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Self-sustained green neuromorphic interfaces

Incorporating neuromorphic electronics in bioelectronic interfaces can provide intelligent responsiveness to environments. However, the signal mismatch between the environmental stimuli and driving amplitude in neuromorphic devices has limited the functional versatility and energy sustainability. He...

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Autores principales: Fu, Tianda, Liu, Xiaomeng, Fu, Shuai, Woodard, Trevor, Gao, Hongyan, Lovley, Derek R., Yao, Jun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8184933/
https://www.ncbi.nlm.nih.gov/pubmed/34099691
http://dx.doi.org/10.1038/s41467-021-23744-2
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author Fu, Tianda
Liu, Xiaomeng
Fu, Shuai
Woodard, Trevor
Gao, Hongyan
Lovley, Derek R.
Yao, Jun
author_facet Fu, Tianda
Liu, Xiaomeng
Fu, Shuai
Woodard, Trevor
Gao, Hongyan
Lovley, Derek R.
Yao, Jun
author_sort Fu, Tianda
collection PubMed
description Incorporating neuromorphic electronics in bioelectronic interfaces can provide intelligent responsiveness to environments. However, the signal mismatch between the environmental stimuli and driving amplitude in neuromorphic devices has limited the functional versatility and energy sustainability. Here we demonstrate multifunctional, self-sustained neuromorphic interfaces by achieving signal matching at the biological level. The advances rely on the unique properties of microbially produced protein nanowires, which enable both bio-amplitude (e.g., <100 mV) signal processing and energy harvesting from ambient humidity. Integrating protein nanowire-based sensors, energy devices and memristors of bio-amplitude functions yields flexible, self-powered neuromorphic interfaces that can intelligently interpret biologically relevant stimuli for smart responses. These features, coupled with the fact that protein nanowires are a green biomaterial of potential diverse functionalities, take the interfaces a step closer to biological integration.
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spelling pubmed-81849332021-06-11 Self-sustained green neuromorphic interfaces Fu, Tianda Liu, Xiaomeng Fu, Shuai Woodard, Trevor Gao, Hongyan Lovley, Derek R. Yao, Jun Nat Commun Article Incorporating neuromorphic electronics in bioelectronic interfaces can provide intelligent responsiveness to environments. However, the signal mismatch between the environmental stimuli and driving amplitude in neuromorphic devices has limited the functional versatility and energy sustainability. Here we demonstrate multifunctional, self-sustained neuromorphic interfaces by achieving signal matching at the biological level. The advances rely on the unique properties of microbially produced protein nanowires, which enable both bio-amplitude (e.g., <100 mV) signal processing and energy harvesting from ambient humidity. Integrating protein nanowire-based sensors, energy devices and memristors of bio-amplitude functions yields flexible, self-powered neuromorphic interfaces that can intelligently interpret biologically relevant stimuli for smart responses. These features, coupled with the fact that protein nanowires are a green biomaterial of potential diverse functionalities, take the interfaces a step closer to biological integration. Nature Publishing Group UK 2021-06-07 /pmc/articles/PMC8184933/ /pubmed/34099691 http://dx.doi.org/10.1038/s41467-021-23744-2 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Fu, Tianda
Liu, Xiaomeng
Fu, Shuai
Woodard, Trevor
Gao, Hongyan
Lovley, Derek R.
Yao, Jun
Self-sustained green neuromorphic interfaces
title Self-sustained green neuromorphic interfaces
title_full Self-sustained green neuromorphic interfaces
title_fullStr Self-sustained green neuromorphic interfaces
title_full_unstemmed Self-sustained green neuromorphic interfaces
title_short Self-sustained green neuromorphic interfaces
title_sort self-sustained green neuromorphic interfaces
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8184933/
https://www.ncbi.nlm.nih.gov/pubmed/34099691
http://dx.doi.org/10.1038/s41467-021-23744-2
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