Multicomponent signal unmixing from nanoheterostructures: overcoming the traditional challenges of nanoscale X-ray analysis via machine learning

David Rossouw; Pierre Burdet; Francisco de la Peña; Caterina Ducati; Benjamin R Knappett; Andrew E H Wheatley; Paul A Midgley

doi:10.1021/acs.nanolett.5b00449

Multicomponent signal unmixing from nanoheterostructures: overcoming the traditional challenges of nanoscale X-ray analysis via machine learning

Nano Lett. 2015 Apr 8;15(4):2716-20. doi: 10.1021/acs.nanolett.5b00449. Epub 2015 Mar 17.

Authors

David Rossouw¹, Pierre Burdet¹, Francisco de la Peña¹, Caterina Ducati¹, Benjamin R Knappett², Andrew E H Wheatley², Paul A Midgley¹

Affiliations

¹ †Department of Materials Science and Metallurgy, University of Cambridge, 27 Charles Babbage Road, Cambridge CB3 0FS, United Kingdom.
² ‡Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, United Kingdom.

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.

Keywords: EDX; ICA; TEM; electron microscopy; nanoparticle.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Image Interpretation, Computer-Assisted / methods*
Imaging, Three-Dimensional / methods
Machine Learning*
Magnetite Nanoparticles / chemistry*
Magnetite Nanoparticles / ultrastructure*
Materials Testing / methods
Microscopy, Electron, Transmission / methods*
Pattern Recognition, Automated / methods
X-Ray Diffraction / methods*

Substances

Magnetite Nanoparticles