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Development of an Amperometric Cholesterol Biosensor Based on Graphene−Pt Nanoparticle Hybrid Material
Abstract
We describe the development of a highly sensitive amperometric biosensor based on the hybrid material derived from nanoscale Pt particles (nPt) and graphene for the sensing of H 2 O 2 and cholesterol. The biosensing platform was developed using the hybrid material and enzymes cholesterol oxidase and cholesterol esterase. Chemically synthesized graphene has been decorated with nanosized Pt particles. The electron microscopic measurements show that the Pt nanoparticles on graphene have an average size of 12 nm and are randomly distributed throughout the surface. The Pt nanoparticle based hybrid material modified electrode efficiently catalyzes the electrochemical oxidation of H 2 O 2 at the potential of 0.4 V, which is >100 mV less positive with respect to the bulk Pt electrode. The sensing platform is highly sensitive and shows linear response toward H 2 O 2 up to 12 mM with a detection limit of 0.5 nM [S/N (signal-to-noise ratio) = 3] in the absence of any redox mediator or enzyme. The combination of electronically highly conductive graphene and catalytically active Pt nanoparticle favors the facilitated electron transfer for the oxidation of H 2 O 2 . The cholesterol biosensor was developed by immobilizing cholesterol oxidase and cholesterol esterase on the surface of graphene−nanoparticle hybrid material. The bienzyme integrated nanostructured platform is very sensitive, selective toward cholesterol, and it has a fast response time. The sensitivity and limit of detection of the electrode toward cholesterol ester are 2.07 ± 0.1 μA/μM/cm 2 and 0.2 μM, respectively. The apparent Michaelis−Menten constant ( K m app ) was calculated to be 5 mM. The sensor does not suffer from the interference due to other common electroactive species and is highly stable. The analytical performance of the hybrid material was further evaluated using screen-printed electrodes with 50 μL of electrolyte.
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Cites
Graphene: Status and Prospects
Geim, A. K. (2009) · Science · doi:10.1126/science.1158877 · Cited by 13,942
Experimental observation of the quantum Hall effect and Berry's phase in graphene
Zhang, Y., Tan, Y.-W., Stormer, H. L., & Kim, P. (2005) · Nature · doi:10.1038/nature04235 · Cited by 13,435
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Biological and chemical sensors based on graphene materials
Liu, Y., Dong, X., & Chen, P. (2012) · Chem. Soc. Rev. · doi:10.1039/c1cs15270j · Cited by 1,748
A review on graphene-based nanocomposites for electrochemical and fluorescent biosensors
Krishnan, S. K., Singh, E., Singh, P., Meyyappan, M., & Nalwa, H. S. (2019) · RSC Advances · doi:10.1039/c8ra09577a · Cited by 785
Electrically-Transduced Chemical Sensors Based on Two-Dimensional Nanomaterials
Meng, Z., Stolz, R. M., Mendecki, L., & Mirica, K. A. (2019) · Chemical Reviews · doi:10.1021/acs.chemrev.8b00311 · Cited by 773
Graphene based metal and metal oxide nanocomposites: synthesis, properties and their applications
Khan, M., Tahir, M. N., Adil, S. F., Khan, H. U., Siddiqui, M. R. H., Al-warthan, A. A., & Tremel, W. (2015) · Journal of Materials Chemistry A · doi:10.1039/c5ta02240a · Cited by 709
A Nanostructured Conductive Hydrogels-Based Biosensor Platform for Human Metabolite Detection
Li, L., Wang, Y., Pan, L., Shi, Y., Cheng, W., Shi, Y., & Yu, G. (2015) · Nano Letters · doi:10.1021/nl504217p · Cited by 422
Ruecha, N., Rangkupan, R., Rodthongkum, N., & Chailapakul, O. (2014) · Biosensors and Bioelectronics · doi:10.1016/j.bios.2013.08.018 · Cited by 342
Nirala, N. R., Abraham, S., Kumar, V., Bansal, A., Srivastava, A., & Saxena, P. S. (2015) · Sensors and Actuators B: Chemical · doi:10.1016/j.snb.2015.04.091 · Cited by 180
Metadata
- Authors
- Dey, R. S., & Raj, C. R.
- Venue
- The Journal of Physical Chemistry C
- Publisher
- American Chemical Society (ACS)
- Published
- 2010-11-17
- Volume
- 114
- Issue
- 49
- Pages
- 21427-21433
- ISSN
- 1932-7447 (ISSN-L)
- 1932-7455
- OpenAlex
- W2068236561
- Cited by
- 299
- References
- 2
- FWCI
- 20.43
- Type
- journal article
- Language
- en
- Open access
- closed
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