Light Output-Dependent Integration Gating for Optimized Pulse Shape Discrimination in Organic Scintillators

ORAL

Abstract

The dual neutron/gamma-ray sensitivity of organic scintillators makes them suitable for a wide range of nuclear measurement applications, including nuclear nonproliferation, nuclear medicine, and fundamental physics. Pulse shape discrimination techniques enable for distinguishing interactions of different particle types and are typically implemented with simple analog techniques or digital renditions of those techniques. Many new digital techniques for pulse shape discrimination have been proposed, but few have reached wider adoption due to their complexity and computational cost. We introduce a new digital technique for pulse shape discrimination based on traditional charge comparison which uses light output-dependent integration gates to optimize neutron/gamma-ray discrimination without increasing the computational cost of pulse analysis. We assessed the quality of neutron/gamma-ray discrimination by employing this new method in EJ-309, EJ-315, and trans-stilbene organic scintillators using measured data taken with a 252Cf spontaneous fission source. We show an improved or comparable figure of merit of neutron/gamma-ray discrimination across all light outputs over the traditional charge comparison method. The average figure of merit of neutron/gamma-ray discrimination for events with light output between 0.1 MeVee and 3.0 MeVee was increased from 1.20 to 1.28, 1.38 to 1.43, 1.54 to 1.67, and 1.85 to 1.92 for two EJ-309s, an EJ-315, and a trans-stilbene detector respectively.

Publication: C. Graham, E. Todd, C. Wilson, S. Clarke, S. Pozzi, and I. Jovanovic, "Light Output-Dependent Integration Gating for Optimized Pulse Shape Discrimination," under review.

Presenters

  • Colton Graham

    University of Michigan

Authors

  • Colton Graham

    University of Michigan

  • Ethan Todd

    University of Michigan - Ann Arbor

  • Caryanne Wilson

    University of Michigan - Ann Arbor

  • Shaun D Clarke

    University of Michigan - Ann Arbor

  • Sara Pozzi

    University of Michigan

  • Igor Jovanovic

    University of Michigan