Influence of energy loss function to the Monte Carlo simulated electron backscattering coefficient

Area of Science:

• Materials Science
• Computational Physics
• Surface Science

Background:

• Electron backscattering coefficients (BSCs) are critical for understanding electron-sample interactions.
• Accurate BSCs are essential for applications like electron microscopy and semiconductor device simulation.
• Previous calculations often relied on simplified models for energy loss functions (ELFs).

Purpose of the Study:

• To refine the calculation of electron backscattering coefficients (BSCs) for beryllium, molybdenum, and tungsten.
• To investigate the impact of energy loss function (ELF) accuracy on BSC predictions.
• To establish the relationship between BSCs and sum rules.

Main Methods:

• Utilized an updated Monte Carlo simulation method.
• Employed relativistic dielectric functional formalism to derive electron inelastic cross-sections.
• Applied Penn's algorithm to extend ELF data into the relevant q-ω plane.

Main Results:

• Achieved improved electron backscattering coefficient (BSC) calculations for Be, Mo, and W.
• Demonstrated that the accuracy of the energy loss function (ELF) significantly influences calculated BSCs.
• Established a clear correlation between BSCs and the f- and ps-sum rules.

Conclusions:

• The refined Monte Carlo method provides more accurate BSCs.
• Accurate ELF data is paramount for reliable electron transport simulations.
• The findings contribute to a deeper understanding of electron-matter interactions.