From STEM-EDXS data to phase separation and quantification using physics-guided NMF
We present the development of a new algorithm which combines state-of-the-art energy-dispersive x-ray (EDX) spectroscopy theory and a suitable machine learning formulation for the hyperspectral unmixing of scanning transmission electron microscope EDX spectrum images.The algorithm is based on non-negative matrix factorization (NMF) incorporating a