Repository logo
Log In(current)
  1. Home
  2. Colleges & Schools
  3. Graduate School
  4. Doctoral Dissertations
  5. IMPROVED SPATIAL RESOLUTION FOR DOUBLE-SIDED STRIP DETECTORS USING LITHIUM INDIUM DISELENIDE SEMICONDUCTORS
Details

IMPROVED SPATIAL RESOLUTION FOR DOUBLE-SIDED STRIP DETECTORS USING LITHIUM INDIUM DISELENIDE SEMICONDUCTORS

Date Issued
May 1, 2023
Author(s)
Gallagher, Jake Alexander  
Advisor(s)
Eric D. Lukosi
Additional Advisor(s)
Jason P. Hayward
Jamie B. Coble
Stefan M. Spanier
Permanent URI
https://trace.tennessee.edu/handle/20.500.14382/29316
Abstract

This research focuses on the evaluation of lithium indium diselenide (LISe) semiconductors in double-sided strip detector (DSSDs) designs as an example for the potential to achieve unparalleled neutron detection efficiency, spatial resolution, and timing resolution detection. LISe semiconductors offer high neutron detection efficiency due to the ~25% atomic ratio of Lithium-6, maximizing its efficiency of ~75% with 1 mm thickness at 2.8 angstroms. Furthermore, the 4.78 MeV 𝑄-value enables high intrinsic gamma discrimination in a pixelated design (electron range). These characteristics make LISe an alternative option for neutron radiography, energy-resolved imaging, and other neutron interrogation techniques. This dissertation summarizes my current efforts to enhance LISe-based neutron imaging systems to achieve an end goal of sub-5 μm spatial resolution and sub-1 μs timing resolution. My research focuses on using MATLAB and Silvaco to simulate the expected response of a LISe DSSD. These various datasets are then trained to Machine Learning models in order to predict the neutron interaction location based upon the induced signal across multiple strip electrodes. In addition, various DSSD designs were simulated to determine the strip electrode width/pitch that optimizes the tradeoff between signal integrity and reconstruction of the neutron absorption location. The addition of electronic and statistical noise to the signal as well as varying the charge collection efficiency was also explored. The improvement upon current neutron imaging systems has the opportunity to open new avenues of research that are not possible today.

Subjects

Lithium indium disele...

neutron imaging

machine learning

neural networks

regression trees

eta-function

Disciplines
Nuclear Engineering
Degree
Doctor of Philosophy
Major
Nuclear Engineering
File(s)
Thumbnail Image
Name

Gallagher_Dissertation_complete.pdf

Size

3.56 MB

Format

Adobe PDF

Checksum (MD5)

03db3a5fdffcfaad734145f05e123467

Thumbnail Image
Name

Gallagher_Dissertation_final.docx

Size

14.46 MB

Format

Microsoft Word XML

Checksum (MD5)

440eac03a82f71f1890a1bcf0bbb60ad


University Libraries

1015 Volunteer Boulevard
Knoxville, TN 37996
865-974-4351

Map & Directions
Donate to the Libraries
  • About
  • John C. Hodges Society
  • Speaking Volumes magazine
  • Outreach
  • Directory
  • Employment
  • Policies
  • Library Intranet
University of Tennessee power T logo

The University of Tennessee, Knoxville
Knoxville, Tennessee 37996
865-974-1000

Events
A-Z
Apply
Privacy
Map
Directory
Give to UT
Accessibility

Built with DSpace-CRIS software - Extension maintained and optimized by 4Science