In advanced optical lithography the requirements of focus control continues to tighten. Usable depth of focus (DoF) is already quite low due to typical sources of focus errors, such as topography, wafer warpage and the thickness of photoresist. And now the usable DoF is further decreased by hotspots (design and imaging hotspots). All these have put extra challenges to improve focus metrology, scanner focus stability calibrations and on-product correction mechanisms.
Asymmetric focus targets are developed to address robustness in focus measurements using diffraction-based focus (DBF and μDBF) metrology. A new layout specific calibration methodology is introduced for baseline focus setup and control in order to improve scanner focus uniformity and stability using the measurements of the above mentioned asymmetric targets. A similar metrology is also used for on product focus measurements. Moreover, a few novel alternative methods are also investigated for on-product focus measurements.
Data shows good correlation between DBF and process on record (POR) method using traditional FEM. The new focus calibration demonstrated robustness, stability and speed. This technical publication will report the data from all the above activities including results from various product layers.
Immersion technology has successfully extends the application of ArF lithography in the semiconductor. However, as we further push the k1 factor below 0.3, the patterning fidelities degrade significantly. In this paper, a novel method to quantify the mask fidelity of complex 2D patterns is proposed. With this method, the critical dimension (CD) error of both edge placement error (EPE) and corner rounding can be well described by using 2 indices "bias" and "blur" respectively. The "bias" is defined as the CD offset between the mask and the targets, and the "blur" is a derived term that can well represent the mask rounding. These 2 indices are not only able to describe the mask quality but also able to link with model parameters that are used in optical proximity correction (OPC) and some other applications. In this paper, we demonstrate the methodology and quantify the actual mask quality on the complex and critical 2D patterning in the advanced nodes.
The impact on yield loss due to systematic defect which remains after Optical Proximity Correction (OPC) modeling has increased, and achieving an acceptable yield has become more difficult in the leading technology beyond 20 nm node production. Furthermore Process-Window has become narrow because of the complexity of IC design and less process margin. In the past, the systematic defects have been inspected by human-eyes. However the judgment by human-eyes is sometime unstable and not accurate. Moreover an enormous amount of time and labor will have to be expended on the one-by-one judgment for several thousands of hot-spot defects. In order to overcome these difficulties and improve the yield and manufacturability, the automated system, which can quantify the shape difference with high accuracy and speed, is needed. Inspection points could be increased for getting higher yield, if the automated system achieves our goal. Defect Window Analysis (DWA) system by using high-precision-contour extraction from SEM image on real silicon and quantifying method which can calculate the difference between defect pattern and non-defect pattern automatically, which was developed by Hitachi High-Technologies, has been applied to the defect judgment instead of the judgment by human-eyes. The DWA result which describes process behavior might be feedback to design or OPC or mask. This new methodology and evaluation results will be presented in detail in this paper.
In 32nm/22nm advanced technology node, double patterning lithography is considered for semiconductor manufacturing.
It necessitates tightened requirement of overlay measurement, i.e. to measure the position of a pattern with respect to that
of a pattern in the underlying layer. The measurement target design plays a fundamental role in overlay precision and
accuracy. Typical alignment target, such as bar-in-bar or box-in-box (BIB), has precision, accuracy, and size restrictions.
This prompts us to look into better alignment targets. Recently, scatterometry-based metrology and profile model
capability have been extended to measure multi-level grating structures. In addition, scatterometry has been shown to be
the best choice for integrated metrology to perform wafer-to-wafer control. Therefore, it makes sense to consider using
scatterometry for overlay measurement.
In this research, the modeling analysis is performed on the spectra taken directly from a real pattern area with grating-ongrating
structure. The critical dimension (CD) at the grating on top and the lateral shift between the top and the bottom
gratings can be detected simultaneously. The lateral shift between the layers can be verified with the traditional overlay
box. Unlike the traditional BIB target that has micrometer CD size, the CD size of the scatterometry overlay (S_OVL)
target is much closer to that on the real device. So, it can much better reflect the overlay (OVL) shift on real devices. We
also studied the non-model-based S_OVL measurement using a 673-nm semiconductor laser with a 10μm x 20μm target
size, wafer-to-wafer control of CD and lateral shifts on some critical layers with grating-on-grating structure, as well as
the CD and OVL variations within layer and from layer to layer for double patterning.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.