Optical Metrology Overlay Accuracy via Sensitivity Landscape Analysis
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Solution Overview
Problem
Current optical metrology technologies face inaccuracies due to large process variations, which can lead to significant errors in overlay measurements, especially in the research and development phase of chip development, and are challenging to accurately estimate in real-time, particularly in overlay field scatterometry where hardware parameters averaging results in loss of overlay sensitivity.
Innovation Solution
The method involves deriving a continuous dependency of metrology metrics on recipe parameters through simulation or preparatory measurements, analyzing these dependencies to determine optimal metrology recipes, and conducting measurements accordingly, thereby improving sensitivity and accuracy by identifying regions of low or zero inaccuracy and adjusting hardware and target designs to enhance measurement robustness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If large process variations are present in the metrology signal, then the overlay measurement becomes more challenging and inaccurate, but the accuracy budget is consumed significantly by these process variation errors
Solution Approach 1:
The patent performs preliminary actions by conducting simulation studies and preparatory measurements to derive continuous dependencies of metrology metrics on recipe parameters before actual measurements. This allows the system to pre-characterize the accuracy landscape and identify optimal measurement conditions, thereby reducing the impact of process variations during actual overlay measurements.
Solution Approach 2:
The patent changes parameters by optimizing recipe parameters (such as wavelength, polarization, and other measurement settings) based on the derived continuous dependencies. By adjusting these parameters to operate in regions of low or zero inaccuracy, the system reduces the harmful effect of process variations on measurement accuracy.
2Ease of operation
If hardware parameters are averaged in overlay field scatterometry, then the measurement process becomes simpler, but overlay sensitivity is lost
Solution Approach 1:
The patent segments the measurement process into two distinct phases: a simulation/preparatory phase where continuous dependencies are derived, and a measurement phase where optimized recipes are applied. This segmentation allows the system to maintain simplicity in the actual measurement process while achieving high overlay sensitivity through pre-optimized parameters.
3Measurement precision
If large scale recipe and target design optimizations are performed, then measurement accuracy improves, but the complexity and time required for optimization increases
Solution Approach 1:
The patent performs the complex optimization actions in advance during simulation and preparatory measurements. By deriving continuous dependencies beforehand, the system eliminates the need for complex real-time optimizations during actual measurements, thereby reducing operational complexity while maintaining high accuracy.
Solution Approach 2:
The patent creates a computational model (copy) of the metrology system through simulation studies. This virtual model allows extensive optimization and characterization of the accuracy landscape without requiring physical experimentation for each optimization step, thereby reducing the complexity and time required for optimization.
4Measurement precision
If real-time estimation of process variation errors is performed, then measurement accuracy can be maintained, but the computational resources and time required increase significantly
Solution Approach 1:
The patent performs error characterization actions in advance by deriving continuous dependencies through simulation and preparatory measurements. This pre-characterization allows the system to quickly identify optimal measurement conditions without requiring computationally intensive real-time error estimation, thereby reducing computational time while maintaining accuracy.
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
This approach significantly enhances the accuracy of optical metrology by reducing inaccuracies in real-time and during the development phase, improving overlay sensitivity and performance, and achieving superior accuracy across different measurement conditions and technologies.
Implementation Method 1
This asymmetry is present in the electromagnetic signal because the latter reflects the interference of electric fields with relative phases that carry the overlay information
Implementation Method 2
In overlay scatterometry (be it pupil scatterometry or field scatterometry) the overlay mark is commonly a grating-over-grating structure
Data Source
AI summary
Methods are provided for deriving a partially continuous dependency of metrology metric(s) on recipe parameter(s), analyzing the derived dependency, determining a metrology recipe according to the analysis, and conducting metrology measurement(s) according to the determined recipe. The dependency may be analyzed in form of a landscape such as a sensitivity landscape in which regions of low sensitivity and/or points or contours of low or zero inaccuracy are detected, analytically, numerically or experimentally, and used to configure parameters of measurement, hardware and targets to achieve high measurement accuracy. Process variation is analyzed in terms of its effects on the sensitivity landscape, and these effects are used to characterize the process variation further, to optimize the measurements and make the metrology both more robust to inaccuracy sources and more flexible with respect to different targets on the wafer and available measurement conditions.