Model-Based Optical Metrology in R: M.o.R.

Description

Reliable optical critical dimension (OCD) metrology in the regime where the inspection wavelength λ is much larger than the critical dimensions (CDs) of the measurand is only possible using a model-based approach. Due to the complexity of the models involved, that often require solving Maxwell's equations, many applications use a library based look-up approach. Here, the best experiment-to-theory fit is found by comparing the measurement data to a library consisting of pre-calculated simulations. One problem with this approach is that it makes the accuracy of the solution dependent on the refinement of the grid. Interpolating between library values requires a uniform grid in most cases, and can also be very time-consuming. We present an approach based on radial basis functions that is fast, accurate and most importantly works on arbitrary grids. The method is implemented in a application based on the programming language R, that additionally allows for Bayesian data analysis, and provides multiple diagnostics.

Resources

Name Format Description Link
57 sourcecode.zip https://data.nist.gov/od/ds/6388F53FD1DBB474E0531A57068183FF1887/sourcecode.zip
47 https://data.nist.gov/od/ds/6388F53FD1DBB474E0531A57068183FF1887/sourcecode.zip.sha256
21 DOI Access to Model-Based Optical Metrology in R: M.o.R. https://doi.org/10.18434/T4/1502429
33 MoR_Documentation.pdf https://data.nist.gov/od/ds/6388F53FD1DBB474E0531A57068183FF1887/MoR_Documentation.pdf
47 https://data.nist.gov/od/ds/6388F53FD1DBB474E0531A57068183FF1887/MoR_Documentation.pdf.sha256

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  • statistics
  • model-based-metrology

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