As semiconductor manufacture feature sizes scale into the nanometer
dimension, circuit layout printability is significantly reduced due to the fundamental
limit of lithography systems. This dissertation studies related research
topics in lithography simulation and optical proximity correction.
A recursive integration method is used to reduce the errors in transmission
cross coefficient (TCC), which is an important factor in the Hopkins
Equation in aerial image simulation. The runtime is further reduced, without
increasing the errors, by using the fact that TCC is usually computed on uniform
grids. A flexible software framework, ELIAS, is also provided, which can
be used to compute TCC for various lithography settings, such as different
illuminations.
Optimal coherent approximations (OCAs), which are used for full-chip
image simulation, can be speeded up by considering the symmetric properties of lithography systems. The runtime improvement can be doubled without
loss of accuracy. This improvement is applicable to vectorial imaging models
as well. Even in the case where the symmetric properties do not hold strictly,
the new method can be generalized such that it could still be faster than the
old method.
Besides new numerical image simulation algorithms, variations in lithography
systems are also modeled. A Variational LIthography Model (VLIM)
as well as its calibration method are provided. The Variational Edge Placement
Error (V-EPE) metrics, which is an improvement of the original Edge
Placement Error (EPE) metrics, is introduced based on the model. A true
process-variation aware OPC (PV-OPC) framework is proposed using the V-EPE
metric. Due to the analytical nature of VLIM, our PV-OPC is only
about 2-3× slower than the conventional OPC, but it explicitly considers the
two main sources of process variations (exposure dose and focus variations)
during OPC.
The EPE metrics have been used in conventional OPC algorithms, but
it requires many intensity simulations and takes the majority of the OPC
runtime. By making the OPC algorithm intensity based (IB-OPC) rather
than EPE based, we can reduce the number of intensity simulations and hence
reduce the OPC runtime. An efficient intensity derivative computation method
is also provided, which makes the new algorithm converge faster than the EPE
based algorithm. Our experimental results show a runtime speedup of more
than 10× with comparable result quality compared to the EPE based OPC.
The above mentioned OPC algorithms are vector based. Other categories
of OPC algorithms are pixel based. Vector based algorithms in general
generate less complex masks than those of pixel based ones. But pixel based algorithms produce much better results than vector based ones in terms of
contour fidelity. Observing that vector based algorithms preserve mask shape
topologies, which leads to lower mask complexities, we combine the strengths
of both categories—the topology invariant property and the pixel based mask
representation. A topological invariant pixel based OPC (TIP-OPC) algorithm
is proposed, with lithography friendly mask topological invariant operations
and an efficient Fast Fourier Transform (FFT) based cost function sensitivity
computation. The experimental results show that TIP-OPC can achieve much
better post-OPC contours compared with vector based OPC while maintaining the mask shape topologies. / text
| Identifer | oai:union.ndltd.org:UTEXAS/oai:repositories.lib.utexas.edu:2152/6664 |
| Date | 23 October 2009 |
| Creators | Yu, Peng |
| Source Sets | University of Texas |
| Language | English |
| Detected Language | English |
| Format | electronic |
| Rights | Copyright is held by the author. Presentation of this material on the Libraries' web site by University Libraries, The University of Texas at Austin was made possible under a limited license grant from the author who has retained all copyrights in the works. |
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