Optical Metrology Wavelength Pruning for Wood Anomaly Errors
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Solution Overview
Problem
Conventional methods for optical metrology face challenges in accurately measuring critical dimensions of grating structures due to resonance issues caused by wavelengths or angles near Wood Anomalies, leading to large measurement errors and high computational costs.
Innovation Solution
The implementation of multivariate outlier detection technology to identify and remove data outliers, specifically wavelengths or angles that cause resonance, from the dataset, thereby generating a modified dataset for more accurate measurements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If wavelengths near Wood Anomaly are used for measurement, then parameter sensitivity increases, but measurement errors increase significantly
Solution Approach 1:
The patent extracts and removes problematic wavelengths (outliers) from the measurement dataset that cause Wood Anomaly and resonant phenomena. By identifying and excluding these specific wavelengths through automated analysis, the system eliminates the source of measurement errors while retaining the beneficial parameter sensitivity of other wavelengths.
Solution Approach 2:
The patent changes the measurement parameters by dynamically selecting and excluding specific wavelengths based on their sensitivity characteristics. The system analyzes wavelength-dependent data and adjusts the dataset to include only those wavelengths that provide high parameter sensitivity without introducing measurement errors from resonant phenomena.
2Measurement precision
If comprehensive wavelength analysis is performed to identify outliers, then measurement accuracy improves, but computational costs increase
Solution Approach 1:
The patent performs preliminary analysis of wavelength-dependent or angle-dependent data before actual measurements to identify and remove outlier wavelengths. This upfront computational effort creates a optimized dataset that reduces the need for complex error correction during subsequent measurements, ultimately lowering total computational costs.
Solution Approach 2:
The patent creates a modified dataset that is a filtered copy of the original comprehensive wavelength data. This copied dataset excludes problematic wavelengths while maintaining the essential measurement information, allowing accurate measurements with reduced computational requirements compared to processing the full wavelength range.
3Adaptability or versatility
If multiple wavelengths are used for CD measurement, then measurement coverage improves, but inclusion of resonant wavelengths introduces errors
Solution Approach 1:
The patent applies local quality by treating different wavelengths differently based on their individual characteristics. Instead of uniformly including or excluding wavelengths, the system analyzes each wavelength's behavior and selectively includes only those that provide good measurement coverage without introducing resonant errors, giving each wavelength its appropriate role in the measurement process.
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 reduces measurement errors and computational costs by excluding overly sensitive wavelengths or angles, resulting in more stable and accurate regression results without the need for physical modeling of Wood anomalies or structure resonances.
Implementation Method 1
A rigorous coupled wave analysis (RCWA) and similar algorithms have been widely used for the study and design of diffraction structures
Implementation Method 2
Wavelengths at or near a Wood Anomaly (referring to a wavelength of electromagnetic radiation passing through a grating that produces a significant variation in intensity in comparison with other wavelengths) or other resonant phenomena may show parameter sensitivity that are orders of magnitude larger
Data Source
AI summary
Automatic wavelength or angle pruning for optical metrology is described. An embodiment of a method for automatic wavelength or angle pruning for optical metrology includes determining a model of a structure including a plurality of parameters; designing and computing a dataset of wavelength-dependent or angle-dependent data for the model; storing the dataset in a computer memory; performing with a processor an analysis of the dataset for the model including applying an outlier detection technology on the dataset, and identifying any data outliers, each data outlier being a wavelength or angle; and, if any data outliers are identified in the analysis of the dataset of the model, removing the wavelengths or angles corresponding to the data outliers from the dataset to generate a modified dataset, and storing the modified dataset in the computer memory.