Abstract
We report on the development of Bragg curve spectroscopy techniques to improve fission fragment identification in the measurement of independent fission product yields. The NIFFTE collaboration’s fissionTPC detector provides ionization energy and particle tracking information from neutroninduced fission targets. A joint effort between PNNL, LLNL, LANL, and the Colorado School of Mines is investigating the ionization profiles deposited by U-235, U-238, and Pu-239 fission products in this detector, with the goal of including additional stopping power information beyond a standard 2E analysis. The aim is to improve the determination of fragment atomic and mass numbers with this information, via methods such as parametric fits and machine learning techniques.
Highlights
This talk focuses on fission product yield measurements made with the Neutron Induced Fission Fragment Tracking Experiment (NIFFTE) TPC detector
We discuss the use of dE/dx information afforded by the tracking capabilities of the NIFFTE TPC to improve fission product identification
The Neutron Induced Fission Fragment Tracking Experiment (NIFFTE) is a collaboration between seven U.S institutions to construct the “fissionTPC” time projection chamber located at the Los Alamos Neutron Science Center (LANSCE)
Summary
This talk focuses on fission product yield measurements made with the NIFFTE TPC detector. It first covers a description of the detector, provides detailed information on the application of the 2E method to measure fission product yields from a 235U target, with preliminary results. We discuss the use of dE/dx information afforded by the tracking capabilities of the NIFFTE TPC to improve fission product identification. The initial application of machine learning techniques to improve this effort is presented
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