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Perovskite-Based Memristor with 50-Fold Switchable Photosensitivity for In-Sensor Computing Neural Network
In-sensor computing can simultaneously output image information and recognition results through in-situ visual signal processing, which can greatly improve the efficiency of machine vision. However, in-sensor computing is challenging due to the requirement to controllably adjust the sensor’s photose...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9268359/ https://www.ncbi.nlm.nih.gov/pubmed/35808058 http://dx.doi.org/10.3390/nano12132217 |
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author | Chen, Qilai Han, Tingting Zeng, Jianmin He, Zhilong Liu, Yulin Sun, Jinglin Tang, Minghua Zhang, Zhang Gao, Pingqi Liu, Gang |
author_facet | Chen, Qilai Han, Tingting Zeng, Jianmin He, Zhilong Liu, Yulin Sun, Jinglin Tang, Minghua Zhang, Zhang Gao, Pingqi Liu, Gang |
author_sort | Chen, Qilai |
collection | PubMed |
description | In-sensor computing can simultaneously output image information and recognition results through in-situ visual signal processing, which can greatly improve the efficiency of machine vision. However, in-sensor computing is challenging due to the requirement to controllably adjust the sensor’s photosensitivity. Herein, it is demonstrated a ternary cationic halide Cs(0.05)FA(0.81)MA(0.14) Pb(I(0.85)Br(0.15))(3) (CsFAMA) perovskite, whose External quantum efficiency (EQE) value is above 80% in the entire visible region (400–750 nm), and peak responsibility value at 750 nm reaches 0.45 A/W. In addition, the device can achieve a 50-fold enhancement of the photoresponsibility under the same illumination by adjusting the internal ion migration and readout voltage. A proof-of-concept visually enhanced neural network system is demonstrated through the switchable photosensitivity of the perovskite sensor array, which can simultaneously optimize imaging and recognition results and improve object recognition accuracy by 17% in low-light environments. |
format | Online Article Text |
id | pubmed-9268359 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-92683592022-07-09 Perovskite-Based Memristor with 50-Fold Switchable Photosensitivity for In-Sensor Computing Neural Network Chen, Qilai Han, Tingting Zeng, Jianmin He, Zhilong Liu, Yulin Sun, Jinglin Tang, Minghua Zhang, Zhang Gao, Pingqi Liu, Gang Nanomaterials (Basel) Article In-sensor computing can simultaneously output image information and recognition results through in-situ visual signal processing, which can greatly improve the efficiency of machine vision. However, in-sensor computing is challenging due to the requirement to controllably adjust the sensor’s photosensitivity. Herein, it is demonstrated a ternary cationic halide Cs(0.05)FA(0.81)MA(0.14) Pb(I(0.85)Br(0.15))(3) (CsFAMA) perovskite, whose External quantum efficiency (EQE) value is above 80% in the entire visible region (400–750 nm), and peak responsibility value at 750 nm reaches 0.45 A/W. In addition, the device can achieve a 50-fold enhancement of the photoresponsibility under the same illumination by adjusting the internal ion migration and readout voltage. A proof-of-concept visually enhanced neural network system is demonstrated through the switchable photosensitivity of the perovskite sensor array, which can simultaneously optimize imaging and recognition results and improve object recognition accuracy by 17% in low-light environments. MDPI 2022-06-28 /pmc/articles/PMC9268359/ /pubmed/35808058 http://dx.doi.org/10.3390/nano12132217 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Chen, Qilai Han, Tingting Zeng, Jianmin He, Zhilong Liu, Yulin Sun, Jinglin Tang, Minghua Zhang, Zhang Gao, Pingqi Liu, Gang Perovskite-Based Memristor with 50-Fold Switchable Photosensitivity for In-Sensor Computing Neural Network |
title | Perovskite-Based Memristor with 50-Fold Switchable Photosensitivity for In-Sensor Computing Neural Network |
title_full | Perovskite-Based Memristor with 50-Fold Switchable Photosensitivity for In-Sensor Computing Neural Network |
title_fullStr | Perovskite-Based Memristor with 50-Fold Switchable Photosensitivity for In-Sensor Computing Neural Network |
title_full_unstemmed | Perovskite-Based Memristor with 50-Fold Switchable Photosensitivity for In-Sensor Computing Neural Network |
title_short | Perovskite-Based Memristor with 50-Fold Switchable Photosensitivity for In-Sensor Computing Neural Network |
title_sort | perovskite-based memristor with 50-fold switchable photosensitivity for in-sensor computing neural network |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9268359/ https://www.ncbi.nlm.nih.gov/pubmed/35808058 http://dx.doi.org/10.3390/nano12132217 |
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