biostudies-literatureUnknown12(1)Li YA 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. ByScience advanceseadz0228https://www.ebi.ac.uk/biostudies/studies/S-EPMC12758516biostudies-literatureMultienergy x-ray imaging enabled by unipolar perovskite detector for intelligent substance identification.PMC12758516Yan SLiu SZhu BWei ZGao FLi YWang SHussain SLei WXue LOu XLiu CXu XZhao JfalseMultienergy x-ray imaging enabled by unipolar perovskite detector for intelligent substance identification.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. By2026-01-01T00:00:00Z2026 Jan2026-06-06T09:46:34.08Z2026-05-28T03:12:18.338ZS-EPMC127585164148171310.1126/sciadv.adz0228