Charged Particle Lithography Stitching Error Reduction
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Solution Overview
Problem
In multiple charged beam direct write lithography, stitching errors occur due to mis-alignment of sub-areas, leading to variations in critical dimension (CD) in overlap regions, which existing techniques fail to adequately address without compromising throughput.
Innovation Solution
A method is introduced to process exposure data by increasing the exposure dose in overlap areas and reducing feature sizes in the overlap pattern data, allowing for higher exposure latitude while maintaining comparable or better CD uniformity in overlap regions compared to non-overlap areas, without incurring a throughput penalty.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple beams are used to expose overlap areas to maintain alignment, then stitching reliability improves, but critical dimension uniformity deteriorates due to dose accumulation
Solution Approach 1:
The patent applies local quality by differentiating the exposure dose in overlap areas from non-overlap areas. Specifically, the system identifies stitching regions where multiple beams converge and assigns them a reduced dose value compared to standard areas. This localized dose adjustment ensures that the accumulated exposure in overlap regions does not exceed the target threshold, thereby maintaining critical dimension uniformity while preserving stitching reliability through multi-beam coverage.
Solution Approach 2:
The patent implements parameter changes by dynamically adjusting the exposure dose parameter based on the spatial location. The system calculates a first dose value for overlap areas and a second dose value for non-overlap areas, where the first dose value is specifically reduced to compensate for multi-beam accumulation. This parameter differentiation resolves the contradiction by allowing multiple beams to expose overlap regions (maintaining reliability) while controlling the total dose to preserve critical dimension uniformity.
2Manufacturing precision
If exposure dose is increased in overlap areas to compensate for mis-alignment, then critical dimension uniformity improves, but throughput deteriorates due to longer exposure time
Solution Approach 1:
The patent applies parameter changes by inverting the conventional approach: instead of increasing dose in overlap areas, it reduces the dose to a first value that is lower than the second value used for non-overlap areas. This counterintuitive parameter adjustment compensates for mis-alignment by ensuring that the reduced dose, when accumulated from multiple beams, still achieves adequate exposure without requiring extended exposure time, thereby maintaining throughput.
Solution Approach 2:
The patent employs partial action by using multiple beams to expose overlap areas, where the combined effect of multiple reduced-dose beams achieves the required exposure level without needing to increase the dose of individual beams or extend exposure duration. This allows the system to compensate for mis-alignment through redundant beam coverage rather than through increased dose or time, preserving throughput.
3Manufacturing precision
If feature size is reduced in overlap pattern data to compensate for over-exposure, then critical dimension uniformity improves, but manufacturing complexity increases
Solution Approach 1:
The patent applies local quality by modifying the pattern data to include a first feature size for features located in overlap areas and a second feature size for features in non-overlap areas. The exposure data processing system identifies the spatial location of each feature and assigns the appropriate size parameter. This localized differentiation ensures that features in overlap regions are sized to compensate for multi-beam exposure accumulation, maintaining critical dimension uniformity while using a systematic approach to manage processing complexity.
Solution Approach 2:
The patent implements preliminary action by pre-processing the exposure data to identify overlap areas and adjust feature sizes before the actual exposure process. The system calculates which regions will be exposed by multiple beams and modifies the pattern data accordingly in advance. This preliminary adjustment of feature sizes in overlap regions prevents over-exposure and maintains critical dimension uniformity, while performing the complex calculations beforehand rather than during real-time exposure.
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 improves critical dimension uniformity in overlap areas, ensuring that features in overlap regions match intended dimensions after development, while maintaining high throughput by utilizing multiple beams to increase exposure dose in overlap areas.
Implementation Method 1
exposing a target using a plurality of charged particle beams
Data Source
AI summary
A method for processing exposure data (40) for exposing a pattern on a target (30) using a plurality of charged particle beams (24), the exposure data comprising pattern data (42) representing one or more features (60) to be written on the target (30) and exposure dose data (52) describing exposure dose of the charged particle beams. The method comprises setting one or more dose values of the exposure dose data (52) such that a sum of dose values corresponding to a position in an overlap area (36) of the target exceeds a maximum dose value for the non-overlap areas (38) of the target where adjacent sub-areas (34) do not overlap, and dividing the pattern data (42) into a plurality of sub-sections (44), each of the sub-sections comprising pattern data describing a part of the pattern to be written in a corresponding sub-area (34) of the target (30), wherein the pattern data (42) comprises overlap pattern data (46) describing a part of the pattern to be written in a corresponding overlap area (36) of the target where adjacent sub-areas (34) overlap, and processing the overlap pattern data (46) to reduce a size of one or more features described by the overlap pattern data.