Summer03 taking aim

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Taking Aim at the Overlay Metrology Budget for 70 nm John Allgair, Dave Benoit, and Gary Seligman, Motorola, Inc. Mike Adel, Mark Ghinovker, Elyakin Kassel, Chris Nelson, and John Robinson, KLA-Tencor Corporation

The current box-in-box (BiB) overlay mark has been the mainstay of optical overlay metrology for the past 15 years. It has served the industry well since its inception, when design rules were substantially greater than one micron and overlay metrology budgets were measured in hundreds of nanometers. Today, three key challenges are faced by metrology engineers: (1) reduction of total metrology uncertainty (TMU) in order to meet advanced design rule process requirements, (2) improved process robustness in the face of advanced processes, and (3) correlation between scribeline metrology and real overlay in the chip at design rule feature size, type, and pitch. A new grating overlay mark and measurement algorithm has been developed to address these concerns, called AIM (Advanced Imaging Metrology).

Introduction

As design rules shrink and wafer processing becomes more complex, traditional metrics of overlay metrology performance such as precision, tool induced shift (TIS), and tool induced shift variation (TIS-3Ďƒ) are becoming less and less adequate to describe all sources of overlay metrology uncertainty.

Contributions to the overlay metrology error budget from wafer processing such as chemical-mechanical planarization (CMP), 1 or the impact of stepper aberrations on metrology mark2 placement are playing a more dominant role and must be understood as we move towards the 70 nm node.

In the current study, overlay metrology performance on short loop wafers processed with 193 nm lithography for front-end (poly to STI active) as well as back-end (via to copper single damascene metal) was evaluated.

In particular, we explore the comparative performance of periodic structure overlay marks with conventional BiB marks, with and without design rule segmentation. We have demonstrated that both non-segmented and design rule segmented grating marks shows significantly improved mark fidelity

and reduced overall measurement uncertainty when compared with non-segmented and design rule segmented BiB respectively.

Measurement methodology and overlay mark design

Conceptually, overlay metrology using periodic structure overlay marks is similar to the BiB method.3 In both cases, two independent structures, one on each layer are printed concentrically and the displacement between their centers of symmetry is measured. However there are a number of significant differences. In BiB, this displacement is measured in units of pixels on the CCD. For periodic structure overlay marks, however, the pitch of the overlay mark is the unit of measure.

This may be user-defined or measured in real-time. The measurement algorithm is also significantly different.

Periodic signals enable many new methodologies compared with edge-based symmetry detection.

In the current study, the majority of data was collected on 40 Âľm and 20 Âľm square overlay marks containing both X and Y overlay capability, examples of which are shown in Figure 1. Several parameters are available to the overlay mark designer and are subject to optimization.

This optimization can be based on any combination of standard performance metrics, process robustness, and Summer 2003

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For the back-end lot, the first patterning step was on a dielectric stack and was processed as a copper (Cu) single-damascene metal layer. This was followed by Cu CMP and deposition of an intermetallic dielectric stack. The second patterning step was at via. The back-end overlay data was obtained by measuring misregistration between via and metal layers.

All measurements were performed on a KLA-Tencor Archer overlay tool. Both single grab and double grab focus techniques were used. Performance testing included the following metrics: F i g u re 1. Example of over lay ma rks. Top row: box-in- box (BiB) designs. Bott om row: AIM periodic s tru c t u re designs.

device correlation. The main overlay mark optimization parameters are overlay mark size, coarse mark pitch, design rule segmentation details, duty-cycle, etc. In order to enable a fair comparison with BiB alternatives, six different box-in-box and box-in-bar contenders were also included. In the front-end and back-end result figures, the grating marks are of two basic varieties: those with only the coarse segmentation (designated as “NS”) as well as those with both coarse and fine (design rule) segmentation (designated as “Seg”). It should be noted that the coarse segmentation is what can be seen optically in Figure 1. For the cases of BiB (frame-inframe), we similarly have coarse segmentation (denoted as “multi-bar”), fine segmentation (denoted as “Seg”), as well as non-segmented (denoted as “NS”) variations.

It was our intention to find the best-of-breed for both grating and BiB targets, as well as to understand the process of target optimization, and the impact of target variations against the four metrics: precision, OMF, TIS, and TIS-3σ.

Dynamic precision

Dynamic precision is a measure of temporal noise during the overlay measurement. It is calculated as 3σ of the distribution of independent measurements of the same overlay mark in ten dynamic loops.

OMF OMF4 is a measure of site-to-site and wafer-to-wafer variation in the overlay measurement. It is calculated as 3σ of the distribution of the independent measurements of a closely printed array of 4 x 4 identical targets, after removal of the dynamic precision contribution.

TIS TIS is a measure of the systematic error contribution to the overlay measurement resulting from the imperfection of the overlay metrology process (tool-target optical interaction). It is calculated as mean of overlay measurements at 0° and 180°:

TIS was measured on nine fields over the wafer. Mean TIS (<TIS>) is defined as follows:

Wafer processing and metrology conditions

Two short-loop wafer lots (front-end and back-end) were run with the reticle having both traditional BiB overlay marks and periodic structure overlay marks. For the front-end lot, the first patterning step was an active layer, followed by STI processing and an oxide CMP step. This was followed by a gate oxide process and polysilicon deposition. The front-end overlay data was obtained by measuring misregistration between poly and active layers.

