Model sensitivity analysis of Monte-Carlo based SEM simulations

Kerim T. Arat*, Cornelis W. Hagen

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

2 Citations (Scopus)
54 Downloads (Pure)


The sensitivity of simulated scanning electron microscopy (SEM) images to the various physical model ingredients is studied using an accurate, but slow simulator, to identify the most important ingredients to include in a reliable and fast SEM image simulator. The quantum mechanical transmission probability (QT) model and the electron-acoustical phonon scattering model are found to have the most significant effect on simulated 2D and 3D metrology results. The linewidth measurement error caused by not including these models in the simulation is less than 2 nm. Specifically, it was found from a comparison to experimental data that the QT model is essential in accurately predicting particular signal features in linescans such as “shadowing”. The simulator is compared with two other publicly available simulators, JMONSEL and CASINO, where the first one is also based on first-principle physics models and the latter one is using phenomenological models. CASINO is the fastest simulator on CPU, but Nebula on GPU is two orders of magnitude faster compared to a single threaded CPU simulation. Only up to 6% speed increase has been achieved by different model choices.

Original languageEnglish
Article number103545
Number of pages10
JournalResults in Physics
Publication statusPublished - 2020


  • Monte-Carlo simulation
  • Quantum mechanics
  • Sensitivity analysis
  • Speed-up
  • Surface effects


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