Proceedings Article | 28 March 2012
KEYWORDS: Line width roughness, Polymers, Photoresist materials, Diffusion, Statistical analysis, Electroluminescence, Diffractive optical elements, Immersion lithography, Lithographic illumination, Lithography
Line width roughness (LWR) is one of the most critical performance indexes for low k1 ArF immersion Lithography.
Several factors are impacting LWR performance during Lithography process, such as structures, anti-reflective coating
(ARC), photoresist, baking condition, illumination condition and track process. However, the structures and ARCs are
strongly related to integration and Etch processes. The illumination conditions, including mask bias, are decided by
simulation software but the track condition usually follows the pervious node at initial step normally. Therefore, it
sometimes shows poor results because of the difference of the under-layer condition. For example, it has been uncovered
that LWR and local CD uniformity (LCDU) became worse while structure changed to Carbon-DARC-Resist (CDR)
from Multi-Layer Resist (MLR).
Generally, photoresist evaluation with baking condition optimization is a typical way to improve LWR performance. The
photoresist formulation contains photosensitive polymers, photoacid generators (PAGs), quenchers, additives, and
solvents. Based on photoresist's point of view, the first two are the most important factors of LWR performance control.
Several designs of experiments (DOEs) were planned with polymers, PAGs, and PEB conditions. The target is to achieve
LWR of CDR under the result of MLR.
In this paper, Polymer DOE1 and its statistical analyses have finished. Compared to de-composition efficiency of each
unit, small protection unit and PEB effect are the most important factors, and bulky protection unit shows less influence
for LWR improvement. Small protection unit is more important than bulky protection unit, and high Ea monomers of
both are good for LWR. Based on previous experiences, we have chosen the acid diffusion length / amount of PAG and
PEB temperature for PAG DOE2 plan. Higher PEB is the most effective to LWR. Shorter diffusion length PAG with
fewer loading amounts is better for MEEF and EL by DOE2 result. The final DOE3 is combined by optimized polymers
by DOE1 and optimized PAG by DOE2. The polymer is used DOE1 Tr2, DOE1 Tr4, and estimated new polymer by
DOE1 result, and the PAG is chosen shorter diffusion PAG-O with the split of loading amount and PEB temperature.
Based on the statistical analyses of DOE3 result, higher PEB temperature is still the most effective to LWR, and new
polymer and DOE1 Tr2 polymer are better for LWR reduction. However, higher PEB temperature would suffer a little
bit of DOF, EL, and MEEF.
In order to achieve the lower LWR, it needs to use DOE1 Tr2 polymer with higher PEB, but insufficient DOE and
MEEF would get at the same time. New polymer by DOE1 combined fewer PAG-O loading amount with lower PEB
could get slower sensitivity for all Litho index's requirements. Through DOE works, we found out the volume of
protection unit and PEB were key factors for good LWR. However, these factors are trades off DOF, EL, and MEEF
against LWR, and they need to optimize for the best balanced Litho performances.