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TIS-3 TIS-3σ is defined as follows:

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TMU The TMU is defined as follows:

Here “PREC” stands for dynamic precision and “OMF” — for overlay mark fidelity, and “Match” corresponds to tool-to-tool matching. The mean TIS can be calibrated and, therefore, is not included in this uncertainty formula. For the studies shown here, only one system was available onsite, so tool-to-tool matching was not possible and, therefore, no matching results are used in the TMU calculations shown here. Rigorous tool-to-tool matching results will be presented elsewhere.

BiB results for a variety of target types are on the righthand side of all the subsequent figures, for comparison to the various grating target results. Small overlay marks included in some of the measurements are 20 µm in size, when available. Figure 2 shows precision results.

The periodic structure overlay marks improve precision by a factor of two. Figure 3 shows OMF results. In this case the improvement is by a factor of three.

In order to study the advantages of the grating overlay methodology, a variety of targets — both BiB and grating — were included. Degrees of freedom include coarse segmentation — to the order of one or two microns — of the marks (called multi-bar, in the case of BiB), as well as fine (at or near design rule) segmentation, duty cycle, and the like.

TIS results vary substantially between the various target designs, as seen in Figure 4. For example it can be seen that segmenting BiB targets to make them more representative of device features can significantly degrade TIS performance, a problem that is not seen in the corresponding grating targets studied here. Not surprisingly, reducing the overall grating target size has been seen to substantially improve TIS results. TIS-3σ results show, on average, very little difference between grating targets and BiB results, as seen in Figure 5.

F i g u re 2. Dynamic precision results as a function of overlay mark design.

F i g u re 4. TIS results as a function of overlay mark design.

F i g u re 3. OMF results as a funct ion of overlay mar k design.

F i g u re 5. TI S variability results as a function of overlay mark design.

Front-end results

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Back-end results

Similar studies were carried out for the back-end wafers. Again we see consistently sub-2 nm precision results for the grating marks, as well as for some of the BiB marks (Figure 8). It should be noted that trying to put coarse (multi-bar) and fine (device size) segmentation onto BiB targets can lead to a serious degradation in precision performance, a problem that was not seen in the corresponding grating targets. Also, again we see a substantial improvement in OMF with the grating targets as compared to the BiB results (Figure 9).

F i g u re 6. Measurement uncertainty fo r fron t-end wafer s. Small AIM marks use OMF data from NS AIM marks with a 20 percent penal ty.

The contributions of precision, OMF, and TIS-3σ can be combined to calculate the TMU as defined above.

This metric is plotted in Figure 6. Since OMF arrays were not included in the reticle sets for the 20 µm targets, the OMF value of the non-segmented grating marks, with a 20 percent penalty, was assumed. Figure 7 shows a 40 percent improvement of TMU of the grating targets over the BiB targets on average. This improvement is due, in large part, to the corresponding improvements in precision and OMF. F i g u re 8. Preci sion results as a function of overlay ma rk des ign.

F i g u re 7. Comparison of overlay model ing residuals for fro n t - e n d overlay marks.

F i g u re 9. OMF results as a funct ion of overl ay mar k design.

The data from all marks (sampled in the four corners of the field, nine fields per wafer) was modeled with a standard linear regression correctable model, including wafer and field translation, scale and rotation. Figure 7 shows the distribution and 3σ values of residuals for the different non-segmented overlay marks. Residual errors can include process noise, metrology noise, as well as unmodeled systematics. In this study, a significant reduction of unwanted residuals was seen in the grating targets as compared to the corresponding BiB results.

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TIS and TIS-3σ results were measured for the back-end wafers as well. On average, there is a slight improvement in TIS for the grating targets, however, individual targets vary as can be seen in Figure 10. For TIS-3σ results, we again see very little difference between grating marks and the corresponding BiB targets (Figure 11), which is similar to the results for the front-end wafers.

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improvement in the TMU can be seen in the grating results as compared to many of the BiB results. Of particular importance, adding coarse and fine segmentation to BiB targets in an effort to make them process compatible and device representative, seriously degrades the performance of those marks. This problem is not seen in any of the corresponding grating marks.

F i g u re 10. TIS results as a function of overlay ma rk design.

F i g u re 13. Distribution of resi dual s for back-end overlay mark.

F i g u re 11. TIS varia bil ity result s as a f unction of o verla y mark design.

The contributions of precision, OMF, and TIS-3σ can be combined to calculate the TMU. This metric is plotted in Figure 12. Since OMF data is not present for the 20 µm marks on these wafers, the OMF value of the non-segmented AIM marks, with a 20 percent penalty, is used. Similarly to the front-end results, a substantial

The data from all marks (four sites per field, nine fields per wafer) were modeled with a standard linear regression correctable overlay model including wafer and field translation, scale, and rotation. Figure 13 compares the different non-segmented overlay mark designs in terms of model residuals. Residual values are comprised of process noise, metrology noise, as well as unmodeled systematics. Residuals represent errors that cannot be readily eliminated in a standard production scenario.

