(Invited) High Catalytic Activity for Ethanol Bioelectrooxidation at Hybrid Electrocatalysts

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© 2020 ECS - The Electrochemical Society
, , Citation Adalgisa Rodrigues De Andrade et al 2020 Meet. Abstr. MA2020-01 2787 DOI 10.1149/MA2020-01512787mtgabs

2151-2043/MA2020-01/51/2787

Abstract

The use of enzymes immobilized onto the surface of electrodes as the main catalyst in biological fuel cells has been extensively reported. A biofuel cell provides a means to obtain clean, renewable energy and have great potential to be used as alternative energy source for low power devices. There still a lot of important issues in the development of these device, one of them, is to obtain the maximum power density from the fuel for this is important to immobilize a group of enzymes to perform a cascade in order to maximize the fuel oxidation.

Recently, we have concentrated our goal to the develop hybrid nanomaterials with MWCNT in order to immobilize efficiently the enzymes and organic catalyst. We will report a number of approaches to combine enzymes with a recently developed TEMPO-modified linear poly(ethylenimine) (TEMPO-LPEI) coupled with carboxylate multi-walled carbon nanotubes (MWCNT-COOH) to transform ethanol, ethylene glycol into CO2. In the case of ethanol extraction of 12 electrons per molecule at a single hybrid anode has been obtained with success. This simple methodology can replace the use of enzymatic cascade (7-8 enzymes) and may improve the application in biofuel cells.

The electrochemical response of the enzyme system (MWCNT-COOH/LPEI/OxOx) at increasing concentrations of ethanol confirms the excellent activity of these hybrid bioanodes.

To confirm complete ethanol oxidation to CO2, electrolysis of ethanol was performed for using different electrode systems hybrid systems. Product analysis allowed us to correlate the increase in current with the formation of CO2 as main product. The modification of nanomaterials to obtain a large energy output form an enzymatic system will be highlighted.

Acknowledge: FAPESP (grants # 2017/20431-7 and 2014/50945-4 ), CNPq (grant (465571/2014-0) and CAPES 001. Army Research Office MURI (W911NF-14-1-0263).

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10.1149/MA2020-01512787mtgabs