Quantitative Design of Perovskite X-Ray Flat-Panel Detectors Enabled by Numerical Parameter Optimization

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Authors: Yuhao Zhang, Zimeng Li, Xin Zhang, Xulong Pang, Yihong Qi, Xiaokun Liang, Zonghai Sheng, Dong Liang, Hairong Zheng, Mengling Xia, Yongshuai Ge, Haodi Wu
Cited by: 1
References: 42

Abstract

Metal halide perovskites have emerged as promising candidates for direct X-ray detection owing to their strong attenuation, excellent charge transport, and low-temperature processability . High X-ray absorption efficiency requires thick perovskite layers, while increased thickness simultaneously raises the probability of charge carriers being trapped by defects, leading to an inherent trade-off. Achieving an optimal balance therefore requires careful optimization of key parameters such as absorber thickness and operating electric field. However, recent studies have not systematically optimized these detection parameters. Here, we establish a simulation framework based on cascaded linear system theory to systematically optimize the performance of MAPbI3-based X-ray detectors. The model quantifies the trade-off between X-ray absorption and charge collection, identifying an optimal thickness of 460 μm and an electric-field range that maximizes sensitivity while preserving spatial resolution. Guided by the simulation, we fabricate pixelated detectors integrated with thin-film transistor backplanes. The optimized detector exhibits a high sensitivity of 6588 μC·Gyair-1·cm-2and a spatial resolution of 3.23 lp/mm at a 200 μm pixel size, in good agreement with theoretical predictions. Furthermore, the detector demonstrates high-quality two-dimensional and three-dimensional imaging capabilities, highlighting its potential for advanced medical and industrial X-ray imaging applications.

Fields of Study & Subjects

Perovskite Materials and Applications Magnetic and transport properties of perovskites and related materials Electronic and Structural Properties of Oxides

Publication details

Journal / source
IEEE Transactions on Nuclear Science
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Volume
73
Issue
6
Pages
2405–2413
Publication date
11 May 2026