ArticleChemical & biomedical imaging2024
Optimal Sparse Energy Sampling for X-ray Spectro-Microscopy: Reducing the X-ray Dose and Experiment Time Using Model Order Reduction.
Article in Chemical & biomedical imaging, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed.
- Sparse X-ray spectro-tomography for high-sensitivity three-dimensional chemical imaging at the nanoscale.Nature communications · 2026Article
- Reducing acquisition time and radiation damage: data-driven subsampling for spectro-microscopy.Journal of synchrotron radiation · 2026Article
- In situ ptychographic x-ray nanotomography of temperature-controlled crystallization processes.Nature communications · 2026Article
- Multidimensional Tracking and Clustering of Electrochemical Reactions in the Positive Electrode of Lithium-Ion Batteries via Operando X‑ray Nanoscale Chemical Imaging.Chemical & biomedical imaging · 2026Article
- 3DCryoHolder: a new open access 3D printable system to store and transport silicon nitride membranes under cryogenic conditions for spectromicroscopy at low temperature.Journal of synchrotron radiation · 2025Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The application of X-ray spectro-microscopy to image changes in the chemical state in application areas such as catalysis, environmental science, or biological samples can be limited by factors such as the speed of measurement, the presence of dilute concentrations, radiation damage, and thermal drift during the measurement. We have adapted a reduced-order model approach, known as the discrete empirical interpolation method, which identifies how to optimally subsample the spectroscopic information, accounting for background variations in the signal, to provide an accurate approximation of an equivalent full spectroscopic measurement from the sampled material. This approach uses readily available prior information to guide and significantly reduce the sampling requirements impacting both the total X-ray dose and the acquisition time. The reduced-order model approach can be adapted more broadly to any spectral or spectro-microscopy measurement where a low-rank approximation can be made from prior information on the possible states of a system, and examples of the approach are presented.
Identifiers
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.