Date of Completion
5-6-2017
Embargo Period
5-3-2017
Advisors
Moshe Gai, Gerald Dunne, Peter Schweitzer
Field of Study
Physics
Degree
Master of Science
Open Access
Open Access
Abstract
The Primordial Lithium problem of Big Bang Nucleosynthesis (BBN), a prediction of 7Li abundance which is considerably larger than observed, has important implications for the standard model of cosmology. Since 7Li is produced by the later decay of 7Be it is important to study the destruction of 7Be during the epoch of BBN, in order to examine possible reduction of the predicted abundance of 7Li, in particular the destruction of 7Be with neutrons. The high flux of 50 keV epithermal neutrons (1010 n/sec/cm2) produced by a Liquid Lithium (LiLiT) target at the Soreq Applied Research Accelerator Facility (SARAF) in Yavne, Israel offers opportunities for research at BBN energy. Due to the high intensity of the neutron flux at SARAF, background can be overwhelming for spectroscopic detectors.
The plastic polymer CR-39 (poly allyl diglycol carbonate - PADC, C12H18O7) was chosen as a detector that can withstand the high neutron and associated gamma-ray flux. CR-39 Nuclear Track Detectors (NTD) have been calibrated for detection of alpha-particles and protons in a high neutron flux environment. These detectors can be used to detect damage caused by ionizing radiation on the plastic through a process of chemical etching. Charged particles leave behind a trademark path of chemical bonds broken by incoming ionized radiation. After chemical etching, the broken bonds are visible under a microscope in the form of circular pits. A segmentation algorithm was developed using ImageJ/FIJI to analyze the pits and calibrate the detectors for use in the 7Be and neutron experiment at SARAF.
Recommended Citation
Kading, Emily E., "Calibration of CR-39 Nuclear Track Detectors with Alpha-Particles and Protons for a Measurement of Neutron Interactions with 7Be and the Primordial 7Li Problem" (2017). Master's Theses. 1065.
https://digitalcommons.lib.uconn.edu/gs_theses/1065
Major Advisor
Moshe Gai