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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...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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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. |
format | Online Article Text |
id | pubmed-8184933 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
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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