3 March 2010 A novel decomposition of source kernel for OPC modeling
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Abstract
The accuracy and efficiency of OPC (Optical Proximity Correction) modeling have become paramount important at the low k1 lithography. However the accuracy of OPC model has to compromise with the efficiency of model calibration and pattern correction, since the model accuracy is usually improved by using more kernels to represent the model but the runtime of model setup and pattern correction also increase as kernel count increasing. A novel decomposition of source kernel for OPC model calibration was presented in this study to maintain the model accuracy and preserve the OPC runtime at acceptable level. Firstly, the source kernel was decomposed into multiple subsource kernels and then the magnitude of electric field for each decomposed sub-source was modulated in frequency domain. Finally, the resultant source can be the combination of many different sub-sources to represent the tool-specific characteristics. The model accuracy, model stability and modeling runtime were compared among decomposed source, ideal source and measured source models. The results showed modeling residual RMS error, predictive capability of decomposed source can be reduced to be comparable to measured source and superior to the ideal source. As for the modeling efficiency, the decomposed source is up to 5 times faster than the measured source but just few percentages slower than the ideal source approach.
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C. T. Hsuan, T. S. Wu, Fred Lo, Elvis Yang, T. H. Yang, K. C. Chen, Chih-Yuan Lu, "A novel decomposition of source kernel for OPC modeling", Proc. SPIE 7640, Optical Microlithography XXIII, 764037 (3 March 2010); doi: 10.1117/12.845763; https://doi.org/10.1117/12.845763
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