High Accuracy 65nm OPC Verification: Full Process Window Model vs. Critical Failure ORC

It is becoming more and more difficult to ensure robust patterning after OPC due to the continuous reduction of layout dimensions and diminishing process windows associated with each successive lithographic generation. Lithographers must guarantee high imaging fidelity throughout the entire range of normal process variations. The techniques of Mask Rule Checking (MRC) and Optical Rule Checking (ORC) have become mandatory tools for ensuring that OPC delivers robust patterning. However the first method relies on geometrical checks and the second one is based on a model built at best process conditions. Thus those techniques do not have the ability to address all potential printing errors throughout the process window (PW). To address this issue, a technique known as Critical Failure ORC (CFORC) was introduced that uses optical parameters from aerial image simulations. In CFORC, a numerical model is used to correlate these optical parameters with experimental data taken throughout the process window to predict printing errors. This method has proven its efficiency for detecting potential printing issues through the entire process window [1]. However this analytical method is based on optical parameters extracted via an optical model built at single process conditions. It is reasonable to expect that a verification method involving optical models built from several points throughout PW would provide more accurate predictions of printing errors for complex features. To verify this approach, compact optical models similar to those used for standard OPC were built and calibrated with experimental data measured at the PW limits. This model is then applied to various test patterns to predict potential printing errors. In this paper, a comparison between these two approaches is presented for the poly layer at 65 nm node patterning. Examples of specific failure predictions obtained separately with the two techniques are compared with experimental results. The details of implementing these two techniques on full product layouts are also included in this study

Adoption of opc and the impact on design and layout

With the adoption of various combinations of resolution enhancement techniques (RET) for IC lithography, different process constraints are placed on the IC layout. The final layout used for mask production is dramatically different than the original designer’s intent. To insure that EDA tools developed for applying RET techniques can have optimal performance, layout methodology must change to create a true “target ” layer that represents the actual design intent. Verification of the final layout is then expanded from LVS and DRC to also include lithography process simulation, which compares results to this desired “target” and governs the application of RET

Adoption of opc and the impact on design and layout

With the adoption of various combinations of resolution enhancement techniques (RET) for IC lithography, different process constraints are placed on the IC layout. The final layout used for mask production is dramatically different than the original designer’s intent. To insure that EDA tools developed for applying RET techniques can have optimal performance, layout methodology must change to create a true “target ” layer that represents the actual design intent. Verification of the final layout is then expanded from LVS and DRC to also include lithography process simulation, which compares results to this desired “target” and governs the application of RET

Accurate mask model for advanced nodes

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Evaluation of OPC Mask Printing with a Raster Scan Pattern Generator

MEBES ® 50 kV mask pattern generators use Raster Graybeam ™ writing, providing an effective grid that is 32 × finer than the print grid. The electron beam size and print pixel size are variable between 60 nm and 120 nm, allowing a tradeoff between resolution and write time. Raster scan printing optimizes throughput by transferring precisely the amount of data to the mask that is consistent with the chosen resolution. As with other raster output devices, mask write times are not affected by pattern complexity. This paper examines the theoretical performance of Raster Graybeam for model-based optical proximity correction (OPC) patterns and provides examples of mask patterning performance. A simulation tool is used to model the MEBES eXara ™ system writing strategy, which uses four writing passes, interstitial print grids, offset scans, and eight dose levels per pass. It is found that Raster Graybeam produces aerial image quality equivalent to the convolution of the input pattern data with a Gaussian point spread function. Resolution of 90 nm is achieved for equal lines and spaces, supporting subresolution assist features. Angled features are a particular strength of raster scan patterning, with feature quality and write time that are independent of feature orientation