Electron backscattering from solid targets: Elastic scattering calculations

Hannachi, M.; Rouabah, Z.; Champion, C.; Bouarissa, N.

doi:10.1016/j.elspec.2014.07.006

Cited by 5 publications

(5 citation statements)

References 25 publications

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“…Furthermore, it is consistent with the results of the previous theoretical models of positron implantation in solid targets (Dapor, 1996;Jensen and Walker, 1993) as well as with the available experimental data reported in the literature (Coleman et al, 1992) within the experimental uncertainty. It is to be noted that the positron backscattering coefficient is much smaller than the electrons backscattering coefficient (Hannachi et al, 2014). This can be traced back to the difference of the elastic scattering cross section of crystal atoms for positrons and electrons.…”

Section: Resultsmentioning

confidence: 99%

Positron backscattering from solid targets: Modeling of scattering processes via various approaches

Kribaa

Rouabah

Loirec

et al. 2016

Micron

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Monte Carlo simulation of 1-4keV positron backscattering from semi-infinite solid targets ranging from Be (z=4) to Au (z=79) with normal angle of incidence is here reported. In our study, the elastic and inelastic scattering cross sections are modeled by using various approaches based on either a classical or a quantum mechanical treatment. Calculations of positron backscattering coefficient are then reported for the solid targets of interest. The results obtained show a fairly good agreement with the data available in the literature. The dependence of the positron backscattering coefficient versus the atomic number of the solid target of interest has been investigated. In this respect, polynomial functions are proposed which does not require any recourse to Monte Carlo calculations.

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Section: Resultsmentioning

confidence: 99%

Positron backscattering from solid targets: Modeling of scattering processes via various approaches

Kribaa

Rouabah

Loirec

et al. 2016

Micron

Self Cite

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“…Several different expressions for η in the SR‐DSCSs are available in the literature, 24 which yield different MC‐simulation results 17 . Suitable DSCSs for MC simulations depend on the material and the experimental conditions 18 . To achieve realistic MC‐simulation data, the MC‐simulation package must be first calibrated to the particular sample material and experimental setup.…”

Section: Methodsmentioning

confidence: 99%

“…17 Suitable DSCSs for MC simulations depend on the material and the experimental conditions. 18 To achieve realistic MC-simulation data, the MC-simulation package must be first calibrated to the particular sample material and experimental setup. To obtain the dependence of the simulated BSE intensity on the sample thickness, the MC simulations were performed in the thickness range between 1 and 3000 nm with 10 nm thickness intervals.…”

Section: Monte-carlo Simulationsmentioning

confidence: 99%

“…17 Suitable DSCSs for MC simulations depend on the material and the experimental conditions. 18 To achieve reliable MC-simulation data, the used MC-simulation software must be first calibrated with the particular material system and experimental setup. Comparing MC-simulated intensities with measurements validate the calibration and enables reliable prediction of BSE contrast as well as optimisation of the imaging parameters.…”

Section: Introductionmentioning

confidence: 99%

“…MC‐simulated image intensities strongly depend on the used differential scattering cross‐section (DSCS) or, in more detail, on the screening parameter in the screened Rutherford cross‐section 17 . Suitable DSCSs for MC simulations depend on the material and the experimental conditions 18 . To achieve reliable MC‐simulation data, the used MC‐simulation software must be first calibrated with the particular material system and experimental setup.…”

Section: Introductionmentioning

confidence: 99%

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Quantitative analysis of backscattered‐electron contrast in scanning electron microscopy

Čalkovský

Müller

Gerthsen

2022

Journal of Microscopy

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Backscattered-electron scanning electron microscopy (BSE-SEM) imaging is a valuable technique for materials characterisation because it provides information about the homogeneity of the material in the analysed specimen and is therefore an important technique in modern electron microscopy. However, the information contained in BSE-SEM images is up to now rarely quantitatively evaluated. The main challenge of quantitative BSE-SEM imaging is to relate the measured BSE intensity to the backscattering coefficient η and the (average) atomic number 𝑍 to derive chemical information from the BSE-SEM image. We propose a quantitative BSE-SEM method, which is based on the comparison of Monte-Carlo (MC) simulated and measured BSE intensities acquired from wedge-shaped electron-transparent specimens with known thickness profile.The new method also includes measures to improve and validate the agreement of the MC simulations with experimental data. Two different challenging samples (ZnS/Zn(O x S 1-x )/ZnO/Si-multilayer and PTB7/PC 71 BM-multilayer systems) are quantitatively analysed, which demonstrates the validity of the proposed method and emphasises the importance of realistic MC simulations for quantitative BSE-SEM analysis. Moreover, MC simulations can be used to optimise the imaging parameters (electron energy, detection-angle range) in advance to avoid tedious experimental trial and error optimisation. Under optimised imaging conditions pre-determined by MC simulations, the BSE-SEM technique is capable of distinguishing materials with small composition differences.

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