The requirement of larger common overlap process window in EUV patterning is getting stronger when the design pitch continues to shrink. The reflective optics in EUV generate various imaging issues due to mask 3-dimensional (M3D) effects. Therefore, sub-resolution assistant features (SRAFs) insertion is preferred for the resolution enhancement technology. SRAFs insertion can create a dense optical environment that will prevent strong best focus shift between semi-isolated and isolated features. From the previous study, SRAFs insertion and stochastic printing can be modeled and verified with a flow utilizing a compact resist 3D model (R3D) in conjunction with stochastic model. In this work, additional SRAFs investigations and studies extend to a better choice of alternative EUV mask absorbers that can mitigate M3D effects and have better lithography performance. In this paper, a low-n dark field EUV mask with regular hole grid design and positive tone development (PTD) is considered. The SEM (scanning electron microscope) images of through pitches with various SRAFs sizes and combination of SRAF to main space are collected. The SRAFs printing pixels can be captured and modeled with compact resist stochastic modeling. The results can be verified using average printed area (APA) metric with a R3D model and the simulation studies have proved the SRAFs printing sensitivity to the photomask biases.
The common process window of EUV patterning is being limited when the 1-dimensional (1D) pitch shrinks to 32nm or below. There are many investigations and studies that propose an alternative EUV photomask absorber to mitigate photomask 3-dimensional (3D) topology effects and can partially mitigate the contrast fading effect and reduce through pitch best focus shift.1,2,3 Another method to counter photomask 3D effects, is sub-resolution assistant features (SRAFs). SRAF insertion is one possible way to create a dense optical environment, which will prevent strong best focus shift from semi-isolated to isolated features. However, the side effect of SRAF insertion is unwanted SRAF printing occurring on the surface or bottom of the photoresist.4 In order to predict the partial removal or small residues of photoresist after the lithographic development process, a flow of compact photoresist 3D modeling (R3D) in conjunction with stochastic modeling can be adopted. In this paper, a bright field EUV photomask with regular 1D line-space grid design and positive tone development (PTD) are considered. The SEM images of through pitch 1D structures with various sizes of SRAFs are collected. To quantify SRAF printing, pixel brightness is compared to resist-opened background area, the printing SRAF regions can then be identified and clustered. Compact resist stochastic modeling is also performed by line-width roughness (LWR) sampling and used to predict SRAFs printing pixels by using Average Printing Area (APA) method with R3D modeling.5 Therefore, not only severe SRAF printing events can be predicted well, but also the accurate prediction of SRAF printing with very low probabilities can also be achieved.
Photon absorption statistics combined with a simple model of resist chemistry triggered by each absorbed photon leads to a family of stochastic models with a Gaussian Random Field deprotection. Two important aspects of such models are discussed. First, the generalizations to stochastic reaction-diffusion models, accounting for the effects of depletion, and to models accounting for both exposure-resist stochastic and other process parameter variations, are presented. Second, several options for the stochastic metrics of EUVL processes, both meaningful and useful for lithographers and fast enough to be applicable to the full chip OPC and verification, are described, and some details of their implementations for the full-chip OPC verification and the results of tests are presented. The relation of one of the introduced stochastic metrics to the stochastic-caused variability of the electrical conductance of vertical interconnects (vias) is explained.
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