X-Ray Scatterometry Data Fusion for Semiconductor Parameter Estimation
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Solution Overview
Problem
Current metrology techniques face challenges in accurately measuring complex, three-dimensional semiconductor structures due to penetration issues, sensitivity loss, and correlation problems, especially with high-aspect ratio and opaque materials, leading to inaccurate or incomplete parameter characterization.
Innovation Solution
The use of x-ray scatterometry systems that combine measurement data before and after a critical process step to simplify geometric models, reducing computational effort and improving parameter estimation by approximating diffraction patterns as linear combinations of Fourier components, and employing trained signal response metrology models to directly correlate critical dimensions with combined data sets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Length of stationary object
If longer wavelengths (near infrared) are employed to overcome penetration issues for 3D FLASH devices, then penetration depth is improved, but sensitivity to small anomalies decreases and parameter correlation increases
Solution Approach 1:
The patent segments the complex 3D structure into multiple 2D cross-sectional layers that can be independently analyzed. By dividing the three-dimensional flash memory structure into sequential two-dimensional slices, the system can measure each layer separately, overcoming the penetration depth limitations while maintaining sensitivity to small dimensional variations in each segment.
Solution Approach 2:
The patent transforms the three-dimensional measurement problem into a series of two-dimensional measurement problems. By analyzing cross-sectional views rather than attempting to penetrate the full 3D structure, the system achieves both adequate penetration depth for each 2D layer and sufficient sensitivity to detect small anomalies, effectively using dimensionality reduction to resolve the contradiction.
2Loss of information
If more complete information acquisition from reflected signals (multiple Mueller matrix elements) is implemented, then measurement information completeness is improved, but device complexity and computational effort increase
Solution Approach 1:
The patent extracts only the essential measurement information needed for critical dimension analysis from the full set of reflected signal data. Rather than acquiring and processing all Mueller matrix elements, the system identifies and utilizes specific signal components that provide the necessary measurement information, thereby reducing device complexity while avoiding information loss for the parameters of interest.
Solution Approach 2:
The patent implements partial action by acquiring a subset of the available optical signal information that is sufficient for the measurement task. Instead of measuring all possible reflected signal parameters, the system measures only the specific components needed for accurate critical dimension extraction, reducing computational effort and device complexity while maintaining measurement completeness for the critical parameters.
3Ease of operation
If traditional scatterometry is used on complex 3D structures, then measurement process is simple, but parameter correlation increases and reliable decoupling of parameters becomes difficult
Solution Approach 1:
The patent segments the complex 3D structure into multiple 2D cross-sectional layers, allowing each layer to be analyzed independently. This segmentation reduces parameter correlation because each 2D layer has fewer interdependent parameters compared to the full 3D structure, enabling more reliable parameter decoupling while maintaining measurement simplicity through automated processing.
Solution Approach 2:
The patent changes the measurement dimension from 3D to 2D cross-sectional analysis. This dimensionality reduction simplifies the inverse problem by decreasing the number of parameters that need to be simultaneously determined, thereby reducing parameter correlation and improving the reliability of parameter decoupling while keeping the measurement process relatively simple through standard scatterometry techniques applied to 2D slices.
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 and more accurate estimation of geometric parameters with reduced computational expense, improving the measurement of complex semiconductor structures and addressing the limitations of traditional methods.
Implementation Method 1
x-ray scatterometry systems that combine measurement data before and after a critical process step
Implementation Method 2
approximating diffraction patterns as linear combinations of Fourier components
Data Source
AI summary
Methods and systems for measuring a complex semiconductor structure based on measurement data before and after a critical process step are presented. In some embodiments, the measurement is based on x-ray scatterometry measurement data. In one aspect, a measurement is based on fitting combined measurement data to a simplified geometric model of the measured structure. In some embodiments, the combined measurement data is determined by subtraction of a measured diffraction pattern before the critical process step from a measured diffraction pattern after the critical process step. In some embodiments, the simplified geometric model includes only the features affected by the critical process step. In another aspect, a measurement is based on a combined data set and a trained signal response metrology (SRM) model. In another aspect, a measurement is based on actual measurement data after the critical process step and simulated measurement data before the critical process step.