Issue 24, 2023

In situ quantitative polymerization of dopamine on dual functional carbon nanotubes as high stability and rate capacity anodes for potassium ion storage

Abstract

Polydopamine (PDA) as an anode of potassium ion batteries (PIBs) has received a lot of attention due to its convenient preparation, environment friendliness, and low cost. However, due to the low conductivity of organic polydopamine, the active substance can easily dissolve in the cycle process, which leads to a low rate performance and short cycle life of PIBs. Here, dopamine was quantitatively polymerized onto the surface of a carbon-intertwined network of carbon nanotubes (CNTs). By means of density functional theory calculation and electrochemical measurement, the adsorption/desorption of potassium ions by oxygen-containing and nitro-containing functional groups in PDA and its promotion by CNTs are revealed. The π–π superposition effect between dopamine and CNTs effectively alleviates the dissolution of PDA during the cycle. A combination of PDA and CNTs could resolve low conductivity issues and provide excellent battery cycle performance. Results show that PDA@CNT-10 exhibits a high reversible capacity (223 mA h g−1, 200 cycles at 0.2 A g−1) and a long cycle life (151 mA h g−1, 3000 cycles at 1 A g−1). When first used as an organo-potassium hybrid capacitor assembled from the anode of the battery and activated carbon as the cathode, it can provide a high reversible capacity (76 mA h g−1, 2000 cycles at 2 A g−1), which promotes the potential application of PIBs in the future.

Graphical abstract: In situ quantitative polymerization of dopamine on dual functional carbon nanotubes as high stability and rate capacity anodes for potassium ion storage

Supplementary files

Article information

Article type
Paper
Submitted
13 Apr 2023
Accepted
15 May 2023
First published
16 May 2023

Nanoscale, 2023,15, 10330-10341

In situ quantitative polymerization of dopamine on dual functional carbon nanotubes as high stability and rate capacity anodes for potassium ion storage

Y. Fu, B. Hu, G. Ma and M. Zhang, Nanoscale, 2023, 15, 10330 DOI: 10.1039/D3NR01701J

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