Abstract
The hyperspectral X-ray imaging has long been sought in various fields from material analysis to medical diagnosis. Here we propose a semiconductor detector structure to realize multi-energy imaging at potentially low cost. The device is designed based on the dramatically energy-dependent attenuation of X-ray in solids. An array or a two-/three-dimensional matrix of semiconductor cells is used to map the X-ray intensity along its trajectory. The X-ray spectrum could be extracted from a Laplace like transform or a regression via supervised machine learning. We conceptually demonstrated an energy-resolved X-ray detection with a regular silicon CMOS camera and a dummy sample of copper wires on top of an aluminum flake. The experiment provides energy-resolved X-ray image of the sample. The demonstration shows an energy resolution of less than 10 keV. We concluded that the proposed edge-on structure is potentially useful as energy-resolved high efficiency low-cost X-ray detectors.
Published Version
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