Thermodynamics of the Oxygen Reduction Reaction on Surfaces of Nitrogen-Doped Graphene

V. A. Kislenko; Кисленко В. А.; S. V. Pavlov; Павлов С. В.; S. A. Kislenko; Кисленко С. А.

doi:10.31857/S0044453723110158

Thermodynamics of the Oxygen Reduction Reaction on Surfaces of Nitrogen-Doped Graphene

Авторлар: Kislenko V.A.¹^,2, Pavlov S.V.², Kislenko S.A.²
Мекемелер:
1. Skolkovo Institute of Science and Technology
2. Joint Institute for High Temperatures, Russian Academy of Sciences
Шығарылым: Том 97, № 11 (2023)
Беттер: 1547-1555
Бөлім: ХИМИЧЕСКАЯ ТЕРМОДИНАМИКА И ТЕРМОХИМИЯ
##submission.dateSubmitted##: 26.12.2023
##submission.datePublished##: 01.11.2023
URL: https://ogarev-online.ru/0044-4537/article/view/233047
DOI: https://doi.org/10.31857/S0044453723110158
EDN: https://elibrary.ru/VLDXBV
ID: 233047

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Аннотация

DFT modeling is used to calculate the free energy profiles of oxygen reduction in acidic and alkaline media on surfaces of nitrogen-doped graphene rather than defect-free graphene. Both four- and two-electron mechanisms of associative reaction are considered. Calculations are made in the grand canonical ensemble at a fixed electrode potential. It is shown that calculations at a fixed potential differ considerably from ones generally accepted at a fixed surface charge. It is found that the electrocatalytic effect of the nitrogen impurity is associated with an increase in the OOH intermediate’s energy of chemisorption that reduces the energy of the oxygen molecule’s protonation reaction. It is also shown that a nitrogen impurity inhibits the two-electron reaction mechanism in an alkaline medium.

Негізгі сөздер

oxygen reduction reaction, electrocatalysis, graphene, nitrogen impurity

Әдебиет тізімі

Ferriday T.B., Middleton P.H. // Int. J. Hydrogen Energy. 2021. V. 46. № 35. P. 18489.
Ma R., Lin G., Zhou Y. et al. // npj Comput. Mater. 2019. V. 5. № 1. P. 78.
Zhang L., Lin C., Zhang D. et al. // Adv. Mater. 2019. V. 31. № 13. P. 1805252.
Wang B., Liu B., Dai L. // Adv. Sustain. Syst. 2021. V. 5. № 1. P. 2000134.
Jia Y., Zhang L., Zhuang L. et al. // Nat. Catal. 2019. V. 2. № 8. P. 688.
Begum H., Ahmed M.S., Kim Y.-B. // Sci. Rep. 2020. V. 10. № 1. P. 12431.
Tabassum H., Zou R., Mahmood A. et al. // J. Mater. Chem. A. 2016. V. 4. № 42. P. 16469.
Lai L., Potts J., Zhan D. et al. // Energy Environ. Sci. 2012. V. 5. № 7. P. 7936.
Wan K., Yu Z.-P., Li X.-H. et al. // ACS Catal. 2015. V. 5. № 7. P. 4325.
Rauf M., Zhao Y.-D., Wang Y.-C. et al. // Electrochem. commun. 2016. V. 73. P. 71.
Yang H., Miao J., Hung S.-F. et al. // Sci. Adv. 2016. V. 2. № 4. P. e1501122.
Kim I.T., Song M., Kim Y. et al. // Int. J. Hydrogen Energy. 2016. V. 41. № 47. P. 22026.
Guo D., Shibuya R., Akiba C. et al. // Science. 2016. V. 351. № 6271. P. 361.
Okamoto Y. // Appl. Surf. Sci. 2009. V. 256. № 1. P. 335.
Ikeda T., Boero M., Huang S.-F. et al. // J. Phys. Chem. C. 2008. V. 112. № 38. P. 14706.
Zhang L., Xia Z. // Ibid. 2011. V. 115. № 22. P. 11170.
Wan X., Shui J. // Sci. Adv. 2022. V. 1. № 1. P. e1400129.
Nørskov J.K., Rossmeisl J., Logadottir A. et al. // J. Phys. Chem. B. 2004. V. 108. № 46. P. 17886.
Yu L., Pan X., Cao X. et al. // J. Catal. 2011. V. 282. № 1. P. 183.
Oberhofer H. Handbook of Materials Modeling. Methods: Theory and Modeling. Cham: Springer International Publishing, 2018. 1987 p.
Sundararaman R., Goddard W.A., Arias T.A. // J. Chem. Phys. 2017. V. 146. № 11. P. 114104.
Kim D., Shi J., Liu Y. // J. Am. Chem. Soc. 2018. V. 140. № 29. P. 9127.
Kislenko V.A., Pavlov S.V., Kislenko S.A. // Electrochim. Acta. 2020. V. 341. P. 136011.
Pavlov S.V., Kislenko V.A., Kislenko S.A. // J. Phys. Chem. C. 2020. V. 124. № 33. P. 18147–18155.
Gao G., Wang L.-W. // J. Catal. 2020. V. 391. P. 530.
Sundararaman R., Letchworth-Weaver K., Schwarz K. et al. // SoftwareX. 2017. V. 6. P. 278.
Grimme S., Antony J., Ehrlich S. et al. // J. Chem. Phys. 2010. V. 132. № 15. P. 154104.
Garrity K.F., Bennett J.W., Rabe K.M. et al. // Comput. Mater. Sci. 2014. V. 81. P. 446.
Kakaei K., Esrafili M.D., Ehsani A. Chapter 6 – Oxygen Reduction Reaction // Graphene Surfaces / ed. Kakaei K., Esrafili M.D., Ehsani A. Elsevier, 2019. V. 27. P. 203–252.
Yan H.J., Xu B., Shi S.Q., Ouyang C.Y. // J. Appl. Phys. 2012. V. 112. № 10. P. 104316.
Gunceler D., Letchworth-Weaver K., Sundararaman R. et al. // Model. Simul. Mater. Sci. Eng. 2013. V. 21. № 7. P. 74005.
Ashcroft N., Mermin D. Solid State Physics. Cengage Learning, 1976. 848 p.
Sorescu D.C., Jordan K.D., Avouris P. // J. Phys. Chem. B. 2001. V. 105, № 45. P. 11227.
Heller I., Kong J., Williams K.A. et al. // J. Am. Chem. Soc. 2006. V. 128. № 22. P. 7353.
Savin G.I., Shabanov B.M., Telegin P.N., Baranov A.V. // Lobachevskii J. Math. 2019. V. 40. № 11. P. 1853.
Zacharov I., Arslanov R., Gunin M. et al. // Open Eng. 2019. V. 9. № 1. P. 512.