Semiconductor Measurement Validation via Simulated Data Comparison
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Solution Overview
Problem
The scaling down of semiconductor ICs leads to complex measurement challenges on wafer topography surfaces, causing errors in tools like scanning electron microscopes, requiring significant labor and time for verification.
Innovation Solution
A method involving a smart review engine that generates simulated measurement data using SEM tool parameters, allowing for comparison with actual data to validate accuracy and efficiency, reducing human intervention in the validation process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If scaling down is performed to increase production efficiency and lower costs, then productivity improves, but measurement precision deteriorates due to complex topography and scaled down features causing measurement errors
Solution Approach 1:
The patent creates a simulated measurement data copy that mirrors the actual measurement process. The simulation engine generates synthetic measurement data based on design data and measurement tool parameters, allowing validation without additional physical measurements. This copying approach maintains measurement precision while preserving the benefits of scaling down for productivity.
Solution Approach 2:
The patent performs preliminary simulation of measurement data before actual measurement validation. By pre-generating simulated measurement data and establishing validation criteria in advance, the system prepares the validation framework beforehand, enabling quick comparison and validation of actual measurements without time-consuming manual verification processes.
2Measurement precision
If manual verification is performed to ensure measurement accuracy, then measurement precision is maintained, but loss of time increases due to significant labor and time required for verification
Solution Approach 1:
The patent implements self-service validation where the measurement tool automatically compares actual measurement data against simulated measurement data using predefined validation criteria. The system validates its own measurements without requiring external manual verification, maintaining measurement precision while eliminating the time and labor costs associated with manual verification processes.
Solution Approach 2:
The patent establishes a feedback mechanism where measurement data is automatically validated by comparing it with simulated data, and validation results are fed back to confirm measurement accuracy. This automated feedback loop replaces manual verification, maintaining precision while reducing verification time significantly through systematic automated comparison and validation.
3Productivity
If automated validation is implemented to reduce time and labor, then productivity improves, but device complexity increases due to the smart review engine and simulation requirements
Solution Approach 1:
The patent designs the simulation engine to serve multiple functions: generating simulated measurement data, validating actual measurements, and providing verification results. This multi-functional approach consolidates what could be separate complex systems into a single versatile engine, improving verification productivity while managing device complexity through functional integration rather than proliferation of separate components.
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 method significantly reduces the time and labor required for verifying measurement data by automating the validation process, improving accuracy and efficiency in IC manufacturing.
Implementation Method 1
performing a measurement on the material feature by applying an electron beam on the material feature and collecting a secondary electron signal from the material feature using a scanning electron microscope (SEM) tool
Implementation Method 2
collecting a secondary electron signal from the material feature
Data Source
AI summary
A method includes receiving, into a measurement tool, a substrate having a material feature, wherein the material feature is formed on the substrate according to a design feature. The method further includes applying a source signal on the material feature, collecting a response signal from the material feature by using the measurement tool, and with a computer connected to the measurement tool, calculating a simulated response signal from the design feature. The method further includes, with the computer, in response to determining that a difference between the collected response signal and the simulated response signal exceeds a predetermined value, causing the measurement tool to re-measure the material feature.