Hyperspectral X-ray Imaging with TES Detectors for Nanoscale Chemical Speciation Mapping

Carpenter, M.; Croce, Mark P.; Baker, Zachary K.; Batista, Enrique R.; Caffrey, Michael; Fontes, C. J.; Koehler, K.; Kossmann, Shannon; McIntosh, Kathryn; Rabin, Michael W.; Renck, B. W.; Wagner, G.; Wilkerson, Marianne P.; Yang, Ping; Yoho, Michael; Ullom, Joel N.; Bennett, Douglas A.; O’Neil, Galen C.; Reintsema, C. D.; Schmidt, Daniel R.; Hilton, G. C.; Swetz, Daniel S.; Becker, Daniel; Gard, Johnathon D.; Imrek, J.; Mates, J. A. B.; Morgan, Kelsey M.; Yan, Daikang; Wessels, Abigail L.; Cantor, Robin; Hall, John A.; Carver, Dale

doi:10.1007/s10909-020-02456-9

Cited by 10 publications

(4 citation statements)

References 29 publications

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“…Researchers at Los Alamos National Laboratory have reported on the development of a laboratory-scale “hyperspectral X-ray imaging” approach that has the potential to make this type of analysis routine for many applications. 197 They are building two instruments. One is based on ultra-high-resolution X-ray emission spectroscopy with large transition-edge sensor microcalorimeter arrays in a scanning electron microscope for mapping chemical information (molecular formula, phase, oxidation state, hydration) and, as the ability of the instrument to determine chemical species depends on identification of different compounds from their spectra, they are building a complementary instrument to measure high-resolution X-ray emission spectra from known bulk materials.…”

Section: Elemental Speciation Analysismentioning

confidence: 99%

Atomic Spectrometry Update: review of advances in elemental speciation

Clough

Harrington

Hill

et al. 2021

J. Anal. At. Spectrom.

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Section: Elemental Speciation Analysismentioning

confidence: 99%

Atomic Spectrometry Update: review of advances in elemental speciation

Clough

Harrington

Hill

et al. 2021

J. Anal. At. Spectrom.

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“…Unlike conventional images, HSI extends beyond spatial features, offering detailed one-dimensional spectral profiles per pixel [4]. At the same time, hyperspectral imaging has a wide range of potential in various electromagnetic radiation frequency ranges, such as X-ray, ultraviolet, visible and near-infrared, and terahertz [5][6][7][8][9]. With applications spanning agriculture, geology, ecology, and mineralogy [10][11][12][13], HSI faces challenges in classification due to its high spectral resolution and noise, potentially leading to dimensionality disaster and reduced classification accuracy, especially with limited training samples [14,15].…”

Section: Introductionmentioning

confidence: 99%

Advanced Hyperspectral Image Analysis: Superpixelwise Multiscale Adaptive T-HOSVD for 3D Feature Extraction

Dai,

Ma,

Zhang

2024

Sensors

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Hyperspectral images (HSIs) possess an inherent three-order structure, prompting increased interest in extracting 3D features. Tensor analysis and low-rank representations, notably truncated higher-order SVD (T-HOSVD), have gained prominence for this purpose. However, determining the optimal order and addressing sensitivity to changes in data distribution remain challenging. To tackle these issues, this paper introduces an unsupervised Superpixelwise Multiscale Adaptive T-HOSVD (SmaT-HOSVD) method. Leveraging superpixel segmentation, the algorithm identifies homogeneous regions, facilitating the extraction of local features to enhance spatial contextual information within the image. Subsequently, T-HOSVD is adaptively applied to the obtained superpixel blocks for feature extraction and fusion across different scales. SmaT-HOSVD harnesses superpixel blocks and low-rank representations to extract 3D features, effectively capturing both spectral and spatial information of HSIs. By integrating optimal-rank estimation and multiscale fusion strategies, it acquires more comprehensive low-rank information and mitigates sensitivity to data variations. Notably, when trained on subsets comprising 2%, 1%, and 1% of the Indian Pines, University of Pavia, and Salinas datasets, respectively, SmaT-HOSVD achieves impressive overall accuracies of 93.31%, 97.21%, and 99.25%, while maintaining excellent efficiency. Future research will explore SmaT-HOSVD’s applicability in deep-sea HSI classification and pursue additional avenues for advancing the field.

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“…In the X-ray energy range, the application fields of TES mainly include synchrotron-based beamline endstations [4][5][6][9][10][11][12], accelerators, EBIT [8,[13][14][15], X-ray astronomy [16][17][18]and electron microscopy [19], etc. The X-ray flux of the beamline stations based on synchrotron radiation and free electron laser is much higher than that of laboratory-level sources.…”

Section: Introductionmentioning

confidence: 99%

“…In X-ray astronomy, TES X-ray detectors are used in Micro-X sounding rocket experiments, and will be used in space science observation platforms such as ATHENA and HUBS satellites [16][17][18]. In the applications related with electron microscopy, TES X-ray detectors are introduced into scanning electron microscopy for elemental distribution and valence analysis with high spatial resolution [19,27,28].…”

Section: Introductionmentioning

confidence: 99%

Transition edge sensor based detector: from X-ray to $γ$-ray

Zhang¹,

Xia²,

Sun³

et al. 2022

Preprint

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The Transition Edge Sensor(TES) is extremely sensitive to the change of temperature, combined with the high-Z metal of a certain thickness, it can realize high energy resolution measurement of particles such as Xray. X-ray with energies below 10 keV have very weak penetrating ability, so only a few microns thick of gold or bismuth can guarantee a quantum efficiency higher than 70%. Therefore, the entire structure of the TES X-ray detector for this energy range can be realized with the microfabrication process. However, for X-ray or γ-ray from 10 keV to 200 keV, sub-millimeter absorber layers are required, which cannot be realized by microfabrication process. This paper first briefly introduces a set of TES X-ray detectors and their auxiliary systems, then focus on the introduction of the TES γ-ray detector, with absorber based on an sub-millimeter lead-tin alloy sphere. The detector has a quantum efficiency above 70% near 100 keV, and an energy resolution of about

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Hyperspectral X-ray Imaging with TES Detectors for Nanoscale Chemical Speciation Mapping

Cited by 10 publications

References 29 publications

Atomic Spectrometry Update: review of advances in elemental speciation

Atomic Spectrometry Update: review of advances in elemental speciation

Advanced Hyperspectral Image Analysis: Superpixelwise Multiscale Adaptive T-HOSVD for 3D Feature Extraction

Transition edge sensor based detector: from X-ray to $γ$-ray

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