Retrieving the Quantitative Chemical Information at Nanoscale from Scanning Electron Microscope Energy Dispersive X-ray Measurements by Machine Learning.

@article{Jany2017RetrievingTQ,
  title={Retrieving the Quantitative Chemical Information at Nanoscale from Scanning Electron Microscope Energy Dispersive X-ray Measurements by Machine Learning.},
  author={Benedykt R Jany and Arkadiusz Janas and Franciszek Krok},
  journal={Nano letters},
  year={2017},
  volume={17 11},
  pages={
          6520-6525
        }
}
The quantitative composition of metal alloy nanowires on InSb semiconductor surface and gold nanostructures on germanium surface is determined by blind source separation (BSS) machine learning method using non-negative matrix factorization from energy dispersive X-ray spectroscopy (EDX) spectrum image maps measured in a scanning electron microscope (SEM). The BSS method blindly decomposes the collected EDX spectrum image into three source components, which correspond directly to the X-ray… 

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