Optical Metrology Recipe Optimization for Semiconductor Structures
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Solution Overview
Problem
Current optical metrology techniques face challenges in accurately measuring complex, high-aspect ratio, three-dimensional semiconductor structures with opaque materials due to limited penetration of optical radiation and increased parameter correlation, leading to longer measurement times and reduced measurement precision.
Innovation Solution
The method involves optimizing measurement recipes by reducing the set of measurement technologies and machine parameters using process variation and spectral sensitivity information to create a constrained measurement model, allowing for faster and more precise characterization of structural and material characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple measurement technologies and large ranges of machine parameters are used to measure complex semiconductor structures, then measurement coverage and characterization capability are improved, but measurement time and computation time increase significantly
Solution Approach 1:
The patent segments the measurement process by dividing complex structures into multiple measurement zones and using different measurement technologies for different zones. This allows selective measurement of critical areas without measuring the entire structure, reducing overall measurement time while maintaining coverage of important features.
Solution Approach 2:
The patent applies partial action by performing measurements at selected machine parameters rather than scanning the entire parameter range. By identifying critical parameter regions that provide sufficient measurement information, the system achieves adequate characterization with reduced measurement time and computational load.
2Adaptability or versatility
If measurements are performed over large ranges of machine parameters, then measurement coverage is improved, but illumination intensity at any particular wavelength decreases and signal uncertainty increases
Solution Approach 1:
The patent applies local quality by concentrating measurement resources at specific machine parameters where the structure exhibits maximum sensitivity. Instead of uniform measurement across all parameters, the system identifies and focuses on local regions in parameter space that provide the most information, thereby improving signal quality and reducing uncertainty.
Solution Approach 2:
The patent performs measurements at selected machine parameters rather than scanning the entire parameter range. By identifying critical parameter regions that provide sufficient measurement information, the system achieves adequate characterization with reduced signal uncertainty.
3Adaptability or versatility
If multiple measurement technologies are used simultaneously, then characterization capability is improved, but device complexity and measurement time increase
Solution Approach 1:
The patent segments the measurement task by assigning different measurement technologies to different measurement zones or parameter ranges. This allows the system to use multiple technologies without requiring all to operate simultaneously, reducing system complexity while maintaining comprehensive characterization capability.
Solution Approach 2:
The patent selectively applies measurement technologies based on the specific measurement requirements. Not all technologies are used for every measurement, but only those necessary for the particular structure and parameters being measured, thereby reducing overall system complexity.
4Reliability
If optical radiation is used to measure high-aspect ratio, three-dimensional structures, then non-destructive measurement is achieved, but penetration to bottom layers becomes difficult
Solution Approach 1:
The patent measures structures from multiple dimensional perspectives by varying angles of incidence and using multiple measurement zones. Instead of attempting to penetrate deeply through high-aspect ratio structures in a single direction, the system accesses different layers and regions by changing the measurement geometry, enabling comprehensive characterization without requiring deep penetration.
Data Source
AI summary
An optimized measurement recipe is determined by reducing the set of measurement technologies and ranges of machine parameters required to achieve a satisfactory measurement result. The reduction in the set of measurement technologies and ranges of machine parameters is based on available process variation information and spectral sensitivity information associated with an initial measurement model. The process variation information and spectral sensitivity information are used to determine a second measurement model having fewer floating parameters and less correlation among parameters. Subsequent measurement analysis is performed using the second, constrained model and a set of measurement data corresponding to a reduced set of measurement technologies and ranges of machine parameters. The results of the subsequent measurement analysis are compared with reference measurement results to determine if a difference between the estimated parameter values and the parameter values derived from the reference measurement is within a predetermined threshold.