Due to the importance of errors in lithography scanners, masks, and computational lithography in low-k1 lithography,
application software is used to simultaneously reduce them. We have developed “Masters” application software, which is
all-inclusive term of critical dimension uniformity (CDU), optical proximity effect (OPE), overlay (OVL), lens control
(LNS), tool maintenance (MNT) and source optimization for wide process window (SO), for compensation of the issues
on imaging and overlay.
In this paper, we describe the more accurate and comprehensive solution of OPE-Master, LNS-Master and SO-Master
with functions of analysis, prediction and optimization. Since OPE-Master employed a rigorous simulation, a root cause
of error in OPE matching was found out. From the analysis, we had developed an additional knob and evaluated a proof-of-
concept for the improvement. Influence of thermal issues on projection optics is evaluated with a heating prediction,
and an optimization with scanner knobs on an optimized source taken into account mask 3D effect for obtaining usable
process window. Furthermore, we discuss a possibility of correction for reticle expansion by heating comparing
calculation and measurement.
As Moore's Law drives CD smaller and smaller, overlay budget is shrinking rapidly. Furthermore, the cost of advanced
lithography tools prohibits usage of latest and greatest scanners on non-critical layers, resulting in different layers being
exposed with different tools; a practice commonly known as 'mix and match.' Since each tool has its unique signature,
mix and match becomes the source of high order overlay errors. Scanner alignment performance can be degraded by a
factor of 2 in mix and match, compared to single tool overlay operation. In a production environment where scanners
from different vendors are mixed, errors will be even more significant. Mix and match may also be applied to a single
scanner when multiple illumination modes are used to expose critical levels. This is because different illuminations will
have different impact to scanner aberration fingerprint. The semiconductor technology roadmap has reached a point
where such errors are no longer negligible.
Mix and match overlay errors consist of scanner stage grid component, scanner field distortion component, and process
induced wafer distortion. Scanner components are somewhat systematic, so they can be characterized on non product
wafers using a dedicated reticle. Since these components are known to drift over time it becomes necessary to monitor
them periodically, per scanner, per illumination.
In this paper, we outline a methodology for automating characterization of mix and match errors, and a control system
for real-time correction.
High index immersion lithography (HIL) is one candidate for the next generation lithography technology following
water immersion lithography. This technology may require only moderate changes of chip making processes and result in
lower cost of ownership (CoO) compared with other technologies such as double processing, extreme ultra violet
lithography (EUVL), and nano-imprinting, and other technologies. In this paper, the current status of high index lens
material and immersion fluid development compared with our requirements is discussed considering microlithographic
lens design feasibility and attainable NA.
Overlay accuracy is a key issue in the semiconductor manufacturing process. To achieve overlay requirements, we developed compensation functions, i.e. Enhanced Global Alignment (EGA), Super Distortion Matching (SDM), and Grid Compensation for Matching (GCM). These functions are capable to reduce all the components except local linear components caused by a wafer global deformation. In this paper we introduce a novel correction framework which includes new compensation function called Shot Correction by Grid Parameter; thereby enabling further enhancements to overlay. Using this novel framework, we show both simulation and experimental data demonstrating improved overlay accuracy.
Outliers in measurement often interfere with alignment. They are caused by sudden damages in the alignment mark, and existence of particles, resist damages and so on. In a conventional way to identify outliers, the observations that have larger residual than previously determined threshold are identified as outlier. It works well only with the operator’s labor of adjusting the threshold according to the deviation of ordinaries (non-outliers). However, labor is a problem especially in Small-Quantity Large-Variation fabrication such as for ASIC, System-LSI and so on. A novel method for elimination of the labor has been developed. It utilizes normal mixture models whose number of components is determined based on the Maximum Penalized Likelihood (MPL) method. It can be regarded as an identification method that determines threshold adaptively using ordinaries’ deviation. Simulation results show that the penalty coefficient, the only parameter of the method, can be a constant in the variation of ordinarie's deviation. It also shows that in the absence of outliers, the accuracy of the method is comparable with the maximum likelihood estimation that is commonly considered to be the best method when the observations follow the normal distribution. The method performs better than conventional ones when there are a sufficient number of observations (no less than ten) in the standard Enhanced Global Alignment (EGA). Superiority of the adaptive method is dependent upon the probability of outlier occurrence, variation of the situation, the number of observations and the complexity of the model fitted to the observations.
Advanced stepper or scanner needs extremely high accuracy alignment system. This alignment accuracy is mainly affected by the errors caused by mark deformations and by optical system. To improve the alignment accuracy of our wafer alignment system called 'FIA' we have developed a method called the 'FFO'. Our studies have already shown that FFO has the effect of reducing the errors caused by mark deformations. To examine the errors caused by optical system, new approaches are adopted. In the new approaches a simulation method and a suitable experimental are used. The simulation results by the new method, Spatial Frequency Analysis of Image, show the relation between defocus and the errors caused by optical system and the superiority of FFO. Suitable experimental system brings us the same results as the simulation method. As a result, FFO also has a positive effect on the errors caused by optical system. FIA with FFO is much more accurate alignment sensor for ULSI production.