Fast and accurate lithography simulation and optical proximity correction for nanometer design for manufacturing
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.