Real-Time Metrology Recipe Optimization for Semiconductor Wafer Throughput
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current metrology systems face challenges in efficiently generating measurement recipes for semiconductor structures, particularly due to the complexity of high aspect ratio structures and opaque materials, leading to delayed recipe optimization and reduced measurement performance, especially for photon-starved systems.
Innovation Solution
The implementation of a system that rapidly updates measurement recipes based on newly acquired data, optimizing for minimum measurement uncertainty or time, and incorporating feedback control to adjust metrology system settings, such as illumination angles and energy, to improve measurement throughput and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Volume of moving object
If traditional scatterometry measurement recipes are used for complex 3D semiconductor structures, then measurement depth penetration is improved, but measurement sensitivity and parameter decoupling deteriorate
Solution Approach 1:
The system dynamically adjusts measurement wavelengths and angles based on the specific structure being measured. By making the measurement parameters adaptive rather than fixed, the system can optimize for both depth penetration and parameter sensitivity depending on the target structure characteristics.
Solution Approach 2:
The system changes physical parameters (wavelength, angle of incidence) to optimize measurement performance. By selecting appropriate wavelengths from a broad spectrum and adjusting illumination angles, the system achieves both sufficient penetration depth and adequate sensitivity for parameter extraction.
2Measurement precision
If measurement recipes are optimized for high sensitivity and low correlation, then measurement accuracy is improved, but the number of required measurements increases, reducing throughput
Solution Approach 1:
The system performs a limited number of strategic measurements rather than exhaustive measurements across all possible parameters. By selecting only the most informative measurement combinations, the system achieves sufficient accuracy without the throughput penalty of complete characterization.
Solution Approach 2:
The system extracts only the critical parameters needed for process control rather than measuring all possible structure characteristics. This selective approach focuses measurement resources on the most impactful parameters, maintaining accuracy while improving throughput.
3Adaptability or versatility
If more complex optical metrology tools with multiple angles and wavelengths are used, then measurement capability for challenging structures is improved, but recipe generation time increases
Solution Approach 1:
The system pre-calculates and stores optimal measurement recipes for different structure types before actual measurement is needed. This preliminary preparation eliminates the need for time-consuming real-time optimization, allowing rapid deployment of appropriate measurement sequences.
Solution Approach 2:
The system dynamically selects from pre-computed recipes based on real-time structure identification. This approach combines the versatility of having multiple optimized recipes available with the speed of immediate selection, avoiding the computational burden of generating recipes on-the-fly.
4Volume of moving object
If longer wavelengths are used to penetrate deep into 3D FLASH devices, then depth penetration is improved, but light intensity decreases, causing sensitivity loss
Solution Approach 1:
The system employs periodic modulation of the illumination source and synchronized detection. By using time-resolved measurement techniques with modulated light sources, the system enhances signal detection capability at deeper depths where intensity is reduced, effectively compensating for the intensity loss through temporal gating and synchronization.
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 measurement recipe generation, reducing delays and improving measurement performance by iteratively updating recipes and adjusting system settings in real-time, thereby enhancing wafer throughput and measurement quality.
Implementation Method 1
scatterometry critical dimension (SCD) measurements are performed
Implementation Method 2
optical radiation to penetrate to the bottom layers
Implementation Method 3
optical radiation can penetrate many layers of translucent materials
Data Source
AI summary
Methods and systems for improving a measurement recipe describing a sequence of measurements employed to characterize semiconductor structures are described herein. A measurement recipe is repeatedly updated before a queue of measurements defined by the previous measurement recipe is fully executed. In some examples, an improved measurement recipe identifies a minimum set of measurement options that increases wafer throughput while meeting measurement uncertainty requirements. In some examples, measurement recipe optimization is controlled to trade off measurement robustness and measurement time. This enables flexibility in the case of outliers and process excursions. In some examples, measurement recipe optimization is controlled to minimize any combination of measurement uncertainty, measurement time, move time, and target dose. In some examples, a measurement recipe is updated while measurement data is being collected. In some examples, a measurement recipe is updated at a site while data is collected at another site.