Electron trap filling and emptying through simulations: Studying the shift of the maximum intensity position in Thermoluminescence and Linearly Modulated Optically Stimulated Luminescence curves. (April 2022) - Tsoutsoumanos, E.; Konstantinidis, P.G.; Polymeris, G.S.; Karakasidis, T.; Kitis, G.
Abstract: In the present work, the response of peak positions in Linearly Modulated Optically Stimulated Luminescence (LM-OSL) curves as a function of physical and technical parameters were investigated and compared theoretically; specifically, the time or temperature values ( t m, T m ) of their maximum intensity ( I m ). The stimulation modes of Thermoluminescence (TL) and LM-OSL differ slightly in terms of peak resemblance (geometrical structure) but differ greatly as physical phenomena, so it could be ideal to study the effects responsible for electron trap filling or trap emptying. These simulations could also extend our knowledge in Stimulated Luminescence phenomena regarding expected experimental outcomes. In the present study, four simulation experiments were conducted based on the One Trap – One Recombination center (OTOR) model for the case of equal re-trapping and recombination probabilities signifying second order kinetics. The first experiment defines the T m shifting for various heating and optical stimulation rates. The second depicts an electron trap filling process, in which dose progresses from a low value until the saturation state. In the third experiment, a trap emptying procedure was simulated via thermal bleaching (Isothermal Decay), whereas in the final one, the same trap emptying procedure was conducted via optical bleaching (Continuous wave optically stimulated luminescence) for different time spans. Generally the t m, T m shifting in trap emptying processes, is proven, according to simulations, to follow a similar behavior to the t m, T m shift as a function of heating or optical stimulation rate. Regarding trap filling, t m and T m shift to lower values as the dose increases. Highlights: Simulations by numerically integrating the OTOR model equations using Python. Calculation of the temperature and time at the maximum intensity of each curve. Study of LM-OSL components and TL glow curves versus trap population. Peak maximum position versus heating or optical stimulation rate and trap occupancy.