No abstract

In this paper, we study row-based detailed placement refinement for triple patterning lithography (TPL), which asks to find a refined detailed placement solution as well as a valid TPL layout decomposition under the objective of minimizing the number of stitches and the half-perimeter wirelength. Our problem does not have precoloring solutions of cells as the input, and it allows using techniques, including white space insertion, cell flipping, adjacent-cell swapping, and vertical cell movement, to optimize the solution quality. We first present (resource-constrained) shortest-path-based algorithms for several TPL-aware single-row placement problems that allow or disallow perturbing a given cell ordering. Based on these algorithms, we then propose an approach to our TPL-aware detailed placement refinement problem, which first minimizes the number of stitches and then minimizes the wirelength. Finally, we report extensive experimental results to demonstrate the effectiveness and efficiency of our approach.Index Terms-Detailed placement refinement, layout decomposition, triple patterning lithography (TPL).

No abstract

Extreme Ultraviolet lithography requires defect free multilayer-coated masks. The defects in multilayer-coated masks originate from several sources including: the incoming substrate, pre-multilayer deposition cleaning, multilayer deposition, and handling processes. A previous study showed the majority of currently detectable defects are contributed by the incoming substrate. The purpose of this study is to understand the ability of multilayer deposition to modulate the size and shape of substrate pits, and to, ultimately, enable us to determine if a defect of a particular size and shape is tolerable, and will result in a non-printable pit after coating. In order to execute a systematic study, pits with controlled sizes and shapes were required. Programmed pit arrays were generated using Focused Ion Beam (FIB). The arrays were designed to contain pits of various widths and depths. The physical size of these pits was measured using Atomic Force Microscope (AFM) and Scanning Electron Microscope (SEM) both before and after multilayer deposition. These programmed pit arrays were also used to probe the sensitivity of a state of the art Lasertec M1350 defect inspection system to defect size and shape both before and after coating. Finally, the results were compared to those from natural pits. The programmed defects generated in this study will also enable further development of defect mitigation by other planarization techniques as well as improving inspection recipes.