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Cited by 568

The DOI matches its Crossref record; 17 of the 17 references it cites were found in a registry or an index.

Organic Bioelectronics: Bridging the Signaling Gap between Biology and Technology

Open access
Simon, Daniel T., Gabrielsson, Erik O., Tybrandt, Klas, Berggren, Magnus·2016·Chemical Reviews

Abstract

The electronics surrounding us in our daily lives rely almost exclusively on electrons as the dominant charge carrier. In stark contrast, biological systems rarely use electrons but rather use ions and molecules of varying size. Due to the unique combination of both electronic and ionic/molecular conductivity in conducting and semiconducting organic polymers and small molecules, these materials have emerged in recent decades as excellent tools for translating signals between these two realms and, therefore, providing a means to effectively interface biology with conventional electronics-thus, the field of organic bioelectronics. Today, organic bioelectronics defines a generic platform with unprecedented biological recording and regulation tools and is maturing toward applications ranging from life sciences to the clinic. In this Review, we introduce the field, from its early breakthroughs to its current results and future challenges.

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Crossref · 10.1021/acs.chemrev.6b00146

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Metadata

Authors
Simon, D. T., Gabrielsson, E. O., Tybrandt, K., & Berggren, M.
Venue
Chemical Reviews
Published
2016-07-01
Volume
116
Issue
21
Pages
13009-13041
ISSN
  • 0009-2665 (ISSN-L)
  • 1520-6890
OpenAlex
W2464811097
Cited by
568
References
17
FWCI
9.28
Type
journal article
Language
en
Open access
hybrid

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CoChat. (2026). Citation check: Organic Bioelectronics: Bridging the Signaling Gap between Biology and Technology. https://app.cochat.ai/papers/10.1021/acs.chemrev.6b00146
The paper
Simon, D. T., Gabrielsson, E. O., Tybrandt, K., & Berggren, M. (2016). Organic Bioelectronics: Bridging the Signaling Gap between Biology and Technology. Chemical Reviews. https://doi.org/10.1021/acs.chemrev.6b00146

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.