Proximity distance.(The Lithography Expert)

0ptical proximity effects are a well-known problem in optical lithography--the printed size of a given feature is a function of other features in its proximity. This problem has an equally well-known solution--optical proximity correction (OPC), the modification of the mask layout to compensate for these proximity effects. The most popular and accurate method of OPC is to use a model to predict proximity effects. The main contributor to this is the optical imaging itself. Considering just this phenomenon, an important question to ask is how far do these proximity effects extend?

OPC models break the maskup into computationally manageable segments that are then simulated and stitched back together again. But because of proximity effects, the actual simulation area has to be made larger than the segment being used so that an accurate result can be achieved within the area being corrected. The amount of buffer distance that must be added to each side of the correction area should equal the proximity distance. If too small a buffer is chosen the results will not be sufficiently accurate. If too large a buffer is chosen, simulation times will be unnecessarily long. What determines this proximity distance, and how should the operator of an OPC tool determine the correct buffer distance for the simulations?

To answer these questions, let us assume a very simple process model: an ideal threshold resist that puts the edge of the final printed feature at the point where the image reaches a certain threshold intensity. Also, to make a picture of our problem that is as straightforward as possible, consider an isolated space surrounded by chrome on the mask. If no other features are around this space, it will print at the desired critical dimension (CDnom). Now suppose that a second feature is placed to the right of this space. How close can this second feature come before it starts to affect the dimension of our target space?

The optical interaction of the two features depends on the spatial coherence of the illumination. For incoherent illumination, the small intensity coming from the second feature ([I.sub.2]) will overlap and add to the intensity of the first feature ([I.sub.1]) at its edge, changing its size. Using our threshold model, a small change in the right edge position ([DELTA]x) can be estimated to be

[DELTA]x = [I.sub.2]/[dI.sub.1]/dx] (1)

[FIGURE 1 OMITTED]

Putting this in terms of the normalized image log-slope (NILS),