Maskless Lithography Data Conversion for Deterministic Memory
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Solution Overview
Problem
Maskless lithography machines face challenges in efficiently converting and processing large amounts of vector format pattern data into bitmap format due to non-deterministic memory requirements, which complicates storage and real-time corrections.
Innovation Solution
A method involving rendering and quantizing vector pattern data to generate intermediate pattern data, followed by re-sampling and re-quantizing to produce output pattern data in a spatially mapped array format, allowing for deterministic storage and real-time corrections, including proximity effect corrections and dose adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If vector format pattern data is used for maskless lithography, then complex manipulations and corrections can be performed, but the memory requirement becomes non-deterministic and cannot be determined in advance
Solution Approach 1:
The patent applies preliminary action by performing rendering and quantizing of vector pattern data into bitmap format before the actual lithography exposure process. This preprocessing step converts the non-deterministic vector data into a deterministic bitmap representation, allowing the system to determine the exact memory requirements in advance while still enabling complex manipulations and corrections to be performed on the rendered data.
2Quantity of substance
If vector format pattern data is converted directly to bitmap format, then memory requirement becomes deterministic, but complex manipulations and corrections become difficult
Solution Approach 1:
The system performs preliminary rendering and quantizing of vector data to bitmap format before exposure, enabling deterministic memory requirements. The rendered bitmap data then allows for various corrections including pattern shifting, scaling, and proximity effect corrections to be applied while maintaining deterministic storage characteristics.
3Loss of time
If fully converted pattern data is stored, then all processing can be performed in advance, but large storage capacity is required
Solution Approach 1:
The patent applies local quality by rendering and quantizing only the specific pattern data portions that are needed for each exposure field, rather than converting and storing all possible pattern data. This allows processing to be performed in advance for the required data while minimizing storage capacity requirements through selective conversion and on-demand processing of different field portions.
Data Source
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AI summary
A method and system for exposing a target according to pattern data in a maskless lithography machine generating a plurality of exposure beamlets for exposing the target. The method comprises providing input pattern data in a vector format, rendering and quantizing the input pattern data to generate intermediate pattern data, and re-sampling and re-quantizing the intermediate pattern data to generate output pattern data. The output pattern data is supplied to the lithography machine, and the beamlets generated by the lithography machine are modulated on the basis of the output pattern data.