Pattern Roughness Analyses in Advanced Lithography: Power Spectral Density and Autocorrelation

Abstract

With development of advanced lithography processes, simultaneous reduction of line width and edge roughness along with the shrinkage of critical dimension of main feature is a continuous challenge. Recent years, unbiased roughness characterization was introduced in pattern roughness analysis by applying power spectral density method. Through power spectral density analysis, the data of all measurement points from scanning electron microscope are processed by Fourier transform, and the roughness behaviors of inspected pattern are converted from spatial domain to frequency domain. Autocorrelation analysis is an effective means to identify the periodic behavior of line width or edge roughness. In our research, roughness of dense lines under different lithography conditions, including reflectivity of bottom anti-reflection coating materials, photoresist, illumination and post exposure bake temperature, was characterized using power spectral density, autocorrelation methods as well as with standard deviation.