Optical Proximity Correction (OPC) can be formulated as a constrained optimization problem. The constraints are mask constraint rules for space and width. These are sometimes called Mask Rule Checks (MRC), or Design Rule Checks (DRC). At 90nm and below, intelligent constraint handling is required for good OPC. In this paper, we show a technique for OPC constraint checking which is built in to the OPC feedback algorithm. The system is flexible enough to allow relaxed rules for corner-to-corner checking versus edge-to-edge checking. Also, the system can categorize checks by the length of the edges being compared. Lastly, the system can create special checks from line-ends to other features, or any user-defined edge type to any other user-defined edge type. In addition, we present a method for multiple layer enclosure rules which can be used for multiple exposure OPC. These enclosure constraints are useful for assurance of overlay tolerance.
Mask manufacturing for the 100 and 65nm nodes is accompanied by an increasing deployment of VSB mask writing machines. The continuous integration trend in design and broad deployment of RET have a tremendous impact on file size and pattern complexity. The impact on the total turn-around time for a design is twofold: the time to get the data ready for the hand-off to the mask writer is growing but also the time it actually takes to write the mask is heavily influenced by the size and complexity of the data. Different parameters are measures of how the flow and the particular tooling impact both portions. The efficiency of the data conversion flow conducted by a software tool can be measured by the output file size, the scalability of the computing during parallel processing on multiple processors and the total cpu-time for the transformation. The mask writing of a particular data set is affected by the file size and the shot count. The latter one is the total amount of shots that are required to expose all patterns on the mask. The shot count can be estimated based on the figure count by type and their dimensions. The results of the fracturing have an impact on the mask quality -- in particular the grid size and the number and locations of small figures.
KEYWORDS: Optical proximity correction, Photomasks, Systems modeling, Data modeling, Convolution, System on a chip, Sodium, Lithography, Photoresist processing, Process modeling
Fast lithography simulation and its use in optical proximity correction (OPC) is the topic of this paper. We summarize a model-based OPC system which uses simulation in a feedback loop to generate corrections to the mask. At the heart of our OPC system are tools for fast simulation of the optical and process physics of lithography. For image simulation, we apply a sum of coherent systems approximation to Hopkins partial coherence model and then use lookup tables for high speed sparse image simulation over arbitrary mask geometry. Image intensity simulation at a single point is achieved with O(Me) computation where Me is the number of polygon edges in a region surrounding the point. This allows more than 10,000 aerial image points per second and mask image perturbation speeds of 51,000 points per second on an HP700 workstation. A simplified physically based, empirically parameterized resist model is then used to determine edge placements, given the image intensity samples. Together, these systems make up a 'process-tuned' simulation model which can be used for OPC. The accuracy of the overall model is shown by comparing to empirical measurement data. By integrating the fast simulation tools with our OPC system, we can correct a 48 X 27 micrometers 2 area in 6 iterations at 96 sec/iteration.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.