An after etch overlay measurement on device is typically used as a reference overlay as this is what determines the final overlay. The delta between on target overlay from after develop (ADI) and this reference overlay on device after etch (AEI) is known as the metrology to device offset (MTD). As the fab overlay is controlled by a run-to-run control of ADI overlay, it is preferred to minimize the MTD. The MTD concept in overlay metrology has long been present in the industry and many ways to mitigate this problem have been adopted (such as designing overlay target at ADI that has a similarly low aberration response as the device, or dialing in a static offset between ADI and AEI overlay, etc.). As overlay margins continue to shrink, existing methods start to show gaps and are insufficient to suppress the MTD to an acceptable level on the few most critical overlay layers. In order to address this gap, we need to deploy a much wider solution space that provides an integrated design-lithography-etch solution. In order to characterize the MTD, (assuming that target design in ADI has already minimized aberration response delta between target and device), it is important to understand that there are two major components to MTD: (1) an inaccuracy in ADI overlay (metrology artifacts mostly due to the presence of target asymmetry) and (2) etch to litho offset due to any post ADI added effects such as etch induced expansion and/or stress release etc. However, the above two components are strongly coupled and traditional characterization methods have difficulty in separating their contribution to the measurement. In this technical paper we will discuss novel methods (data driven as well as model-based) to decouple these and multi-lot results will show that MTD can be further minimized compared to traditional static correction between ADI and AEI.
The on-product overlay roadmap demands an aggressive overlay requirement in the advanced node. Currently the on-product overlay is dominated by effects coming from wafer processing and overlay target detectability. Processing effects such as symmetric stack variation and asymmetric overlay target deformations are expected to become limiting for accurate overlay measurements in future nodes
. Increased accuracy requirements and overall complexity in product stacks require a sensor with a higher flexibility. To address this an advanced metrology system is introduced in the fab, providing full flexibility in the selection of measurement wavelengths. On top of the wavelength flexibility, the increased wavelength switching speed enables the use of asymmetry robust recipes by combining multiple wavelength measurements at each overlay target.
In this paper we will introduce a method to select the most accurate multi-wavelength recipe that provides significant improvement in accuracy compared to the best single wavelength recipe. We will introduce KPIs to monitor the health of the multi-wavelength measurement. The KPIs are reported per site indicating the accuracy for every measured point.
Additionally we will show our steps towards the recovery of the points flagged by multi-wavelength KPI by a combination of measuring more wavelengths and an accuracy guided region of interest selection.
KEYWORDS: Overlay metrology, Semiconducting wafers, Etching, Polarization, Metrology, Scanning electron microscopy, Physics, Signal processing, Monte Carlo methods, Semiconductor manufacturing
Success of diffraction-based overlay (DBO) technique1,4,5 in the industry is not just for its good precision and low toolinduced shift, but also for the measurement accuracy2 and robustness that DBO can provide. Significant efforts are put in to capitalize on the potential that DBO has to address measurement accuracy and robustness. Introduction of many measurement wavelength choices (continuous wavelength) in DBO is one of the key new capabilities in this area. Along with the continuous choice of wavelengths, the algorithms (fueled by swing-curve physics) on how to use these wavelengths are of high importance for a robust recipe setup that can avoid the impact from process stack variations (symmetric as well as asymmetric). All these are discussed. Moreover, another aspect of boosting measurement accuracy and robustness is discussed that deploys the capability to combine overlay measurement data from multiple wavelength measurements. The goal is to provide a method to make overlay measurements immune from process stack variations and also to report health KPIs for every measurement. By combining measurements from multiple wavelengths, a final overlay measurement is generated. The results show a significant benefit in accuracy and robustness against process stack variation. These results are supported by both measurement data as well as simulation from many product stacks.
The optical coupling between gratings in diffraction-based overlay triggers a swing-curve1,6 like response of the target’s signal contrast and overlay sensitivity through measurement wavelengths and polarizations. This means there are distinct measurement recipes (wavelength and polarization combinations) for a given target where signal contrast and overlay sensitivity are located at the optimal parts of the swing-curve that can provide accurate and robust measurements. Some of these optimal recipes can be the ideal choices of settings for production. The user has to stay away from the non-optimal recipe choices (that are located on the undesirable parts of the swing-curve) to avoid possibilities to make overlay measurement error that can be sometimes (depending on the amount of asymmetry and stack) in the order of several “nm”. To accurately identify these optimum operating areas of the swing-curve during an experimental setup, one needs to have full-flexibility in wavelength and polarization choices. In this technical publication, a diffraction-based overlay (DBO) measurement tool with many choices of wavelengths and polarizations is utilized on advanced production stacks to study swing-curves. Results show that depending on the stack and the presence of asymmetry, the swing behavior can significantly vary and a solid procedure is needed to identify a recipe during setup that is robust against variations in stack and grating asymmetry. An approach is discussed on how to use this knowledge of swing-curve to identify recipe that is not only accurate at setup, but also robust over the wafer, and wafer-to-wafer. KPIs are reported in run-time to ensure the quality / accuracy of the reading (basically acting as an error bar to overlay measurement).
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