journal article·2024-06-05

Nonconductive Metal Oxide Gas Diffusion Layer for Mitigating Electrowetting during CO2 Electrolysis

Robert Haaring, Phil Woong Kang, Jae Won Lee, Junpyo Lee, Hyunjoo Lee

ACS Applied Materials & Interfaces· Volume 16· Issue 22
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Abstract

Gas diffusion electrodes (GDEs) are extensively used for high current density electrochemical CO 2 electrolysis (ECO 2 R), enabled by significantly reducing mass transfer resistance of CO 2 to the catalyst layer. Conventionally, these GDEs are based upon hydrophobic carbon-based gas-diffusion layers (GDLs) that facilitate the gas transport; however, these supports are prone to flood with electrolyte during electrolysis. This potential-induced flooding, known as electrowetting, is related to the inherent conductivity of carbon and limits the activity of ECO 2 R. To investigate the effect of electrical conductivity more carefully, a GDE is constructed based on a Cu mesh with a nonconductive microporous GDL applied to this substrate, the latter composed of a mixture of metal oxide and polytetrafluoroethylene. With alumina as the metal oxide, a stable operation is obtained at −200 mA cm –2 with 70% selectivity for ECO 2 R (with over half toward C 2+ products) without flooding as observed by in situ microscopy. On the contrary, with a Vulcan carbon-based GDL, the initial activity is rapidly lost as severe flooding ensues. It is reasoned that electrowetting is averted by virtue of the nonconductive nature of alumina, providing a new perspective on alternative GDL compositions and their influence on ECO 2 R performance.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Electrowetting and Microfluidic Technologies · CO2 Reduction Techniques and Catalysts · Gas Sensing Nanomaterials and Sensors

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

Affiliations

Department of Chemical and Biomolecular Engineering, Korea Advanced Institute of Science and Technology, Daejeon 34141, South Korea

Funding

National Research Foundation of Korea · Saudi Aramco-KAIST CO2 Management Center

References (49)

Show source-provided references
1. Lazard. · Lazard’s Levelized Cost of Energy Analysis – Version · 2023 · 16
2. 10.1038/s41560-021-00973-910.1038/s41560-021-00973-9 ↗
3. 10.1021/acs.iecr.7b0351410.1021/acs.iecr.7b03514 ↗
4. 10.1016/j.xpro.2021.10088910.1016/j.xpro.2021.100889 ↗
5. 10.1021/acs.accounts.3c0034910.1021/acs.accounts.3c00349 ↗
6. 10.1039/C8EE03134G10.1039/C8EE03134G ↗
7. 10.1039/D0CS00230E10.1039/D0CS00230E ↗
8. 10.1038/s42004-023-00836-210.1038/s42004-023-00836-2 ↗
9. 10.3390/catal1006071310.3390/catal10060713 ↗
10. 10.1021/acsenergylett.0c0218410.1021/acsenergylett.0c02184 ↗
11. 10.1002/aenm.20200048810.1002/aenm.202000488 ↗
12. 10.1002/cssc.20190254710.1002/cssc.201902547 ↗
13. 10.1021/acssuschemeng.2c0019510.1021/acssuschemeng.2c00195 ↗
14. 10.1021/acsaem.2c0278310.1021/acsaem.2c02783 ↗
15. Pletcher D. · 1984 · 110.1039/9781847559944 ↗
16. 10.1021/acsenergylett.2c0188510.1021/acsenergylett.2c01885 ↗
17. 10.1021/acsenergylett.0c0240110.1021/acsenergylett.0c02401 ↗
18. 10.1039/D3YA00285C10.1039/D3YA00285C ↗
19. 10.1021/acsaem.1c0071510.1021/acsaem.1c00715 ↗
20. 10.1149/1945-7111/abaa1a10.1149/1945-7111/abaa1a ↗
21. 10.1021/acsami.0c2199710.1021/acsami.0c21997 ↗
22. 10.1126/science.aas910010.1126/science.aas9100 ↗
23. 10.1088/0953-8984/17/28/R0110.1088/0953-8984/17/28/R01 ↗
24. 10.1021/acs.jpcc.2c0651710.1021/acs.jpcc.2c06517 ↗
25. 10.1021/acsenergylett.2c0155510.1021/acsenergylett.2c01555 ↗
26. 10.1038/s41467-020-20397-510.1038/s41467-020-20397-5 ↗
27. 10.1002/elsa.20210015810.1002/elsa.202100158 ↗
28. 10.1021/acsaem.2c0305410.1021/acsaem.2c03054 ↗
29. 10.1126/science.aay421710.1126/science.aay4217 ↗
30. 10.1038/s41467-023-42348-610.1038/s41467-023-42348-6 ↗
31. 10.1021/acsenergylett.4c0011410.1021/acsenergylett.4c00114 ↗
32. 10.1002/celc.20210127910.1002/celc.202101279 ↗
33. 10.1021/acsaem.2c0016010.1021/acsaem.2c00160 ↗
34. 10.1021/acscatal.8b0510910.1021/acscatal.8b05109 ↗
35. 10.1039/C9TA06736A10.1039/C9TA06736A ↗
36. 10.1016/j.jpowsour.2022.23099810.1016/j.jpowsour.2022.230998 ↗
37. 10.1016/j.jpowsour.2016.02.04310.1016/j.jpowsour.2016.02.043 ↗
38. 10.1002/aenm.20210366310.1002/aenm.202103663 ↗
39. 10.1016/j.jpowsour.2014.12.11810.1016/j.jpowsour.2014.12.118 ↗
40. 10.1021/acsenergylett.1c0061210.1021/acsenergylett.1c00612 ↗
41. 10.1002/adma.20180311110.1002/adma.201803111 ↗
42. 10.1021/acs.nanolett.9b0274810.1021/acs.nanolett.9b02748 ↗
43. 10.1016/j.jpowsour.2015.09.12410.1016/j.jpowsour.2015.09.124 ↗
44. 10.1002/anie.20160128210.1002/anie.201601282 ↗
45. 10.1002/anie.20221043210.1002/anie.202210432 ↗
46. 10.1039/D2NR01563C10.1039/D2NR01563C ↗
47. 10.1021/acsanm.1c0051410.1021/acsanm.1c00514 ↗
48. 10.1021/acsenergylett.9b0257610.1021/acsenergylett.9b02576 ↗
49. 10.1039/D0EE02589E10.1039/D0EE02589E ↗