Back to Search
Start Over
Multicomponent Signal Unmixing from Nanoheterostructures:Overcoming the Traditional Challenges of Nanoscale X-ray Analysisvia Machine Learning.
- Source :
-
Nano Letters . Apr2015, Vol. 15 Issue 4, p2716-2720. 5p. - Publication Year :
- 2015
-
Abstract
- The chemical composition of coreâshellnanoparticle clustershave been determined through principal component analysis (PCA) andindependent component analysis (ICA) of an energy-dispersive X-ray(EDX) spectrum image (SI) acquired in a scanning transmission electronmicroscope (STEM). The method blindly decomposes the SI into threecomponents, which are found to accurately represent the isolated andunmixed X-ray signals originating from the supporting carbon film,the shell, and the bimetallic core. The composition of the latteris verified by and is in excellent agreement with the separate quantificationof bare bimetallic seed nanoparticles. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 15306984
- Volume :
- 15
- Issue :
- 4
- Database :
- Academic Search Index
- Journal :
- Nano Letters
- Publication Type :
- Academic Journal
- Accession number :
- 102002531
- Full Text :
- https://doi.org/10.1021/acs.nanolett.5b00449