Electrochemical performance of nanofibrous highly flexible electrodes enhanced by different structural configurations

Due to their unique physicomechanical properties, one dimensional (1D) nanostructured conductive materials offer remarkable potential as a flexible electroactive medium for developing miniaturized electronic devices such as supercapacitors, sensors and actuators. In this work, thin films composed of nanocomposite nanofibers with two different architectures, i.e. whiskered nanofibers (WNFs) and hierarchical-structured nanofibers (H-SNFs), were fabricated and their capability to serve as flexible and bendable electrodes were evaluated. The main difference of these two architectures is how the distributions of the nano-fillers (carboxylated multiwalled carbon nanotubes, CMWCNTs) through the nanofibers, i.e. the isotropic and anisotropic arrangements, lead to WNFs and H-SNFs, respectively. The percolation threshold of conduction for the H-SNFs (composed of 0.5 wt% CMWCNTs) and the WNFs (composed of 5 wt% CMWCNTs) were 0.13 S cm(-1) and 0.07 S cm(-1), respectively. Moreover, according to the electrochemical characterizations, although the WNFs had ten orders of magnitude higher nanotube content, the electroactivity and electron transfer rate of H-SNFs was considerably higher than those of WNFs, so that the cyclic voltammetric peak currents of H-SNFs was approximately 1.6 times higher than that of WNFs. As a proof-of-concept, our results indicate that the structural configuration is a major determinative factor, which can largely dictate the final electrical and electrochemical properties of the nanocomposite nanofibers. The bending durability results showed good electrochemical performance even upon 100 bending cycles with 120 bending angles (retained 93.4% and 83.3% of the initial peak currents for H-SNFs and WNFs, respectively). These two flexible nanocomposite nanofibrous structures could be promising materials for the development of flexible electrodes for biosensing to energy storage applications. (C) 2017 Elsevier Ltd. All rights reserved.