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The graphoepitaxial assembly of cylinder-forming block copolymers assembled into holes is investigated through theoretically informed coarse grained Monte Carlo simulations (TICG MC). The aim is to identify conditions leading to assembly of cylinders that span the entire thickness of the holes, thereby enabling applications in lithography. Three hole geometries are considered, including cylinders, elliptical cylinders, and capsule-shaped holes. Four distinct morphologies of cylinder forming poly(styrene-b-methyl methacrylate) (PS-b-PMMA) block copolymers are observed in cylinders and elliptical holes, including cylinders, spheres, partial cylinders, and wall-bound cylinders. Additional morphologies are observed in capsuleshaped holes. PMMA cylinders that extend through the entire hole are found with PMMA-wetting surfaces; a weak wetting condition is needed on the bottom of the hole and a strong wetting condition is necessary on the sides of the hole. Simu-lated are also used to explore the morphologies that arise when holes are overfilled, or when PMMA homopolymers are added in blends with copolymers. We find that overfilling can alter considerably the morphological behavior of copolymers in cylinders and, for blends; we find that when the homopolymer concentration is >10%, the range of conditions for formation of PMMA cylinders that extend through the entire hole is increased. In general, results from simulations (TICG) are shown to be comparable to those of self-consistent (SCFT) calculations, except for conditions where fluctuations become important.identifying the conditions leading to formation of ideal cylinders that span the entire thickness of the confining hole. In this work, we use simulations to identify such conditions. Graphoepitaxy relies on topography to guide the assembly of block copolymers. Segalman et al. [8][9][10][11] used primarily poly (styrene-b-2vinyl pyridine) (PS-b-P2VP) sphere forming block copolymers. Work by Cheng et al. 20,21 considered poly(styrene-b-ferrocenylsilane) (PS-b-PFS) sphere-forming diblock copolymers. One important outcome of that work was to show that defects in the confining walls can have a pronounced influence in the resulting morphology, and give rise to defective microdomains. 22 Lamellar-forming poly(styrene-b-ethyl-alt-propylene) (PS-b-PEP) block copolymers have also been assembled in trenches under preferential wetting of the PS, 23,24 and Hammond andThis article was published online on 16 December 2014. An error was subsequently identified. This notice is included in the online and print versions to indicate that it has been corrected 31 January 2015.

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In this paper we present a method that optimizes the OPC model generation process. The elements in this optimized flow include: an automated test structure layout engine; automated SEM recipe creation and data collection; and OPC model anchoring/validation software. The flow is streamlined by standardizing and automating these steps and their inputs and outputs. A major benefit of this methodology is the ability to perform multiple OPC "screening" refinement loops in a short time before embarking on final model generation. Each step of the flow is discussed in detail, as well as our multi-pass experimental design for converging on a final OPC data set. Implementation of this streamlined process flow drastically reduces the time to complete OPC modeling, and allows generation of multiple complex OPC models in a short time, resulting in faster release and transfer of a next-generation product to manufacturing.Keywords: CD-SEM, OPC, pattern matching, SEM image analysis, edge placement error, automatic recipe generation INTRODUCTIONCreating advanced OPC models for new technology nodes is an increasingly challenging aspect of lithographic process development. Increased complexity of patterns and illumination conditions and an ever increasing calibration space with each technology node means that each critical layer requires hundreds to thousands of CD-SEM measurements to characterize OPC behavior adequately and allow generation of an accurate OPC model. 1 With each new technology node, the number of levels requiring model-based OPC (MBOPC) increases significantly. As illustrated in Figure 1, the number of levels employing MBOPC has been rising with each successive node since the 180-nm node; the increase in the number of MBOPC levels greatly accelerated between the 130 nm and 90-nm nodes and has been increasing at about the same rate ever since. 2 In addition to more levels needing MBOPC, use of assist features is increasing significantly, and the number of variables needed to describe and implement proximity correction adequately is escalating (Fig. 2). Sub-resolution assist feature (SRAF) optimization requires multiple placement scenarios for each line/space or hole combination, further increasing the need for a very large body of data to develop optimal OPC corrections. In addition to the large body of data required, multiple passes and iteration of OPC generation are required to gain optimal correction. * mecoles@ti.com; phone 1 972 995-2205; fax 1 972 995-6383

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