This study introduces the simulation framework THOR, which was designed to include the creation and transport of electrons and holes in pixelated semiconductors detectors used for x-ray imaging in the PENELOPE v. 2014 Monte Carlo code and its penEasy v.2015 extension. Following the simulation of radiation transport and energy deposition in the detector, the THOR code breaks down into electron-hole pair (EHP) creation, transport, trapping, and modes of detection, including simulations of energy integrating and photon counting detectors. Validation of the THOR code was conducted using the ARTEMIS code. This study shows the impact of the simulation parameters (detector geometry, photon energy, charge carrier dispersion, etc.) on the detector performance metrics. Notably, the energy cut-off for electrons and photons were found to significantly influence accuracy and computational speed, with the identification of the optimal value as 250 eV for improved computational performance without sacrificing accuracy. The ability to adjust the energy necessary to create an EHP specifically for a-Se sensors introduce a novel approach to balancing speed and accuracy effectively. Moreover, the THOR code allows the user to choose the bias direction and which charge is collected, showing the code’s adaptability across various operational scenarios and materials. For instance, the results showed that using a negative bias and collecting holes results in less spatial resolution because the charge would have to travel a longer distance to be collected. Moreover, the trapping is also a factor, since the and the probability of trapping increases with the distance traveled by the charge carrier. The inclusion or exclusion of charge trapping in simulations can significantly influence the detector efficiency, with differences up to 60%. Analysis of physical parameters such as photon energy, detector thickness, composition, and applied electric field provides insights into their effects on detector performance metrics. Understanding these effects is essential for optimizing imaging systems for specific applications, thereby advancing diagnostic capabilities and patient care in medical imaging. In summary, this study offers a comprehensive understanding of detector behavior and simulation optimization, aiming to enhance imaging techniques.
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