Lithography Process Model Calibration via Contour Alignment
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Solution Overview
Problem
Current lithographic processes face challenges in accurately reproducing patterns with features smaller than the classical resolution limit, leading to difficulties in achieving precise electrical functionality and performance, particularly due to limitations in projection optics and design layouts.
Innovation Solution
A method is introduced to improve process models by aligning measured contours from image capture devices with simulated contours, determining offsets, and calibrating the models to reduce differences, which involves modifying features such as diffusion rates and acid/base concentrations in optical proximity correction models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If conventional lithographic processes are used to transfer patterns, then manufacturing throughput is maintained, but manufacturing precision deteriorates for features smaller than the classical resolution limit
Solution Approach 1:
The patent modifies parameters within the process model, specifically adjusting diffusion rates and acid/base concentrations in optical proximity correction models to improve pattern reproduction accuracy for sub-resolution features
Solution Approach 2:
The patent creates a calibrated process model that copies and simulates the actual lithographic process behavior, allowing virtual optimization before physical manufacturing. This involves aligning measured contours with simulated contours to create an accurate digital twin of the patterning process
2Manufacturing precision
If optical proximity correction is applied to improve pattern accuracy, then manufacturing precision improves, but computational overhead increases
Solution Approach 1:
The patent performs optical proximity correction calculations in advance during the model calibration phase, storing the corrected parameters for reuse. This preliminary computation avoids repeated heavy calculations during actual pattern generation, reducing computational overhead while maintaining precision
Solution Approach 2:
The patent optimizes computational parameters by adjusting diffusion rates and chemical concentrations in the process model, achieving accurate pattern prediction with reduced computational complexity through simplified yet effective parameter adjustments
Data Source
AI summary
A method for improving a process model for a patterning process, the method including obtaining a) a measured contour from an image capture device, and b) a simulated contour generated from a simulation of the process model. The method also includes aligning the measured contour with the simulated contour by determining an offset between the measured contour and the simulated contour. The process model is calibrated to reduce a difference, computed based on the determined offset, between the simulated contour and the measured contour.