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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...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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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. |
format | Online Article Text |
id | pubmed-10600253 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
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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