Study of light collection as a function of scintillator surface roughness

Kilimchuk, I.V.; Тарасов, В. А.; Vlasova, I. D.

doi:10.1016/j.radmeas.2010.01.027

Cited by 6 publications

(3 citation statements)

References 8 publications

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“…In this context, simulation software that can precisely predict the behavior and impact of each of the components influencing the photon transport prior to detection is needed to study potential design improvements 4 . Variations in the scintillator intrinsic properties, geometry, and surface finish can strongly affect the behavior of scintillation photons at the crystal sides and consequently their detection 5–7 …”

Section: Introductionmentioning

confidence: 99%

“…4 Variations in the scintillator intrinsic properties, geometry, and surface finish can strongly affect the behavior of scintillation photons at the crystal sides and consequently their detection. [5][6][7] To perform those simulations, open-source simulation toolkits as Geant4 8 and GATE 9 can be used. In previous works, we developed a look-up-table (LUT) model of crystals reflectance computed from a 3D measurement of crystal surface to address significant deficiencies in the optical modeling capabilities of GATE.…”

Section: Introductionmentioning

confidence: 99%

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Technical Note: Standalone application to generate custom reflectance Look‐Up Table for advanced optical Monte Carlo simulation in GATE/Geant4

2021

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Purpose The need for high‐fidelity modeling of radiation detectors to perform reliable detector performance optimization using Monte Carlo simulations requires to accurately simulate the light transport in the scintillator and the light collection by the photodetector. In this work, we implement our well‐validated crystal reflectance model computed from three‐dimensional (3D) crystal surface measurement in a standalone open‐source application to allow researchers to generate fully customized crystal reflectance look‐up‐tables (LUTs) to be used in optical Monte Carlo simulation. Methods The LUTDavisModel application can be installed in a few minutes on Windows, macOS, and Linux, using 26 MB of space. MATLAB Runtime is required and is automatically installed with the application. The core algorithm has been previously validated experimentally and implemented in GATE v8.0. The standalone is divided into five panels, each of which performing a specific task: generate LUTs from a combination of surface type, scintillator, and coupling medium available in the database (such as LSO or BGO) or custom; compute LUTs with the reflectors available and custom coupling thickness; create a mixture of coupling media to account for possible defects in the optical coupling; plot precomputed LUTs for visual comparison. Tooltips and errors/warnings facilitate the navigation. The reported computational times were obtained with an Intel Core i7 MacBook Pro. Results LUTs can be generated with computational time ranging from a few minutes to several hours depending on the selected surface, sampling, and computational power. A longer time is needed when using rough surfaces and thick coupling media (hundreds of μm) due to increased photon tracking. Conclusions We developed a user‐friendly standalone application to generate LUTs that can be used inside GATE Monte Carlo simulations. It can be easily downloaded, installed, and used. Future optimizations will expand the database, decrease the computational time through greater parallelization, and include the generation of LUTs to study Cerenkov photons transport.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Technical Note: Standalone application to generate custom reflectance Look‐Up Table for advanced optical Monte Carlo simulation in GATE/Geant4

2021

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“…The most important feature of CsI:Tl scintillators is their ability to grow in columnar structure (Kim et al, 2007). This reduces the lateral light spread and promotes the directional light passing due to the internal reflection on column boundaries (Ananenko et al, 2004;Zhao et al, 2004;Kilimchuk et al, 2010;Fedorov et al, 2013).…”

Section: Introductionmentioning

confidence: 99%