Evaluation of cost-driven triple patterning lithography decomposition

As the current 193nm ArF immersion lithography technology is approaching its bottleneck, multiple patterning techniques have to be introduced to fulfill the process requirements in the sub-20nm technology node. Among all different patterning techniques, triple patterning lithography (TPL) is one of the major options for 14 nm or 10 nm technology node, which has a substantial requirement on process control and cost control at the same time. Patterning decomposition is the key step for the success of TPL. In the conventional TPL lithography, a constant spacing distance d_min is used to determine whether two nearby features should be on the same mask. However, in reality, the no-print and the best-print scenarios can never be separated by a clear constant number. Indeed, the decomposition criteria is closed related to lithography printing parameters, pattern types, and geometry distances. The conventional spacing rule with a constant number is way too simple. In this paper, we re-evaluate the conventional minimum spacing rule and utilize a local pattern cost model to evaluate our previous optimal TPL algorithm. Given a user specified local pattern aware cost model, our algorithm can easily embed the model into our formulation and compute an optimal solution. This demonstrates the extendability and robustness of our previous TPL algorithm.