To further gain insights into the spectral imaging of EELS, many spectra are acquired as the electron probe is rastered across the specimen, forming a 2D spectral map [64]. The number of scanned points and the signal-to-noise ratio (SNR) of EELS imaging quality are limited by the amount of signal, instrument stability, and user’s time. This is greatly improved with the advent of aberration-corrected electron microscopes, which allow a larger probe-forming apertures and improve collection optics [65, 66]. Most often, the interested area contained in the core loss energy edges, where they appear in the EELS spectrum with a shape and energy onset uniquely defined by a specimen’s excitation of core-level electrons to the available density of states in the conduction band and modified by the core–hole interaction, it has been shown that the background often follows an inverse power law [67]. The signal is usually obtained after the background has been modeled and substracted over the edge of interest. However, atomic resolution EELS maps are often oversampled with pixel dimensions smaller than the probes’ transfer limit. This can be well solved with local background averaging (LBA) to estimate the background signal. This approach provides an improved background modeling, where its position can be averaged with those from neighboring spectra to obtain an accurate background signal at every position, and the reduced noise could enable a more reliable background fit and extrapolation, showing a dramatic improvement in the image contrast and SNR. Meanwhile, if the spectrum is taken in very large energy windows, the error in each channel is not equal, especially for backgrounds in the first few hundred electron volts of a spectrum. This can be overcome by iterative weighted least-squares approaches to incorporate the change in variance over the background to combine with LBA [68]. In general, the detection limits and SNR of images extracted from spectroscopic mapping highly depend on the signal processing methods, where the pre-edge power law background modeling can greatly affect the accuracy and range of the extrapolated background. In addition, LBA works well when the background has been spatially oversampled, avoiding the distortions of EELS fine structure.
Figure 2.4 High signal-to-noise EEL spectrum acquired by the accumulating 1 s exposures while scanning repeatedly. The insets present a 50 frame average in false color from the stacks of images created during the acquisitions, showing clear threefold coordination (a) or fourfold coordination (b) of the Si atom. Source: Reproduced with permission from Ramasse et al. [61]. Copyright 2013, American Chemical Society.
In summary, the EELS acquired by Cs-TEM can yield precise electronic structure information at the sub-nano level. Optimizing acquisition procedures would result in very high SNR data. The foreign species on a substrate and even bonding differences between dopant species would be distinguishable with electron energy loss spectroscopy. Another concept that should be emphasized in this part is that experimental configuration for atomic column imaging is not only to make a small incident probe but also to optimize the acquisition condition associated with the delocalization in elastic and inelastic scattering. The incoherent EELS imaging allows to interpret the core loss images, which are informative in material science. The observation of local inhomogeneity would endow the discussion of local crystal distortions and its unique material properties beyond the stoichiometric understanding of the average crystal structure. The development of Cs-TEM has proved its powerful function of elemental and chemical analyses of site occupancy in material microstructure characterization.
2.1.4 Applications in Amorphous Nanomaterial Characterization
The recent progress of Cs-TEM provides a solid foundation to investigate the structures and compositions at the atomic level or in a complex environment with gas or liquid. This can then be integrated with energy-dispersive X-ray spectroscopy (EDS) and EELS techniques to observe the structure evolution of the materials and to investigate the mechanism of the composition changes. Notably, one achievement in the last few decades is the application of in situ TEM that involves various stimuli to nanomaterials with high-resolution imaging and spectroscopy. These stimuli may include heat, stress, electrical biasing, and ultrashort photon pulses to the materials. However, the high vacuum of TEM within the column to protect the electron gun and to avoid the electron scattering by gases and liquids makes it not compatible with gaseous or liquid environments. The development of environmental transmission electron microscopy (ETEM) has offered great chances to study the dynamic changes in materials with ultrahigh resolution in complex gaseous or liquid environments.
Since the inception of in situ TEM techniques for battery research in 2010 [69], continuous efforts have been made to give a better understanding of material dynamics during electrochemical reactions. In the battery analysis by using TEM, the scientific challenges include how cathodes experience thermal degradation with compromised battery safety, what is the charge storage mechanism for electrodes with different elements, and how Li dendrites evolve during Li intercalation. As a stable electrode, intercalation should work without obvious structural degradation during ion insertion/extraction. To evaluate the structural changes with the high spatial and temporal resolution, the advantages of in situ TEM with aberration corrector are obvious. One typical example is the case of MnO2 cathode, which possesses a one-dimensional tunneled structure. An asynchronous lattice expansion was found to be driven by a sequential Jahn–Teller distortion of [MnO6] octahedral [70]. The dynamic observation of structure degradation demonstrates the powerful capability of in situ TEM in studying the localized reaction mechanisms. Inspired by these observations, the battery performance can be improved by structure modification, such as minimizing the particle size or tracing the dopant component to reduce the structural degradation. Interestingly, nanosized transitional metal oxides, sulfides, and fluorides (MX) showed that lithium storage through a conversion reaction between metal oxide and LiX is reversible,