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Rapid sensing of hidden objects and defects using a single-pixel diffractive terahertz sensor

Terahertz waves offer advantages for nondestructive detection of hidden objects/defects in materials, as they can penetrate most optically-opaque materials. However, existing terahertz inspection systems face throughput and accuracy restrictions due to their limited imaging speed and resolution. Fur...

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Autores principales: Li, Jingxi, Li, Xurong, Yardimci, Nezih T., Hu, Jingtian, Li, Yuhang, Chen, Junjie, Hung, Yi-Chun, Jarrahi, Mona, Ozcan, Aydogan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10600253/
https://www.ncbi.nlm.nih.gov/pubmed/37880258
http://dx.doi.org/10.1038/s41467-023-42554-2
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author Li, Jingxi
Li, Xurong
Yardimci, Nezih T.
Hu, Jingtian
Li, Yuhang
Chen, Junjie
Hung, Yi-Chun
Jarrahi, Mona
Ozcan, Aydogan
author_facet Li, Jingxi
Li, Xurong
Yardimci, Nezih T.
Hu, Jingtian
Li, Yuhang
Chen, Junjie
Hung, Yi-Chun
Jarrahi, Mona
Ozcan, Aydogan
author_sort Li, Jingxi
collection PubMed
description Terahertz waves offer advantages for nondestructive detection of hidden objects/defects in materials, as they can penetrate most optically-opaque materials. However, existing terahertz inspection systems face throughput and accuracy restrictions due to their limited imaging speed and resolution. Furthermore, machine-vision-based systems using large-pixel-count imaging encounter bottlenecks due to their data storage, transmission and processing requirements. Here, we report a diffractive sensor that rapidly detects hidden defects/objects within a 3D sample using a single-pixel terahertz detector, eliminating sample scanning or image formation/processing. Leveraging deep-learning-optimized diffractive layers, this diffractive sensor can all-optically probe the 3D structural information of samples by outputting a spectrum, directly indicating the presence/absence of hidden structures or defects. We experimentally validated this framework using a single-pixel terahertz time-domain spectroscopy set-up and 3D-printed diffractive layers, successfully detecting unknown hidden defects inside silicon samples. This technique is valuable for applications including security screening, biomedical sensing and industrial quality control.
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spelling pubmed-106002532023-10-27 Rapid sensing of hidden objects and defects using a single-pixel diffractive terahertz sensor Li, Jingxi Li, Xurong Yardimci, Nezih T. Hu, Jingtian Li, Yuhang Chen, Junjie Hung, Yi-Chun Jarrahi, Mona Ozcan, Aydogan Nat Commun Article Terahertz waves offer advantages for nondestructive detection of hidden objects/defects in materials, as they can penetrate most optically-opaque materials. However, existing terahertz inspection systems face throughput and accuracy restrictions due to their limited imaging speed and resolution. Furthermore, machine-vision-based systems using large-pixel-count imaging encounter bottlenecks due to their data storage, transmission and processing requirements. Here, we report a diffractive sensor that rapidly detects hidden defects/objects within a 3D sample using a single-pixel terahertz detector, eliminating sample scanning or image formation/processing. Leveraging deep-learning-optimized diffractive layers, this diffractive sensor can all-optically probe the 3D structural information of samples by outputting a spectrum, directly indicating the presence/absence of hidden structures or defects. We experimentally validated this framework using a single-pixel terahertz time-domain spectroscopy set-up and 3D-printed diffractive layers, successfully detecting unknown hidden defects inside silicon samples. This technique is valuable for applications including security screening, biomedical sensing and industrial quality control. Nature Publishing Group UK 2023-10-25 /pmc/articles/PMC10600253/ /pubmed/37880258 http://dx.doi.org/10.1038/s41467-023-42554-2 Text en © The Author(s) 2023 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Li, Jingxi
Li, Xurong
Yardimci, Nezih T.
Hu, Jingtian
Li, Yuhang
Chen, Junjie
Hung, Yi-Chun
Jarrahi, Mona
Ozcan, Aydogan
Rapid sensing of hidden objects and defects using a single-pixel diffractive terahertz sensor
title Rapid sensing of hidden objects and defects using a single-pixel diffractive terahertz sensor
title_full Rapid sensing of hidden objects and defects using a single-pixel diffractive terahertz sensor
title_fullStr Rapid sensing of hidden objects and defects using a single-pixel diffractive terahertz sensor
title_full_unstemmed Rapid sensing of hidden objects and defects using a single-pixel diffractive terahertz sensor
title_short Rapid sensing of hidden objects and defects using a single-pixel diffractive terahertz sensor
title_sort rapid sensing of hidden objects and defects using a single-pixel diffractive terahertz sensor
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10600253/
https://www.ncbi.nlm.nih.gov/pubmed/37880258
http://dx.doi.org/10.1038/s41467-023-42554-2
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