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  • Several factors influencing...
    Ding, Yifan; Yang, Junkai; Ji, Yu; Guo, Qinwen; Li, Xiangfei; Wang, Luyao; Meng, Ying; Shen, Xi; Yao, Yuan; Yu, Richeng

    Journal of microscopy (Oxford), August 2022, Volume: 287, Issue: 2
    Journal Article

    Electron energy‐loss spectroscopy (EELS) is widely applied combining with transmission electron microscopes with high spatial resolution, but its interpretation is a challenging task. One of the reasons is that the factors affecting EELS are very complicated. In this paper, we focus on the several factors involved in density functional theory (DFT) calculations. The sensitivity of calculated energy‐loss near‐edge structure (ELNES) to spin order, pressure and on‐site Coulomb energy U has been discussed. Since EELS technique detects the local environment of atoms, the influence of spin order cannot be ignored. The chemical shifts and peak intensity of ELNES are also closely related to corresponding pressure. The correlation effects are very important for transition metal compounds and play a key role in EELS simulations. An overview of the effects of these factors on the ELNES is presented with the help of Wien2k code. The antiferromagnetic order results in the decreasing of intensities of related peaks and the moving of the peaks to high energy loss. The decreasing of lattice parameters causes the ELNES peaks to shift to high energy loss, and the peak shifts at the higher energy loss are more significant. The increase of correlation effect leads to the ELNES peaks to shift to high energy loss accompanied by the increase of the relative intensity of the peaks which locate at higher energy loss. Our work helps to understand how these factors affect EELS and to explain and predict the experimental EELS spectra. Through the discussion of these factors, we propose that some factors could not be ignored in EELS simulations. Lay description Transmission electron microscope (TEM) is a powerful scientific instrument, which can be used for small size imaging. In recent decades, it has helped scientists to make important discoveries such as carbon nanotube and quasicrystal and has been widely used in materials science, condensed matter physics, structural biology and other fields. The principle of transmission electron microscope is similar to that of optical microscope, but its resolution is far superior to that of optical microscope. Compared with the resolution of optical microscope about 300 nm, the resolution of transmission electron microscope can reach 0.039 nm at present. In addition to excellent spatial resolution, transmission electron microscope has many functions such as structural analysis, elemental composition analysis and electronic structure analysis. TEM can be also used to carry out in situ observation and time resolution observation. Because of its several advantages mentioned above, transmission electron microscopy attracts much attention since its birth in the early 1930s. The early TEM was considered to be used only to magnify the observed object, but the electron energy‐loss spectroscopy (EELS) gives it the ability to determine the composition of the sample and analyse the electronic structure. EELS is widely applied combining with transmission electron microscopes with high spatial resolution, but its interpretation is a challenging task. One of the reasons is that the factors affecting EELS are very complicated. In this paper, we focus on several factors involved in density functional theory calculations. The sensitivity of calculated energy‐loss near‐edge structure to spin order, lattice compression and expansion, and on‐site Coulomb energy is discussed. Since EELS technique detects the local environment of atoms, the influence of spin order cannot be ignored. The chemical shift and peak intensity of EELS are also closely related to corresponding lattice parameters. The correlation effects are very important for transition metal compounds and play a key role in EELS simulations. Our work helps to understand how these factors affect EELS and to explain and predict the experimental EELS spectra. Through the discussion on these factors, we provide a useful guidance for more precise EELS simulations.