The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Highly Sensitive Glucose Sensor Based on Pt Nanoparticle/Polyaniline Hydrogel Heterostructures
Abstract
Glucose enzyme biosensors have been shown useful for a range of applications from medical diagnosis, bioprocess monitoring, to beverage industry and environmental monitoring. We present here a highly sensitive glucose enzyme sensor based on Pt nanoparticles (PtNPs)-polyaniline (PAni) hydrogel heterostructures. High-density PtNPs were homogeneously loaded onto the three-dimensional (3D) nanostructured matrix of the PAni hydrogel. The PtNP/PAni hydrogel heterostructure-based glucose sensor synergizes the advantages of both the conducting hydrogel and the nanoparticle catalyst. The porous structure of the PAni hydrogel favored the high density immobilization of the enzyme and the penetration of water-soluble molecules, which helped efficiently catalyze the oxidation of glucose. In addition, the PtNPs catalyzed the decomposition of hydrogen peroxide that was generated during the enzymatic reaction. The transferred charges from these electrochemical processes were efficiently collected by the highly conducting PtNP/PAni hydrogel heterostructures. The glucose enzyme sensor based on this heterostructure exhibited unprecedented sensitivity, as high as 96.1 μA·mM(-1)·cm(-2), with a response time as fast as 3 s, a linear range of 0.01 to 8 mM, and a low detection limit of 0.7 μM.
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Cites
Electrochemical Glucose Biosensors
Wang, J. (2008) · Chemical Reviews · doi:10.1021/cr068123a · Cited by 3,498
Electrochemical Glucose Sensors and Their Applications in Diabetes Management
Heller, A., & Feldman, B. (2008) · Chemical Reviews · doi:10.1021/cr068069y · Cited by 1,707
Hierarchical nanostructured conducting polymer hydrogel with high electrochemical activity
Pan, L., Yu, G., Zhai, D., Lee, H. R., Zhao, W., Liu, N., Wang, H., Tee, B. C.-K., Shi, Y., Cui, Y., et al. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1202636109 · Cited by 1,216
Self-citationPhotoemission from mass-selected monodispersed Pt clusters
Eberhardt, W., Fayet, P., Cox, D. M., Fu, Z., Kaldor, A., Sherwood, R., & Sondericker, D. (1990) · Physical Review Letters · doi:10.1103/physrevlett.64.780 · Cited by 284
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Zhu, C., Yang, G., Li, H., Du, D., & Lin, Y. (2015) · Analytical Chemistry · doi:10.1021/ac5039863 · Cited by 1,741
Liu, X., Liu, J., Lin, S., & Zhao, X. (2020) · Materials Today · doi:10.1016/j.mattod.2019.12.026 · Cited by 1,023
Zhu, C., Du, D., Eychmüller, A., & Lin, Y. (2015) · Chemical Reviews · doi:10.1021/acs.chemrev.5b00255 · Cited by 672
El-Husseiny, H. M., Mady, E. A., Hamabe, L., Abugomaa, A., Shimada, K., Yoshida, T., Tanaka, T., Yokoi, A., Elbadawy, M., & Tanaka, R. (2022) · Materials Today Bio · doi:10.1016/j.mtbio.2021.100186 · Cited by 533
Hydrogel Based Sensors for Biomedical Applications: An Updated Review
Tavakoli, J., & Tang, Y. (2017) · Polymers · doi:10.3390/polym9080364 · Cited by 434
Ultrahigh‐Conductivity Polymer Hydrogels with Arbitrary Structures
Yao, B., Wang, H., Zhou, Q., Wu, M., Zhang, M., Li, C., & Shi, G. (2017) · Advanced Materials · doi:10.1002/adma.201700974 · Cited by 423
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
Self-citationNanocomposite hydrogel-based strain and pressure sensors: a review
Sun, X., Yao, F., & Li, J. (2020) · Journal of Materials Chemistry A · doi:10.1039/d0ta06965e · Cited by 420
3D nanostructured conductive polymer hydrogels for high-performance electrochemical devices
Zhao, Y., Liu, B., Pan, L., & Yu, G. (2013) · Energy & Environmental Science · doi:10.1039/c3ee40997j · Cited by 396
Self-citationBandodkar, A. J., Jeerapan, I., You, J.-M., Nuñez-Flores, R., & Wang, J. (2016) · Nano Letters · doi:10.1021/acs.nanolett.5b04549 · Cited by 341
Tao, B., Lin, C., Deng, Y., Yuan, Z., Shen, X., Chen, M., He, Y., Peng, Z., Hu, Y., & Cai, K. (2019) · Journal of Materials Chemistry B · doi:10.1039/c8tb03272f · Cited by 290
High-performance non-enzymatic glucose detection: using a conductive Ni-MOF as an electrocatalyst
Qiao, Y., Liu, Q., Lu, S., Chen, G., Gao, S., Lu, W., & Sun, X. (2020) · Journal of Materials Chemistry B · doi:10.1039/d0tb00131g · Cited by 247
From design to applications of stimuli-responsive hydrogel strain sensors
Zhang, D., Ren, B., Zhang, Y., Xu, L., Huang, Q., He, Y., Li, X., Wu, J., Yang, J., Chen, Q., et al. (2020) · Journal of Materials Chemistry B · doi:10.1039/c9tb02692d · Cited by 199
Chen, X., Gao, H., Xing, L., Dong, W., Li, A., Cheng, P., Liu, P., & Wang, G. (2019) · Energy Storage Materials · doi:10.1016/j.ensm.2018.08.024 · Cited by 128
Reusable, Robust, and Accurate Laser-Generated Photonic Nanosensor
Yetisen, A. K., Montelongo, Y., da Cruz Vasconcellos, F., Martinez-Hurtado, J. L., Neupane, S., Butt, H., Qasim, M. M., Blyth, J., Burling, K., Carmody, J. B., et al. (2014) · Nano Letters · doi:10.1021/nl5012504 · Cited by 123
Das, S., Chakraborty, P., Mondal, S., Shit, A., & Nandi, A. K. (2016) · ACS Applied Materials & Interfaces · doi:10.1021/acsami.6b09468 · Cited by 86
Wang, Z., Dong, S., Gui, M., Asif, M., Wang, W., Wang, F., & Liu, H. (2018) · Analytical Biochemistry · doi:10.1016/j.ab.2017.12.010 · Cited by 59
Kundu, M. K., Sadhukhan, M., & Barman, S. (2015) · Journal of Materials Chemistry B · doi:10.1039/c4tb01740d · Cited by 54
Atta, N. F., Galal, A., & El-Ads, E. H. (2019) · Journal of Electroanalytical Chemistry · doi:10.1016/j.jelechem.2019.113523 · Cited by 22
Metadata
- Authors
- Zhai, D., Liu, B., Shi, Y., Pan, L., Wang, Y., Li, W., Zhang, R., & Yu, G.
- Venue
- ACS Nano
- Publisher
- American Chemical Society (ACS)
- Published
- 2013-03-14
- Volume
- 7
- Issue
- 4
- Pages
- 3540-3546
- ISSN
- 1936-0851 (ISSN-L)
- 1936-086X
- OpenAlex
- W2031449366
- Cited by
- 814
- References
- 4
- FWCI
- 42.14
- Type
- journal article
- Language
- en
- Open access
- closed
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