Metrology Target Verification Using OCD-Based Design Compensation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current semiconductor metrology target designs lack accuracy due to inaccuracies in stack and topography descriptions, leading to potential incorrect target geometry selection and reduced measurement fidelity.
Innovation Solution
The proposed method involves using OCD data to estimate discrepancies between designed and actual metrology targets, adjusting the target design model to compensate for these discrepancies, and incorporating verification targets optimized for OCD sensor measurements to enhance accuracy and fidelity of metrology measurements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional metrology target designs are used, then manufacturing simplicity is maintained, but measurement precision deteriorates due to inaccuracies in stack and topography descriptions
Solution Approach 1:
The patent applies preliminary action by performing OCD measurements and discrepancy analysis on metrology targets before final target geometry selection. The method estimates discrepancies between target models and actual targets, then adjusts the metrology target design model in advance to compensate for these discrepancies, ensuring higher measurement precision before the actual measurement process begins.
Solution Approach 2:
The patent implements feedback by using OCD measurement data to estimate discrepancies between designed and actual metrology targets. This feedback loop allows the system to adjust and refine the target design model based on actual measurement results, continuously improving measurement precision through iterative optimization.
2Measurement precision
If target design models are adjusted to compensate for discrepancies, then measurement precision improves, but manufacturing complexity increases
Solution Approach 1:
The patent applies parameter changes by adjusting the metrology target design model parameters based on OCD measurement data and estimated discrepancies. The method modifies target geometry parameters, stack descriptions, and topography characteristics to compensate for manufacturing variations, thereby improving measurement precision while maintaining manufacturability through controlled parameter optimization.
3Measurement precision
If verification targets optimized for OCD sensors are incorporated, then measurement fidelity improves, but device complexity increases
Solution Approach 1:
The patent applies universality by designing verification targets that serve multiple functions: they are optimized for OCD sensor measurements while also being compatible with other metrology tools. The verification targets incorporate features that enable both OCD-based discrepancy estimation and general metrology measurements, reducing the need for separate target designs for different measurement systems.
Data Source
AI summary
Metrology target design methods and verification targets are provided. Methods comprise using OCD data related to designed metrology target(s) as an estimation of a discrepancy between a target model and a corresponding actual target on a wafer, and adjusting a metrology target design model to compensate for the estimated discrepancy. The dedicated verification targets may comprise overlay target features and be size optimized to be measureable by an OCD sensor, to enable compensation for inaccuracies resulting from production process variation. Methods also comprise modifications to workflows between manufacturers and metrology vendors which provide enable higher fidelity metrology target design models and ultimately higher accuracy of metrology measurements.