Enhancing CO Selectivity in CO2 Photoreduction via Local Hydrophobic Modifications in S-Scheme Heterojunctions
Source abstract
Abstract
To address the challenge of competitive H 2 O adsorption in photocatalytic CO 2 reduction, localized hydrophobicity-modified S-scheme heterojunctions (WS/o-CN) were synthesized by combining WS 2 and g-C 3 N 4, which was modified by the addition of CTAB. Structural characterization and contact angle testing confirmed the formation of S-scheme heterojunctions and the specific structural role of CTAB. The optical, electrochemical properties, and gas adsorption capacity of the catalysts were analyzed, followed by in situ XPS and fs-TA tests to investigate the energy band structure and electron transfer paths. These results showed that localized hydrophobic modification reduces the surface proton concentration while maintaining efficient electron–hole separation in the S-scheme heterojunction. Testing the photocatalytic activity of WS/o-CN showed that the yield of CO reached 23.24 μmol g –1 h –1 with a high selectivity of 74.7%. Combined with molecular dynamics simulations and in situ DRIFTS tests, the results demonstrated that the introduction of the nonpolar long carbon chain CTAB effectively inhibits the adsorption of heterogeneous H 2 O on the catalyst surface while enhancing the maximum adsorption of CO 2 . The localized hydrophobicity reduces the proton concentration on the surface of g-C 3 N 4, which in turn suppresses the absorption of photogenerated electrons by the HER reaction. This facilitates the efficient and selective conversion of CO 2 to CO. This study highlights a surface engineering strategy that couples electronic structure optimization with interfacial wettability control, providing valuable insights into the design of selective and efficient photocatalysts for CO 2 -to-CO conversion.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Advanced Photocatalysis Techniques · CO2 Reduction Techniques and Catalysts · Ga2O3 and related materials
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Multiphase Flow in Power Engineering, School of Energy and Power Engineering
Xi’an Jiaotong University
School of Materials Science and Engineering
Nanyang Technological University
Institute of Flexible Electronics Technology of THU
Tsinghua University
Funding
National Key Research and Development Program of China
References (63)
Show source-provided references
1. 10.1039/D4SC01896F10.1039/D4SC01896F ↗
2. 10.1021/acscatal.0c0094710.1021/acscatal.0c00947 ↗
3. 10.1002/anie.20170162710.1002/anie.201701627 ↗
4. 10.1021/acscatal.3c0021910.1021/acscatal.3c00219 ↗
5. 10.1002/adma.20240191410.1002/adma.202401914 ↗
6. 10.1002/adma.20220530310.1002/adma.202205303 ↗
7. 10.1021/acscatal.4c0075810.1021/acscatal.4c00758 ↗
8. 10.1016/j.chempr.2020.06.01010.1016/j.chempr.2020.06.010 ↗
9. 10.1039/D3EE03282E10.1039/D3EE03282E ↗
10. 10.1039/D3SC03681B10.1039/D3SC03681B ↗
11. 10.1002/anie.20220879110.1002/anie.202208791 ↗
12. 10.1002/anie.20231774010.1002/anie.202317740 ↗
13. 10.1002/anie.20211033610.1002/anie.202110336 ↗
14. 10.1002/adma.20180071810.1002/adma.201800718 ↗
15. 10.1021/acsnano.4c1815010.1021/acsnano.4c18150 ↗
16. 10.1021/acsnano.3c1035210.1021/acsnano.3c10352 ↗
17. 10.1038/s41929-018-0108-310.1038/s41929-018-0108-3 ↗
18. 10.1002/anie.20190805810.1002/anie.201908058 ↗
19. 10.1016/j.apcatb.2024.12465810.1016/j.apcatb.2024.124658 ↗
20. 10.1021/jacs.2c0248610.1021/jacs.2c02486 ↗
21. 10.1021/acscatal.3c0398310.1021/acscatal.3c03983 ↗
22. 10.1038/s41467-020-16847-910.1038/s41467-020-16847-9 ↗
23. 10.1038/s41467-023-39351-210.1038/s41467-023-39351-2 ↗
24. 10.1016/j.apcatb.2020.11963010.1016/j.apcatb.2020.119630 ↗
25. 10.1038/s41467-024-44753-x10.1038/s41467-024-44753-x ↗
26. 10.1016/j.apcatb.2020.11911410.1016/j.apcatb.2020.119114 ↗
27. 10.1016/j.apcatb.2018.03.06810.1016/j.apcatb.2018.03.068 ↗
28. 10.1016/j.cej.2023.14316010.1016/j.cej.2023.143160 ↗
29. 10.1021/acscatal.4c0040910.1021/acscatal.4c00409 ↗
30. 10.1021/jacs.0c1039710.1021/jacs.0c10397 ↗
31. 10.1021/jacs.4c0008210.1021/jacs.4c00082 ↗
32. 10.1021/acscatal.4c0154410.1021/acscatal.4c01544 ↗
33. 10.1021/acsami.5b0990110.1021/acsami.5b09901 ↗
34. 10.1021/acsami.7b1883510.1021/acsami.7b18835 ↗
35. 10.1002/adma.20190286810.1002/adma.201902868 ↗
36. 10.1002/anie.20190453710.1002/anie.201904537 ↗
37. 10.1021/acsaem.0c0088110.1021/acsaem.0c00881 ↗
38. 10.1021/acsanm.3c0334910.1021/acsanm.3c03349 ↗
39. 10.1021/acscatal.4c0102010.1021/acscatal.4c01020 ↗
40. 10.1021/acscatal.4c0282310.1021/acscatal.4c02823 ↗
41. 10.1002/adfm.20200429310.1002/adfm.202004293 ↗
42. 10.1021/acs.jpclett.9b0260510.1021/acs.jpclett.9b02605 ↗
43. 10.1038/srep1922110.1038/srep19221 ↗
44. 10.1021/acsnano.3c1227410.1021/acsnano.3c12274 ↗
45. 10.1021/jacs.3c1475710.1021/jacs.3c14757 ↗
46. 10.1007/s11426-019-9639-010.1007/s11426-019-9639-0 ↗
47. 10.1002/anie.20230678610.1002/anie.202306786 ↗
48. 10.1002/adma.20210031710.1002/adma.202100317 ↗
49. 10.1038/s41560-022-01188-210.1038/s41560-022-01188-2 ↗
50. 10.1002/adfm.20230960310.1002/adfm.202309603 ↗
51. 10.1021/acsenergylett.4c0041610.1021/acsenergylett.4c00416 ↗
52. 10.1021/acsnano.4c0035010.1021/acsnano.4c00350 ↗
53. 10.1021/acsami.2c1269510.1021/acsami.2c12695 ↗
54. 10.1103/PhysRevB.82.07511610.1103/PhysRevB.82.075116 ↗
55. 10.1103/PhysRevB.59.741310.1103/PhysRevB.59.7413 ↗
56. 10.1063/1.338234410.1063/1.3382344 ↗
57. 10.1016/j.softx.2015.06.00110.1016/j.softx.2015.06.001 ↗
58. 10.1021/j100308a03810.1021/j100308a038 ↗
59. 10.1002/jcc.2014510.1002/jcc.20145 ↗
60. 10.1021/j100142a00410.1021/j100142a004 ↗
61. 10.1039/b508541a10.1039/b508541a ↗
62. 10.1002/jcc.2288510.1002/jcc.22885 ↗
63. 10.1063/5.000704510.1063/5.0007045 ↗