Substrate Chuck Flatness Monitoring via Spread Front Interference
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Solution Overview
Problem
The need for real-time monitoring of substrate chuck flatness changes during nanoimprint lithography or inkjet adaptive planarization to detect and address contamination events, such as particles landing on the wafer chuck, which affect overlay and defect quality, and determine if the flatness change is permanent or temporary.
Innovation Solution
Monitoring the spread front image using a spread camera to detect interference fringes and determine the exact location of flatness changes, applying corrective actions when repeating outliers are detected across multiple substrates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If real-time monitoring of substrate chuck flatness is implemented using spread front imaging, then substrate chuck cleanliness and flatness can be detected promptly, but system complexity and measurement requirements increase
Solution Approach 1:
The patent uses the spread front of liquid material as an intermediary medium to indirectly monitor substrate chuck flatness. Instead of directly measuring chuck surface conditions, the system observes how the liquid spread front behaves when contacting the chuck surface, which reveals flatness and cleanliness issues without requiring direct contact sensors on the chuck itself.
Solution Approach 2:
The patent replaces direct mechanical contact measurement methods with optical imaging of the spread front. Instead of using physical sensors that would require direct contact with the substrate chuck surface, the system uses cameras to capture images of the liquid spread pattern, substituting mechanical measurement with optical detection.
2Measurement precision
If multiple image sequences are analyzed to detect repeating outliers, then detection accuracy improves, but processing time and computational requirements increase
Solution Approach 1:
The patent establishes baseline flatness measurements from initial image sequences before production runs. By pre-characterizing the normal spread front patterns and interference fringe positions, the system creates reference data that enables faster real-time comparison during actual monitoring, reducing the computational burden during time-critical detection phases.
Solution Approach 2:
The system continuously compares new spread front images against established baselines and provides real-time feedback on deviations. When outliers are detected, the system can trigger alerts or automated corrections, creating a closed-loop monitoring system that improves detection efficiency by focusing computational resources on anomalous conditions rather than continuously processing all data at full depth.
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
Enables real-time detection and correction of substrate chuck flatness issues, ensuring consistent planarization and reducing defects by identifying and addressing temporary or permanent changes.
Implementation Method 1
obtaining multiple fluid spread image sequences containing interference fringes that appear during a film shaping process
Data Source
AI summary
A method for monitoring substrate chuck flatness by monitoring a spread front using a spread camera to detect a change in flatness of a substrate chuck in real time. The method includes obtaining multiple fluid spread image sequences containing interference fringes that appear during a film shaping process for a series of substrates, determining locations of outliers based on radial distances of the interference fringes for each substrate from the series of substrates and applying a corrective action to the substrate chuck when there are repeating outliers at similar locations across multiple substrates from the series of substrates.