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Exploring the potential of ionic bipolar diodes for chemical neural interfaces
Linköping University, Department of Science and Technology, Physics and Electronics. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-9845-446X
2017 (English)In: Soft Matter, ISSN 1744-683X, E-ISSN 1744-6848, Vol. 13, no 44, p. 8171-8177Article in journal (Refereed) Published
Abstract [en]

Technology interfaces which can imitate the chemically specific signaling of nervous tissues are attractive for studying and developing therapies for neurological disorders. As the signaling in nervous tissue is highly spatiotemporal in nature, an interfacing technology should provide local neurotransmitter release in the millisecond range. To obtain such a speed, the neurotransmitters must be stored close to the release point, while avoiding substantial passive leakage. Here we theoretically investigate whether ionic bipolar diodes can be used for this purpose. We find that if a sufficiently large reverse potential is applied, the passive leakage can be suppressed to negligible levels due to the high local electric field within the bipolar diode. The influences of various design parameters are studied to determine the optimal design and operation. Finally, the delivery speed of the component is evaluated using time-dependent simulations, which show that the release of neurotransmitters to physiologically relevant concentrations can be achieved in less than 10 ms. Altogether, the results suggest that ionic bipolar diodes constitute a highly attractive technology for achieving high speed low leakage addressable delivery circuits for neural interfaces.

Place, publisher, year, edition, pages
ROYAL SOC CHEMISTRY , 2017. Vol. 13, no 44, p. 8171-8177
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Identifiers
URN: urn:nbn:se:liu:diva-143359DOI: 10.1039/c7sm01732dISI: 000415352100019PubMedID: 29104986OAI: oai:DiVA.org:liu-143359DiVA, id: diva2:1162800
Note

Funding Agencies|Swedish Government Strategic Research Area in Materials Science on Functional Materials at Linkoping University (Faculty Grant SFO Mat LiU) [2009 00971]

Available from: 2017-12-05 Created: 2017-12-05 Last updated: 2017-12-05

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CiteExportLink to record
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  • apa
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