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Electrodeposition of long and well-defined gold nanotubes in polycarbonate (PC) templates is still a major concern due to pore blockage problems. In the present study, we introduce a novel method for electrodeposition of long gold nanotubes within the pores of PC templates for the first time. In order to deposit gold atoms onto the pore walls preferentially, pore walls were functionalized with a coupling agent. Short and thin Ni nanotubes were then electrodeposited at the bottom of the pores. Gold nanotubes were subsequently electrodeposited at constant potentials and low solution concentrations. The morphology of nanotubes was characterized by electron microscopy and their formation... 

Electrodeposition of gold nanowires is carried out in cyanide solution in polycarbonate templates with pore diameter of 80 nm. Electrochemical methods are utilized to characterize the gold electrodeposition and to obtain the nucleation and growth mechanism. The analysis of cyclic voltammograms shows that the electrodeposition of gold nanowires takes place under diffusion control. Current transients reveal that nucleation mechanism is instantaneous with a three-dimensional growth process. The transition-time measurements show that the gold elecrodeposition occurs as one-electron valence involved in the reaction mechanism. Charge transfer coefficient is also found to be 0.67 ± 0.01. The value... 

Development of simple yet precise sensing platforms for rapid determination of biological species and drugs is of paramount importance, not only for analysis of pharmaceutical formulations during the production stage, but also in clinical practices and medical diagnosis. In the present research, we report on the electrochemical determination of atorvastatin (ATOR) by using silver nanowires/gold-modified glassy carbon electrode (Ag NWs/Au/GCE). The modified electrode was constructed through a two-step procedure in which narrow silver nanowires synthesized via a polyol method are drop casted on a pre-modified GCE with electrodeposited gold particles. The results of XRD analysis indicated the... 

Artificial neural networks were used to predict the oxidation peaks potentials of 7 monosaccharides under linear sweep voltammetry regime. Two sets of descriptors, one based on molecular properties calculated through DFT and another based on simple geometric distributions of hydroxyl groups and asymmetric carbon atoms along molecular chains, were employed to introduce the molecules to networks. Relatively, simple networks of (3,3,1) and (3,3,3,1) structures with the number of epochs not exceeding 15 through training process were capable of correctly predicting the peaks positions with R values in the range of 0.97-0.99. © 2008 Elsevier Ltd. All rights reserved