In overlay (OVL) metrology the quality of measurements and the resulting reported values depend heavily on the measurement setup used. For example, in scatterometry OVL (SCOL) metrology a specific target may be measured with multiple illumination setups, including several apodization options, two possible laser polarizations, and multiple possible laser wavelengths. Not all possible setups are suitable for the metrology method as different setups can yield significantly different performance in terms of the accuracy and robustness of the reported OVL values. Finding an optimal measurement setup requires great flexibility in measurement, to allow for high-resolution landscape mapping (mapping the dependence of OVL, other metrics, and details of pupil images on measurement setup). This can then be followed by a method for analyzing the landscape and selecting an accurate and robust measurement setup. The selection of an optimal measurement setup is complicated by the sensitivity of metrology to variations in the fabrication process (process variations) such as variations in layer thickness or in the properties of target symmetry. The metrology landscape changes with process variations and maintaining optimal performance might require continuous adjustments of the measurement setup. Here we present a method for the selection and adjustment of an optimal measurement setup. First, the landscape is measured and analyzed to calculate theory-based accurate OVL values as well as quality metrics which depend on details of the pupil image. These OVL values and metrics are then used as an internal ruler (“self-reference”), effectively eliminating the need for an external reference such as CD-SEM. Finally, an optimal measurement setup is selected by choosing a setup which yields the same OVL values as the self-reference and is also robust to small changes in the landscape. We present measurements which show how a SCOL landscape changes within wafer, wafer to wafer, and lot to lot with intentionally designed process variations between. In this case the process variations cause large shifts in the SCOL landscape and it is not possible to find a common optimal measurement setup for all wafers. To deal with such process variations we adjust the measurement setup as needed. Initially an optimal setup is chosen based on the first wafer. For subsequent wafers the process stability is continuously monitored. Once large process variations are detected the landscape information is used for selecting a new measurement setup, thereby maintaining optimal accuracy and robustness. Methods described in this work are enabled by the ATL (Accurate Tunable Laser) scatterometry-based overlay metrology system.
KEYWORDS: Overlay metrology, Metrology, Electron beam lithography, Lenses, Distance measurement, Electron beams, Raster graphics, Semiconducting wafers, Time metrology, Process control
One of the metrology challenges for massively parallel electron beams is to verify that all the beams that are used perform within specification. The Mapper FLX-1200 platform exposes fields horizontally segmented in 2.2 μm-wide stripes. This yields two parameters of interest: overlay is the registration error with respect to a previous layer, and stitching is the registration error between the stripes. This paper presents five novel overlay targets and one novel stitching target tailored for Mapper’s needs and measured on KLA-Tencor Archer 600 image based overlay (IBO) platform. The targets have been screened by exposure of a variable shaped electron beam lithography machine (Vistec VSB 3054 DW) on two different stacks: resist-to-resist and resist-to-etched silicon, both as a trilayer stack. These marks attain a total measurement uncertainty (TMU) down to 0.3 nm and move-and-measure (MAM) time down to 0.3 seconds for both stacks. The stitching targets have an effective TMU of 0.4 nm and a MAM time of 0.75 seconds. In a follow up experiment, the two best performing overlay targets have been incorporated in an exposure by a Mapper FLX-1200. With the new stack a TMU of 0.3 nm and MAM time of 0.35 s have been attained. For 107 out of 140 selected stripes the slope was constant within 2.5%, the offset smaller than 0.5 nm and correlation coefficient R2 > 0.98.
As the overlay performance and accuracy requirements become tighter, the impact of process parameters on the target
signal becomes more significant. Traditionally, in order to choose the optimum overlay target, several candidates are
placed in the kerf area. The candidate targets are tested under different process conditions, before the target to be used in
mass production is selected. The varieties of targets are left on the mass production mask and although they will not be
used for overlay measurements they still consume kerf real estate. To improve the efficiency of the process we are
proposing the KTD (KLA-Tencor Target Designer). It is an easy to use system that enables the user to select the
optimum target based on advanced signal simulation. Implementing the KTD in production is expected to save 30% of
kerf real estate due to more efficient target design process as well as reduced engineering time.
In this work we demonstrate the capability of the KTD to simulate the Archer signal in the context of advanced
DRAM processes. For several stacks we are comparing simulated target signals with the Archer100 signals. We
demonstrate the robustness feature in the KTD application that enables the user to test the target sensitivity to process
changes. The results indicate the benefit of using KTD in the target optimization process.
The newly emerging lithographic technologies related to the 32nm node and below will require a step function in the
overlay metrology performance, due to the dramatic shrinking of the error budgets. In this work, we present results of an
emerging alternative technology for overlay metrology - Differential signal scatterometry overlay (SCOTM). The
technique is based on spectroscopic analysis of polarized light, reflected from a "grating-on-grating" target. Based on
theoretical analysis and initial data, this technology, as well as broad band bright field overlay, is a candidate technology
that will allow achieving the requirements of the 32nm node and beyond it. We investigate the capability of SCOLTM to
control overlay in a production environment, on complex stacks and process, in the context of advanced DRAM and
Flash technologies. We evaluate several metrology mark designs and the effect on the metrology performance, in view
of the tight TMU requirements of the 32nm node. The results - achieved on the KLA-Tencor's Archer tool, equipped
with both broad band bright field AIMTM and scatterometry SCOLTM sensors - indicate the capability of the SCOLTM
technology to satisfy the advanced nodes requirements.
The overlay metrology budget is typically 1/10 of the overlay control budget resulting in overlay metrology total
measurement uncertainty requirements of 0.57 nm for the most challenging use cases of the 32nm technology generation.
Theoretical considerations show that overlay technology based on differential signal scatterometry (SCOLTM) has
inherent advantages, which will allow it to achieve the 32nm technology generation requirements and go beyond it.
In this work we present results of an experimental and theoretical study of SCOL. We present experimental results,
comparing this technology with the standard imaging overlay metrology. In particular, we present performance results,
such as precision and tool induced shift, for different target designs. The response to a large range of induced
misalignment is also shown. SCOL performance on these targets for a real stack is reported. We also show results of
simulations of the expected accuracy and performance associated with a variety of scatterometry overlay target designs.
The simulations were carried out on several stacks including FEOL and BEOL materials. The inherent limitations and
possible improvements of the SCOL technology are discussed. We show that with the appropriate target design and
algorithms, scatterometry overlay achieves the accuracy required for future technology generations.
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