Multiwalled Carbon Nanotube-N-Doped Graphene/Poly(3,4-ethylenedioxythiophene):Poly(styrenesulfonate) Nanohybrid for Electrochemical Application in Intelligent Sensors and Supercapacitors

Ting Xue; Peng Liu; Jie Zhang; Jingkun Xu; Ge Zhang; Peicong Zhou; Yingying Li; Yifu Zhu; Xinyu Lu; Yangping Wen

doi:10.1021/acsomega.0c02224

Multiwalled Carbon Nanotube-N-Doped Graphene/Poly(3,4-ethylenedioxythiophene):Poly(styrenesulfonate) Nanohybrid for Electrochemical Application in Intelligent Sensors and Supercapacitors

ACS Omega. 2020 Oct 27;5(44):28452-28462. doi: 10.1021/acsomega.0c02224. eCollection 2020 Nov 10.

Authors

Ting Xue^{1

2}, Peng Liu², Jie Zhang^{1

3}, Jingkun Xu^{1

3}, Ge Zhang³, Peicong Zhou², Yingying Li^{1

2}, Yifu Zhu^{1

2}, Xinyu Lu^{1

2}, Yangping Wen²

Affiliations

¹ School of Pharmacy, Jiangxi Science & Technology Normal University, Nanchang 330013, P. R. China.
² Institute of Functional Materials and Agricultural Applied Chemistry, Jiangxi Agricultural University, Nanchang 330045, P. R. China.
³ School of Chemistry & Chemical Engineering, Jiangxi Science & Technology Normal University, Nanchang 330013, P. R. China.

Abstract

In this study, we reported the preparation of a conducting polymeric/inorganic nanohybrid consisting of multiwalled carbon nanotubes (MWCNT), N-doped graphene (NGr), and poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS), and its electrochemical application in intelligent sensors and supercapacitors. The multilayer thin film of the PEDOT:PSS-supported MWCNT-NGr nanohybrid was prepared by a facile layer-by-layer assembly strategy. The obtained conducting polymeric/inorganic nanohybrid modified electrode displayed superior electron transfer ability and a high specific surface area, which was used for electrochemical applications in intelligent sensors and supercapacitors. Remarkably, the fabricated amaranth sensor exhibited a broad linear range of 0.05-10 μM with a limit of detection of 0.015 μM under the optimal conditions. With the help of the response surface methodology, multivariate optimization was used as a substitute for the traditional single variable optimization to reflect the complete real effects of multivariate optimization in a sensing platform. Machine learning implemented by hybrid genetic algorithm-artificial neural network was used as an intelligent analysis model to replace the traditional regression analysis model for realizing intelligent analysis and output of sensing system. The MWCNT-NGr/PEDOT:PSS modified electrode exhibited a considerable specific capacitance of 6.5 mF cm^-2 at a current density of 2.0 mA cm^-2. The proposed results provided a new thought for a nanosensing platform equipped with a supercapacitor as a self-powered electrochemical energy storage system and machine learning as an intelligent analysis and output system in the near future.