Low-Dose 3D Bonding Mapping Through "Soft" Core-Loss EELS Tomography and Unsupervised Deep Learning

Abstract: Resolving the 3D chemical configuration of beam-sensitive nanomaterials at high spatial resolution remains a persistent frontier in scanning transmission electron microscopy (STEM). The main limitation lies in the trade-off between high electron dose required for analytical signals and the large number of projections needed for tomographic reconstruction. Here, we achieve dose-efficient 3D bonding mapping of FeO/Fe$3$O$_4$ core-shell nanocubes with high resolution via electron energy loss spectroscopy (EELS). Our approach relies on two developments. First, a standardless "soft" core-loss EELS methodology exploiting Fe-M${2,3}$ edges provides ${\sim}50\times$ higher dose efficiency than conventional Fe-L${2,3}$ edges, using the latter only as a source of FeO and Fe$_3$O$_4$ standards. Second, we introduce multi-channel deep image prior with total variation regularization (DIPm-TV), an unsupervised method for spectroscopic tomography that jointly reconstructs multiple channels by exploiting spatial correlations under sparse-view and low-dose conditions. Using simulated datasets, high-quality reconstructions are obtained from as few as nine projections over $-70^\circ$ to $+70^\circ$, without HAADF-STEM signal or symmetry constraints. Applied to FeO/Fe$_3$O$_4$ nanocubes, Fe-M${2,3}$ EELS maps show improved SNR and spatial resolution, revealing a thin outer FeO shell surrounding the magnetite shell. DIPm-TV yields ${\sim}1$ nm isotropic resolution oxidation-state volumes preserving cubic morphology, recovering the outer FeO shell, and revealing a small internal void, features not accessible with conventional reconstruction methods. This work establishes a pathway for low-dose 2D and 3D analytical mapping of beam-sensitive materials using shallow core-loss edges, enabling orders-of-magnitude dose reduction while maintaining spectral fidelity and reliable 3D information.