SLM Edge Pixel Registration for Nanoimprint Extrusion Control
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Solution Overview
Problem
Existing techniques for registering spatial light modulator (SLM) pixels relative to an imprint field edge in nanoimprint lithography are inaccurate, leading to extrusion defects due to incorrect pixel selection for extrusion control.
Innovation Solution
An on-tool imprinting procedure that generates a set of pixel patterns to identify SLM pixels corresponding to the imprint field edge, using an optical microscope to inspect cured edges and adjust for optical distortions, and generates a frame cure map for precise extrusion control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If initial SLM registration is used to estimate pixel locations, then the registration process is simple and fast, but the accuracy of pixel identification is poor due to optical path distortion
Solution Approach 1:
The patent performs preliminary actions by first obtaining an initial SLM registration to get approximate pixel locations, then uses this as a starting point for more precise edge detection through iterative refinement with the optical microscope, rather than attempting to achieve high precision from the beginning
Solution Approach 2:
The patent implements feedback by using the optical microscope to detect actual imprint field edges and comparing them with the initially estimated pixel locations, then adjusting the pixel identification based on this feedback to compensate for optical path distortion
2Ease of operation
If incorrect SLM pixels are selected for extrusion control, then the control process is simple, but extrusion defects and non-fill defects occur
Solution Approach 1:
The patent replaces simple mechanical pixel selection with an optical detection system that automatically identifies the correct pixels by detecting actual imprint field edges through the optical microscope, substituting manual or simple automated selection with optical feedback-based identification
Solution Approach 2:
The system performs self-service by automatically detecting edge positions and identifying corresponding SLM pixels without requiring manual intervention, with the optical microscope and control system working together to autonomously determine the correct pixel locations for extrusion control
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
Accurately identifies SLM pixels relative to the imprint field edge, reducing non-fill and extrusion defects, and ensuring precise control of formable material distribution during the imprinting process.
Implementation Method 1
uses spatial light modulation to modulate a radiation source to irradiate a formable material near an edge of an imprint field on a substrate to increase the viscosity of resist spreading under the template
Implementation Method 2
The reference film is inspected to generate positional information of elements of the SLM relative to an imprint field edge
Data Source
AI summary
A method for identifying pixels corresponding to an imprint field edge. Generating a set of pixel patterns, each pixel pattern from the set of pixel patterns including edge pixels predicted to be near the imprint field edge of a test imprint field and central pixels corresponding to a center portion of the test imprint field, wherein the edge pixels are turned on, each pixel pattern from the set of pixel patterns having different edge pixels selected and imprinting the test imprint field with a spatially modulated light source that is modulated with at least one pixel pattern from the set of pixel patterns.