Abstract

Computational lithography has become indispensable when developing lithography solutions for advanced technology nodes. One of the essential instruments for optimizing full-chip process windows (PW) is source mask optimization (SMO). To avoid model calibration for each new optimized source, separable resist models need to be created such that a reliable model can be obtained simply by replacing the source in the existing OPC model. In this paper we start from a fully calibrated resist model and optimize a new source for which we want to create a reliable OPC model. Relying on the separability of the model, the initial illumination source is replaced by the new one while not changing any resist model parameters. In order to reach the accuracy needed for OPC, the best focus and best dose still need to be accurately determined. We will investigate two models that have the same new SMO source and original resist model. For one model the best focus and dose are determined by the simulated Bossung plot of one anchor feature. The second model’s best focus and exposure are determined by a small set of FEM experimental data. The quality of these two models is then evaluated by comparing them to a reference model, which is fully calibrated using a complete dataset for the new source. We show that the calibrated FEM OPC model can be extrapolated by simply changing the source. A limited amount of experimental FEM data is required to accurately determine the best focus and exposure for the new source. Best focus and exposure based on the anchor pattern simulation has a higher degree of uncertainty compared to a small set of experimental data.

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