Graduation Semester and Year

Summer 2025

Language

English

Document Type

Thesis

Degree Name

Master of Science in Physics

Department

Physics

First Advisor

Alexander H. Weiss

Second Advisor

Varghese A. Chirayath

Third Advisor

Ali R. Koymen

Abstract

Depth resolved defect and chemical characterization studies using positron annihilation spectroscopy depend on the ability to estimate the fraction of positrons annihilating at surface, in the bulk, at defects or as Positronium. The depth resolution is limited by the implantation profile of the energetic positrons and the diffusion of the thermalized positrons. Here we implement a random walk simulation as described in S. Eichler et al. [1] to track the monoenergetic positrons implanted into multilayer graphene on Cu. For our simulations the implantation depths were sampled from a Makhovian distribution that has been shown to accurately represent the implantation profile of the positrons in various materials. We assume that the positrons are at thermal energies at the implantation depth and start their random walk with a mean velocity considering a Maxwell Boltzmann distribution. The step size or the hop length was sampled from an exponential distribution with a mean diffusion length that was calculated using positron diffusion coefficient taken from literature. The diffusing positrons may reposition to the surface and trap or may annihilate in the bulk. Annihilation fractions for each channel are obtained by comparing the time spent in bulk regions with their respective lifetimes. The simulated energy dependent annihilation fractions from 20 eV to 20 keV are III compared with the surface and bulk fractions reported by H. Mahdy et al. [2] for multilayer graphene on Cu. This framework therefore provides a quantitative tool for validating diffusion models in materials with multilayers, and interfaces using a monoenergetic positron beam.

Keywords

Positron Diffusion, Random Walk Diffusion, Surface Trapping

Disciplines

Condensed Matter Physics | Physics

License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

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