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使用单像素衍射太赫兹传感器快速检测隐藏物体和缺陷。

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

作者信息

Li Jingxi, Li Xurong, Yardimci Nezih T, Hu Jingtian, Li Yuhang, Chen Junjie, Hung Yi-Chun, Jarrahi Mona, Ozcan Aydogan

机构信息

Electrical and Computer Engineering Department, University of California, Los Angeles, CA, 90095, USA.

Bioengineering Department, University of California, Los Angeles, CA, 90095, USA.

出版信息

Nat Commun. 2023 Oct 25;14(1):6791. doi: 10.1038/s41467-023-42554-2.

Abstract

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.

摘要

太赫兹波在材料中隐藏物体/缺陷的无损检测方面具有优势,因为它们能够穿透大多数光学不透明材料。然而,现有的太赫兹检测系统由于成像速度和分辨率有限,面临着吞吐量和精度的限制。此外,基于机器视觉的大像素成像系统由于数据存储、传输和处理需求而遇到瓶颈。在此,我们报告了一种衍射传感器,它使用单像素太赫兹探测器快速检测三维样品中的隐藏缺陷/物体,无需样品扫描或图像形成/处理。利用深度学习优化的衍射层,这种衍射传感器可以通过输出光谱全光学探测样品的三维结构信息,直接表明隐藏结构或缺陷的存在与否。我们使用单像素太赫兹时域光谱装置和三维打印的衍射层对该框架进行了实验验证,成功检测出硅样品内部未知的隐藏缺陷。这项技术在安全筛查、生物医学传感和工业质量控制等应用中具有重要价值。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e686/10600253/c850c2fbf611/41467_2023_42554_Fig1_HTML.jpg

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