Transmission electron microscopy/electron energy loss spectroscopy measurements and ab initio calculation of local magnetic moments at nickel grain boundaries

Quantitative Characterization by Transmission Electron Microscopy and Its Application to Interfacial Phenomena in Crystalline Materials

This paper reviews quantitative characterization via transmission electron microscopy (TEM) and its application to interfacial phenomena based on the results obtained through the studies. Several signals generated by the interaction between the specimen and the electron beam with a probe size of less than 1 nm are utilized for a quantitative analysis, which yields considerable chemical and physical information. This review describes several phenomena near the interfaces, e.g., clear solid-vapor interface (surface) segregation of yttria in the zirconia nanoparticles by an energy-dispersive X-ray spectroscopy analysis, the evaluation of the local magnetic moment at the grain boundary in terms of electron energy loss spectroscopy equipped with TEM, and grain boundary character dependence of the magnetism. The direct measurement of the stress to the dislocation transferred across the grain boundary and the microstructure evolution focused on the grain boundary formation caused by plastic deformation are discussed as examples of material dynamics associated with the grain boundary. Finally, the outlook for future investigations of interface studies, including the recent progress, is also discussed.

Electron energy loss spectroscopy database synthesis and automation of core-loss edge recognition by deep-learning neural networks

The ionization edges encoded in the electron energy loss spectroscopy (EELS) spectra enable advanced material analysis including composition analyses and elemental quantifications. The development of the parallel EELS instrument and fast, sensitive detectors have greatly improved the acquisition speed of EELS spectra. However, the traditional way of core-loss edge recognition is experience based and human labor dependent, which limits the processing speed. So far, the low signal-noise ratio and the low jump ratio of the core-loss edges on the raw EELS spectra have been challenging for the automation of edge recognition. In this work, a convolutional-bidirectional long short-term memory neural network (CNN-BiLSTM) is proposed to automate the detection and elemental identification of core-loss edges from raw spectra. An EELS spectral database is synthesized by using our forward model to assist in the training and validation of the neural network. To make the synthesized spectra resemble the real spectra, we collected a large library of experimentally acquired EELS core edges. In synthesize the training library, the edges are modeled by fitting the multi-Gaussian model to the real edges from experiments, and the noise and instrumental imperfectness are simulated and added. The well-trained CNN-BiLSTM network is tested against both the simulated spectra and real spectra collected from experiments. The high accuracy of the network, 94.9%, proves that, without complicated preprocessing of the raw spectra, the proposed CNN-BiLSTM network achieves the automation of core-loss edge recognition for EELS spectra with high accuracy.

The Effect of Vacancies on Grain Boundary Segregation in Ferromagnetic fcc Ni

This work presents a comprehensive and detailed ab initio study of interactions between the tilt Σ5(210) grain boundary (GB), impurities X (X = Al, Si) and vacancies (Va) in ferromagnetic fcc nickel. To obtain reliable results, two methods of structure relaxation were employed: the automatic full relaxation and the finding of the minimum energy with respect to the lattice dimensions perpendicular to the GB plane and positions of atoms. Both methods provide comparable results. The analyses of the following phenomena are provided: the influence of the lattice defects on structural properties of material such as lattice parameters, the volume per atom, interlayer distances and atomic positions; the energies of formation of particular structures with respect to the standard element reference states; the stabilization/destabilization effects of impurities (in substitutional (s) as well as in tetragonal (iT) and octahedral (iO) interstitial positions) and of vacancies in both the bulk material and material with GBs; a possibility of recombination of Si⁽ⁱ⁾+Va defect to Si^(s) one with respect to the Va position; the total energy of formation of GB and Va; the binding energies between the lattice defects and their combinations; impurity segregation energies and the effect of Va on them; magnetic characteristics in the presence of impurities, vacancies and GBs. As there is very little experimental information on the interaction between impurities, vacancies and GBs in fcc nickel, most of the present results are theoretical predictions, which may motivate future experimental work.