New model of nuclear particle tracks in dielectric minerals
- 15 May 1981
- journal article
- research article
- Published by American Physical Society (APS) in Physical Review B
- Vol. 23 (10), 5213-5229
- https://doi.org/10.1103/physrevb.23.5213
Abstract
The microscopic structure of latent tracks in silicates is analyzed using small-angle x-ray scattering methods. Latent tracks are constituted of extended defects, separated by gap zones loaded with point defects. The variation of the linear density of extended defects along the path of the incident ions cannot be scaled with functions previously used, such as the primary rate of ionization. Upon a thermal annealing, the extended defects are much more stable than point defects. These latent tracks are chemically etched and their etching rates are inferred from optical and scanning electron-microscope observations. From these combined studies of latent and etched tracks, a model for the registration of etchable tracks in silicates is developed. In this model, the extended defects dominate the chemical etching and thermal annealing behavior of etchable tracks. The marked differences observed in the sensitivity of various silicates are no longer attributed to a radiation damage mechanism, which would operate much more efficiently in specific silicates, but to the etching behavior of each mineral. Indeed, for a given incident ion, the linear density of extended defects in a given part of the ion residual range appears to be similar in all silicates. This model is used in the framework of a Monte Carlo statistical code to predict etched track-length distributions in silicates, including those relevant to partially annealed tracks. The striking agreement between these predictions and the corresponding observations strongly support our model. It enables us to discuss the most important concepts previously proposed to account for the registration of etchable tracks in silicates, and to suggest a few preliminary guidelines for improving the use of solid-state track detectors.Keywords
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