Excited state luminescence signals from a random distribution of defects: A new Monte Carlo simulation approach for feldspar

Details

Serval ID
serval:BIB_104710048875
Type
Article: article from journal or magazin.
Collection
Publications
Title
Excited state luminescence signals from a random distribution of defects: A new Monte Carlo simulation approach for feldspar
Journal
Journal of Luminescence
Author(s)
Pagonis Vasilis, Friedrich Johannes, Discher Michael, Müller-Kirschbaum Anna, Schlosser Veronika, Kreutzer Sebastian, Chen Reuven, Schmidt Christoph
ISSN
0022-2313
Publication state
Published
Issued date
03/2019
Peer-reviewed
Oui
Volume
207
Pages
266-272
Language
english
Abstract
This paper presents Monte Carlo simulations of tunneling recombination in random distributions of defects. Simulations are carried out for four common luminescence phenomena in solids exhibiting tunneling recombination, namely continuous wave infrared stimulated luminescence (CW-IRSL), thermoluminescence (TL), isothermal thermoluminescence (iso-TL) and linearly modulated infrared stimulated luminescence (LM-IRSL). Previous modeling work has shown that these phenomena can be described by the same partial differential equation, which must be integrated numerically over two variables, the elapsed time and the donor-acceptor distance. We here present a simple and fast Monte Carlo approach which can be applied to these four phenomena, and which reproduces the solution of the partial differential equation, without the need for numerical integrations. We show that the method is also applicable to cases of truncated distributions of nearest neighbor distances, which characterize samples that underwent multiple optical or thermal pretreatments. The accuracy and precision of the Monte Carlo method are tested by comparing with experimental data from several feldspar samples.
Keywords
Monte Carlo mode,l Feldspar model, Excited state luminescence in feldspars
Web of science
Create date
17/10/2020 20:29
Last modification date
23/12/2022 11:56
Usage data