Electrochemical Characterization of Graphene Microelectrodes for Biological Applications
Source abstract
Abstract
Abstract Graphene is a promising material both as a coating for existing neural electrodes as well as for transparent electrodes made exclusively from graphene. We studied graphene‐based microelectrodes by investigating their recording and stimulation properties in order to evaluate their suitability for neuronal implants. In this work, we compare three different electrode material compositions. Microelectrode arrays (MEA) with an electrode size of about 700 μm2 were prepared of gold, graphene on gold, and plain graphene on glass substrate. In order to reduce polymer contamination during graphene transfer, we employed a polymer‐free transfer and lift‐off process. Impedance studies revealed a value of 2.3 MΩ at 1 kHz for plain, and 0.88 MΩ for graphene on gold. Neuronal recording experiments showed a sufficient SNR for both graphene‐based materials and a stable impedance, unaffected by surface degradation metal electrodes are known for. Stimulation measurements yielded a charge injection capacity of 0.15 mC/cm2 using biphasic pulses of 1 ms and 1 μA transparent graphene electrodes. Cyclic voltammetry revealed a large voltage range of −1.4 V to +1.6 V before water electrolysis occurs. Graphene‐coated gold microelectrodes show enhanced recording properties, whereas plain graphene electrodes might be better suited for stimulation applications.
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Research context
OpenAlex topics: Neuroscience and Neural Engineering · Conducting polymers and applications · Electrochemical sensors and biosensors
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
BioMEMS Lab University of Applied Sciences Aschaffenburg Würzburger Straße 45 63743 Aschaffenburg Germany
Department of Chemistry Eduard-Zintl Institute for Inorganic and Physical Chemistry Technische Universität Darmstadt Alarich-Weiss-Straße 12 64287 Darmstadt Germany
Funding
Neurointerface
References (27)
Show source-provided references
1. 10.1016/j.bios.2017.09.03410.1016/j.bios.2017.09.034 ↗
2. 10.3389/fneng.2014.0001510.3389/fneng.2014.00015 ↗
3. 10.1007/s11517-015-1430-410.1007/s11517-015-1430-4 ↗
4. Kim R. · Open · 2014 · 4 · 129
5. 10.1007/s00542-013-1958-x10.1007/s00542-013-1958-x ↗
6. 10.1088/1741-2560/10/1/01600910.1088/1741-2560/10/1/016009 ↗
7. 10.1039/c3cp44251a10.1039/c3cp44251a ↗
8. 10.3762/bjnano.5.19610.3762/bjnano.5.196 ↗
9. 10.1016/j.nano.2012.12.00410.1016/j.nano.2012.12.004 ↗
10. 10.1038/ncomms625810.1038/ncomms6258 ↗
11. 10.3390/bios701000110.3390/bios7010001 ↗
12. 10.1038/ncomms625910.1038/ncomms6259 ↗
13. 10.1007/s10867-015-9382-310.1007/s10867-015-9382-3 ↗
14. 10.1088/2053-1583/3/2/02400410.1088/2053-1583/3/2/024004 ↗
15. 10.1002/adhm.20160143310.1002/adhm.201601433 ↗
16. 10.3762/bjnano.8.20210.3762/bjnano.8.202 ↗
17. Brunton E. K. · Front. Neurol. Neurosci. · 2015 · 9
18. S. Negi R. Bhandari F. Solzbacher Annual International Conference of the IEEE Engineering in Medicine and Biology 2012.
19. 10.1021/nl803363710.1021/nl8033637 ↗
20. 10.1021/nl203733r10.1021/nl203733r ↗
21. 10.1021/nn203377t10.1021/nn203377t ↗
22. Moser J. · Appl. Phys. Lett. · 2007 · 91
23. 10.1016/j.physrep.2009.02.00310.1016/j.physrep.2009.02.003 ↗
24. 10.1021/nl801827v10.1021/nl801827v ↗
25. 10.1016/j.biomaterials.2010.06.01610.1016/j.biomaterials.2010.06.016 ↗
26. 10.1038/srep3352610.1038/srep33526 ↗
27. 10.1109/TBME.2002.80548710.1109/TBME.2002.805487 ↗