# Reconstructing Detailed Line Profiles of Lamellar Gratings from GISAXS Patterns with a Maxwell Solver

## TL;DR

This paper demonstrates that GISAXS combined with a Maxwell solver can accurately reconstruct detailed nanostructure line profiles, including critical dimensions, with sub-nanometer precision, enabling advanced dimensional metrology.

## Contribution

It introduces a novel approach using Maxwell's equations and GISAXS to reconstruct detailed nanostructure profiles with high accuracy, validated by statistical methods.

## Key findings

- Reconstructed line widths down to 55 nm.
- Achieved sub-nanometer uncertainty in critical parameters.
- Validated the method with MCMC sampling.

## Abstract

Laterally periodic nanostructures were investigated with grazing incidence small angle X-ray scattering (GISAXS) by using the diffraction patterns to reconstruct the surface shape. To model visible light scattering, rigorous calculations of the near and far field by numerically solving Maxwell's equations with a finite-element method are well established. The application of this technique to X-rays is still challenging, due to the discrepancy between incident wavelength and finite-element size. This drawback vanishes for GISAXS due to the small angles of incidence, the conical scattering geometry and the periodicity of the surface structures, which allows a rigorous computation of the diffraction efficiencies with sufficient numerical precision. To develop dimensional metrology tools based on GISAXS, lamellar gratings with line widths down to 55 nm were produced by state-of-the-art e-beam lithography and then etched into silicon. The high surface sensitivity of GISAXS in conjunction with a Maxwell solver allows a detailed reconstruction of the grating line shape also for thick, non-homogeneous substrates. The reconstructed geometrical line shape models are statistically validated by applying a Markov chain Monte Carlo (MCMC) sampling technique which reveals that GISAXS is able to reconstruct critical parameters like the widths of the lines with sub-nm uncertainty.