4.6 Article

BSA-AuNCs based enhanced photoelectrochemical biosensors and its potential use in multichannel detections

出版社

ELSEVIER SCIENCE SA
DOI: 10.1016/j.jphotochem.2017.03.034

关键词

BSA-AuNCs; GO; LBL; H2O2; Dopamine; Photoelectrochemistry; Multichannel; Separation efficiency

资金

  1. National Natural Science Foundation of China [61471207, 61271099, 61501039]
  2. Natural Science Foundation of Tianjin [14JCYBJC16700]
  3. Natural Science Foundation of Beijing [2162017]

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Herein we present the development of a bovine serum albumin (BSA)-coated fluorescent gold nanocluster (BSA-AuNC)/graphene oxide (GO) hybrid nanocomposite-based photoelectrochemical (PEC) biosensor, which can be used for multichannel detection of both hydrogen peroxide (H2O2) and dopamine (DA) within one chip at negative and positive potentials, respectively. BSA-AuNC-based biosensors generally exhibit poor PEC sensing performance owing to their poor separation of photoexcited electron-hole pairs and low electrode coverage. Consequently, improved AuNC/GO hybrid nanocomposites and a layer-by-layer (LBL) method are introduced in this study. The enhancement was investigated by exploring the optimum concentration of GO (0.12 mg mL(-1)) and LBL number (four layers) for the preparation of the BSA-AuNC materials, revealing that GO plays different enhancement roles in the detection of H2O2 and DA. Compared to the results from other gold nanoclusters with different ligands, the photoelectrical enhancement of BSA-AuNCs can be achieved for both negative and positive potentials simultaneously with the same optimum GO concentration and LBL number. Thus, the detection of H2O2 and DA was achieved by BSA-AuNC/GO multilayers with enhanced sensing properties and easier fabrication processes. The two enhancement methods acting together led to an improvement in the limits of detection (LODs) from 325 mu M to 23 mu M (H2O2) and from 7.45 mu M to 1.5 mu M (DA). Thus, our strategy shows great potential for the improvement of PEC sensing structure, and provides a method for multichannel detection. (C) 2017 Elsevier B.V. All rights reserved.

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