Regularized level-set-based inverse lithography algorithm for IC mask synthesis

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.

Fast Level-Set-Based Inverse Lithography Algorithm for Process Robustness Improvement and Its Application

Inverse lithography technology （ILT） is one of the promising resolution enhancement techniques （RETs）, as the advanced integrated circuits （IC） technology nodes still use the 193 nm light source. Among all the algorithms for ILT, the level-set-based ILT （LSB-ILT） is a feasible choice with good production result in practice. However, existing ILT algorithms optimize masks at nominal process condition without giving sufficient attention to the process variations, and thus the optimized masks show poor performance with focus and dose variations. In this paper, we put forward a new LSB-ILT algorithm for process robustness improvement with fast convergence. In order to account for the process variations in the optimization, we adopt a new form of the cost function by adding the objective function of process variation band （PV band） to the nominal cost. We also adopt the hybrid conjugate gradient （CG） method to reduce the runtime of the algorithm. We perform experiments on ICCAD 2013 benchmarks and the results show that our algorithm outperforms the top two winners of the ICCAD 2013 contest by 6.5%. We also adopt the attenuated phase shift mask （att-PSM） in the experiment with test cases from industry. The results show that our new algorithm has a fast convergence speed and reduces the process manufacturability index （PMI） by 38.77% compared with the LSB-ILT algorithm without the consideration of PV band.