Hotspot-aware DSA Grouping and Mask Assignment

TL;DR

This paper introduces a heuristic method for DSA grouping and mask assignment that significantly reduces hotspots and conflicts in directed self-assembly processes, improving yield and reliability in semiconductor manufacturing.

Contribution

A novel hotspot-aware heuristic for DSA grouping and MP decomposition that reduces hotspots by 78% compared to hotspot-unaware methods.

Findings

Eliminates 78% of hotspots and conflicts

Results are within 24% of the optimal ILP solution

Improves defect reduction in DSA processes

Abstract

In Directed Self Assembly (DSA), poor printing of guiding templates can cause misassembly resulting in high defect probability. Therefore, hotspots should be avoided in the choice of the DSA groups. Accordingly, Directed Self-Assembly (DSA) technologies which use Multiple Patterning (MP) to print the guiding templates need to be aware of hotspots during the DSA grouping and MP Decomposition. In this paper, we present a hotspot-aware heuristic for DSA grouping and MP decomposition. Results show that that the proposed heuristic eliminates 78% of the hotspots and conflicts that result from using a hotspot-unaware grouping and decomposition algorithm. In comparison to the optimal solution using Integer Linear Programming, the proposed heuristic results in ~24% more violations.