The Čerenkov limit of Si, GaAs and GaP in electron energy loss spectrometry

Horák, Michal; Stöger-Pollach, Michael

doi:10.1016/j.ultramic.2015.06.005

Cited by 20 publications

(16 citation statements)

References 13 publications

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“…The effects of Cerenkov losses can result in shifts in band-gap onset positions and dramatically alter the intensity of different valence EELS features (Gu et al, 2007; Stöger-Pollach, 2008). The intensity of Cerenkov loss effects vary with the material being examined, but are most pronounced when high operating voltages are used and when spectra are collected from thick sample regions (Horák & Stöger-Pollach, 2015). The EELS analysis here was carried out using an operating voltage of 200 kV, which is considered to be in the energy regime for Cerenkov losses.…”

Section: Resultsmentioning

confidence: 99%

Characterization of Lithium Ion Battery Materials with Valence Electron Energy-Loss Spectroscopy

Castro

Dravid

2018

Microsc Microanal

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Cutting-edge research on materials for lithium ion batteries regularly focuses on nanoscale and atomic-scale phenomena. Electron energy-loss spectroscopy (EELS) is one of the most powerful ways of characterizing composition and aspects of the electronic structure of battery materials, particularly lithium and the transition metal mixed oxides found in the electrodes. However, the characteristic EELS signal from battery materials is challenging to analyze when there is strong overlap of spectral features, poor signal-to-background ratios, or thicker and uneven sample areas. A potential alternative or complementary approach comes from utilizing the valence EELS features (<20 eV loss) of battery materials. For example, the valence EELS features in LiCoO2 maintain higher jump ratios than the Li-K edge, most notably when spectra are collected with minimal acquisition times or from thick sample regions. EELS maps of these valence features give comparable results to the Li-K edge EELS maps of LiCoO2. With some spectral processing, the valence EELS maps more accurately highlight the morphology and distribution of LiCoO2 than the Li-K edge maps, especially in thicker sample regions. This approach is beneficial for cases where sample thickness or beam sensitivity limit EELS analysis, and could be used to minimize electron dosage and sample damage or contamination.

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Section: Resultsmentioning

confidence: 99%

Characterization of Lithium Ion Battery Materials with Valence Electron Energy-Loss Spectroscopy

Castro

Dravid

2018

Microsc Microanal

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“…If we consider measured raw EEL spectra in Figure 1(a), we clearly see that the peak at 1.08 eV corresponding to the longitudinal dipole mode is the most noticeable when using 120 keV electron beam. In the case of 300 keV electron beam the background is enhanced by relativistic effects like the Čerenkov radiation as the speed of the 300 keV electron is higher than the speed of the light in the silicon nitride membrane [4] with the refractive index around 2. On the other hand, the raw EEL spectra measured with a 60 keV electron beam has the highest background in the lower energy loss region.…”

Section: United Statesmentioning

confidence: 99%

Influence of primary beam energy on localized surface plasmon resonances mapping by STEM-EELS

Horák

Šikola²

2021

Microsc Microanal

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“…We first tried to duplicate earlier obtained results for the bandgap in GaAs [1,6] by using normal STEM mode. Measurements were performed at 60, 80 and 120 kV and with sample thicknesses in the range of 20 -150 nm.…”

Section: Normal Stem On-axismentioning

confidence: 99%

“…The onsets of bandgap excitations are defined by the intersection of a horizontal line describing the background in front of the bandgap and a linear line describing the EEL spectrum in between the bandgap and 2.5 eV (after which the spectrum changes its shape, as expected). The respective bandgaps are now directly read out as 1.42 eV ± 0.02 (GaAs), 1.61 eV ± 0.03 eV (Al0.25Ga0.75As1-xNx) and 1.7 eV ± 0.03 (Al0.25Ga0.75As). These values are (close to) equal to the known (GaAs and Al0.25Ga0.75As) or expected (Al0.25Ga0.75As1-xNx) direct bandgaps for these materials [17][18][19].…”

Section: Low-mag Off-axismentioning

confidence: 99%

Bandgap measurement of high refractive index materials by off-axis EELS

et al. 2017

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In the present work Cs aberration corrected and monochromated scanning transmission electron microscopy electron energy loss spectroscopy (STEM-EELS) has been used to explore experimental set-ups that allow bandgaps of high refractive index materials to be determined. Semi-convergence and -collection angles in the µrad range were combined with off-axis or dark field EELS to avoid relativistic losses and guided light modes in the low loss range to contribute to the acquired EEL spectra. Off-axis EELS further supressed the zero loss peak and the tail of the zero loss peak. The bandgap of several GaAs-based materials were successfully determined by simple regression analyses of the background subtracted EEL spectra. The presented set-up does not require that the acceleration voltage is set to below the Čerenkov limit and can be applied over the entire acceleration voltage range of modern TEMs and for a wide range of specimen thicknesses.

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The Čerenkov limit of Si, GaAs and GaP in electron energy loss spectrometry

Cited by 20 publications

References 13 publications

Characterization of Lithium Ion Battery Materials with Valence Electron Energy-Loss Spectroscopy

Characterization of Lithium Ion Battery Materials with Valence Electron Energy-Loss Spectroscopy

Influence of primary beam energy on localized surface plasmon resonances mapping by STEM-EELS

Bandgap measurement of high refractive index materials by off-axis EELS

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