Abstract
Measurement and control of line edge roughness (LER) is one of the most challenging issues facing patterning technology. As the critical dimensions (CDs) of patterned structures decrease, an LER of only a few nanometers negatively impacts device performance. Here, Mueller matrix (MM) spectroscopic ellipsometry-based scatterometry is used to characterize LER in periodic line-space structures in 28-nm pitch Si fin samples fabricated by directed self-assembly patterning. The optical response of the MM elements is influenced by structural parameters like pitch, CDs, height, and side-wall angle, as well as the optical properties of the materials. Evaluation and decoupling MM element response to LER from other structural parameters requires sensitivity analysis using scatterometry models that include LER. Here, an approach is developed that can be used to characterize LER in Si fins by comparing the optical responses generated by systematically varying the grating shape and measurement conditions. Finally, the validity of this approach is established by comparing the results obtained from power spectral density analysis of top down scanning electron microscope images and cross-sectional transmission electron microscope image of the 28-nm pitch Si fins.
Highlights
The semiconductor industry continues to drive patterning solutions that enable reduced device dimensions
When the wavelength of roughness that appears along the line edge is small relative to the critical dimensions (CDs), the line edge roughness (LER) is termed as high-frequency LER and when the wavelength of the roughness is large compared to the CD, the LER is characterized as low-frequency LER
This paper demonstrates the use of Mueller matrix spectroscopic ellipsometry (MMSE)-based scatterometry for quantifying LER in directed self-assembly (DSA) patterned Si fins with the help of multiparameter scatterometry models
Summary
The semiconductor industry continues to drive patterning solutions that enable reduced device dimensions. This is known as the inverse approach of scatterometry, and can be carried out with the help of linear and nonlinear regression methods wherein the structural profile is achieved through an iterative procedure that repeatedly requires computation of the forward optical modeling or with the help of a library search method, wherein an optical response library is generated prior to the measurement, and a best-fit match with the measured spectra is determined with the help of algorithms.[3]. Mueller measurements have better sensitivities to small structural changes and provide more information about the sample than traditional spectroscopic ellipsometry (SE) and spectroscopic reflectometry (SR) measurement.[9,10] Profile reconstruction of patterned structures in scatterometry models that incorporate line roughness has been largely neglected likely because it increases the number of floating parameters and the correlation between these parameters and computation time. The multiparameter scatterometry models that include the surface roughness as demonstrated in this study can be used offline for predictive modeling and a librarybased search can be carried out as a quick and effective approach for LER measurements
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