Optical Parametric Model Optimization Using Near Field Intensity
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for structural analysis using rigorous couple wave approach (RCWA) are inefficient due to the need for extensive computation and time-consuming trial and error processes in optimizing optical parametric models, especially for three-dimensional structures, which require cross-sectional images that are costly, labor-intensive, and destructive to obtain.
Innovation Solution
The method involves determining near optical field responses at different wavelengths and angles to identify regions of high optical field intensity, allowing for targeted modification of optical models to improve fit quality, thereby reducing the number of candidate model loops and computation time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the number of diffraction orders is increased to improve simulation accuracy, then the accuracy of RCWA solution is improved, but the computation time increases nonlinearly
Solution Approach 1:
The patent applies local quality by identifying and focusing computational resources on specific regions of high optical field intensity rather than uniformly processing the entire structure. By locating common regions of high intensity across multiple wavelengths and angles, the method selectively refines the model in critical areas while using coarser modeling in less important regions, thus achieving high accuracy where needed while reducing overall computation time.
Solution Approach 2:
The patent employs preliminary action by performing a preliminary scan across multiple wavelengths and angles of incidence to identify regions of high optical field intensity before finalizing the model. This preliminary identification of critical regions allows subsequent optimization efforts to be focused efficiently, avoiding unnecessary computations in areas that do not significantly impact the overall measurement accuracy.
2Measurement precision
If cross-sectional electron micrographs are obtained to guide model construction, then the model accuracy is improved, but the process becomes costly, labor-intensive, and destructive
Solution Approach 1:
The patent uses optical field intensity distributions as virtual copies or proxies for physical cross-sectional imaging. Instead of physically sectioning and imaging the structure with electron microscopes, the method creates computational representations of the optical fields that interact with the structure, allowing model validation and guidance without destroying the actual sample or requiring complex preparation procedures.
Solution Approach 2:
The patent replaces the mechanical and chemical processes of physical cross-sectioning and electron microscopy with optical field simulations. By substituting physical destruction with computational modeling of optical interactions, the method achieves similar model-guiding functionality without the costs, time, and sample destruction associated with traditional electron micrography.
3Productivity
If the number of candidate model loops is reduced to decrease computation time, then the productivity is improved, but the measurement precision may be compromised
Solution Approach 1:
The patent applies local quality by concentrating optimization iterations on specific parameters and regions that have the greatest impact on measurement accuracy, rather than uniformly exploring all possible model variations. By identifying critical regions of high optical field intensity, the method focuses computational effort where it matters most, achieving good model fit with fewer overall iterations.
Solution Approach 2:
The patent uses preliminary identification of high-intensity regions and their sensitivity to structural parameters to guide the optimization process. This preliminary analysis allows the method to prioritize which model parameters to adjust and in what order, reducing the number of iterative loops needed to achieve convergence while maintaining measurement precision.
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 reduces the time needed to achieve good model results by quickly identifying critical regions for modification, optimizing optical parametric models with improved accuracy and efficiency, and enhancing sensitivity to structural parameters.
Implementation Method 1
determining near optical field responses at different wavelengths and angles to identify regions of high optical field intensity
Data Source
AI summary
Optimization of optical parametric models for structural analysis using optical critical dimension metrology is described. A method includes determining a first optical model fit for a parameter of a structure. The first optical model fit is based on a domain of quantities for a first model of the structure. A first near optical field response is determined for a first quantity of the domain of quantities and a second near optical field response is determined for a second, different quantity of the domain of quantities. The first and second near optical field responses are compared to locate a common region of high optical field intensity for the parameter of the structure. The first model of the structure is modified to provide a second, different model of the structure. A second, different optical model fit is determined for the parameter of the structure based on the second model of the structure.