Beyond FinFET device nodes, nanosheet is the next transistor architecture in CMOS scaling roadmaps. On top of the newer device architectures and materials, several other CMOS scaling boosters are being considered, and can help in further to improve the power, performance and area scaling. Backside power delivery network (BSPDN) is one of the promising scaling boosters, e.g. it disengages metal routing resources from the frontside, resulting in a lower routing congestion. Hence, the BSPDN booster paves the way for higher frequency and lower area footprint. However, ad-hoc standard cell design and optimization is required to connect the BSPDN network to the logic devices located in the front-end-of-line (FEOL). In this study, the implementation of different connection options to the BSPDN are studied in imec’s A14 nanosheet node: i.e. Through Silicon Via in the Middle of Line (TSVM), buried power rail (BPR) and direct backside contact (BSC). The different implications on standard cell design, as cell track height, routing and main process challenges are then compared to the classic frontside power delivery option. Finally, high-density (HD) standard cell libraries are implemented and characterized. Normalized area and delay comparisons at the library-level are presented. Area gains can rise up to 25% in case of BSC BSPDN option. Furthermore, maximum delay gains can vary up to 20% depending on standard cell type.
KEYWORDS: Semiconducting wafers, Back end of line, Nanosheets, Logic, Standards development, Metals, Fin field effect transistors, Semiconductors, Optical lithography, Nanotechnology
Fin depopulation, thinner and taller fins, and the step towards Nanosheet technologies has been helping in maintaining the rhythm of the semiconductor technology roadmap. Nevertheless, further area scaling causes a drastic reduction in active width as well as a challenging routability. On this regard, the Complementary-FET is a strong contender as device for next generation technologies. The stack of p- on n-FETs offers several opportunities for device scaling and optimization. However, it also poses several challenges that need to be carefully analyzed in a design-technology cooptimization framework.
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