Establishment and validation of an electron inelastic mean free path database for narrow bandgap inorganic compounds with a machine learning approach.

Narrow bandgap inorganic compounds are extremely important in many areas of physics. However, their basic parameter database for surface analysis is incomplete. Electron inelastic mean free paths (IMFPs) are important parameters in surface analysis methods, such as electron spectroscopy and electron microscopy.

Unveiling the principle descriptor for predicting the electron inelastic mean free path based on a machine learning framework.

The TPP-2M formula is the most popular empirical formula for the estimation of the electron inelastic mean free paths (IMFPs) in solids from several simple material parameters. The TPP-2M formula, however, poorly describes several materials because it relies heavily on the traditional least-squares analysis. Herein, we propose a new framework based on machine learning to overcome the weakness.

Observation of Plasmon Energy Gain for Emitted Secondary Electron in Vacuo.

Plasmon gain by core-level electrons or elastic electrons observed in past studies seems to be of no practical value in material characterization, mainly because of their ultralow signal intensities. Nevertheless, in the emission spectra of Au samples, we have observed plasmon gain in secondary electrons. The electrons gain energy from surface plasmons after escaping from the surface and thereby only carry surface-plasmon information in the vacuum above the surface.

Calculations of electron inelastic mean free paths. XII. Data for 42 inorganic compounds over the 50 eV to 200 keV range with the full Penn algorithm.

We have calculated inelastic mean free paths (IMFPs) for 42 inorganic compounds (AgBr, AgCl, AgI, AlO, AlAs, AlN, AlSb, cubic BN, hexagonal BN, CdS, CdSe, CdTe, GaAs, GaN, GaP, GaSb, GaSe, InAs, InP, InSb, KBr, KCl, MgF, MgO, NaCl, NbC, NbC, NbC, PbS, PbSe, PbTe, SiC, SiO, SnTe, TiC, TiC, VC, VC, YAlO, ZnS, ZnSe, and ZnTe) for electron energies from 50 eV to 200 keV. These calculations were made with energy-loss functions (ELFs) obtained from measured optical constants for 15 compounds while calculated ELFs were utilized for the other 27 compounds. Checks based on ELF sum rules showed that the calculated ELFs were superior to the measured ELFs that we had used previously.

Virtual substrate method for nanomaterials characterization.

Characterization techniques available for bulk or thin-film solid-state materials have been extended to substrate-supported nanomaterials, but generally non-quantitatively. This is because the nanomaterial signals are inevitably buried in the signals from the underlying substrate in common reflection-configuration techniques. Here, we propose a virtual substrate method, inspired by the four-point probe technique for resistance measurement as well as the chop-nod method in infrared astronomy, to characterize nanomaterials without the influence of underlying substrate signals from four interrelated measurements.

X-ray fluorescence analysis of Cr(6+) component in mixtures of Cr(2)O(3) and K(2)CrO(4).

X-ray fluorescence analysis using Cr K(alpha) spectra was applied to the determination of the mixing ratio of Cr(6+) to (Cr(6+) + Cr(3+)) in several mixtures of K(2)CrO(4) and Cr(2)O(3). Because the powder of K(2)CrO(4) contained large particles that were more than 50 microm in diameter, it was ground between a pestle and a mortar for about 8 h. The coarse particles still remaining were removed by using a sieve with 325-mesh (44 microm) in order to reduce the difference in absorption effects between emissions from Cr(6+) and those from Cr(3+).

Surface excitations in surface electron spectroscopies studied by reflection electron energy-loss spectroscopy and elastic peak electron spectroscopy.

Surface excitations, in addition to bulk excitation, undergone by signal electrons in surface electron spectroscopies, such as Auger electron spectroscopy, and X-ray photoelectron spectroscopy, play an important role in the formation of electron spectra. Those inelastic scattering processes not only induce decay in the peak intensity, but also form background appearing in the lower kinetic energy side of relevant peaks. Information on surface excitation is essential in addition to bulk excitations for the quantification of material surfaces by surface electron spectroscopies, and extensive studies have been devoted to it.

Grazing exit electron probe microanalysis of submicrometer inclusions in metallic materials.

Grazing exit electron probe microanalysis (GE-EPMA) is a new method of EPMA in which characteristic X-rays emitted from only near-surface regions of a specimen are detected at extremely low exit angles near 0 degrees (the grazing exit condition). This technique requires the analytical objects exist on a flat surface. Therefore, the GE-EPMA analysis has been used only for the analysis of particles or a thin film on a flat substrate so that there were only few applications for practical analysis.