University of Illinois Urbana-Champaign

Simultaneous fast and slow neutron detection with superheated droplet detector and real-time readout system

Liu, Yi

Content Files
LIU-DISSERTATION-2017.pdf

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https://hdl.handle.net/2142/98096

Description

Title
Simultaneous fast and slow neutron detection with superheated droplet detector and real-time readout system
Author(s)
Liu, Yi
Issue Date
2017-05-05
Director of Research (if dissertation) or Advisor (if thesis)
Sullivan, Clair Julia
Doctoral Committee Chair(s)
Sullivan, Clair Julia
Committee Member(s)
  • d'Errico, Francesco
  • Stubbins, James F.
  • Meng, Ling-Jian
Department of Study
Nuclear, Plasma, & Rad Engr
Discipline
Nuclear, Plasma, Radiolgc Engr
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Date of Ingest
2017-09-29T16:37:44Z
Keyword(s)
  • Neutron detection
  • Superheated droplet detector
  • Radiation portal monitors
  • Neutron dosimeter
  • Neutron spectrometer
Abstract
Alternative slow neutron detection technologies are desired in response to needs by homeland security and radiation safety. Superheated droplet detectors (SDD) have the potential to be used in both situations because they have many distinct characteristics, such as photon insensitivity, passive operation, tissue-equivalent composition, isotropic response, flexible size, and low cost. A neutron detection system based on SDDs is developed in this research for simultaneous detection of fast neutrons and slow neutrons. The detection system is composed of two SDDs and an imaging-readout system. One of the SDDs is doped with 3.4\% $^6$LiCl, and the other one is a regular SDD. In the imaging-readout system of the detection system, machine learning algorithms are developed for accurate bubble counting. The algorithms show a much better accuracy and precision than traditionally used algorithms.
Graduation Semester
2017-08
Type of Resource
text
Permalink
http://hdl.handle.net/2142/98096
Copyright and License Information
Copyright 2017 Yi Liu

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Graduate Theses and Dissertations at Illinois