Enhanced Quantitative Analysis of Resist Image Contrast upon Line Edge Roughness (LER)

Mike Williamson
(Professor Andrew R. Neureuther)
(DARPA) MDA972-01-1-0021 and (SRC) 2001-MC-460

Image enhancement and lateral size analysis tools are used to quantitatively examine roughness via scanning electron microscopy (SEM) and atomic force microscopy (AFM). The tools are then applied to study the effects of aerial image contrast and threshold set points (see Figure 1) upon LER and side edge roughness (SER) of several different DUV chemically amplified resists, using programmed double exposures with an ASML 248 nm wavelength stepper tool to create variable contrast levels. The threshold set point is defined as the minimum exposure dose necessary for resist development. Results show that in the case of Shipley's UV210, for instance, LER and SER do not increase significantly until aerial image contrast drops below around 38% (see Figure 2).

Advanced measurement and analysis techniques are used to yield a deeper understanding of and higher confidence in the data collected. AFM analysis of a sidewall yields two-dimensional information regarding that sidewall. Aside from merely mentioning SER values, the frequency and size of roughness are studied. In examining the data, roughness is typically seen as smooth, low rolling hills of about 20 nm peak:peak spacing and 1 nm height. The randomness of roughness can also be studied using this method, to help understand root causes or LER and SER.

SEM analysis itself falls prey to optical aberrations analogous to those seen in lithography. Astigmation, defocus, and other aberrations blur the micrograph, which is used to quantitatively assess LER. Even a system with no aberrations still has diffraction limited blurring. Deblurring the micrograph can improve image quality, therefore enhancing the accuracy of the LER data extracted from the SEM image. Deblurring is performed by iteratively solving for the point spread function (PSF) of the unknown blurring source and deconvolving the image with the PSF (see Figure 3). The LER does indeed change significantly. One example shows root mean square LER equal to 4.7 nm before image enhancement and 5.9 nm afterwards. Aside from improving the LER data, this technique also helps to determine the most significant aberrations seen in the SEM tool by analyzing the PSF used to deconvolve the image


Figure 1: Aerial image contrast variation at two different energy threshold set points

Figure 2: Effect of aerial image contrast upon SER at 0.3 intensity threshold set point

Figure 3: Deconvolving an SEM image with a calculated PSF in order to improve image quality and receive more accurate LER values

More information (http://mingus.eecs.berkeley.edu/~mvw) or

Send mail to the author : (mvw@eecs.berkeley.edu)


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