Methods for energy dispersive x-ray spectroscopy with photon-counting and deconvolution techniques

TL;DR

This paper introduces methods combining Bragg spectroscopy, photon counting, and deconvolution algorithms to enhance signal-to-noise ratios in energy dispersive X-ray spectroscopy, aiding material analysis under extreme conditions.

Contribution

It presents a comprehensive approach for constructing high-quality spectra from camera images using novel combination of techniques validated on synthetic and experimental data.

Findings

Enhanced SNR in X-ray spectra using proposed methods

Validated techniques on high-energy density science data

Improved spectral analysis for materials under extreme conditions

Abstract

Spectroscopic techniques are essential for studying material properties, but the small cross-sections of some methods may result in low signal-to-noise ratios (SNRs) in the collected spectra. In this article we present methods, based on combining Bragg spectroscopy with photon counting and deconvolution algorithms, which increase the SNRs, making the spectra better suited to further analysis. We aim to provide a comprehensive guide for constructing spectra from camera images. The efficacy of these methods is validated on synthetic and experimental data, the latter coming from the field of high-energy density (HED) science, where x-ray spectroscopy is essential for the understanding of materials under extreme thermodynamic conditions.