. Li H. · Environ. Sci. · 2016 · 9 · 3135
6. 10.1002/aenm.20190145710.1002/aenm.201901457 ↗
7. Guo W. · Environ. Sci. · 2021 · 14 · 576
8. 10.1021/nl200225j10.1021/nl200225j ↗
9. 10.1038/s41586-018-0109-z10.1038/s41586-018-0109-z ↗
10. 10.1002/aenm.20130127810.1002/aenm.201301278 ↗
11. 10.1038/nenergy.2017.10510.1038/nenergy.2017.105 ↗
12. 10.1038/nnano.2014.23310.1038/nnano.2014.233 ↗
13. 10.1016/j.xcrp.2020.10021510.1016/j.xcrp.2020.100215 ↗
14. 10.1016/j.carbon.2022.01.04210.1016/j.carbon.2022.01.042 ↗
15. 10.1126/science.120077010.1126/science.1200770 ↗
16. 10.1038/ncomms555410.1038/ncomms5554 ↗
17. 10.1038/ncomms441010.1038/ncomms4410 ↗
18. 10.1002/adma.20120457610.1002/adma.201204576 ↗
19. 10.1038/ncomms223410.1038/ncomms2234 ↗
20. 10.1021/acsnano.6b0241510.1021/acsnano.6b02415 ↗
21. 10.1126/science.119437210.1126/science.1194372 ↗
22. 10.1038/nenergy.2016.9710.1038/nenergy.2016.97 ↗
23. 10.1002/advs.20210166410.1002/advs.202101664 ↗
24. 10.1126/sciadv.150084910.1126/sciadv.1500849 ↗
25. 10.1021/nn500150j10.1021/nn500150j ↗
26. 10.1002/adma.20130133210.1002/adma.201301332 ↗
27. 10.1038/ncomms244610.1038/ncomms2446 ↗
28. 10.1038/ncomms348710.1038/ncomms3487 ↗
29. 10.1039/C7TA02041D10.1039/C7TA02041D ↗
30. 10.1016/j.joule.2018.04.00210.1016/j.joule.2018.04.002 ↗
31. 10.1021/acsami.5b1265210.1021/acsami.5b12652 ↗
32. 10.1038/s41467-018-04937-810.1038/s41467-018-04937-8 ↗
33. Augustyn V. · Environ. Sci. · 2014 · 7 · 1597
34. 10.1021/jp074464w10.1021/jp074464w ↗
35. 10.1038/srep0140810.1038/srep01408 ↗
36. 10.1021/nl102661q10.1021/nl102661q ↗
37. 10.1126/science.121674410.1126/science.1216744 ↗
38. 10.1021/nn402077v10.1021/nn402077v ↗
39. 10.1016/j.nanoen.2013.01.00710.1016/j.nanoen.2013.01.007 ↗
40. 10.1021/nl802558y10.1021/nl802558y ↗
41. 10.1021/ja710617810.1021/ja7106178 ↗
42. 10.1016/j.ensm.2018.12.00610.1016/j.ensm.2018.12.006 ↗
43. 10.1002/adma.20170047010.1002/adma.201700470 ↗
44. 10.1021/acsnano.7b0446710.1021/acsnano.7b04467 ↗
45. 10.1016/j.jpowsour.2016.05.08510.1016/j.jpowsour.2016.05.085 ↗
46. 10.1039/C5NR06113J10.1039/C5NR06113J ↗
47. 10.1038/nnano.2014.9310.1038/nnano.2014.93 ↗
48. 10.1038/srep0297510.1038/srep02975 ↗
49. 10.1002/aenm.20110011410.1002/aenm.201100114 ↗
50. 10.1038/s41467-018-05723-210.1038/s41467-018-05723-2 ↗
51. 10.1039/C4TA01468E10.1039/C4TA01468E ↗
52. 10.1126/science.124650110.1126/science.1246501 ↗
53. 10.1038/nnano.2010.16210.1038/nnano.2010.162 ↗
54. 10.1002/advs.20200495710.1002/advs.202004957 ↗
55. 10.1021/nl803857910.1021/nl8038579 ↗
56. 10.1038/natrevmats.2016.9810.1038/natrevmats.2016.98 ↗
57. 10.1038/s41565-021-01020-010.1038/s41565-021-01020-0 ↗