X-Ray Scatterometry Library Seeding for Complex Semiconductor Structures
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing metrology techniques face challenges in accurately and efficiently measuring complex semiconductor structures due to increasing complexity, small resolution requirements, and the use of opaque materials, leading to high computational effort and convergence issues in regression analysis.
Innovation Solution
Transform measured detector image data into diffraction order efficiency data and compare it with a pre-computed parameter-efficiency library to select seed values for regression, reducing computational effort by operating in efficiency space rather than image space.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional scatterometry measurement methods are used on complex semiconductor structures, then measurement capability is maintained, but computational effort becomes excessive and convergence issues arise
Solution Approach 1:
The patent introduces diffraction order efficiency data as an intermediary between the raw detector image data and the parameter extraction process. By transforming image data into efficiency data and comparing it with a pre-computed library, the method creates a simplified intermediate representation that reduces computational complexity while maintaining measurement accuracy
Solution Approach 2:
The patent performs preliminary transformation of detector image data into diffraction order efficiency data before the main parameter extraction process. Additionally, a library of efficiency data is pre-computed and stored, allowing the measurement system to bypass computationally intensive real-time calculations and instead use efficient library matching
2Reliability
If regression analysis is performed in image space, then complete information is utilized, but computational effort and time increase significantly
Solution Approach 1:
The patent changes the parameter space from raw image data to diffraction order efficiency data. This transformation converts the regression problem from operating in high-dimensional image space to operating in a reduced efficiency space, maintaining convergence reliability while dramatically reducing computational time
3Length of stationary object
If longer wavelengths are used to penetrate deep layers, then depth penetration is improved, but sensitivity to small anomalies decreases
Solution Approach 1:
The patent addresses the wavelength trade-off by introducing a new dimension in the analysis - diffraction order efficiency space. Instead of relying solely on wavelength selection to balance penetration and sensitivity, the method transforms the measurement data into efficiency space where both deep-layer and surface-feature information can be simultaneously extracted through library matching
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
Accurate X-ray scatterometry measurements of complex semiconductor structures are achieved with significantly less computational effort, increasing the likelihood of converging to the global minimum.
Implementation Method 1
X-ray illumination radiation is directed to one or more semiconductor structures and an image of radiation scattered from the one or more semiconductor structures is detected
Data Source
AI summary
Methods and systems for performing X-ray model based scatterometry measurements of semiconductor structures with reduced computational effort are described herein. More specifically, measured detector image data is transformed to diffraction order efficiency data. The measured diffraction order efficiency data is compared with a parameter-efficiency library including simulated diffraction order efficiency data and associated sets of specimen parameter values. One or more sets of specimen parameter values are selected as seed values for regression on the measured detector image data based on the fit between the measured and simulated diffraction order efficiency data. The seed values are provided as initial values of one or more parameters of interest for the first iteration of the regression. The seed values enable the image based regression to converge to the global minimum with a dramatically reduced number of iterations. Thus, accurate X-ray scatterometry measurements of complex semiconductor structures are realized with less computational effort.