Novel Data Analysis Tool for the Evaluation of Coincidence Doppler Broadening Spectra of the Positron-Electron Annihilation Line

TL;DR

This paper introduces an open-source Python tool for analyzing Coincidence Doppler Broadening Spectroscopy data, improving elemental detection accuracy and enabling better background reduction in positron-electron annihilation studies.

Contribution

The paper presents a novel modular software solution for CDBS data analysis, including features like spectra averaging and an advanced background reduction algorithm.

Findings

Enhanced background suppression by about tenfold at high Doppler shifts.

Facilitates reliable extraction of elemental signatures from CDBS spectra.

Supports analysis of complex material compositions with improved accuracy.

Abstract

Coincidence Doppler Broadening Spectroscopy (CDBS) of the 511 keV annihilation line reveals the elemental signature at the annihilation site in matter. For this reason, CDBS enables the analysis of foreign atoms in the host matrix, vacancy-solute complexes and precipitates in solids. Due to the lack of a comprehensive program for the analysis of CDBS data we developed a modular python-based open source software solution for the reliable extraction of the annihilation line to provide so-called ratio curves highlighting the elemental signature in the spectra. In particular, the new program allows the readout and spectra averaging of multiple detector pairs. Moreover, we implemented an improved algorithm to further reduce the background by about one order of magnitude at high Doppler shifts.