Interpretation of Stark broadening measurements on a spatially integrated plasma spectral line★
LAPLACE, Université de Toulouse, UMR 5213 CNRS, INPT, UPS, Toulouse, France
* e-mail: email@example.com
Accepted: 22 November 2022
Published online: 16 December 2022
In thermal plasma spectroscopy, Stark broadening measurement of hydrogen spectral lines is considered to be a good and reliable measurement for electron density. Unlike intensity based measurements, Stark broadening measurements can pose a problem of interpretation when the light collected is the result of a spatial integration. Indeed, when assuming no self-absorption of the emission lines, intensities simply add up but broadenings do not. In order to better understand the results of Stark broadening measurements on our thermal plasma which has an unneglectable thickness, a Python code has been developed based on local thermodynamic equilibrium (LTE) assumption and calculated plasma composition and properties. This code generates a simulated pseudo experimental (PE) Hα spectral line resulting from an integration over the plasma thickness in a selected direction for a given temperature profile. The electron density was obtained using the Stark broadening of the PE spectral line for different temperature profiles. It resulted that this measurement is governed by the maximum electron density profile up until the temperature maximum exceeds that of the maximum electron density. The electron density obtained by broadening measurement is 60–75% of the maximum electron density.
The present article is published after the retraction of the paper https://doi.org/10.1051/epjap/2022220008 after the authors detected an error in the numerical determination of the PE spectral line. All errors have been corrected. The corrections in respect to the retracted paper can be found highlighted in yellow in the Supplementary material at: https://www.epjap.org/10.1051/epjap/2022220263/olm.
© J. Thouin et al., Published by EDP Sciences, 2022
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.