Abstract
The chemical composition of core–shell nanoparticle clusters have been determined through principal component analysis (PCA) and independent component analysis (ICA) of an energy-dispersive X-ray (EDX) spectrum image (SI) acquired in a scanning transmission electron microscope (STEM). The method blindly decomposes the SI into three components, which are found to accurately represent the isolated and unmixed X-ray signals originating from the supporting carbon film, the shell, and the bimetallic core. The composition of the latter is verified by and is in excellent agreement with the separate quantification of bare bimetallic seed nanoparticles.
Highlights
The transmission electron microscope (TEM) is a popular analytical tool for nanoscale characterization due to its high flexibility and capacity to perform spectroscopy at high spatial resolution.[1]
In electron energy-loss spectroscopy (EELS), blind source separation (BSS) methods such as independent component analysis[4] (ICA) and non-negative matrix factorization[5] have been applied to the separation of components from a mixture.[6−9] In principle, the same approach could be taken for energy-dispersive X-ray (EDX) spectrum image (SI) analysis, as has been demonstrated previously.[10,11]
We apply ICA to EDX spectrum images of core−shell nanostructures to recover the composition of the buried cores, and we verify the result by the separate quantification of bare bimetallic seed particles
Summary
The transmission electron microscope (TEM) is a popular analytical tool for nanoscale characterization due to its high flexibility and capacity to perform spectroscopy at high spatial resolution.[1]. Heterogeneous volumes remain challenging to characterize by TEM techniques in regions where there is a spatial overlap of different phases within the beam path, such as a second phase precipitate embedded inside a matrix. In electron energy-loss spectroscopy (EELS), blind source separation (BSS) methods such as independent component analysis[4] (ICA) and non-negative matrix factorization[5] have been applied to the separation of components from a mixture.[6−9] In principle, the same approach could be taken for EDX spectrum image (SI) analysis, as has been demonstrated previously.[10,11] in EELS, the energy loss near edge structure (ELNES) can be used to verify the accuracy of the decomposition,[6] in EDX the lower energy resolution prevents a similar corroboration method. We apply ICA to EDX spectrum images of core−shell nanostructures to recover the composition of the buried cores, and we verify the result by the separate quantification of bare bimetallic seed particles
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