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Monte Carlo Electromagnetic Cross Section Production Method for Low Energy Charged Particle Transport Through Single Molecules

The present state of modeling radio-induced effects at the cellular level neglects to account for the microscopic inhomogeneity of the nucleus from the non-aqueous contents by approximating the entire cellular nucleus as a homogenous medium of water. Charged particle track-structure calculations utilizing this principle of superposition are thereby neglecting to account for approximately 30% of the molecular variation within the nucleus. To truly understand what happens when biological matter is irradiated, charged particle track-structure calculations need detailed knowledge of the secondary electron cascade, resulting from interactions with not only the primary biological component – water – but also the non-aqueous contents, down to very low energies.

This paper presents developments for a novel approach, which to our knowledge has never been done before, to reducing the homogenous water approximation. The purpose of our work is to develop of a completely self-consistent computational method for predicting molecule-specific ionization, excitation, and scattering cross sections in the very low energy regime that can be applied in a condensed history Monte Carlo track-structure code. The present methodology begins with the calculation of a solution to the many-body Schrödinger equation and proceeds to use Monte Carlo methods to calculate the perturbations in the internal electron field to determine the aforementioned processes. Results are computed for molecular water in the form of linear energy loss, secondary electron energies, and ionization-to-excitation ratios and compared against the low energy predictions of the GEANT4-DNA physics package of the Geant4 simulation toolkit.

Identiferoai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/151357
Date16 December 2013
CreatorsMadsen, Jonathan R
ContributorsAkabani, Gamal, Ford, John, Perez, Lisa
Source SetsTexas A and M University
LanguageEnglish
Detected LanguageEnglish
TypeThesis, text
Formatapplication/pdf

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