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Controlling Cu Migration on Resistive Switching, Artificial Synapse, and Glucose/Saliva Detection by Using an Optimized AlO(x) Interfacial Layer in a-CO(x)-Based Conductive Bridge Random Access Memory
[Image: see text] The Cu migration is controlled by using an optimized AlO(x) interfacial layer, and effects on resistive switching performance, artificial synapse, and human saliva detection in an amorphous-oxygenated-carbon (a-CO(x))-based CBRAM platform have been investigated for the first time....
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2020
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7114759/ https://www.ncbi.nlm.nih.gov/pubmed/32258939 http://dx.doi.org/10.1021/acsomega.0c00795 |
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author | Ginnaram, Sreekanth Qiu, Jiantai Timothy Maikap, Siddheswar |
author_facet | Ginnaram, Sreekanth Qiu, Jiantai Timothy Maikap, Siddheswar |
author_sort | Ginnaram, Sreekanth |
collection | PubMed |
description | [Image: see text] The Cu migration is controlled by using an optimized AlO(x) interfacial layer, and effects on resistive switching performance, artificial synapse, and human saliva detection in an amorphous-oxygenated-carbon (a-CO(x))-based CBRAM platform have been investigated for the first time. The 4 nm-thick AlO(x) layer in the Cu/AlO(x)/a-CO(x)/TiN(x)O(y)/TiN structure shows consecutive >2000 DC switching, tight distribution of SET/RESET voltages, a long program/erase (P/E) endurance of >10(9) cycles at a low operation current of 300 μA, and artificial synaptic characteristics under a small pulse width of 100 ns. After a P/E endurance of >10(8) cycles, the Cu migration is observed by both ex situ high-resolution transmission electron microscopy and energy-dispersive X-ray spectroscopy mapping images. Furthermore, the optimized Cu/AlO(x)/a-CO(x)/TiN(x)O(y)/TiN CBRAM detects glucose with a low concentration of 1 pM, and real-time measurement of human saliva with a small sample volume of 1 μL is also detected repeatedly in vitro. This is owing to oxidation–reduction of Cu electrode, and the switching mechanism is explored. Therefore, this CBRAM device is beneficial for future artificial intelligence application. |
format | Online Article Text |
id | pubmed-7114759 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | American Chemical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-71147592020-04-03 Controlling Cu Migration on Resistive Switching, Artificial Synapse, and Glucose/Saliva Detection by Using an Optimized AlO(x) Interfacial Layer in a-CO(x)-Based Conductive Bridge Random Access Memory Ginnaram, Sreekanth Qiu, Jiantai Timothy Maikap, Siddheswar ACS Omega [Image: see text] The Cu migration is controlled by using an optimized AlO(x) interfacial layer, and effects on resistive switching performance, artificial synapse, and human saliva detection in an amorphous-oxygenated-carbon (a-CO(x))-based CBRAM platform have been investigated for the first time. The 4 nm-thick AlO(x) layer in the Cu/AlO(x)/a-CO(x)/TiN(x)O(y)/TiN structure shows consecutive >2000 DC switching, tight distribution of SET/RESET voltages, a long program/erase (P/E) endurance of >10(9) cycles at a low operation current of 300 μA, and artificial synaptic characteristics under a small pulse width of 100 ns. After a P/E endurance of >10(8) cycles, the Cu migration is observed by both ex situ high-resolution transmission electron microscopy and energy-dispersive X-ray spectroscopy mapping images. Furthermore, the optimized Cu/AlO(x)/a-CO(x)/TiN(x)O(y)/TiN CBRAM detects glucose with a low concentration of 1 pM, and real-time measurement of human saliva with a small sample volume of 1 μL is also detected repeatedly in vitro. This is owing to oxidation–reduction of Cu electrode, and the switching mechanism is explored. Therefore, this CBRAM device is beneficial for future artificial intelligence application. American Chemical Society 2020-03-17 /pmc/articles/PMC7114759/ /pubmed/32258939 http://dx.doi.org/10.1021/acsomega.0c00795 Text en Copyright © 2020 American Chemical Society This is an open access article published under an ACS AuthorChoice License (http://pubs.acs.org/page/policy/authorchoice_termsofuse.html) , which permits copying and redistribution of the article or any adaptations for non-commercial purposes. |
spellingShingle | Ginnaram, Sreekanth Qiu, Jiantai Timothy Maikap, Siddheswar Controlling Cu Migration on Resistive Switching, Artificial Synapse, and Glucose/Saliva Detection by Using an Optimized AlO(x) Interfacial Layer in a-CO(x)-Based Conductive Bridge Random Access Memory |
title | Controlling Cu Migration on Resistive Switching, Artificial
Synapse, and Glucose/Saliva Detection by Using an Optimized AlO(x) Interfacial Layer in a-CO(x)-Based Conductive Bridge Random Access Memory |
title_full | Controlling Cu Migration on Resistive Switching, Artificial
Synapse, and Glucose/Saliva Detection by Using an Optimized AlO(x) Interfacial Layer in a-CO(x)-Based Conductive Bridge Random Access Memory |
title_fullStr | Controlling Cu Migration on Resistive Switching, Artificial
Synapse, and Glucose/Saliva Detection by Using an Optimized AlO(x) Interfacial Layer in a-CO(x)-Based Conductive Bridge Random Access Memory |
title_full_unstemmed | Controlling Cu Migration on Resistive Switching, Artificial
Synapse, and Glucose/Saliva Detection by Using an Optimized AlO(x) Interfacial Layer in a-CO(x)-Based Conductive Bridge Random Access Memory |
title_short | Controlling Cu Migration on Resistive Switching, Artificial
Synapse, and Glucose/Saliva Detection by Using an Optimized AlO(x) Interfacial Layer in a-CO(x)-Based Conductive Bridge Random Access Memory |
title_sort | controlling cu migration on resistive switching, artificial
synapse, and glucose/saliva detection by using an optimized alo(x) interfacial layer in a-co(x)-based conductive bridge random access memory |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7114759/ https://www.ncbi.nlm.nih.gov/pubmed/32258939 http://dx.doi.org/10.1021/acsomega.0c00795 |
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