Modified fractal iron oxide magnetic nanostructure: A novel and high performance platform for redox protein immobilization, direct electrochemistry and bioelectrocatalysis application

A novel biosensing platform based on fractal-pattern of iron oxides magnetic nanostructures (FIOMNs) and mixed hemi/ad-micelle of sodium dodecyl sulfate (SDS) was designed for the magnetic immobilization of hemoglobin (Hb) at a screen printed carbon electrode (SPCE). The FIOMNs was successfully synthesized through hydrothermal approach and characterized by atomic force microscopy (AFM), scanning electron microscopy (SEM) and X-ray diffraction (XRD). In order to provide guidelines for the mixed hemi/ad-micelle formation, zeta-potential isotherms were investigated. The construction steps of the biosensor were evaluated by electrochemical impedance spectroscopy, cyclic voltammetry and Fourier transform infrared spectroscopy. Direct electron transfer of Hb incorporated into the biocomposite film was realized with a pair of quasi-reversible redox peak at the formal potential of - 0.355 V vs. Ag/AgCl attributing to heme Fe(III)/Fe(II) redox couple. The results suggested that synergistic functions regarding to the hyper-branched and multidirectional structure of FIOMNs and the dual interaction ability of mixed hemi/ad-micelle array of SDS molecules not only induce an effective electron transfer between the Hb and the underlying electrode (high heterogeneous electron transfer rate constant of 2.08 s(-1)) but also provide powerful and special microenvironment for the adsorption of the redox proteins. Furthermore, the biosensor displayed an excellent performance to the electrocatalytic reduction of H2O2 with a detection limit of 0.48 mu M and Michaelis-Menten constant (K-m) value of 44.2 mu M. The fabricated biosensor represented the features of sensitivity, disposable design, low sample volume, rapid and simple preparation step, and acceptable anti-interferences, which offer great perspectives for the screen-determination of H2O2 in real samples. (C) 2016 Elsevier B.V. All rights reserved.