Metrology Apparatus Isolating Process Effects for Overlay Accuracy
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Solution Overview
Problem
Conventional dark-field image-based overlay measurements in lithographic processes are inaccurate due to the inability to distinguish between layer misalignment and process effects, such as structural asymmetry, which can arise from wafer processing steps like CMP, leading to incorrect overlay measurements.
Innovation Solution
A method and apparatus that determine a first quality metric value while mitigating process effect parameters and a second quality metric value without mitigation, allowing for the calculation of a process effect parameter to isolate and quantify structural asymmetries, thereby improving the accuracy of overlay measurements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If dark-field image-based overlay measurements are used, then measurement speed is improved, but measurement precision deteriorates due to inability to distinguish layer misalignment from process effects
Solution Approach 1:
The measurement process is segmented into two distinct calculations: a first quality metric that mitigates process effects and a second quality metric that does not mitigate process effects. By separating these measurements and comparing them, the system can isolate and quantify process effects while maintaining measurement speed.
Solution Approach 2:
The patent introduces an intermediary process effect parameter that acts as a mediator between the two quality metric calculations. This parameter captures the difference between mitigated and non-mitigated measurements, allowing the system to account for process effects without sacrificing measurement speed.
2Measurement precision
If process effect mitigation is applied to quality metric calculation, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent extracts the process effect component by taking the difference between the first quality metric (with mitigation) and the second quality metric (without mitigation). This extraction isolates the process effect parameter, allowing precise overlay measurements while keeping the additional computational complexity manageable.
Solution Approach 2:
The system changes parameters by performing calculations under different conditions (with and without process effect mitigation) and comparing the results. This parameter-based approach allows precision improvement through systematic variation of measurement conditions rather than complex hardware modifications.
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 more precise monitoring and control of lithographic processes by directly measuring process effects, reducing inaccuracies in overlay measurements and enhancing the reliability of process control.
Implementation Method 1
an optical system for illuminating said structure with measurement radiation; a detector for detecting the measurement radiation scattered by the structure
Data Source
AI summary
Disclosed are a method, computer program and a metrology apparatus for measuring a process effect parameter relating to a manufacturing process for manufacturing integrated circuits on a substrate. The method comprises determining for a structure, a first quality metric value for a quality metric from a plurality of measurement values each relating to a different measurement condition while cancelling or mitigating for the effect of the process effect parameter on the plurality of measurement values and a second quality metric value for the quality metric from at least one measurement value relating to at least one measurement condition without cancelling or mitigating for the effect of the process effect parameter on the at least one measurement value. The process effect parameter value for the process effect parameter can then be calculated from the first quality metric value and the second quality metric value, for example by calculating their difference.