Unlike the front-end results, the back-end results show no clear difference between grating results and BiB results for this study.

Discussion

F i g u re 12. Measurement uncertain ty for back-end wafers. Small AIM

The key outcome of the performance study was that the TMU was estimated by the RMS of the precision, TIS-3σ, and OMF. For this particular study, only one system was available on site, so no tool-to-tool matching results were included. The measurement uncertainty calculated in this way shows a 40 percent reduction for the grating marks compared to BiB. The major contributors to this performance improvement were OMF and precision, which were both improved by nearly a factor of two on the front-end layer. TIS-3σ was observed to improve when design rule segmentation was implemented, while OMF was marginally degraded.

By contrast, BiB targets show substantial performance

marks use OMF data from NS AIM marks with a 20 percent penalty.

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degradation when design-rule segmentation is incorporated. Several different pitches and segmentation schemes were reviewed and this has allowed the development of a methodology for target design optimization.

This study was primarily based on 40-µm square targets, with both X and Y included. Due to their nature, no clear zone is required around the targets, which facilitates close packing. Clearly, as scribe-lines shrink, even this valuable real estate must be conserved. As a result, preliminary studies of 20-µm square targets were included here. Initial results indicate good performance, including substantial improvement in TIS results Target optimization was a key part of this study. The grating targets offer numerous degrees of freedom, including overall size, coarse pitch, coarse duty-cycle, fine pitch, fine duty-cycle, lines versus holes, as well as techniques to minimize the influence of undesired lithography and process effects. Methodologies were developed to determine optimal targets for a given process based on optical overlay measurements as well as SEM validations.

Overlay regression modeling is a standard part of all state-of-the-art wafer processes. The goal is to determine the stepper/scanner correctables that minimize the residuals (e.g. translation, scale, rotation, etc.).

Residuals come as a result of process noise, metrology noise, as well as unmodeled systematics. The goal of the grating targets is to minimize the effects of process and metrology noise, as well as systematic effects (such as degradation of the targets due to CMP and deposition, etc) to which we do not want to be sensitive. As a result, one might expect the residuals to be reduced with the introduction of the grating targets, as we saw with the front-end results. A larger statistical sampling of data will be required, however, to be conclusive on this issue. The added sensitivity of these targets to the effects to which the transistors are prone (coma, etc.) may in fact increase the residuals based on current modeling methods.

Conclusion

As Moore’s Law drives the semiconductor industry to tighter and tighter specifications, improvements need to be made in processing, metrology, and process control. Within the lithography community historically, overlay concerns have taken the back seat to issues around CD control. As we approach the 70 nm node, however, overlay concerns rival those of CD and, in 34

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fact, the distinction between the two becomes blurred.

The ominous hurdles ahead require thinking “outside the box,” in order to provide overlay metrology which is process robust and which correlates to actual device overlay. We have shown that BiB targets do not show sufficient potential for process robustness and designrule segmentation; whereas a novel grating overlay target does and can substantially improve precision, OMF and TIS, resulting in substantially reduced TMU. Acknowledgements

The authors would like to thank the following people for their invaluable contribution: Naaz Ullah for her work in preparing the Archer 10 for production in the Dan Noble Center; Traci Smith, Ivan Amador, and Mike Boatright for layout work required to generate the AIM targets on test reticles; and Pavel Izikson for assistance in analyzing the overlay data. A version of this article originally published in the 2003 SPIE Microlithography proceedings 5038, SPIE Microlithography Conference, February 2003, Santa Clara, California, USA. References 1 . Plambeck, Bert F.; Knoll, Noam; Lord, Patrick, C h a r a cterization of Chemical Mechanical Polished Overlay Ta rgets Using Coherence Probe Micro s c o p y, Integrated C i rcuit Metro l o g y, Inspection and Process Control IX, P roceedings of SPIE Vol. 2439 (1995), p.298.

2 . Luci, Alberto; Ballarin, Eugenio G. Optimization of Overlay Markers to Limit measurement error Induced During Exposure by lens Aberration Effects, Metrology, Inspection, and process Control for Microlithography XVI, Proceedings of SPIE Vol. 4690 (2002), p.374.

3 . M. Adel, M. Ghinovker, B. Golovanevsky, P. Izikson, E. Kassel, D. Yaffe, F. Bruckstein, R. Goldenberg, Y. Rubner & M. Rudzsky Optimized Overlay Metrology Fiducials: T h e o ry and Experiment, to be published in IEEE Tr a n s a ctions on Semiconductor Manufacturing.

4 . Mike Adel, Mark Ghinovker, Jorge Poplawski, Elyakim Kassel, Pavel Izikson, Ivan Pollentier, Philippe Leray, David Laidler Characterization of Overlay Mark Fidelity, published in SPIE 2003 pro c e e d i n g s .