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Programmable black phosphorus image sensor for broadband optoelectronic edge computing
Image sensors with internal computing capability enable in-sensor computing that can significantly reduce the communication latency and power consumption for machine vision in distributed systems and robotics. Two-dimensional semiconductors have many advantages in realizing such intelligent vision s...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8933397/ https://www.ncbi.nlm.nih.gov/pubmed/35304489 http://dx.doi.org/10.1038/s41467-022-29171-1 |
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author | Lee, Seokhyeong Peng, Ruoming Wu, Changming Li, Mo |
author_facet | Lee, Seokhyeong Peng, Ruoming Wu, Changming Li, Mo |
author_sort | Lee, Seokhyeong |
collection | PubMed |
description | Image sensors with internal computing capability enable in-sensor computing that can significantly reduce the communication latency and power consumption for machine vision in distributed systems and robotics. Two-dimensional semiconductors have many advantages in realizing such intelligent vision sensors because of their tunable electrical and optical properties and amenability for heterogeneous integration. Here, we report a multifunctional infrared image sensor based on an array of black phosphorous programmable phototransistors (bP-PPT). By controlling the stored charges in the gate dielectric layers electrically and optically, the bP-PPT’s electrical conductance and photoresponsivity can be locally or remotely programmed with 5-bit precision to implement an in-sensor convolutional neural network (CNN). The sensor array can receive optical images transmitted over a broad spectral range in the infrared and perform inference computation to process and recognize the images with 92% accuracy. The demonstrated bP image sensor array can be scaled up to build a more complex vision-sensory neural network, which will find many promising applications for distributed and remote multispectral sensing. |
format | Online Article Text |
id | pubmed-8933397 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-89333972022-04-01 Programmable black phosphorus image sensor for broadband optoelectronic edge computing Lee, Seokhyeong Peng, Ruoming Wu, Changming Li, Mo Nat Commun Article Image sensors with internal computing capability enable in-sensor computing that can significantly reduce the communication latency and power consumption for machine vision in distributed systems and robotics. Two-dimensional semiconductors have many advantages in realizing such intelligent vision sensors because of their tunable electrical and optical properties and amenability for heterogeneous integration. Here, we report a multifunctional infrared image sensor based on an array of black phosphorous programmable phototransistors (bP-PPT). By controlling the stored charges in the gate dielectric layers electrically and optically, the bP-PPT’s electrical conductance and photoresponsivity can be locally or remotely programmed with 5-bit precision to implement an in-sensor convolutional neural network (CNN). The sensor array can receive optical images transmitted over a broad spectral range in the infrared and perform inference computation to process and recognize the images with 92% accuracy. The demonstrated bP image sensor array can be scaled up to build a more complex vision-sensory neural network, which will find many promising applications for distributed and remote multispectral sensing. Nature Publishing Group UK 2022-03-18 /pmc/articles/PMC8933397/ /pubmed/35304489 http://dx.doi.org/10.1038/s41467-022-29171-1 Text en © The Author(s) 2022 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 Lee, Seokhyeong Peng, Ruoming Wu, Changming Li, Mo Programmable black phosphorus image sensor for broadband optoelectronic edge computing |
title | Programmable black phosphorus image sensor for broadband optoelectronic edge computing |
title_full | Programmable black phosphorus image sensor for broadband optoelectronic edge computing |
title_fullStr | Programmable black phosphorus image sensor for broadband optoelectronic edge computing |
title_full_unstemmed | Programmable black phosphorus image sensor for broadband optoelectronic edge computing |
title_short | Programmable black phosphorus image sensor for broadband optoelectronic edge computing |
title_sort | programmable black phosphorus image sensor for broadband optoelectronic edge computing |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8933397/ https://www.ncbi.nlm.nih.gov/pubmed/35304489 http://dx.doi.org/10.1038/s41467-022-29171-1 |
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