Abstract
We present a way to analyze the chemical composition of periodical multilayer structures using the simultaneous analysis of grazing incidence hard X-Ray reflectivity (GIXR) and normal incidence extreme ultraviolet reflectance (EUVR). This allows to combine the high sensitivity of GIXR data to layer and interface thicknesses with the sensitivity of EUVR to the layer densities and atomic compositions. This method was applied to the reconstruction of the layered structure of a LaN/B multilayer mirror with 3.5 nm periodicity. We have compared profiles obtained by simultaneous EUVR and GIXR and GIXR-only data analysis, both reconstructed profiles result in a similar description of the layered structure. However, the simultaneous analysis of both EUVR and GIXR by a single algorithm lead to a ∼ 2x increased accuracy of the reconstructed layered model, or a more narrow range of solutions, as compared to the GIXR analysis only. It also explains the inherent difficulty of accurately predicting EUV reflectivity from a GIXR-only analysis.
Highlights
In order to account for the different sensitivities of X-rays and extreme ultraviolet (EUV) radiation to the chemical composition of the layers, we propose to add the chemical composition of layers and interfaces as a parameters during the combined fit of grazing incidence hard X-Ray reflectivity (GIXR) and extreme ultraviolet reflectance (EUVR) data
The GIXR curve was fitted almost perfectly, the calculated EUVR curve does not fit to the measurements at all
It is clear that the structure parameters obtained from a GIXR-only fit are not sufficient to predict the multilayer characteristics in the EUV range
Summary
These range from nanomaterials in general to XUV reflecting Bragg optics, down to atomic scale dimensions [1]. Traditional characterization of such, periodic multilayer mirrors usually involves two types of measurements of the reflectance, one performed using hard x-rays at grazing incidence (GIXR), and a second performed at an application relevant wavelength. A structural model obtained from hard x-ray reflectometry analysis is generally not able to accurately predict the application relevant reflectivity data. Soft x-rays are extremely sensitive to the compositional parameters of the layers, such as stoichiometry and the presence of impurity atoms, but the analysis of such data suffers from the large correlation between model parameters that describe the measurement curves
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