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Conductively coupled flexible silicon electronic systems for chronic neural electrophysiology.

Publication ,  Journal Article
Li, J; Song, E; Chiang, C-H; Yu, KJ; Koo, J; Du, H; Zhong, Y; Hill, M; Wang, C; Zhang, J; Chen, Y; Tian, L; Zhong, Y; Fang, G; Viventi, J; Rogers, JA
Published in: Proceedings of the National Academy of Sciences of the United States of America
October 2018

Materials and structures that enable long-term, intimate coupling of flexible electronic devices to biological systems are critically important to the development of advanced biomedical implants for biological research and for clinical medicine. By comparison with simple interfaces based on arrays of passive electrodes, the active electronics in such systems provide powerful and sometimes essential levels of functionality; they also demand long-lived, perfect biofluid barriers to prevent corrosive degradation of the active materials and electrical damage to the adjacent tissues. Recent reports describe strategies that enable relevant capabilities in flexible electronic systems, but only for capacitively coupled interfaces. Here, we introduce schemes that exploit patterns of highly doped silicon nanomembranes chemically bonded to thin, thermally grown layers of SiO2 as leakage-free, chronically stable, conductively coupled interfaces. The results can naturally support high-performance, flexible silicon electronic systems capable of amplified sensing and active matrix multiplexing in biopotential recording and in stimulation via Faradaic charge injection. Systematic in vitro studies highlight key considerations in the materials science and the electrical designs for high-fidelity, chronic operation. The results provide a versatile route to biointegrated forms of flexible electronics that can incorporate the most advanced silicon device technologies with broad applications in electrical interfaces to the brain and to other organ systems.

Duke Scholars

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Published In

Proceedings of the National Academy of Sciences of the United States of America

DOI

EISSN

1091-6490

ISSN

0027-8424

Publication Date

October 2018

Volume

115

Issue

41

Start / End Page

E9542 / E9549

Related Subject Headings

  • Silicon
  • Models, Neurological
  • Electrophysiological Phenomena
  • Electrodes
 

Citation

APA
Chicago
ICMJE
MLA
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Li, J., Song, E., Chiang, C.-H., Yu, K. J., Koo, J., Du, H., … Rogers, J. A. (2018). Conductively coupled flexible silicon electronic systems for chronic neural electrophysiology. Proceedings of the National Academy of Sciences of the United States of America, 115(41), E9542–E9549. https://doi.org/10.1073/pnas.1813187115
Li, Jinghua, Enming Song, Chia-Han Chiang, Ki Jun Yu, Jahyun Koo, Haina Du, Yishan Zhong, et al. “Conductively coupled flexible silicon electronic systems for chronic neural electrophysiology.Proceedings of the National Academy of Sciences of the United States of America 115, no. 41 (October 2018): E9542–49. https://doi.org/10.1073/pnas.1813187115.
Li J, Song E, Chiang C-H, Yu KJ, Koo J, Du H, et al. Conductively coupled flexible silicon electronic systems for chronic neural electrophysiology. Proceedings of the National Academy of Sciences of the United States of America. 2018 Oct;115(41):E9542–9.
Li, Jinghua, et al. “Conductively coupled flexible silicon electronic systems for chronic neural electrophysiology.Proceedings of the National Academy of Sciences of the United States of America, vol. 115, no. 41, Oct. 2018, pp. E9542–49. Epmc, doi:10.1073/pnas.1813187115.
Li J, Song E, Chiang C-H, Yu KJ, Koo J, Du H, Zhong Y, Hill M, Wang C, Zhang J, Chen Y, Tian L, Fang G, Viventi J, Rogers JA. Conductively coupled flexible silicon electronic systems for chronic neural electrophysiology. Proceedings of the National Academy of Sciences of the United States of America. 2018 Oct;115(41):E9542–E9549.
Journal cover image

Published In

Proceedings of the National Academy of Sciences of the United States of America

DOI

EISSN

1091-6490

ISSN

0027-8424

Publication Date

October 2018

Volume

115

Issue

41

Start / End Page

E9542 / E9549

Related Subject Headings

  • Silicon
  • Models, Neurological
  • Electrophysiological Phenomena
  • Electrodes