Optical Proximity Correction Modeling for Topography Effects
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Solution Overview
Problem
In the design of integrated circuits, the optical proximity effect causes pattern distortion due to diffraction and light interference, leading to inaccuracies in semiconductor device fabrication, particularly as feature sizes approach the wavelength of light sources used in photolithography processes.
Innovation Solution
An optical proximity correction (OPC) modeling method and system that predicts topography effects by generating region filters, edge functions, and characteristic kernels to model the interactions between material patterns and boundary regions, allowing for the generation of bulk and edge image signals to create a final model signal that corrects for pattern distortions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If the wavelength of light source is reduced to achieve smaller feature sizes, then manufacturing precision is improved, but optical proximity effects such as diffraction and light interference increase causing pattern distortion
Solution Approach 1:
The patent applies optical proximity correction (OPC) that performs preliminary modifications to the photomask pattern design before fabrication. The system calculates and applies corrective features such as serifs, hammerheads, and spacing adjustments to compensate for anticipated diffraction and interference effects, thereby pre-correcting the pattern to achieve the desired final geometry despite optical distortions
Solution Approach 2:
The patent modifies various parameters of the photomask pattern including line widths, spacing, angles, and the addition of auxiliary features. By changing these geometric parameters in the OPC process, the system compensates for optical proximity effects and achieves accurate pattern transfer at reduced feature sizes
2Measurement precision
If conventional OPC methods are used without considering pattern stack structure, then processing complexity is reduced, but prediction accuracy of topography effects is insufficient
Solution Approach 1:
The patent segments the pattern stack structure into multiple layers and materials, modeling each layer's optical properties separately. The OPC system divides the complex stack into manageable components (e.g., mandrel layer, spacer layer, material layers) and calculates their individual contributions to topography effects, enabling accurate prediction while maintaining computational feasibility
Solution Approach 2:
The patent introduces an intermediate modeling step that calculates topography effects as a separate component before final OPC application. The system uses characteristic kernels and region filters as intermediaries to model the interaction between light and the pattern stack structure, bridging the gap between simplified conventional OPC and the need for accurate topography prediction
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The OPC modeling method effectively predicts and mitigates topography effects in pattern stack structures, ensuring accurate pattern transfer and reducing distortions in semiconductor device fabrication, thereby improving the precision of integrated circuit design.
Implementation Method 1
pattern distortion may occur due to diffraction, light interference, etc.
Implementation Method 2
pattern distortion may occur due to diffraction, light interference, etc.
Data Source
AI summary
An optical proximity correction modeling method for predicting a topography effect due to a pattern stack structure that includes a first material pattern, a second material pattern, and a boundary region between the first material pattern and the second material pattern. The method includes generating a first region filter that corresponds to the first material pattern, a second region filter that corresponds to the second material pattern, and an edge function corresponding to the boundary region; generating a bulk image signal from a layout using the first region filter and the second region filter; generating an edge image signal from the layout using the edge function, a characteristic kernel that represents characteristics of the boundary region, the first region filter, and the second region filter; and generating a final model signal from the bulk image signal and the edge image signal.