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Analysis of ethanol in fermentation samples by a robust nanocomposite-based microbial biosensor

pmid: 22350332
A robust microbial biosensor was constructed from a bionanocomposite prepared by a direct mixing of bacterial cells of Gluconobacter oxydans and carbon nanotubes with ferricyanide employed as a mediator for enhanced sensitivity of ethanol oxidation. A successful integration of the device into flow injection analysis mode of operation provided a high sensitivity of detection of (74 ± 2.7) μA mM(-1) cm(-2), a low detection limit of 5 μM and a linear range from 10 μM up to 1 mM. A short response time of the biosensor allowed a sample throughput of 67 h(-1) at 0.3 ml min(-1). The biosensor exhibited high operational stability with a decrease in the biosensor response of 1.7% during 43 h of continuous operation. The device was used to analyse ethanol in fermentation samples with a good agreement with a HPLC method.
- Institute of Chemistry Slovakia
- Slovak Academy of Sciences Slovakia
- Institute of Chemistry Slovakia
Gluconobacter oxydans, Ethanol, Nanotubes, Carbon, Biosensing Techniques, Sensitivity and Specificity, Nanocomposites, Fermentation, Ferricyanides
Gluconobacter oxydans, Ethanol, Nanotubes, Carbon, Biosensing Techniques, Sensitivity and Specificity, Nanocomposites, Fermentation, Ferricyanides
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).21 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
