Process-Aware Metrology Model Generation for Semiconductor Wafer Structures
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current optical critical dimension (CD) metrology in semiconductor manufacturing is limited by the need for cross-section images, which are time-consuming and costly to prepare, leading to inaccurate initial measurements and poor repeatability due to the complexity of constructing models for three-dimensional structures and variations in process conditions.
Innovation Solution
A computer-implemented method for generating an optical model of a semiconductor wafer structure without using images, by selecting nominal and different process parameter values, simulating characteristics, and determining parameterization based on variations, allowing for the development of models before wafer processing and reducing noise from experimental data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If cross-section images are used to construct accurate models of semiconductor structures, then measurement accuracy is improved, but preparation time and cost increase significantly
Solution Approach 1:
The patent performs preliminary simulation of structure characteristics and optical signatures before actual wafer processing. By predicting process outcomes and constructing models in advance based on simulated data, the system eliminates the need for time-consuming cross-section preparation while maintaining measurement accuracy.
Solution Approach 2:
The patent creates virtual copies of semiconductor structures through simulation. Instead of physically preparing cross-sections, the system generates simulated optical signatures that replicate what would be measured from actual structures, allowing accurate model construction without physical sample preparation.
2Measurement precision
If cross-section images are used to construct models, then initial measurement accuracy improves, but repeatability deteriorates due to model construction complexity
Solution Approach 1:
The patent uses simulated optical signatures as virtual copies of actual measurements. This standardized simulation approach ensures consistent model construction across different measurements, improving repeatability while maintaining accuracy through controlled simulation parameters.
Solution Approach 2:
The patent systematically varies simulation parameters to match different process conditions and structure variations. By controlling and documenting all simulation parameters, the system achieves both accuracy through parameter optimization and repeatability through consistent parameter management.
3Productivity
If models are constructed before cross-section images are available, then productivity is improved, but measurement accuracy deteriorates due to guesswork
Solution Approach 1:
The patent performs preliminary model construction using simulation data before cross-section images are available. The simulation-based approach provides accurate predictions of structure characteristics, eliminating guesswork while enabling immediate model usage for productivity improvement.
4Loss of substance
If fewer cross-sections are prepared to reduce cost, then loss of substance is reduced, but measurement precision deteriorates due to insufficient data coverage
Solution Approach 1:
The patent generates multiple simulated optical signatures representing different process variations and structure types. These virtual copies provide comprehensive data coverage equivalent to multiple physical cross-sections, maintaining measurement precision while eliminating the cost and material loss of actual cross-section preparation.
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 enables faster, more accurate, and repeatable optical measurements of semiconductor structures, allowing for real-time adjustment of processing conditions and improved device performance prediction, reducing the need for costly cross-section imaging and experimental noise.
Implementation Method 1
electromagnetic calculations can predict how light will scatter from that structure
Data Source
Figure 1
Figure 2
Figure 3
AI summary
Systems and methods for process aware metrology are provided.