Paper
28 March 2007 Circuit-based SEM contour OPC model calibration
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Abstract
In order to achieve the necessary OPC model accuracy, the requisite number of SEM CD measurements has exploded with each technology generation. At 65 nm and below, the need for OPC and/or manufacturing verification models for several process conditions (focus, exposure) further multiplies the number of measurements required. SEM-contour based OPC model calibration has arisen as a powerful approach to deliver robust and accurate OPC models since every pixel now adds information for input into the model, substantially increasing the parameter space coverage. To date however, SEM contours have been used to supplement the hundreds or thousands of discreet CD measurements to deliver robust and accurate models. While this is still perhaps the optimum path for high accuracy, there are some cases where OPC test patterns are not available, and the use of existing circuit patterns is desirable to create an OPC model. In this work, SEM contours of in-circuit patterns are utilized as the sole data source for OPC model calibration. The use scenario involves 130 nm technology which was initially qualified for production with the use of rule-based OPC, but is shown to benefit from model based OPC. In such a case, sub-nanometer accuracy is not required, and in-circuit features can enable rapid development of sufficiently accurate models to provide improved process margin in manufacturing.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kyle Patterson, Jim Vasek, Chi Min Yuan, George E. Bailey, Ir Kusnadi, Thuy Do, and John L. Sturtevant "Circuit-based SEM contour OPC model calibration", Proc. SPIE 6521, Design for Manufacturability through Design-Process Integration, 65211N (28 March 2007); https://doi.org/10.1117/12.713044
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KEYWORDS
Calibration

Optical proximity correction

Data modeling

Scanning electron microscopy

Model-based design

Critical dimension metrology

Process modeling

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