Comparison of Commercial and Lab-Made MWCNT Buckypaper: Physicochemical Properties and Bioelectrocatalytic O2 Reduction
Abstract Buckypapers have emerged as an important material for the construction of enzyme‐based electrodes and biofuel cells for energy harvesting. In this work, commercial and lab‐made buckypapers have been compared to establish their properties for future use as advanced bioelectrodes. The physical properties of the paper‐like carbon nanotube films were characterised by electron microscopy, four‐point probe conductivity, X‐ray photoelectron spectroscopy and Raman spectroscopy. The electrochemical properties were investigated by voltammetry in the absence and presence of redox probes. Bioelectrocatalytic oxygen reduction was evaluated with iron‐protoporphyrin modified buckypapers after immobilisation of bilirubin oxidase. Lab‐made buckypaper exhibited a wider potential window, lower background capacitance, and cleaner voltammetry compared to commercial buckypaper. The catalytic current of lab‐made buckypaper was 10‐fold larger due to factors which include the 10‐fold larger BET surface area, higher enzyme loading, more defective structure, and the smaller nanotube diameters. The presence of porphyrin groups enhanced the catalytic current in O2‐saturated solution up to 0.5 mA cm−2 and 1.3 mA cm−2 for commercial and lab‐made buckypaper, respectively. This work sheds new light on the effects of various physicochemical properties on the electrochemical and DET‐type bioelectrocatalytic activity of buckypapers, and promises to be important for the development of bioelectronics devices.
Références
- Titre
- Comparison of Commercial and Lab-Made MWCNT Buckypaper: Physicochemical Properties and Bioelectrocatalytic O2 Reduction
- Type de publication
- Article de revue
- Année de publication
- 2018
- Auteurs
- Chen, Xiaohong, Gross Andrew J., Giroud Fabien, Holzinger Michael, and Cosnier Serge
- Revue
- Electroanalysis
- Start Page
- in press (doir: 10.1002/elan.201800136)
- ISSN
- 10400397
Soumis le 24 mai 2018