Inulinase immobilization on polyethylene glycol/polypyrrole multiwall carbon nanotubes producing a catalyst with enhanced thermal and operational stability.

This paper describes the development of a simple method for mixed non-covalent and covalent bonding of partially purified inulinase on functionalized multiwall carbon nanotubes (f-MWCNTs) with polypyrrole (PPy). The pyrrole (Py) was electrochemically polymerized on MWCNTs in order to fabricate MWCNTs/PPy nanocomposite. Two multiple forms of enzyme were bound to N-H functional groups from PPy and -COO- from activated MWCNTs to yield a stable MWCNTs/PPy/PEG immobilized preparation with increased thermal stability. Fourier transform infrared (FTIR) spectroscopy and scanning electron microscopy (SEM) were used to confirm functionalization of nanoparticles and immobilization of the enzyme. The immobilization yield of 85% and optimal enzyme load of 345 µg protein onto MWCNTs was obtained. The optimum reaction conditions and kinetic parameters were established using the UV-Vis analytical assay. The best functional performance for prepared heterogeneous catalyst has been observed at pH 3.6 and 10, and at the temperatures of 60 and 80ºC. The half-life (t 1/2) of the immobilized inulinase at 60 and 80ºC was found to be 231 and 99 min, respectively. The reusability of the immobilized formulation was evaluated based on a method in which the enzyme retained 50% of its initial activity, which occurred after the eighteenth operation cycle.

Enhanced model for determining the number of graphene layers and their distribution from X-ray diffraction data.

A model consisting of an equation that includes graphene thickness distribution is used to calculate theoretical 002 X-ray diffraction (XRD) peak intensities. An analysis was performed upon graphene samples produced by two different electrochemical procedures: electrolysis in aqueous electrolyte and electrolysis in molten salts, both using a nonstationary current regime. Herein, the model is enhanced by a partitioning of the corresponding 2θ interval, resulting in significantly improved accuracy of the results. The model curves obtained exhibit excellent fitting to the XRD intensities curves of the studied graphene samples. The employed equation parameters make it possible to calculate the j-layer graphene region coverage of the graphene samples, and hence the number of graphene layers. The results of the thorough analysis are in agreement with the calculated number of graphene layers from Raman spectra C-peak position values and indicate that the graphene samples studied are few-layered.