Process Proximity Correction by Neural Networks

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概要

• 論文の詳細を見る

• Making an accurate and quick critical dimension (CD) prediction is required for higher integrated device. Because simulation tools are consisted of many process parameters and models, it is hard that process parameters are optimized to match with the CD results for various patterns. This paper presents a method of improving accuracy of predicting CD results by applying the CD difference between simulation and experimental data value to neural network algorithm to reduce the CD difference caused by optical proximity effect.

• Published by the Japan Society of Applied Physics through the Institute of Pure and Applied Physicsの論文
• 2003-06-15

著者

• YOO Ji-Yong

  VUV Lithography Lab., Hanyang University

• PARK Jun-Taek

  VUV Lithography Lab., Hanyang University

• KIM Hyeongsoo

  Hynix Semiconductor

• AN Ilsin

  VUV Lithography Lab., Hanyang University

• OH Hye-Keun

  VUV Lithography Lab., Hanyang University

• Jeon Kyoung-ah

  Vuv Lithography Lab. Hanyang University

• Oh Hye-Keun

  VUV Lithography Lab., Hanyang University, Ansan, Kyunggido 425-791, Korea

• An Ilsin

  VUV Lithography Lab., Hanyang University, Ansan, Kyunggido 425-791, Korea

• Yoo Ji-Yong

  VUV Lithography Lab., Hanyang University, Ansan, Kyunggido 425-791, Korea

関連論文

• Process Proximity Correction by Neural Networks
• Process Proximity Correction by Neural Networks

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