GPU-accelerated CZT detector simulation with charge build-up effects

被引:1
|
作者
Delcourt, A. [1 ]
Montemont, G. [1 ]
机构
[1] CEA Leti, 17 Ave Martyrs, Grenoble, France
关键词
Detector modelling and simulations II (electric fields; charge transport; multiplication and induction; pulse formation; electron emission; etc); Gamma detectors (scintillators; CZT; HPGe; HgI etc); Simulation methods and programs; Solid state detectors;
D O I
10.1088/1748-0221/18/02/P02005
中图分类号
TH7 [仪器、仪表];
学科分类号
0804 ; 080401 ; 081102 ;
摘要
The simulation of semiconductor detectors is a key tool for developping and studying their behavior. In general, simulations of CZT detectors assume the crystal to be perfect, meaning that its properties are uniform. However, structural defects appearing in the crystal during growth modify these properties. Moreover, dynamic phenomena like polarization can appear. In particular, the electric field inside the detector can be disturbed by bulk charges, which creates uncertainties on measurement of incident photon energy and on interaction position estimated by sub-pixel positioning.One of the main issues of a simulation considering these non-uniformities is its complexity, especially if multiple or evolving electric field distributions have to be considered. Hence, we have de-veloped a model accepting electric field modifications and allowing to observe quickly the detector's response modifications with the electric field. We leveraged GPU to address such computational bur-den. Indeed, we can afford to consider more complex simulations as the computation time is reduced.In this study, we introduced different types of spatial defects which may be found in real CZT crystals (point-like, planar, etc.) to observe quickly and easily their impact on the detector's measurement, on both spatial and spectral response.
引用
收藏
页数:12
相关论文
共 50 条
  • [31] Space Charge Build-Up in Tubular Channel Ferroelectrets
    Nepal, Neerajan
    Mellinger, Axel
    Pisani Altafim, Ruy Alberto
    2016 IEEE CONFERENCE ON ELECTRICAL INSULATION AND DIELECTRIC PHENOMENA (IEEE CEIDP), 2016, : 388 - 391
  • [32] Web-based, GPU-accelerated, Monte Carlo simulation and visualization of indirect radiation imaging detector performance
    Dong, Han
    Sharma, Diksha
    Badano, Aldo
    MEDICAL PHYSICS, 2014, 41 (12)
  • [33] Analyzing the early structural build-up of accelerated cement pastes
    Dorn, Tobias
    Hirsch, Tamino
    Stephan, Dietmar
    MATERIALS AND STRUCTURES, 2021, 54 (02)
  • [34] Analyzing the early structural build-up of accelerated cement pastes
    Tobias Dorn
    Tamino Hirsch
    Dietmar Stephan
    Materials and Structures, 2021, 54
  • [35] GPU-accelerated artificial neural network potential for molecular dynamics simulation
    Zhang, Meng
    Hibi, Koki
    Inoue, Junya
    COMPUTER PHYSICS COMMUNICATIONS, 2023, 285
  • [36] A GPU-ACCELERATED MULTIPHASE COMPUTATIONAL TOOL FOR ASTEROID FRAGMENTATION/PULVERIZATION SIMULATION
    Zimmerman, Ben J.
    Wie, Bong
    SPACEFLIGHT MECHANICS 2016, PTS I-IV, 2016, 158 : 3575 - 3591
  • [37] GPU-Accelerated Sparse LU Factorization for Circuit Simulation with Performance Modeling
    Chen, Xiaoming
    Ren, Ling
    Wang, Yu
    Yang, Huazhong
    IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, 2015, 26 (03) : 786 - 795
  • [38] Method for scalable and performant GPU-accelerated simulation of multiphase compressible flow
    Radhakrishnan, Anand
    Le Berre, Henry
    Wilfong, Benjamin
    Spratt, Jean-Sebastien
    Rodriguez Jr, Mauro
    Colonius, Tim
    Bryngelson, Spencer H.
    COMPUTER PHYSICS COMMUNICATIONS, 2024, 302
  • [39] GPU-accelerated transient lattice Boltzmann simulation of bubble column reactors
    Shu, Shuli
    Zhang, Jingchang
    Yang, Ning
    CHEMICAL ENGINEERING SCIENCE, 2020, 214
  • [40] GPU-accelerated direct numerical simulation of Burgers equation by CUDA Fortran
    Satake, Shin-ichi
    Yoshimori, Hajime
    THMT-12. PROCEEDINGS OF THE SEVENTH INTERNATIONAL SYMPOSIUM ON TURBULENCE, HEAT AND MASS TRANSFER, 2012, : 2192 - 2202