Multienergy x-ray imaging enabled by unipolar perovskite detector for intelligent substance identification.
Authors
Affiliations (3)
Affiliations (3)
- School of Electronic Science and Engineering, Southeast University, Nanjing, Jiangsu, China.
- Department of Physics, Chemistry and Biology (IFM), Linköping University, Linköping, Sweden.
- State Key Laboratory of Mechanics and Control of Mechanical Structures, Key Laboratory for Intelligent Nano Materials and Devices of the Ministry of Education, Institute for Frontier Science, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu, China.
Abstract
A challenge with state-of-the-art projection x-ray imaging technologies is their limited ability to identify unknown substances. Here, we develop an intelligent multienergy x-ray imaging technique capable of precisely distinguishing different substances and labeling them with diverse colors. Our design uses a series of x-ray attenuation coefficient ratios under different x-ray energies as substance-specific markers. For this purpose, unipolar perovskite x-ray detectors are carefully engineered to resolve the x-ray energies into seven channels using a customized algorithm. Combining machine learning and a comprehensive x-ray attenuation ratio database of common materials enables accurate recognition of low-density biological tissues composed of light elements with similar atomic numbers. By transforming the intensity scale in conventional x-ray images into an attenuation coefficient ratio, our work presents a proof of concept for color-coded x-ray imaging, highlighting its potential for applications in energy-dispersive computed tomography, targeted drug delivery, quantum physics, and universe exploration.