Sparse X-ray Spectro-Tomography for High-Sensitivity Three-Dimensional Chemical Imaging at the Nanoscale

Achieving three-dimensional (3D) chemical imaging with scanning x-ray microscopy is often hindered by the prohibitively long acquisition time. In this work, we develop a method that drastically reduces the data requirement by two orders of magnitude, making such measurement practically feasible. This is accomplished through sparse and stochastic energy sampling combined with a joint spectral-tomographic reconstruction algorithm. Using this approach, we reveal the reduced oxidation state of Co on the surface of a cycled lithium-ion battery particle and its correlation with the depletion of Mn in 3D. This technique enables comprehensive 3D material characterization with high sensitivity and multimodality, opening opportunities in various scientific and technological fields where volumetric chemical information at the nanoscale is essential.