Sensitivity of SEM width measurements to model assumptions

Abstract

The most accurate width measurements in a scanning electron microscope (SEM) require raw images to be corrected for instrumental artifacts. Corrections are based upon a physical model that describes the sample-instrument interaction. Models differ in their approaches or approximations in the treatment of scattering cross sections, secondary electron (SE) generation, material properties, scattering at the surface potential barrier, etc. Corrections that use different models produce different width estimates. We have implemented eight models in the JMONSEL SEM simulator. Two are phenomenological models based upon fitting measured yield vs. energy curves. Two are based upon a binary scattering model. Four are variants of a dielectric function approach. These models are compared to each other in pairwise simulations in which the output of one model is fit to the other by using adjustable parameters similar to those used to fit measured data. The differences in their edge position parameters is then a measure of how much these models differ with respect to a width measurement. With electron landing energy, beam width, and other parameters typical of those used in industrial critical dimension measurements, the models agreed to within ±2.0 nm on silicon and ±2.6 nm on copper in 95% of comparisons.

Monte Carlo Simulation of SEM and SAM Images

“…For SEM imaging simulation the physical modeling of SE signal generation in different materials plays a critical role. The influence of different MC models to the linwidth determination has been carefully carried out recently (Villarrubia & Ding, 2009). For a geometric structure modeling of a realistic trapezoidal line shape, many parameters should be taken into account, such as, width, height, foot/corner rounding, sidewall angle and roughness, etc.…”

“…A systematic calculation for different parameters has been done, advancing a step towards building a MBL library. Villarrubia and Ding (Villarrubia & Ding, 2009) have compared eight MC physical models based on phenomenological fitting measured parameters, a binary scattering model and a dielectric function approach. They concluded that, CD linewidths estimated by these models agree to each other within ±2.0 nm on silicon and ±2.6 nm on copper in 95% of comparisons with electron landing energy, beam width, and other parameters typical of those used in industrial CD measurements.…”

“…This consideration has been proven to be more exact than the previous model (Ding & Shimizu, 1996) in deriving secondary electron energy distribution particularly for those materials that having a strong and sharp plasmon energy loss peak in its optical energy loss function, such as, Si and Al. As pointed out by Villarrubia & Ding (Villarrubia & Ding, 2009), the physical model itself could introduce error more or less, in spite of using the most sounded physics. Here, in order to stand out the influence of other factors to the CDs, we would neglect the uncertain error due to the physical model here.…”

Surface Reconstruction From Microscopic Images in Optical Lithography

“…In the industry, however, the main approach to 3D surface reconstruction from SEM images of circuit patterns is based on 1D measurements and Monte Carlo simulations [17]- [19]. Our approach combines SFS techniques from computer vision with the prior knowledge available in industry about the expected patterns and OPC models.…”

Comparison between Energy Straggling Strategy and Continuous Slowing Down Approximation in Monte Carlo Simulation of Secondary Electron Emission of Insulating Materials

“…Secondary electrons are used for imaging in scanning electron microscopes, with applications ranging from secondary electron doping contrast in p-n junctions, [9][10][11][12][13] line-width measurement in critical-dimension scanning electron microscopy, [14][15][16][17][18][19] to the study of biological samples. 20,21) The MC scheme based on the energy straggling strategy takes into account all the single energy losses suffered by each electron in the secondary electron cascade.…”