New inverse methods such as model-based SRAF placement, model-based SRAF optimization, and full main + assist
feature ILT are well known to have considerable benefits in finding flexible mask pattern solutions to improve process
window and CD control. These methods have traditionally relied on compact models that are tuned to match resist
measurements at a single z-height or slice. At this slice in the resist, some critical failure modes such as top loss and
scumming are not detected. In this paper, we describe and present results for a methodology to extend ILT’s process
window improvement capabilities, and to co-optimize mask patterns with awareness of the resist profile. These
improvements are proven to reduce the risk of patterning failures at the bottom and top of critical resist features, which a
typical mask correction process would not alleviate. Ideally, mask optimization would use a full rigorous TCAD resist
model to guide the correction at multiple heights in the resist. However, TCAD models are significantly slower than
compact models in simulations and ILT already has high computational requirements. Therefore, we have generated
compact models which are fitted to the TCAD model resist profile data. We show the significant process window
improvements obtained with this new resist 3D aware ILT methodology.
Kosta Selinidis, Wolfgang Hoppe, Thomas Schmoeller, Thuc Dam, Kevin Hooker, and Guangming Xiao, "Resist 3D aware mask solution with ILT for hotspot repair," Proc. SPIE 10147, Optical Microlithography XXX, 101470Q (Presented at SPIE Advanced Lithography: March 01, 2017; Published: 24 March 2017); https://doi.org/10.1117/12.2257962.
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