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02388nam a2200373Ia 4500 |
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10.1038-s41377-022-00791-y |
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|a 20955545 (ISSN)
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|a Vertical matrix perovskite X-ray detector for effective multi-energy discrimination
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|b Springer Nature
|c 2022
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|z View Fulltext in Publisher
|u https://doi.org/10.1038/s41377-022-00791-y
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|a Multi-energy X-ray detection is sought after for a wide range of applications including medical imaging, security checking and industrial flaw inspection. Perovskite X-ray detectors are superior in terms of high sensitivity and low detection limit, which lays a foundation for multi-energy discrimination. However, the extended capability of the perovskite detector for multi-energy X-ray detection is challenging and has never been reported. Herein we report the design of vertical matrix perovskite X-ray detectors for multi-energy detection, based on the attenuation behavior of X-ray within the detector and machine learning algorithm. This platform is independent of the complex X-ray source components that constrain the energy discrimination capability. We show that the incident X-ray spectra could be accurately reconstructed from the conversion matrix and measured photocurrent response. Moreover, the detector could produce a set of images containing the density-graded information under single exposure, and locate the concealed position for all low-, medium- and high-density substances. Our findings suggest a new generation of X-ray detectors with features of multi-energy discrimination, density differentiation, and contrast-enhanced imaging. © 2022, The Author(s).
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|a Energy discriminations
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|a Energy X-rays
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|a High sensitivity
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|a High-low
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|a Imaging securities
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|a Learning algorithms
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|a Machine learning
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|a matrix
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|a Medical imaging
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|a Multi energy
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|a Perovskite
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|a Security checking
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|a X ray detectors
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|a X-ray detections
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|a X-ray detector
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|a Du, X.
|e author
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|a Niu, G.
|e author
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|a Pang, J.
|e author
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|a Tang, J.
|e author
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|a Wu, H.
|e author
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|a Zhao, S.
|e author
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|t Light: Science and Applications
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