Mean excitation energies for stopping powers in various materials composed of elements hydrogen through argon

Abstract

The basic model of Lindhard and Scharff, known as the local plasma model, is utilized to study the effects of the chemical and physical state of the medium on its stopping power. Unlike previous work with the local plasma model, in which individual electron shifts in the plasma frequency were estimated empirically, the Pines correction derived for a degenerate Fermi gas is shown herein to provide a reasonable estimate even on the atomic scale. Thus, the model is moved to a completely theoretical base requiring no empirical adjustments, adjustments characteristics of past applications. The principal remaining error is in the overestimation of the low-energy absorption properties characteristic of the plasma model in the region of the atomic discrete spectrum, although higher energy phenomena are accurately represented and even excitation-to-ionization ratios are given with fair accuracy. Mean excitation energies for covalently bonded gases and solids, ionic gases and crystals, and metals are calculated using first-order models of the bonded states for which reasonable agreement with the recently evaluated data of Seltzer and Berger is obtained. Hence the methods described herein allow reasonable estimates of mean excitation energy for any physical-chemical combination of material media for stopping power applications.

Lauriston S. Taylor Lecture on Radiation Protection and Measurements

“…Some of these theoretical models such as the MOCA14 (Wilson et al 1984; Charlton et al 1985) and PITS (Stewart et al 2002; Mainardi et al 2004) codes, consider the stochastics of ion tracks in evaluating frequency distributions, but have been limited to dealing with maximum energies of 5 MeV amu −1 and have not been extended to high atomic number and energy ions. A deterministic model of frequency distributions for total energy deposited in small volumes similar to DNA molecules from high-energy ions of interest for cancer therapy and other applications has been developed (Cucinotta and Dicello 2000).…”