论文部分内容阅读
Inverse lithography technology(ILT)is one of the promising resolution enhancement techniques,as the advanced IC technology nodes still use the 193 nm light source.In ILT,optical proximity correction(OPC)is treated as an inverse imaging problem to find the optimal solution using a set of mathematical approaches.Among all the algorithms for ILT,the level-set-based ILT(LSB-ILT)is a feasible choice with good production in practice.However,the manufacturability of the optimized mask is one of the critical issues in ILT;that is,the topology of its result is usually too complicated to manufacture.We put forward a new algorithm with high pattern fidelity called regularized LSB-ILT implemented in partially coherent illumination(PCI),which has the advantage of reducing mask complexity by suppressing the isolated irregular holes and protrusions in the edges generated in the optimization process.A new regularization term named the Laplacian term is also proposed in the regularized LSB-ILT optimization process to further reduce mask complexity in contrast with the total variation(TV)term.Experimental results show that the new algorithm with the Laplacian term can reduce the complexity of mask by over 40%compared with the ordinary LSB-ILT.
Inverse lithography technology (ILT) is one of the promising resolution enhancement techniques, as the advanced IC technology nodes still use the 193 nm light source. In ILT, optical proximity correction (OPC) is treated as an inverse imaging problem to find the optimal solution using a set of mathematical approaches. Among all the algorithms for ILT, the level-set-based ILT (LSB-ILT) is a feasible choice with good production in practice. However, the manufacturability of the optimized mask is one of the critical issues in ILT; that is, the topology of its result is usually too complicated to manufacture. We put forward a new algorithm with high pattern fidelity called regularized LSB-ILT implemented in partially coherent illumination (PCI), which has the advantage of reducing mask complexity by suppressing the isolated irregular holes and protrusions in the edges generated in the optimization process. A new regularization term named the Laplacian term is also proposed in the regularized LSB-ILT optimiza tion process to further reduce mask complexity in contrast with the total variation (TV) term. Experimental results show that the new algorithm with the Laplacian term can reduce the complexity of mask by over 40% compared with the ordinary LSB-ILT.