PROCESS PROXIMITY CORRECTION METHOD BASED ON MACHINE LEARNING, OPTICAL PROXIMITY CORRECTION METHOD INCLUDING THE SAME, AND METHOD OF MANUFACTURING MASK BY USING THE PROCESS PROXIMITY CORRECTION METHOD
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United States of America Patent
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Issued Date -
Sep 26, 2024
app pub date -
Dec 5, 2023
filing date -
Mar 24, 2023
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Abstract
The present disclosure relates to process proximity correction (PPC) methods based on machine learning (ML), optical proximity correction (OPC) methods, and mask manufacturing methods including the PPC methods. One example PPC method based on ML includes obtaining a pattern gauge-based bottom critical dimension (CD) and obtaining pattern gauge-based features from a first layout, performing a gauge clustering operation of grouping and classifying pattern gauges including similar features, calculating distribution parameters in a skew-normal distribution of the pattern gauge-based bottom CD in each cluster, performing ML between the distribution parameters and a feature in each cluster to generate a prediction ML model, predicting a distribution, a maximum limit, and a minimum limit of the pattern gauge-based bottom CD by using the prediction ML model, generating an after cleaning inspection (ACI) target including a maximum process window, and generating a second layout by performing an development inspection (ADI) retarget operation.
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