KEYWORDS: Design for manufacturing, Finite element methods, Process modeling, Computer aided design, Manufacturing, Optimization (mathematics), Data modeling, Convolution, Personal protective equipment, Semiconducting wafers
A layout design that passes the design rule check (DRC) may still have manufacturing problems today, especially around
areas of critical patterns. Thus a design-for-manufacturability (DfM) model, which can simulate the process from
designed layout to wafer and predict the final contours, is necessary. A new kind of DfM model called free-elementmodel
(FEM) is proposed in this paper. The framework of FEM is borrowed from the forward process model, which is
basically a set of convolution kernels in matrix form, yet the unknown variables are the kernel elements instead of
process parameters. The modeling process is transformed into a non-linear optimization problem, with equality
constraints which involve norm-2 regulation of kernels and inner production of any two kernels to keep the
normalization and orthogonality of optimized kernels. Gradient-based method with Lagrange penalty function is
explored to solve the optimization problem to minimize the difference between simulated contours and real contours.
The dimension of kernels in FEM is determined by the cutoff frequency and the ambit. Since kernels are calculated by
optimization method instead of decomposition of transmission cross coefficient (TCC), every element of kernels
becomes a factor to describe the process. FEM is more flexible, and in it all effects that can be integrated into
convolution kernels join naturally, such as the resist deviation and asymmetry of the process. No confidential process
parameters, for example NA and defocus, appear in FEM explicitly, and thus the encapsulated FEM is suitable for IC
manufacturers to publish. Moreover, enhancements and supplements to FEM are discussed in this paper, including the
sufficiency of test patterns. In our experiments, DfM models for 2 process lines are generated based on test patterns, and
the results show that the simulated shapes have an area error less than 2% compared to the real shapes of test patterns and an area error less than 3% compared to the shapes in typical blocks chosen from chip for verification purpose. The root mean square error of contour deviation between the 2 simulation results from FEM and conventional lithographic model is 10nm in a 65nm process.
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