Unraveling the electron transfer rates of highly crystalline carbon nanowires with surface oxides. Issue 38 (9th August 2021) - Deng, Jufeng; Liu, Chong; Madou, Marc
Abstract : In this work, we demonstrate the carbon microstructure transformation from low crystalline glassy carbon to crystalline micro-structure and unravel the electron transfer rates of highly crystalline carbon nanowires with surface oxides. Abstract : In the development of glassy carbon fiber toward graphene fiber, highly crystalline carbon wires have attracted attention. More importantly, a charge cannot be accommodated at the surface of highly oriented pyrolytic graphite as it would be in a metal. In this work, we demonstrate that enhancing the decyanation reaction rate and reducing the nanowire diameter to below the crystallite size (≲50 nm) greatly contribute to the microstructure transformation of carbon from low crystalline glassy carbon to crystalline micro-structure. Using silica surfaces to limit the shrinkage of electrospun nanofibers during oxidation and carbonization, enhances the conversion of alcohol groups to normal carbonyl groups on the surface of the carbon wires derived from PAN fibers deposited with near field electrospinning (NFES). Cyclic voltammograms (CVs) on the carbon nanowires reveal that the enhancement of alcohol groups to normal carbonyl groups slows down the rapid electron transfer on glassy carbon electrodes. Using electrochemical impedance spectroscopy (EIS), we also establish that the electron transfer on the surface of highly crystalline carbon nanowires almost completely depends on the presence of oxygen groups. The highly crystalline structure of nanoscale carbon wires with a large amount of normal carbonyl groups exhibits an ultra-low electron transfer rate (less than 1.2 μm s −1 ), showing the ability to make the charges reside on the highly crystalline carbon nanowires. The straight line in CV allows for EIS measurements at high alternating current voltages, improving upon the non-linearity of traditional electrochemical cells by overcoming the stochastic errors and the lower signal-to-noise ratio for ultra-sensitive biomolecule detection (≤25 mV). The latter could spur the development of a new generation of electrochemical cells and biomedical signal measurements.