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Integration of synaptic phototransistors and quantum dot light-emitting diodes for visualization and recognition of UV patterns
Synaptic photodetectors exhibit photon-triggered synaptic plasticity, which thus can improve the image recognition rate by enhancing the image contrast. However, still, the visualization and recognition of invisible ultraviolet (UV) patterns are challenging, owing to intense background noise. Here,...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Association for the Advancement of Science
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9555778/ https://www.ncbi.nlm.nih.gov/pubmed/36223475 http://dx.doi.org/10.1126/sciadv.abq3101 |
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author | Seung, Hyojin Choi, Changsoon Kim, Dong Chan Kim, Ji Su Kim, Jeong Hyun Kim, Junhee Park, Soo Ik Lim, Jung Ah Yang, Jiwoong Choi, Moon Kee Hyeon, Taeghwan Kim, Dae-Hyeong |
author_facet | Seung, Hyojin Choi, Changsoon Kim, Dong Chan Kim, Ji Su Kim, Jeong Hyun Kim, Junhee Park, Soo Ik Lim, Jung Ah Yang, Jiwoong Choi, Moon Kee Hyeon, Taeghwan Kim, Dae-Hyeong |
author_sort | Seung, Hyojin |
collection | PubMed |
description | Synaptic photodetectors exhibit photon-triggered synaptic plasticity, which thus can improve the image recognition rate by enhancing the image contrast. However, still, the visualization and recognition of invisible ultraviolet (UV) patterns are challenging, owing to intense background noise. Here, inspired by all-or-none potentiation of synapse, we develop an integrated device of synaptic phototransistors (SPTrs) and quantum dot light-emitting diodes (QLEDs), facilitating noise reduction and visualization of UV patterns through on-device preprocessing. The SPTrs convert noisy UV inputs into a weighted photocurrent, which is applied to the QLEDs as a voltage input through an external current-voltage–converting circuit. The threshold switching characteristics of the QLEDs result in amplified current and visible illumination by the suprathreshold input voltage or nearly zero current and no visible illumination by the input voltage below the threshold. The preprocessing of image data with the SPTr-QLED can amplify the image contrast, which is helpful for high-accuracy image recognition. |
format | Online Article Text |
id | pubmed-9555778 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | American Association for the Advancement of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-95557782022-10-26 Integration of synaptic phototransistors and quantum dot light-emitting diodes for visualization and recognition of UV patterns Seung, Hyojin Choi, Changsoon Kim, Dong Chan Kim, Ji Su Kim, Jeong Hyun Kim, Junhee Park, Soo Ik Lim, Jung Ah Yang, Jiwoong Choi, Moon Kee Hyeon, Taeghwan Kim, Dae-Hyeong Sci Adv Physical and Materials Sciences Synaptic photodetectors exhibit photon-triggered synaptic plasticity, which thus can improve the image recognition rate by enhancing the image contrast. However, still, the visualization and recognition of invisible ultraviolet (UV) patterns are challenging, owing to intense background noise. Here, inspired by all-or-none potentiation of synapse, we develop an integrated device of synaptic phototransistors (SPTrs) and quantum dot light-emitting diodes (QLEDs), facilitating noise reduction and visualization of UV patterns through on-device preprocessing. The SPTrs convert noisy UV inputs into a weighted photocurrent, which is applied to the QLEDs as a voltage input through an external current-voltage–converting circuit. The threshold switching characteristics of the QLEDs result in amplified current and visible illumination by the suprathreshold input voltage or nearly zero current and no visible illumination by the input voltage below the threshold. The preprocessing of image data with the SPTr-QLED can amplify the image contrast, which is helpful for high-accuracy image recognition. American Association for the Advancement of Science 2022-10-12 /pmc/articles/PMC9555778/ /pubmed/36223475 http://dx.doi.org/10.1126/sciadv.abq3101 Text en Copyright © 2022 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution License 4.0 (CC BY). https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution license (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Physical and Materials Sciences Seung, Hyojin Choi, Changsoon Kim, Dong Chan Kim, Ji Su Kim, Jeong Hyun Kim, Junhee Park, Soo Ik Lim, Jung Ah Yang, Jiwoong Choi, Moon Kee Hyeon, Taeghwan Kim, Dae-Hyeong Integration of synaptic phototransistors and quantum dot light-emitting diodes for visualization and recognition of UV patterns |
title | Integration of synaptic phototransistors and quantum dot light-emitting diodes for visualization and recognition of UV patterns |
title_full | Integration of synaptic phototransistors and quantum dot light-emitting diodes for visualization and recognition of UV patterns |
title_fullStr | Integration of synaptic phototransistors and quantum dot light-emitting diodes for visualization and recognition of UV patterns |
title_full_unstemmed | Integration of synaptic phototransistors and quantum dot light-emitting diodes for visualization and recognition of UV patterns |
title_short | Integration of synaptic phototransistors and quantum dot light-emitting diodes for visualization and recognition of UV patterns |
title_sort | integration of synaptic phototransistors and quantum dot light-emitting diodes for visualization and recognition of uv patterns |
topic | Physical and Materials Sciences |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9555778/ https://www.ncbi.nlm.nih.gov/pubmed/36223475 http://dx.doi.org/10.1126/sciadv.abq3101 |
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