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Modeling the point-spread function in helium-ion lithography.

Donald Winston1, J Ferrera, L Battistella

  • 1Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. dwinston@mit.edu

Scanning
|September 23, 2011
PubMed
Summary
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This study introduces a hybrid model for helium-ion lithography, combining SRIM software and secondary electron simulations. The findings reveal that energy deposition in resist is more complex than a simple Gaussian distribution.

Area of Science:

  • Lithography and Nanofabrication
  • Computational Physics
  • Materials Science

Background:

  • Helium-ion lithography offers high resolution but requires accurate modeling for process optimization.
  • Existing simulation methods may not fully capture the complex interactions of helium ions and secondary electrons within resist materials.

Purpose of the Study:

  • To develop and validate a hybrid modeling approach for helium-ion lithography.
  • To accurately simulate the spatial distribution of energy deposition in resist materials.
  • To investigate the point spread function in helium-ion lithography.

Main Methods:

  • A hybrid approach combining Stopping and Range of Ions in Matter (SRIM) software for ion trajectories and Monte Carlo simulations for secondary electron trajectories.

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  • Tracing helium-ion paths using SRIM and simulating secondary electron generation and propagation.
  • Comparing simulation results with experimental data.
  • Main Results:

    • The spatial distribution of energy deposition, or point spread function, is not a simple sum of Gaussian functions.
    • The hybrid model accurately predicts energy deposition profiles.
    • Simulations and experiments show deviations from simple Gaussian models.

    Conclusions:

    • The developed hybrid model provides a more accurate representation of energy deposition in helium-ion lithography.
    • Understanding the non-Gaussian nature of the point spread function is crucial for advancing high-resolution lithography.
    • This approach enhances the predictive capability for helium-ion lithography processes.