Issue 14, 2022

Modeling ionization quenching in organic scintillators

Abstract

Recoil nuclei produce high ionization and excitation densities in organic scintillators leading to reduced light yield via ionization quenching. To improve understanding of the relationship between organic scintillator specific luminescence and the characteristics of the recoil particle, this work evaluates proton and carbon light yield data using ionization quenching models over an energy range of tens of keV to several MeV for protons and 1–5 MeV for carbon ions. Previously-measured proton and carbon light yield data were examined for a variety of commercial and novel organic scintillating media: EJ-309, a liquid with pulse shape discrimination (PSD) properties; EJ-204, a fast plastic; EJ-276, a PSD-capable plastic; and a custom organic glass scintillator developed by Sandia National Laboratories. The canonical model of Birks did not adequately describe the ionization quenching behavior. Models proposed by Yoshida et al. and Voltz et al. provided a reasonable description of the proton light yield of a variety of organic scintillators over a broad energy range, but additional work is needed to extend the models to carbon ions. The impact of stopping power data was also investigated by comparing model predictions using SRIM and PSTAR/MSTAR libraries, and the results show a significant discrepancy for carbon ions. This work enhances understanding of ionization quenching and facilitates the accurate modeling of scintillator-based neutron detection systems relevant for medical physics, nuclear security and nonproliferation, and basic science studies.

Graphical abstract: Modeling ionization quenching in organic scintillators

Supplementary files

Article information

Article type
Paper
Submitted
06 Apr. 2022
Accepted
07 Jūn. 2022
First published
16 Jūn. 2022
This article is Open Access
Creative Commons BY-NC license

Mater. Adv., 2022,3, 5871-5881

Modeling ionization quenching in organic scintillators

T. A. Laplace, B. L. Goldblum, J. A. Brown, G. LeBlanc, T. Li, J. J. Manfredi and E. Brubaker, Mater. Adv., 2022, 3, 5871 DOI: 10.1039/D2MA00388K

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