23 May 2011 Evaluation of process variations on OPC model predictions
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Proceedings Volume 8081, Photomask and Next-Generation Lithography Mask Technology XVIII; 80810O (2011); doi: 10.1117/12.897531
Event: Photomask and NGL Mask Technology XVIII, 2011, Yokohama, Japan
Abstract
Process models have been in use for performing proximity corrections to designs for placement on lithography masks for a number of years. In order for these models to be used they must provide an adequate representation of the process while also allowing the corrections themselves to be performed in a reasonable computational time. In what is becoming standard Optical Proximity Correction (OPC), the models used have a largely physical optical model combined with a largely empirical resist model. Normally, wafer data is collected and fit to a model form that is found to be suitable through experience. Certain process variables are considered carefully in the calibration process-such as exposure dose and defocus - while other variables-such film thickness and optical parameter variations are often not considered. As the semiconductor industry continues to march toward smaller and smaller dimensions-with smaller tolerance to errorwe must consider the importance of those process variations. In the present work we describe the results of experiments performed in simulations to examine the importance of many of those process variables which are often regarded as fixed. We show examples of the relative importance of the different variables.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
James Oberschmidt, Samit Barai, Tamer Desouky, Om Prakash Jaiswal, Aditya Padmawar, Ramana Murthy Pusuluri, "Evaluation of process variations on OPC model predictions", Proc. SPIE 8081, Photomask and Next-Generation Lithography Mask Technology XVIII, 80810O (23 May 2011); doi: 10.1117/12.897531; https://doi.org/10.1117/12.897531
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KEYWORDS
Photomasks

Data modeling

Calibration

Critical dimension metrology

Optical proximity correction

Process modeling

Semiconducting wafers

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