In-situelectrochemical polymerization of aniline on flexible conductive substrates for supercapacitors and non-enzymatic ascorbic acid sensors.
Hui LiuYou TaoHuijuan SunTian-Xiong WangZhisheng PengJiyou JinZhongpu WangKang PengHaonan WeiYong Jun LiBao-Hang HanLianfeng SunPublished in: Nanotechnology (2021)
Polyaniline, as a kind of conductive polymer with commercial application prospects, is still under researches in its synthesis and applications. In this work, polyaniline was fabricated on flexible substrates including carbon cloths and polyethylene naphthalate byin situelectropolymerization method. The synthesized flexible electrodes were characterized by scanning electron microscopy, High resolution transmission electron microscope, atomic force microscope, Fourier transform infrared, x-ray diffraction, and x-ray photoelectron spectroscopy. Owing to the conductivity and the reversible redox property, the polyaniline/carbon cloth electrodes show excellent properties such as decent supercapacitor performance and good detection capability toward ascorbic acid. As supercapacitors, the electrodes exhibit a specific capacitance as high as 776 F g-1at a current density of 1 A g-1and a long cycle life of 20 000 times in the three-electrode system. As ascorbic acid sensors, the flexible electrodes demonstrate stable response to ascorbic acid in the range of 1-3000μM with an outstanding sensitivity (4228μA mM-1cm-2), low detection limit (1μM), and a fast response time. This work holds promise for high-performance and low-cost flexible electrodes for both supercapacitors and non-enzymatic ascorbic acid sensors, and may inspire inventions of self-powered electrochemical sensor.
Keyphrases
- electron microscopy
- reduced graphene oxide
- solid state
- low cost
- gold nanoparticles
- high resolution
- label free
- hydrogen peroxide
- carbon nanotubes
- single molecule
- loop mediated isothermal amplification
- mass spectrometry
- real time pcr
- magnetic resonance
- ionic liquid
- artificial intelligence
- high speed
- quantum dots
- current status
- deep learning
- sensitive detection
- molecularly imprinted