wiggling AA figure
A Study of Wiggling AA Modeling and its Impact on Device Performance in Advanced DRAM
October 23, 2020
Fig. 4. Model calibration based on TEM cross sections for (a) fin self-aligned double patterning, (b) source/drain epitaxial growth and contacts, and (c) gate-to-source/drains spacers.
Process Variation Analysis of Device Performance Using Virtual Fabrication: Methodology Demonstrated on a CMOS 14-nm FinFET Vehicle
November 30, 2020

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Whitepaper: Process Window Optimization of DRAM by Virtual Fabrication

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As advanced CMOS scaling and new memory technology development moves forward, increasingly complex and vertical structures cause unexpected challenges in manufacturing and yield. In 3D NAND flash memory, to reduce bit costs and increase chip densities, stacks higher than 192 layers with multi-tier schemes are under development. This, however, casts unprecedented challenges for etching high aspect ratio holes, lithography alignment margin and cross wafer uniformity. Similar problems are occuring in DRAM technology development, as major manufacturers endeavor to scale these devices through new generations at 1xnm, 1ynm and 1znm. Relentless process development and integration challenges are creating scaling issues for 3D DRAM structure technology paths. New integration and patterning schemes are imposing manufacturing and yield challenges in DRAM, as industry focus has shifted from the scaling of predictable unit processes in 2D structures to the full integration of complex 3D structures.

Traditional Design of Experiments (DOEs) for DRAM process characterization and optimization require significant off-process time and wafer costs, and are unacceptably lengthy and expensive. In this study, SEMulator3D is used to model the effect of etch tool variations (such as material selectivity or flux distribution) on device electrical performance. A simple DRAM device study is used to highlight the effect of gate etch behavior and etch step characteristics on electrical performance and yield targets, and to demonstrate how virtual fabrication can efficiently solve complex semiconductor manufacturing and yield challenges during DRAM technology development.

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