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    Area of Science:

    • Photonics and Material Science
    • Computational Imaging
    • X-ray Optics

    Background:

    • Accurate material identification is crucial in various scientific and industrial applications.
    • Current methods for depth-resolved material analysis often require multiple measurements or complex setups.
    • Developing single-pixel, snapshot techniques for material characterization remains a significant challenge.

    Purpose of the Study:

    • To develop a novel method for snapshot, depth-resolved material identification.
    • To demonstrate the capability of a single energy-sensitive pixel for comprehensive object property recovery.
    • To validate the technique's performance at X-ray wavelengths.

    Main Methods:

    • Utilizing a coded aperture with subpixel features to modulate the energy spectrum of coherently scattered photons.
    • Employing an iterative inversion algorithm grounded in compressed sensing theory for data analysis.
    • Implementing a single, energy-sensitive pixel detector for data acquisition.

    Main Results:

    • Achieved high-fidelity object estimation with depth-resolved material identification.
    • Demonstrated successful material identification using only a single, energy-sensitive pixel.
    • Validated the method's effectiveness across various compression ratios exceeding unity.

    Conclusions:

    • The presented method offers a significant advancement in snapshot, depth-resolved material identification.
    • This technique provides a powerful, efficient approach for material characterization at X-ray wavelengths.
    • The coded aperture and compressed sensing approach enables robust object property recovery from limited data.