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Chemical-sensitive graphene modulator with a memory effect for internet-of-things applications
Modern internet of things (IoTs) and ubiquitous sensor networks could potentially take advantage of chemically sensitive nanomaterials and nanostructures. However, their heterogeneous integration with other electronic modules on a networked sensor node, such as silicon-based modulators and memories,...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6444719/ https://www.ncbi.nlm.nih.gov/pubmed/31057821 http://dx.doi.org/10.1038/micronano.2016.18 |
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author | Huang, Haiyu Tao, Li Liu, Fei Ji, Li Hu, Ye Cheng, Mark Ming-Cheng Chen, Pai-Yen Akinwande, Deji |
author_facet | Huang, Haiyu Tao, Li Liu, Fei Ji, Li Hu, Ye Cheng, Mark Ming-Cheng Chen, Pai-Yen Akinwande, Deji |
author_sort | Huang, Haiyu |
collection | PubMed |
description | Modern internet of things (IoTs) and ubiquitous sensor networks could potentially take advantage of chemically sensitive nanomaterials and nanostructures. However, their heterogeneous integration with other electronic modules on a networked sensor node, such as silicon-based modulators and memories, is inherently challenging because of compatibility and integration issues. Here we report a novel paradigm for sensing modulators: a graphene field-effect transistor device that directly modulates a radio frequency (RF) electrical carrier signal when exposed to chemical agents, with a memory effect in its electrochemical history. We demonstrated the concept and implementation of this graphene-based sensing modulator through a frequency-modulation (FM) experiment conducted in a modulation cycle consisting of alternating phases of air exposure and ethanol or water treatment. In addition, we observed an analog memory effect in terms of the charge neutrality point of the graphene, V (cnp), which strongly influences the FM results, and developed a calibration method using electrochemical gate-voltage pulse sequences. This graphene-based multifunctional device shows great potential for use in a simple, low-cost, and ultracompact nanomaterial-based nodal architecture to enable continuous, real-time event-based monitoring in pervasive healthcare IoTs, ubiquitous security systems, and other chemical/molecular/gas monitoring applications. |
format | Online Article Text |
id | pubmed-6444719 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-64447192019-05-03 Chemical-sensitive graphene modulator with a memory effect for internet-of-things applications Huang, Haiyu Tao, Li Liu, Fei Ji, Li Hu, Ye Cheng, Mark Ming-Cheng Chen, Pai-Yen Akinwande, Deji Microsyst Nanoeng Article Modern internet of things (IoTs) and ubiquitous sensor networks could potentially take advantage of chemically sensitive nanomaterials and nanostructures. However, their heterogeneous integration with other electronic modules on a networked sensor node, such as silicon-based modulators and memories, is inherently challenging because of compatibility and integration issues. Here we report a novel paradigm for sensing modulators: a graphene field-effect transistor device that directly modulates a radio frequency (RF) electrical carrier signal when exposed to chemical agents, with a memory effect in its electrochemical history. We demonstrated the concept and implementation of this graphene-based sensing modulator through a frequency-modulation (FM) experiment conducted in a modulation cycle consisting of alternating phases of air exposure and ethanol or water treatment. In addition, we observed an analog memory effect in terms of the charge neutrality point of the graphene, V (cnp), which strongly influences the FM results, and developed a calibration method using electrochemical gate-voltage pulse sequences. This graphene-based multifunctional device shows great potential for use in a simple, low-cost, and ultracompact nanomaterial-based nodal architecture to enable continuous, real-time event-based monitoring in pervasive healthcare IoTs, ubiquitous security systems, and other chemical/molecular/gas monitoring applications. Nature Publishing Group 2016-05-09 /pmc/articles/PMC6444719/ /pubmed/31057821 http://dx.doi.org/10.1038/micronano.2016.18 Text en Copyright © 2016 © 2016 Institute of Electronics, Chinese Academy of Sciences http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Huang, Haiyu Tao, Li Liu, Fei Ji, Li Hu, Ye Cheng, Mark Ming-Cheng Chen, Pai-Yen Akinwande, Deji Chemical-sensitive graphene modulator with a memory effect for internet-of-things applications |
title | Chemical-sensitive graphene modulator with a memory effect for internet-of-things applications |
title_full | Chemical-sensitive graphene modulator with a memory effect for internet-of-things applications |
title_fullStr | Chemical-sensitive graphene modulator with a memory effect for internet-of-things applications |
title_full_unstemmed | Chemical-sensitive graphene modulator with a memory effect for internet-of-things applications |
title_short | Chemical-sensitive graphene modulator with a memory effect for internet-of-things applications |
title_sort | chemical-sensitive graphene modulator with a memory effect for internet-of-things applications |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6444719/ https://www.ncbi.nlm.nih.gov/pubmed/31057821 http://dx.doi.org/10.1038/micronano.2016.18 |
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