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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