EUV lithography resolves features below 11 nm. However, photonic and atomic variations at these photon energies and dimensions lead to less than 1:109 potential stochastic defects causing device failures in stable manufacturing processes. This study investigates a methodology intended to identify root causes of stochastic defects with potential mitigation paths. Simulation techniques using pseudo random numbers are used to identify failing photonic and chemical event or distribution combinations. Failing combinations occurring in many photon-chemical configurations are thought to have potential mitigation methodologies. Photonic effects demonstrated significant impacts on stochastic defect formation with approximately 73% of the photon seeds resulting in a failure in at least 60% of the trials. The material results were mixed with large failure quantities that demonstrated low impacts. The photonic shot noise based failures were dominating in this study and these failures will not be mitigated by material enhancement alone.
The extension of 193nm immersion lithography to the 14nm node and beyond directly encounters a significant reduction in image quality. One of the consequences is that the resist profile varies noticeably, impacting the already limited process window. Resist top-loss, top-rounding, T-top and footing all play significant roles in the subsequent etch process. Therefore, a reliable rigorous model with the capability to correctly predict resist 3D (R3D) profiles is acquiring higher importance. In this paper, we will present a calibrated rigorous model of a negative-tone develop resist. Resist profiles can be well simulated through focus and dose, and cases that match well to the experimental wafer data are validated. Such a model can not only provide early investigation of insights into process limitation and optimization, but can also complement existing OPC models to become R3D-aware in process development.
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