The author described the inelastic scattering cross section of electrons in matter using the Born approximation, generalized oscillator strength, and dielectric function as key parameters. With Born approximation, the electron inelastic scattering cross section in atom can be expressed using the generalized oscillator strength distribution. On the other hand, in dielectric response theory, the inelastic scattering cross section in a solid sample can be expressed in terms of the energy-loss function. Comparing these two equations, the generalized oscillator strength distribution can be expressed in terms of the energy loss function within the range where the dipole approximation is valid. This makes it possible to use the energy loss function to calculate the inelastic scattering cross section in solids in a practical and simple manner. Furthermore, the author shows that from this relationship, it is possible to calculate the squares of the dipole matrix elements of the total inelastic scattering and the static scattering factor.

View full abstract

The interpretation of time-of-flight secondary ion mass spectrometry (TOF-SIMS) data of complex samples is often extremely difficult because TOF-SIMS spectra contain extremely rich information. Therefore, multivariate analysis such as principal component analysis (PCA) and multivariate curve resolution (MCR) have been used to interpret TOF-SIMS data. In addition, the development of a practical TOF-SIMS spectral database is also difficult due to complex factors in the ionization mechanism such as matrix effects. In this study, we evaluated the application of machine learning methods to the development of the TOF-SIMS data prediction system including an automatic label creation method. The chemical structures of model samples described by strings based on simplified molecular-input line-entry system (SMILES) were automatically divided and then used as labels for the prediction system for organic, polymer and peptide samples in order to identify unknown materials. As a result, the TOF-SIMS spectrum prediction system using Random Forest, one of the supervised machine learning methods, achieved a high accuracy more than 0.9.

View full abstract

For quantitative analysis by XPS, the relative sensitivity factors are obtained by evaluating the measured intensity ratio of the pure substances of reference material. This method requires the same measurement conditions, such as the same sample height position for the reference materials. Tungsten dot-array composed of pure materials of tungsten and silicon can have the same height positions for both pure materials. Repeated measurements of the spectral peaks for five days showed that the peak intensity ratio of pure substances achieved the expanded uncertainty of 0.1% under the intermediate reproducibility conditions that had a daily difference in experimental room temperature change of 9˚C. The accuracy of XPS quantitative analysis has room for improvement up to this value.

View full abstract

X-ray photoelectron spectroscopy (XPS), which can analyze elemental compositions and chemical states of sample surfaces, has been applied to in situ and operando observations for energy devices including secondary batteries, especially at synchrotron radiation facilities. This paper reports the results of in situ observations of solution species and operando measurements of all-solid-state batteries using a laboratory-based XPS apparatus.

View full abstract

LIB (Lithium Ion Battery) is used in various places such as mobile devices and electric vehicles. The battery performance of LIB is greatly influenced by SEI (Solid Electrolyte Interphase) coating formed on the negative electrode. It is known that the SEI coating is formed on the negative electrode in nanometer order thickness at the first time of charging. Though the SEI coating is indispensable for the charge and discharge of LIB, if the thickness of the SEI coating increases more than necessary, it leads to the lowering of the battery performance. Therefore, for further performance improvement of LIB, it is important to analyze the structure of SEI coating and to control its thickness. In this paper, a case of XPS depth profile analysis of SEI coating formed on LIB negative electrode using Ar gas cluster ion beam is introduced. A case study of the structural destroy of the SEI coating, which occurs when the same sample is analyzed in depth with Ar monatomic ions, is also introduced.

View full abstract

The activities of The Division of Surface Analysis of The Japan Society of Vacuum and Surface Science (JVSS) are introduced. The objectives of this division are the advancement of surface analysis technologies, the exchange of research information, standardization, and collaboration with researchers in the Asian region. These days this research division has started activities such as web-based video lectures and Q&A sessions, in addition to conventional activities such as lecture sessions and seminars that focus on research presentations.

View full abstract