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Iron Oxide Particles Are the Active Sites for Hydrogen Peroxide Sensing at Multiwalled Carbon Nanotube Modified Electrodes
Abstract
We demonstrate that the "electrocatalytic" hydrogen peroxide detection reported at multiwalled carbon nanotube modified electrodes is due to iron oxide particles arising from the chemical vapor deposition nanotube fabrication process rather than due to intrinsic catalysis attributable to the carbon nanotubes arising, for example, from edge plane-like sites/defects.
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Cited by
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Optically Transparent Cathode for Dye-Sensitized Solar Cells Based on Graphene Nanoplatelets
Kavan, L., Yum, J. H., & Grätzel, M. (2011) · ACS Nano · doi:10.1021/nn102353h · Cited by 527
Recent developments in 2D layered inorganic nanomaterials for sensing
Kannan, P. K., Late, D. J., Morgan, H., & Rout, C. S. (2015) · Nanoscale · doi:10.1039/c5nr03633j · Cited by 454
Advances in carbon nanotube based electrochemical sensors for bioanalytical applications
Vashist, S. K., Zheng, D., Al-Rubeaan, K., Luong, J. H. T., & Sheu, F.-S. (2011) · Biotechnology Advances · doi:10.1016/j.biotechadv.2010.10.002 · Cited by 448
A theoretical simulation on the catalytic oxidation of CO on Pt/graphene
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Metadata
- Authors
- Šljukić, B., Banks, C. E., & Compton, R. G.
- Venue
- Nano Letters
- Publisher
- American Chemical Society (ACS)
- Published
- 2006-06-29
- Volume
- 6
- Issue
- 7
- Pages
- 1556-1558
- ISSN
- 1530-6984 (ISSN-L)
- 1530-6992
- OpenAlex
- W2012709570
- Cited by
- 388
- References
- 0
- FWCI
- 28.68
- Type
- journal article
- Language
- en
- Open access
- closed
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- Šljukić, B., Banks, C. E., & Compton, R. G. (2006). Iron Oxide Particles Are the Active Sites for Hydrogen Peroxide Sensing at Multiwalled Carbon Nanotube Modified Electrodes. Nano Letters. https://doi.org/10.1021/nl060366v
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
