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Investigation of glucose electrooxidation mechanism over N-modified metal-doped graphene electrode by density functional theory approach
Date
2022-10-01
Author
Duzenli, Derya
Önal, Işık
Tezsevin, Ilker
Metadata
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In this work, various precious and non-precious metals reported in the literature as the most effective catalysts for glucose electrooxidation reaction were investigated by the density functional theory (DFT) approach in order to reveal the mechanisms taking place over the catalysts in the fuel cell. The use of a single-atom catalyst model was adopted by insertion of one Au, Cu, Ni, Pd, Pt, and Zn metal atom on the pyridinic N atoms doped graphene surface (NG). beta form of d-glucose in alkaline solution was used to determine the reaction mechanism and intermediates that formed during the reaction. DFT results showed that the desired glucono-lactone was formed on the Cu-3NG electrode in a single-step reaction pathway whereas it was produced via different two-step pathways on the Au and Pt-3NG electrodes. Although the interaction of glucose with Ni, Pd, and Zn-doped surfaces resulted in the deprotonation of the molecule, lactone product formation did not occur on these electrode surfaces. When the calculation results are evaluated in terms of energy content and product formation, it can be concluded that Cu, Pt, and especially Au doped graphene catalysts are effective for direct glucose oxidation in fuel cells reactor.
Subject Keywords
DFT
,
electrooxidation
,
glucose
,
single atom catalyst
,
FUEL-CELL TECHNOLOGY
,
AU CATALYST
,
PLATINUM-ELECTRODES
,
DIRECT BOROHYDRIDE
,
OXYGEN REDUCTION
,
CARBON NANOTUBE
,
OXIDATION
,
NITROGEN
,
PERFORMANCE
,
ACID
URI
https://hdl.handle.net/11511/100551
Journal
JOURNAL OF COMPUTATIONAL CHEMISTRY
DOI
https://doi.org/10.1002/jcc.26981
Collections
Department of Chemical Engineering, Article
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D. Duzenli, I. Önal, and I. Tezsevin, “Investigation of glucose electrooxidation mechanism over N-modified metal-doped graphene electrode by density functional theory approach,”
JOURNAL OF COMPUTATIONAL CHEMISTRY
, vol. 43, no. 26, pp. 1793–1801, 2022, Accessed: 00, 2022. [Online]. Available: https://hdl.handle.net/11511/100551.