Resumo

MARTIN, N. E.; SOFO HARO, M.  e  VALENTE, M.. COMBINED SIMULATION METHODOLOGY FOR A COMPLETE CHARACTERIZATION OF IONIZING RADIATION EFECTS IN DETECTION DEVICES. An. AFA [online]. 2023, vol.34, n.4, pp.1-1. ISSN 0327-358X.  http://dx.doi.org/10.31527/analesafa.2023.34.4.82.

Ionizing radiation detection devices have been widely used in recent years in various applications and experimental fields, such as high energy physics, nuclear physics, and medical imaging. Detailed description of their operational properties and their characterization by means of numerical modelling, as simulations, are key issue to understand the characteristics of radiation detectors in terms of efficiency, resolution and signal-to-noise ratio, since they allow optimizing parameters that will be further used. The modelling processes, as the simulations, are routinely carried out using various tools, like Monte Carlo approaches, for instance: PENELOPE, FLUKA or GEANT4 are used to study the interaction of the radiation with the detector accounting for the whole physical processes. However, transporting electron/hole pairs, as generated through the device sensor to conform the corresponding electronic signals uses tools badsed on the finite element method, such as TCAD (Technology Computer Aided Design), which are developed mainly to help the microelectronics industry to design products. Usually, modelling approaches for radiation transport and electonic signal production are not integrated, thus performing the simulation process by splitting the problem into sucessive independent phases. Within this framework, the present study proposes, implements, and reports on a novel methodology that allows combining the two approaches aimed at integrating the complete simulation, thus achieving a step-by-step integrated modelling flow to describe the interaction of ionizing radiation with the sensor along with the transport of the generated charge to the photodiodes and, finally, to the generation of electronic signals.

Palavras-chave : Monte Carlo Simulation; TCAD; Combined Methodology.

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