Identifying the Critical Oxygenated Functional Groups on Graphene Oxide for Efficient Water Dissociation in Bipolar Membranes
Source abstract
Abstract
Bipolar membranes (BPMs) are emerging options for kinetically accelerating water dissociation (WD) in electrochemical applications. Graphene oxide (GO) with abundant oxygenated functional groups is an efficient catalyst within BPMs to decrease the transmembrane potential. However, the dominant catalytic sites on GO for WD in BPMs have not been experimentally identified, and the reported simulative calculation results are controversial. Herein, we prepared carboxylated and partially hydroxylated GO-based BPMs, and for the first time quantitatively unraveled the correlativity between WD performance and carboxyl group content with tailor-designed experiments. By using a simple mechanical ball milling method, we further improved the bulk density of carboxyl on the GO catalyst, which achieved excellent WD performance during an operation of over 130 h operation. This study provides a subtle and facile strategy for catalyst design to advance BPM technologies.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Membrane-based Ion Separation Techniques · Fuel Cells and Related Materials · Advanced battery technologies research
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
The Key Laboratory of Water and Sediment Sciences, Ministry of Education, College of Environmental Science and Engineering
Peking University
Zhejiang Ecological Civilization Academy
Institute of Carbon Neutrality
Funding
National Key Research and Development Program of China · National Natural Science Foundation of China
References (58)
Show source-provided references
1. 10.1126/science.121193410.1126/science.1211934 ↗
2. 10.1002/ange.20240207010.1002/ange.202402070 ↗
3. 10.1038/s44160-024-00568-810.1038/s44160-024-00568-8 ↗
4. 10.1039/D1EE00271F10.1039/D1EE00271F ↗
5. 10.1021/acs.est.9b0502410.1021/acs.est.9b05024 ↗
6. 10.1021/acsenergylett.7b0076410.1021/acsenergylett.7b00764 ↗
7. 10.1021/acsenergylett.1c0061810.1021/acsenergylett.1c00618 ↗
8. 10.1016/j.memsci.2018.03.05110.1016/j.memsci.2018.03.051 ↗
9. 10.1021/accountsmr.1c0011310.1021/accountsmr.1c00113 ↗
10. 10.1021/acsami.2c1868510.1021/acsami.2c18685 ↗
11. 10.1021/acsenergylett.6b0055710.1021/acsenergylett.6b00557 ↗
12. 10.1038/s41563-024-01943-810.1038/s41563-024-01943-8 ↗
13. 10.1016/S1383-5866(98)00058-610.1016/S1383-5866(98)00058-6 ↗
14. 10.1021/acs.chemmater.0c0282910.1021/acs.chemmater.0c02829 ↗
15. 10.1016/0011-9164(96)00021-510.1016/0011-9164(96)00021-5 ↗
16. 10.1038/s41467-020-19135-810.1038/s41467-020-19135-8 ↗
17. 10.1126/science.aaz148710.1126/science.aaz1487 ↗
18. 10.1021/acscatal.3c0089110.1021/acscatal.3c00891 ↗
19. 10.1016/j.jechem.2022.04.04610.1016/j.jechem.2022.04.046 ↗
20. 10.1021/acsenergylett.4c0046010.1021/acsenergylett.4c00460 ↗
21. 10.1021/cr300115g10.1021/cr300115g ↗
22. Lucas, É.; Bui, J. C.; Hwang, M.; Asymmetric bipolar membrane for high current density electrodialysis operation with exceptional stability. ChemRxiv, Apr. 6, 2023, ver. 1.10.26434/chemrxiv-2023-n4c6x.10.26434/chemrxiv-2023-n4c6x ↗
23. 10.1002/cssc.20150053810.1002/cssc.201500538 ↗
24. 10.1038/s41467-020-20131-110.1038/s41467-020-20131-1 ↗
25. 10.1039/C8EE01192C10.1039/C8EE01192C ↗
26. 10.1021/am503242v10.1021/am503242v ↗
27. 10.1016/j.colsurfa.2017.01.04110.1016/j.colsurfa.2017.01.041 ↗
28. 10.1021/acscentsci.1c0021710.1021/acscentsci.1c00217 ↗
29. 10.1016/j.comptc.2019.11255610.1016/j.comptc.2019.112556 ↗
30. 10.1002/anie.20210448010.1002/anie.202104480 ↗
31. 10.1039/C8EE03276A10.1039/C8EE03276A ↗
32. 10.1002/adma.20230034710.1002/adma.202300347 ↗
33. 10.1002/anie.20230087310.1002/anie.202300873 ↗
34. 10.1016/j.carbon.2020.11.09810.1016/j.carbon.2020.11.098 ↗
35. 10.1038/s41893-022-00870-310.1038/s41893-022-00870-3 ↗
36. 10.1016/j.seppur.2020.11662310.1016/j.seppur.2020.116623 ↗
37. 10.1021/acs.est.2c0470410.1021/acs.est.2c04704 ↗
38. 10.1016/j.jhazmat.2012.07.07110.1016/j.jhazmat.2012.07.071 ↗
39. 10.1021/acs.est.7b0110810.1021/acs.est.7b01108 ↗
40. 10.1021/acs.est.3c0217510.1021/acs.est.3c02175 ↗
41. 10.1021/acsenergylett.0c0184810.1021/acsenergylett.0c01848 ↗
42. 10.1039/C9EE00838A10.1039/C9EE00838A ↗
43. 10.1016/j.carbon.2011.11.01010.1016/j.carbon.2011.11.010 ↗
44. 10.1016/j.matchemphys.2015.05.02310.1016/j.matchemphys.2015.05.023 ↗
45. 10.1021/ie504706w10.1021/ie504706w ↗
46. 10.1021/es505494610.1021/es5054946 ↗
47. 10.1016/j.cej.2024.15110010.1016/j.cej.2024.151100 ↗
48. 10.1039/D3EE00249G10.1039/D3EE00249G ↗
49. 10.1039/C7EE00345E10.1039/C7EE00345E ↗
50. 10.1021/am403019y10.1021/am403019y ↗
51. 10.1021/acs.jpcc.1c0827610.1021/acs.jpcc.1c08276 ↗
52. 10.1002/anie.20240041410.1002/anie.202400414 ↗
53. 10.1021/jz300236w10.1021/jz300236w ↗
54. 10.1021/acsnano.9b0415610.1021/acsnano.9b04156 ↗
55. 10.1016/j.carbon.2022.04.07210.1016/j.carbon.2022.04.072 ↗
56. 10.1021/acs.chemrev.0c0035110.1021/acs.chemrev.0c00351 ↗
57. 10.1016/j.petrol.2022.11037210.1016/j.petrol.2022.110372 ↗
58. 10.1016/j.molliq.2018.12.00910.1016/j.molliq.2018.12.009 ↗