Multi-Beam Writer Blur Correction for Target Elevation Variation
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Solution Overview
Problem
Charged-particle multi-beam processing apparatuses experience blur variation due to target elevation relative to the nominal plane, affecting the uniformity and critical dimension of exposed patterns, particularly in mask manufacturing.
Innovation Solution
A method to compute an exposure pattern that compensates for target elevation by adjusting blanking apertures' dose values and applying a convolution kernel to increase blur uniformly, using an elevation dependence function and partitioning the exposure area into sub-regions, calculating a correction blur value to achieve target blur uniformity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the target is elevated relative to the nominal target plane, then the imaging system can accommodate topography variations, but the blur varies non-uniformly across the exposure area
Solution Approach 1:
The patent applies local quality by determining elevation-specific blur values for different regions of the exposure area. Each local region receives a customized blur correction based on its specific elevation, rather than applying a uniform blur correction across the entire area. This allows the system to maintain uniform pattern quality despite varying target elevations.
Solution Approach 2:
The patent changes the blur parameter dynamically based on elevation. By calculating elevation-dependent blur values and applying differential blur corrections to different local regions, the system compensates for elevation variations. This parameter adaptation ensures uniform critical dimension across the exposure area despite topography changes.
2Manufacturing precision
If differential blur correction is applied to each local region, then pattern uniformity is improved, but computational complexity and processing time increase
Solution Approach 1:
The patent segments the exposure area into multiple local regions, each processed independently with its own elevation and blur characteristics. This segmentation allows the complex problem of uniform blur correction across varying terrain to be broken down into manageable local calculations, balancing precision with computational feasibility.
Solution Approach 2:
The patent performs preliminary elevation determination and blur value calculation for each local region before the actual exposure process. By pre-computing the elevation-dependent blur corrections and storing them for later application, the system reduces real-time computational requirements during exposure while maintaining high precision.
3Measurement precision
If blur is increased uniformly across the exposure area, then edge characterization is improved, but resolution decreases
Solution Approach 1:
The patent applies local quality by determining elevation-specific blur values for different regions of the exposure area. Each local region receives a customized blur correction based on its specific elevation, rather than applying a uniform blur correction across the entire area. This allows the system to maintain uniform pattern quality despite varying target elevations.
Solution Approach 2:
The patent changes the blur parameter dynamically based on elevation. By calculating elevation-dependent blur values and applying differential blur corrections to different local regions, the system compensates for elevation variations. This parameter adaptation ensures uniform critical dimension despite topography changes.
Data Source
AI summary
In order to compensate for undesired effects of varying elevation of a target with respect to a nominal target plane, during writing a desired pattern on the target in a charged-particle beam apparatus, the pattern is re-calculated in each of a number of segments of the target plane by: determining an elevation of the target in the segment from the nominal target plane; determining a local blur value which represents the actual value of blur corresponding to the elevation, with regard to a dependence of the blur upon the elevation of the target; calculating a convolution kernel which represents a point spreading function realizing a local blur value; and re-calculating a nominal exposure pattern by applying the kernel to the pattern. The convolution kernel corresponds to introducing an additional blur into the pattern in the segment, increasing the blur to a given target blur value which is uniform to all segments.


