AI enhanced strong-field terahertz spectral detection and imaging Article Swipe
YOU?
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· 2025
· Open Access
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· DOI: https://doi.org/10.1016/j.isci.2025.113747
Terahertz (THz) waves demonstrate advantages including broad absolute bandwidth, low photon energy, and superior penetration capability, showing significant potential in nondestructive testing and spectroscopic imaging applications. However, current techniques face challenges including unknown material refractive indices, pulse signal aliasing, and time-consuming detection processes, which hinder the advancement and commercialization of THz-based nondestructive testing. This work presents a nondestructive testing system employing an enhanced 4-inch spintronic strong-field THz emitter, integrated with neural-network-assisted thickness prediction and contour detection. The system achieves micrometer-scale accuracy for ultrathin materials and rapid defect identification in large-scale samples. Experimental results demonstrate 99.8% measurement accuracy within ±8 μm for micrometer-scale samples, with submillimeter-level depth resolution for defect characterization and contour imaging. This technology demonstrates scalability and high flexibility, laying the foundation for thickness measurement of multilayer composite coatings and internal defect detection in complex materials, showing broad prospects in surface coating processing, component maintenance, and cultural heritage preservation.
Related Topics
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1016/j.isci.2025.113747
- OA Status
- gold
- References
- 28
- OpenAlex ID
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Raw OpenAlex JSON
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https://doi.org/10.1016/j.isci.2025.113747Digital Object Identifier
- Title
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AI enhanced strong-field terahertz spectral detection and imagingWork title
- Type
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articleOpenAlex work type
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-10-11Full publication date if available
- Authors
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Mingxuan Zhang, Shaojie Liu, Jiahui Li, Zehao Yang, Zejun Ren, Deyin Kong, Yang Wu, Lin Du, Peidi Yang, Xinxiong Chen, Songbo Cui, Caihua Wan, Xiaojun WuList of authors in order
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https://doi.org/10.1016/j.isci.2025.113747Publisher landing page
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://doi.org/10.1016/j.isci.2025.113747Direct OA link when available
- Cited by
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0Total citation count in OpenAlex
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28Number of works referenced by this work
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