Multicomponent Signal Unmixing from Nanoheterostructures: Overcoming the Traditional Challenges of Nanoscale X-ray Analysis via Machine Learning

作者：Rossouw David^*; Burdet Pierre; de la Pena Francisco; Ducati Caterina; Knappett Benjamin R; Wheatley Andrew E H; Midgley Paul A

来源：Nano Letters, 2015, 15(4): 2716-2720.

DOI：10.1021/acs.nanolett.5b00449

• ICA
• EDX
• TEM
• electron microscopy
• nanoparticle

The chemical composition of coreshell 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.

• 出版日期2015-4