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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. This paper reports 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 sensor all-optically probes 3D structural information, directly indicating the presence/absence of hidden structures or defects. The framework was experimentally validated, successfully detecting unknown hidden defects inside silicon samples. This technique is valuable for applications including security screening, biomedical sensing, and industrial quality control.
Publisher
Nature Communications
Published On
Oct 25, 2023
Authors
Jingxi Li, Xurong Li, Nezih T. Yardimci, Jingtian Hu, Yuhang Li, Junjie Chen, Yi-Chun Hung, Mona Jarrahi, Aydogan Ozcan
Tags
terahertz waves
nondestructive detection
hidden defects
deep learning
industrial quality control
3D structural information
sensor technology
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