Doping and pretreatment optimized the adsorption of *OCHO on bismuth for the electrocatalytic reduction of CO 2 to formate
Source abstract
Abstract
Electrocatalytic reduction of CO2 to formate is considered as a promising method to achieve carbon neutrality, and the introduction of heteroatoms is an effective strategy to improve the catalytic activity and selectivity of catalysts. However, the structural reconstruction behavior of catalysts driven by voltage is usually ignored. Therefore, we used Cu/Bi2S3 as a model to reveal the dynamic reduction process in different atmospheric environments. The catalyst showed an outstanding faradaic efficiency of 94% for formate and a long-term stability of 100 h, and exhibited a high current density of 280 mA cm-2 in a flow cell. The experimental results and theoretical calculations show that the introduction of copper enhances the adsorption of CO2, accelerates the charge transfer and reduces the formation barrier of *OCHO, thus promoting the formation of formate. This work draws attention to the effects of saturated gases in the electrolyte during structural evolution and provides a possibility for designing catalysts with high catalytic activity.
Source: europepmc · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: CO2 Reduction Techniques and Catalysts · Ionic liquids properties and applications · Carbon dioxide utilization in catalysis
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
State Key Laboratory of Applied Organic Chemistry, Frontiers Science Center for Rare Isotopes, College of Chemistry and Chemical Engineering, Lanzhou University, Lanzhou 730000, China
Beijing National Laboratory for Molecular Sciences, State Key Laboratory of Rare Earth Materials Chemistry and Applications, PKU-HKU Joint Laboratory in Rare Earth Materials and Bioinorganic Chemistry, College of Chemistry and Molecular Engineering Peking University, Beijing 100871, China
Funding
Natural Science Foundation of Gansu Province · National Key Research and Development Program of China · Special Fund Project of Guiding Scientific and Technological Innovation Development of Gansu Province · Higher Education Discipline Innovation Project · Fundamental Research Funds for the Central Universities · National Natural Science Foundation of China
References (43)
Show source-provided references
1. Shin · Nat. Commun. · 2022 · 13 · 548210.1038/s41467-022-33199-8 ↗
2. Kibria · Adv. Mater. · 2019 · 31 · 180716610.1002/adma.201807166 ↗
3. Li · Chem. Soc. Rev. · 2022 · 51 · 123410.1039/D1CS00893E ↗
4. Zhang · J. Am. Chem. Soc. · 2021 · 143 · 380810.1021/jacs.0c11450 ↗
5. Kim · J. Am. Chem. Soc. · 2021 · 143 · 92510.1021/jacs.0c11008 ↗
6. Wang · Nat. Commun. · 2022 · 13 · 375410.1038/s41467-022-31427-9 ↗
7. Huang · Science · 2021 · 372 · 107410.1126/science.abg6582 ↗
8. Peng · Nat. Commun. · 2021 · 12 · 158010.1038/s41467-021-21901-1 ↗
9. Yang · Natl. Sci. Rev. · 2022 · nwac24810.1093/nsr/nwac248 ↗
10. Wang · Adv. Mater. · 2021 · 33 · 200579810.1002/adma.202005798 ↗
11. Wang · Angew. Chem., Int. Ed. · 2021 · 60 · 2294010.1002/anie.202110000 ↗
12. Jiang · Energy Environ. Sci. · 2020 · 13 · 285610.1039/D0EE01486A ↗
13. Zhang · Adv. Energy Mater. · 2022 · 12 · 220032110.1002/aenm.202200321 ↗
14. Yang · Chin. J. Catal. · 2022 · 43 · 167410.1016/S1872-2067(21)63943-8 ↗
15. Chen · Nano-Micro Lett. · 2021 · 13 · 18910.1007/s40820-021-00703-6 ↗
16. Zeng · Adv. Funct. Mater. · 2022 · 32 · 220112510.1002/adfm.202201125 ↗
17. Chen · ACS Catal. · 2021 · 11 · 1459610.1021/acscatal.1c04182 ↗
18. Zhang · ACS Catal. · 2021 · 11 · 1110310.1021/acscatal.1c02556 ↗
19. Chi · Nat. Commun. · 2021 · 12 · 583510.1038/s41467-021-26124-y ↗
20. Wang · J. Am. Chem. Soc. · 2022 · 144 · 2275910.1021/jacs.2c11109 ↗
21. Zhao · Appl. Catal., B · 2020 · 266 · 11862510.1016/j.apcatb.2020.118625 ↗
22. Ko · Nat. Commun. · 2022 · 13 · 220510.1038/s41467-022-29783-7 ↗
23. Li · ACS Catal. · 2022 · 12 · 992210.1021/acscatal.2c02627 ↗
24. Yuan · Adv. Energy Mater. · 2022 · 12 · 220097010.1002/aenm.202200970 ↗
25. Tang · Sep. Purif. Technol. · 2020 · 236 · 11624310.1016/j.seppur.2019.116243 ↗
26. Kresse · Phys. Rev. B: Condens. Matter Mater. Phys. · 1996 · 54 · 1116910.1103/PhysRevB.54.11169 ↗
27. Kresse · Comput. Mater. Sci. · 1996 · 6 · 1510.1016/0927-0256(96)00008-0 ↗
28. Perdew · Phys. Rev. Lett. · 1996 · 77 · 386510.1103/PhysRevLett.77.3865 ↗
29. Perdew · J. Chem. Phys. · 1996 · 105 · 998210.1063/1.472933 ↗
30. Grimme · J. Comput. Chem. · 2006 · 27 · 178710.1002/jcc.20495 ↗
31. Bao · Small · 2022 · 18 · 220113110.1002/smll.202201131 ↗
32. Zhang · Adv. Funct. Mater. · 2022 · 32 · 211307510.1002/adfm.202113075 ↗
33. Fu · Adv. Funct. Mater. · 2022 · 32 · 210718210.1002/adfm.202107182 ↗
34. Sui · Small · 2022 · 18 · 210568210.1002/smll.202105682 ↗
35. Wang · J. Mater. Chem. A · 2022 · 10 · 783010.1039/D1TA09961B ↗
36. Li · Nanoscale · 2017 · 9 · 923010.1039/C7NR03182C ↗
37. Liu · Adv. Mater. · 2022 · 34 · 220256810.1002/adma.202202568 ↗
38. Trentelman · J. Raman Spectrosc. · 2009 · 40 · 58510.1002/jrs.2184 ↗
39. Yao · Angew. Chem., Int. Ed. · 2021 · 60 · 1817810.1002/anie.202104747 ↗
40. Wuttig · Proc. Natl. Acad. Sci. U. S. A. · 2016 · 113 · E458510.1073/pnas.1602984113 ↗
41. Li · ACS Energy Lett. · 2022 · 7 · 145410.1021/acsenergylett.2c00326 ↗
42. Zhou · Angew. Chem., Int. Ed. · 2022 · 61 · e20220583210.1002/anie.202205832 ↗
43. Fu · Adv. Mater. · 2022 · 34 · 220285410.1002/adma.202202854 ↗