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      Ultrasensitive and simultaneous detection of hydroquinone, catechol and resorcinol based on the electrochemical co-reduction prepared Au-Pd nanoflower/reduced graphene oxide nanocomposite

      , , , , , ,
      Electrochimica Acta
      Elsevier BV

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          Au@Ag Heterogeneous Nanorods as Nanozyme Interfaces with Peroxidase-Like Activity and Their Application for One-Pot Analysis of Glucose at Nearly Neutral pH.

          As substitutes for natural peroxidases, most nanomaterial-based enzyme mimetics (nanozymes) have unique properties such as high stability, low-cost, large surface area, and high catalytic activity. However, they usually work in acidic conditions and thus impede their real applications. In this work, by modulating the nanostructure, composition, and surface property of the bimetallic materials, the positively charged poly(diallyldimethylammonium)-stabilized Au@Ag heterogeneous nanorods (NRs) were developed as synergistic peroxidase-like interfaces, which exhibited high activity over a wide pH range (pH 4.0-6.5) using 2,2'-azino-bis(3-ethylbenzthiazoline-6-sulfonic acid) diammonium salt (ABTS) as the chromogenic substrate. At pH 6.5, the peroxidase-like activity for the Au@Ag heterogeneous NRs was stable and optimal within 20-40 °C. Moreover, the Au@Ag heterogeneous NRs showed excellent temperature stability and long-term storage stability. Given these characters, the detection of H2O2 at pH 6.5 was proposed on the basis of the Au@Ag heterogeneous NRs catalyzing the colorimetric reaction of H2O2 and ABTS, where the oxidized ABTS showed a typical absorption peak at 414 nm. The absorbance at 414 nm was linear with H2O2 concentration from 0.01 to 10 mM. Further, considering that Au@Ag heterogeneous NRs and glucose oxidase (GOx) have similar optimal pH for catalytic activities, a novel one-pot method for the detection of glucose was developed by the coupled catalytic reaction using GOx, Au@Ag heterogeneous NRs, and ABTS at nearly neutral pH (pH 6.5) and 37 °C. This proposed method had simple and rapid processes, wide linear range (0.05-20 mM), and reliability for the successful analysis of real samples. On the basis of these attractive and unique characteristics, Au@Ag heterogeneous NRs can become promising substitutes for peroxidase in analytical chemistry and environmental science.
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            A facile electrochemical sensor based on reduced graphene oxide and Au nanoplates modified glassy carbon electrode for simultaneous detection of ascorbic acid, dopamine and uric acid

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              Electrospun carbon nanofibers decorated with Ag-Pt bimetallic nanoparticles for selective detection of dopamine.

              Electrospun nanoporous carbon nanofibers (pCNFs) decorated with Ag-Pt bimetallic nanoparticles have been successfully synthesized by combining template carbonization and seed-growth reduction approach. Porous-structured polyacrylonitrile (PAN) nanofibers (pPAN) were first prepared by electrospinning PAN/polyvinylpyrrolidone (PVP) blend solution, followed by subsequent water extraction and heat treatment to obtain pCNFs. Ag-Pt/pCNFs were then obtained by using pCNFs as support for bimetallic nanoparticle loading. Thus, the obtained Ag-Pt/pCNFs were used to modify glassy carbon electrode (GCE) for selective detection of dopamine (DA) in the presence of uric acid (UA) and ascorbic acid (AA). This novel sensor exhibits fast amperometric response and high sensitivity toward DA with a wide linear concentration range of 10-500 μM and a low detection limit of 0.11 μM (S/N = 3), wherein the interference of UA and AA can be eliminated effectively.
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                Author and article information

                Journal
                Electrochimica Acta
                Electrochimica Acta
                Elsevier BV
                00134686
                March 2017
                March 2017
                : 231
                : 677-685
                Article
                10.1016/j.electacta.2017.02.060
                d78f7d8c-1567-476f-b92d-d39109abb70e
                © 2017

                https://www.elsevier.com/tdm/userlicense/1.0/

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