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Self-Aligned Quadruple Patterning (SAQP) is one of the most leading techniques in 14 nm node and beyond. However, the construction of feasible layout configurations must follow stricter constraints than in LELELE triple patterning process. Some SAQP layout decomposition methods were recently proposed. However, due to strict constraints required for feasible SAQP layout, the decomposition strategy considering an arbitrary layout does not seem realistic. In this paper, we propose a new routing method for feasible SAQP layout requiring no decomposition. Our method performs detailed routing by correct-by-construction approach and offers compliant layout configuration without any pitch conflict.

In this paper, we propose a new flexible routing method for Self-Aligned Double Patterning (SADP). SADP is one of the most promising candidates for patterning sub-20 nm node advanced technology but wafer images must satisfy tighter constraints than litho-etch-litho-etch process. Previous SADP routing methods require strict constraints induced from the relation between mandrel and trim patterns, so design freedom is unexpectedly lost. Also these methods assume to form narrow patterns by trimming process without consideration of resolution limit of optical lithography. The proposed method realizes flexible SADP routing with dynamic coloring requiring no decomposition to extract mandrel patterns and no worries about coloring conflicts. The proposed method uses realizable trimming process only for insulation of patterns. The effectiveness of the proposed method is confirmed in the experimental comparisons.

A neural network (NN)-based approach with a lumped model is found to be much more promising to predict process proximity effects (PPEs) caused through space patterning processes than a conventional tandem-based approach with a consecutive physical model. The NN-based lumped approach can improve PPE prediction accuracy by 25% compared to the conventional tandem-based approach, subject to the same workload of experimental data acquisition, and reach the specification of PPE residual in 3x nm node with smaller amounts of data volume than any other approach. Process proximity correction scheme using the NN-based lumped model built for 3x nm node can achieve the expected correction accuracy for various kinds of one-dimensional patterns. It is anticipated that the NN-based lumped PPE prediction model will greatly improve the prediction and/or correction accuracy in the space patterning technology process for 3x nm node and beyond.

Flow of fixing of hot spot induced by optical variation among exposure tools is discussed for quick ramp-up of high volume products. To achieve robust pattern formation for optical variation, following hot spot detection and fixing approaches are introduced: i) at the design stage, hot spot detection within the optical variation space and hot spot fixing by layout modification or OPC optimization, ii) in order to efficiently detect hot spots within the optical variation space, lithography simulation by combinations of optical parameters determined by the design of experiment (DoE), iii) at the manufacturing stage, hot spot fixing by adjustment of optical parameters using the multi-variable optimization to match OPE between the primary and secondary exposure tool.

Robust optical proximity correction (OPC) and design for manufacturability (DFM) methodology for optical variation among exposure tools is proposed. It is demonstrated that application of the methodology improves standard deviation of CD difference for target CD by 33% compared with the case of using the conventional methodology. Under the low-k1 lithography condition, hot spots induced by optical variation among exposure tools delay ramp-up of production of high-volume products. To realize robust pattern formation for all exposure tools, the following new methodologies are introduced : i) OPC modeling methodology using actual optics of primary tool, ii) OPC processing methodology using averaged or designed optics, iii) at the design stage, hot spot detection within the optical variation space centered on average or designed optics and hot spot fixing by layout modification or OPC optimization, iv) at the manufacturing stage, hot spot detection using actual optics and hot spot fixing by optical adjustment of troubled tool.