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Optimization of Photolithography CD Control Using VWF and Optolith
The progress in semiconductor technology towards even smaller device geometries demands continuous refinements of the photolithography process. Optical projection lithography is still a widely used technology, though it is coming very close to its resolution limit in sub-half -micron regime. Therefore, CD-control and optimization of all stages of photolithography process are the biggest concern of current and future optical lithography. Traditional method of CD control analyzes the depth-of-focus and exposure latitude using Smile (Bossung) curves and Exposure-Defocuse (ED) Tree. This method is not sufficient because it fails to involve other critical process parameters such as reticle CD, Numerical Aperture,NA, resist thickness, and ABC development parameters into consideration. Moreover, it is very difficult to use the traditional method to control other important metrics (e.g. sidewall angle) simultaneously with CD. The only feasible approach is to
Moreover, automatic fitting of simulated RSMs to experimental ones is the only reliable way to calibrate the empirical parameters involved in simulation. All these can be done using Optolith and the Automation and Production Tools of Virtual Wafer Fab (VWF). To demonstrate this approach, a simple DOE was prepared which involves only two input parameters; image defocus and expose dose. All other parameters were constant: reticle CD was 0.5 microns, NA=0.52, resist thickness was 1 micron. Latin Hypercube random design with only 50 samples was used. It appeared that even these few experimental points were enough to build an acceptable RSM. Figure 1 shows
the RSM presented as a contour plot of measured CD. The contours
in upper part of the plot correspond to smaller CDs (overexposed
resist), while contours in the lower part correspond to larger CDs
(underexposed resist). Only area in the center of the plot (exposed
doses = 160 - 180 mJ/cm2, and image defocus between approximately
-0.7 and 0.6 microns) corresponds to a measured CD close to reticle
CD. This type of plot can be used for estimation of a "window"
of defocus and exposure dose values which result in measured CDs
within certain tolerances.
Another way to analyze the RSM is to build a Smile
plot (Figure 2). This is measured CD
as a function of defocus for several values of exposure dose. From
this plot one can estimate that the best depth of focus can be achieved
with exposure dose around = 160 - 180 mJ/cm2. However,
it should be also realized that measured CDs will be slightly smaller
( ~0.45 microns) than nominal.
Even this two-parameter RSM analysis has some advantages over traditional CD control method because it needs fewer number of simulations and provides more flexible method of visualization. In the second DOE two more parameters, reticle CD and NA, were added. Around 300 simulation points were enough to build acceptable response surfaces for measured CD and sidewall angle. The new RSM allows Smile and ED-tree plots for
various reticle CDs and NAs to be plotted. It also allows CD control
and optimization simultaneously for several line widths. For example,
Figure 3a , Figure
3b and Figure 3c show how depth
of focus changes with the exposure dose for 3 values of reticle
CD. It is obvious that the optimal dose for one CD is not the optimum
for another. This type of analysis may help to find an optimal solution
because different lines in the layout could appear in different
focal planes. Therefore depth of focus may be not so critical for
some linewidths but could be very crucial for others.
The next series of plots (Figure
4a, Figure 4b and Figure
4c) shows how drastically depth of focus curves depend on numerical
aperture. It means that NA could serve as a very sensitive optimization
parameter. Finally, Figure 5 demonstrates
sidewall angles vs Focal Position.
Figure
5. Averaged sidewall angles vs It has been shown that the combination of
Optolith and VWF can serve as a powerful tool for advanced CD control
and optimization of modern photolithography processes.
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