2018/11/19 by Alberto Eljarrat, Eljarrat, Alberto, Christoph T. Koch +1 · 1 citation
Biochemistry, Genetics and Molecular Biology · Materials Science · #Advanced Electron Microscopy Techniques and Applications #Applied Physics (physics.app-ph) #Electron and X-Ray Spectroscopy Techniques #FOS: Physical sciences #Machine Learning in Materials Science #Materials Science (cond-mat.mtrl-sci)
paper · pdf · doi:10.48550/arxiv.1811.07575
openalex publication_date 2018/11/19 · openalex created_date 2022/09/28 · openalex updated_date 2026/07/28
Low-loss electron energy loss spectroscopy (EELS) in the scanning\ntransmission electron microscope (STEM) probes the valence electron density and\nrelevant optoelectronic properties such as band gap energies and other band\nstructure transitions. The measured spectra can be formulated in a dielectric\ntheory framework, comparable to optical spectroscopies and ab-initio\nsimulations. Moreover, Kramers-Kronig analysis (KKA), an inverse algorithm\nbased on the homonym relations, can be employed for the retrieval of the\ncomplex dielectric function (CDF). However, spurious contributions\ntraditionally not considered in this framework typically impact low-loss EELS\nmodifying the spectral shapes and precluding the correct measurement and\nretrieval of the dielectric information. A relativistic KKA algorithm is able\nto account for the bulk and surface radiative-loss contributions to low-loss\nEELS, revealing the correct dielectric properties. Using a synthetic low-loss\nEELS model, we propose some modifications on the naive implementation of this\nalgorithm that broadens its range of application. The robustness of the\nalgorithm is improved by regularization, appliying previous knowledge about the\nshape and smoothness of the correction term. Additionally, our efficient\nnumerical integration methodology allows processing hyperspectral datasets in a\nreasonable amount of time. Harnessing these abilities, we show how simultaneous\nrelativistic KKA processing of several spectra can share information to produce\nan improved result.\n