Modeling of Signal Generation in Gamma-Ray Detectors
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AbstractGamma ray detectors are widely used devices in nuclear physics research. The GRETINA gamma ray detector signiÂ¿cantly improves upon existing technologies like Gammasphere due to its novel segmentation design, however much work is needed in order to maximize its full capabilities. In particular, there are problematic regions on the detector that could strongly beneÂ¿t from high Â¿delity computational modeling. This project will develop accurate bulk-and surface-transport models of charged carriers as well as codes for computing the electric Â¿elds in the GRETINA crystals. Moreover, we will focus our eÂ¿orts on poorly understood regions of the devices such as the passivated surface where the measured signals are highly pathological. These developments will yield a more accurate set of basis signals from which to eÂ¿ciently determine the location of gamma ray events. Ultimately, this will vastly improve the performance of these detectors. Monte Carlo models of charged carrier bulk-transport were developed during Phase I. ReÂ¿nements were also developed along with prototype codes for computing the electric Â¿eld in the entire crystal. The codes reproduce results from commercially available software. The Phase II project will extend the code to more accurately model transport in the crystal bulk, implement methods for computing surface carrier transport on problematic passivated surfaces, and extend Â¿eld calculation code to incorporate more realistic boundary conditions. The new computational infrastructure will then be used to understand the surface physics of the GRETINA detectors. Commercial Applications and other Benefits as described by the awardee: This project will enhance modeling both bulk-and surface-transport in semiconductors. Studies performed during Phase II will also be made available to the nuclear physics community via peer-reviewed journal articles and conference presentations in order to disseminate knowledge gained to the nuclear physics community.
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