4.7 Article

Uniformly dispersed PtNi alloy nanoparticles in porous N-doped carbon nanofibers with high selectivity and stability for hydrogen peroxide detection

期刊

SENSORS AND ACTUATORS B-CHEMICAL
卷 261, 期 -, 页码 354-363

出版社

ELSEVIER SCIENCE SA
DOI: 10.1016/j.snb.2018.01.169

关键词

PtNi alloy nanoparticle; Porous N doped carbon nanofiber; Embedded structure; Non-enzymatic sensor; H2O2 detection

资金

  1. National Natural Science Foundation of China [21576247, 21706242]

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Highly dispersed Pt-based nanoparticles with superior electrocatalytic selectivity and stability are urgently needed for non-enzymatic electrochemical detection of H2O2. Herein, we prepared PtNi alloy nanoparticles dispersed in N-doped carbon nanofibers (PtNi/NCNFs) by pyrolyzing electrospun nanofibers composites from polyvinyl pyrrolidone and Pt/Ni-based salts. Characterization results indicated that PtNi alloy nanoparticles (average 9.0 nm) were homogeneously dispersed and embedded in NCNFs porous matrix. The electrochemical tests suggested that PtNi/NCNFs(3:1) displayed the highest electrocatalytic activity for H2O2 reduction compared with Pt/NCNFs, Ni/NCNFs and other PtNi/NCNFs samples. PtNi/NCNFs(3:1)-based sensor showed excellent analytical properties towards H2O2 with wide linear range (0.5 mu M-8 mM), high sensitivity (248.5 mu AmM-1 cm(-2)), low detection limit (0.0375 mu M), high selectivity and anti-interference, attributing to the highly dispersion of nanoparticles and synergistic effect between PtNi alloy nanoparticles and NCNFs. The PtNi/NCNFs-based sensor had superior reproducibility due to the uniformity of PtNi/NCNFs and good stability because of the embedded structure, which prevented the aggregation and detachment of nanoparticles during repeated uses. More interestingly, the as-fabricated sensor displayed satisfactory recoveries and relative standard deviation (RSD) for detection of H2O2 in milk samples. The above results manifested that PtNi/NCNFs had potential to be selected as a candidate for fabricating non-enzymatic H2O2 sensors. (C) 2018 Elsevier B.V. All rights reserved.

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