Thermalization of electron-hole pairs in LaBr3, CeBr3 and CLLB: Monte Carlo simulation

PHYSICAL REVIEW MATERIALS(2024)

Cited 0|Views5
No score
Abstract
A Monte Carlo model is used to investigate electron-hole (e-h) generation created by incident gamma-ray radiation in LaB3, CeBr3, and Cs2LiLaBr6 (CLLB) scintillators. Our approach follows the detailed energy loss mechanisms and describes the microscopic structure of ionization tracks in order to address differences in the scintillation properties of these three materials. The mean energy required to create an e-h pair, W, theoretical light yield, and the spatial distribution of e-h pairs are determined. We found that W approaches constant and similar values at high incident energies for LaB3 and CLLB, suggesting that these materials should have similar light yields. However, the experimental light yield of CLLB is almost half that of LaBr3. Unlike for LaBr3, W of CeBr3 increases with increasing energy excitation and shows a nonlinear behavior in e-h creation, potentially explaining slightly lower light yield and worse energy resolution of CeBr3. Furthermore, we observed that the spatial distributions of electron-hole pairs in LaBr3 and CeBr3 are very similar, while the number of high-density e-h domains in CLLB is greater in comparison. This discrepancy could explain the lower light yield of CLLB. The thermalization model of e-h pairs showed that the longitudinal optical phonon energy has a profound effect on the thermalization time and distance of e-h pairs, leading to a much higher density of excitation in LaBr3 but a more diffuse one in CLLB. This effect leads to steeper gradients in LaBr3, resulting in varying density effects and worse proportionality, while CLLB suffers from more uniform but more pronounced quenching. The fraction of nonradiatively recombined electrons in LaBr3 and CLLB was estimated to be 30% and 45%, respectively. These results correlate well with experimental observations of the scintillation properties of these materials. The approach can be used to predict the expected properties of new materials and support further development of existing materials.
More
Translated text
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined