Simulation study of a highly efficient, high resolution X-ry sensor based on self-organizing aluminum oxide

TL;DR

This study uses Monte Carlo simulations to evaluate a novel aluminum oxide-based X-ray sensor design that aims to improve efficiency and resolution in X-ray imaging.

Contribution

The paper introduces a new modeling approach for AlOx matrices and assesses their imaging performance across various parameters using Monte Carlo simulations.

Findings

High quantum efficiency achieved with optimized AlOx structures

Enhanced spatial resolution demonstrated in simulations

Good image homogeneity observed across different configurations

Abstract

State of the art X-ray imaging sensors comprise a trade-off between the achievable efficiency and the spatial resolution. To overcome such limitations, the use of structured and scintillator filled aluminum oxide (AlOx) matrices has been investigated. We used Monte-Carlo (MC) X-ray simulations to determine the X-ray imaging quality of these AlOx matrices. Important factors which influence the behavior of the matrices are: filling factor (surface ratio between channels and 'closed' AlOx), channel diameter, aspect ratio, filling material etc. Therefore we modeled the porous AlOx matrix in several different ways with the MC X-ray simulation tool ROSI [1] and evaluated its properties to investigate the achievable performance at different X-ray spectra, with different filling materials (i.e. scintillators) and varying channel height and pixel readout. In this paper we focus on the quantum efficiency, the spatial resolution and image homogeneity.