Abstract
Efforts to map atomic-scale chemistry at low doses with minimal noise using electron microscopes are fundamentally limited by inelastic interactions. Here, fused multi-modal electron microscopy offers high signal-to-noise ratio (SNR) recovery of material chemistry at nano- and atomic-resolution by coupling correlated information encoded within both elastic scattering (high-angle annular dark-field (HAADF)) and inelastic spectroscopic signals (electron energy loss (EELS) or energy-dispersive x-ray (EDX)). By linking these simultaneously acquired signals, or modalities, the chemical distribution within nanomaterials can be imaged at significantly lower doses with existing detector hardware. In many cases, the dose requirements can be reduced by over one order of magnitude. This high SNR recovery of chemistry is tested against simulated and experimental atomic resolution data of heterogeneous nanomaterials.
Highlights
Modern scanning transmission electron microscopes (STEM) can focus sub-angstrom electron beams on and between atoms to quantify structure and chemistry in real space from elastic and inelastic scattering processes
The chemical composition of specimens is revealed by spectroscopic techniques produced from inelastic interactions in the form of energy-dispersive X-rays (EDX)[1,2] or electron energy loss (EELS)[3,4]
We introduce fused multi-modal electron microscopy, a technique offering high signal-to-noise ratio (SNR) recovery of nanomaterial chemistry by linking correlated information encoded within both high-angle annular dark-field detector (HAADF) and EDX/EELS
Summary
Modern scanning transmission electron microscopes (STEM) can focus sub-angstrom electron beams on and between atoms to quantify structure and chemistry in real space from elastic and inelastic scattering processes. Direct interpretation of atomic structure at higher-SNR is provided by elastically scattered electrons collected in a high-angle annular dark-field detector (HAADF); this signal under-describes the chemistry[9]. Reaching the lowest doses at the highest SNR requires fusing both elastic and inelastic scattering modalities. Detector signals—such as HAADF and EDX/EELS—are analyzed separately for insight into structural, chemical, or electronic properties[10]. Data fusion, popularized in satellite imaging, goes further than correlation by linking the separate signals to reconstruct new information and improve measurement accuracy[11,12,13]. Successful data fusion designs an analytical model that faithfully represents the relationship between modalities, and yields a meaningful combination without imposing any artificial connections[14]
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