Leveraging Soft Acid‐Base Interactions Alters the Pathway for Electrochemical Nitrogen Oxidation to Nitrate with High Faradaic Efficiency
Source abstract
Abstract
Abstract Electrocatalytic nitrogen oxidation reaction (N 2 OR) offers a sustainable alternative to the conventional methods such as the Haber–Bosch and Ostwald oxidation processes for converting nitrogen (N 2 ) into high‐value‐added nitrate (NO 3 − ) under mild conditions. However, the concurrent oxygen evolution reaction (OER) and inefficient N 2 absorption/activation led to slow N 2 OR kinetics, resulting in low Faradaic efficiencies and NO 3 − yield rates. This study explored oxygen‐vacancy induced tin oxide (SnO 2 ‐O v ) as an efficient N 2 OR electrocatalyst, achieving an impressive Faradaic efficiency (FE) of 54.2% and a notable NO 3 − yield rate (22.05 µg h −1 mg cat −1 ) at 1.7 V versus reversible hydrogen electrode (RHE) in 0.1 m Na 2 SO 4 . Experimental results indicate that SnO 2 ‐O v possesses substantially more oxygen vacancies than SnO 2 , correlating with enhanced N 2 OR performance. Computational findings suggest that the superior performance of SnO 2 ‐O v at a relatively low overpotential is due to reduced thermodynamic barrier for the oxidation of *N 2 to *N 2 OH during the rate‐determining step, making this step energetically favorable than the oxygen adsorption step for OER. This work demonstrates the feasibility of ambient nitrate synthesis on the soft acidic Sn active site and introduces a new approach for rational catalyst design.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Ammonia Synthesis and Nitrogen Reduction · Advanced Photocatalysis Techniques · Electrocatalysts for Energy Conversion
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Institute of Nano Science and Technology Sector‐81 Mohali Punjab 140306 India
Department of Physics SRM University AP Amaravati Andhra Pradesh 522 240 India
Department of Pharmaceutical Chemistry College of Pharmacy King Saud University Riyadh 11451 Saudi Arabia
Centre for Computational and Integrative Sciences SRM University AP Amaravati Andhra Pradesh 522 240 India
Funding
Science and Engineering Research Board · Board of Research in Nuclear Sciences
References (40)
Show source-provided references
1. 10.1021/acsnano.1c0810910.1021/acsnano.1c08109 ↗
2. 10.1039/C9CS00280D10.1039/C9CS00280D ↗
3. 10.1126/science.aad499810.1126/science.aad4998 ↗
4. 10.1126/science.aar661110.1126/science.aar6611 ↗
5. 10.1002/adfm.20200898310.1002/adfm.202008983 ↗
6. 10.1002/adfm.20230380310.1002/adfm.202303803 ↗
7. 10.20517/energymater.2023.6710.20517/energymater.2023.67 ↗
8. 10.1039/D0EE01241F10.1039/D0EE01241F ↗
9. 10.1021/acsenergylett.1c0161410.1021/acsenergylett.1c01614 ↗
10. 10.1002/anie.20211540910.1002/anie.202115409 ↗
11. 10.1038/s44160-024-00522-810.1038/s44160-024-00522-8 ↗
12. 10.1002/sus2.22610.1002/sus2.226 ↗
13. 10.1021/cs401013v10.1021/cs401013v ↗
14. 10.1002/adfm.20240077310.1002/adfm.202400773 ↗
15. 10.1021/acscatal.3c0530710.1021/acscatal.3c05307 ↗
16. 10.1002/anie.20200292310.1002/anie.202002923 ↗
17. 10.1039/D3QM00291H10.1039/D3QM00291H ↗
18. 10.1002/adma.20200218910.1002/adma.202002189 ↗
19. 10.1002/anie.20201401710.1002/anie.202014017 ↗
20. 10.1002/adma.20210818010.1002/adma.202108180 ↗
21. 10.1002/adfm.20230822910.1002/adfm.202308229 ↗
22. 10.1002/aenm.20230191810.1002/aenm.202301918 ↗
23. 10.1021/acs.jpclett.2c0245910.1021/acs.jpclett.2c02459 ↗
24. 10.1002/aenm.20230061510.1002/aenm.202300615 ↗
25. 10.1021/acscatal.1c0436010.1021/acscatal.1c04360 ↗
26. 10.1021/acs.jpclett.2c0076910.1021/acs.jpclett.2c00769 ↗
27. 10.1021/acsnano.4c0223110.1021/acsnano.4c02231 ↗
28. 10.1016/j.cej.2021.12882710.1016/j.cej.2021.128827 ↗
29. 10.1002/adfm.20240831410.1002/adfm.202408314 ↗
30. 10.1002/ece2.2610.1002/ece2.26 ↗
31. 10.1039/D3MH02141F10.1039/D3MH02141F ↗
32. 10.1002/adfm.20230347310.1002/adfm.202303473 ↗
33. 10.1002/ece2.2610.1002/ece2.26 ↗
34. 10.1016/j.apsusc.2017.05.17610.1016/j.apsusc.2017.05.176 ↗
35. Applied Surface Science 420 399https://doi.org/10.1016/j.apsusc.2017.05.176.10.1016/j.apsusc.2017.05.176 ↗
36. 10.1038/s41467-023-40991-710.1038/s41467-023-40991-7 ↗
37. 10.1016/j.checat.2021.10.01110.1016/j.checat.2021.10.011 ↗
38. 10.1039/D1SC00752A10.1039/D1SC00752A ↗
39. 10.1021/acscatal.3c0274710.1021/acscatal.3c02747 ↗
40. 10.1039/D2SC02625B10.1039/D2SC02625B ↗