76360z by KLA Corporation

Inspecting EUV mask blanks with a 193-nm system Stan Stokowski*a, Joshua Glasser a, Gregg Inderhees a, Phani Sankuratri b a KLA-Tencor Corp., One Technology Drive, Milpitas, CA 95035, USA; bPhani Sankuratri ,46958 Masonic Terrace, Fremont, CA 94539 Abstract Data and simulation results characterizing the capability of a DUV system to inspect EUV mask blanks and substrates are reported. Phase defects and particles on multilayer (ML) surfaces, ARC-coated absorber, and substrate material are considered. In addition to the previously reported results of inspecting phase defects on multilayer surfaces, phase defects on a quartz substrate surface are shown. The principle of phase detection is described. Simulations show that the 22-nm node requirement for phase defect detection should be met, assuming a reduction in the multilayer roughness. Initial inspections of deposited SiO2 spheres show sensitivities of at least 40 nm on ML and quartz; however, the availability of calibrated spheres of smaller diameters has limited testing below this value. Simulation results show relative sensitivities for detecting SiO2 spheres of different diameters on various EUV materials. Keywords: EUV blank inspection, phase defects, particles, DUV inspection, EUV multilayer roughness

1. INTRODUCTION EUV mask blank development requires inspection and metrology equipment to be available now. The industry desires to have an actinic (13.5 nm) inspection tool; however, it will be some number of years before a production-worthy tool is available at this wavelength. In the meantime we must use DUV mask inspection systems to enable rapid development of EUV mask blanks with low numbers of defects. At the 2009 International Symposium on Extreme Ultraviolet Lithography in Prague, Czech Republic, 18-21 October 2009 we reported1 on using a 193-nm system (TeronTM 600) to detect phase defects on multilayer-coated (ML) EUV blanks. We compared our DUV images with those from the actinic Advanced Inspection Tool (AIT) at Lawrence Berkeley National Laboratory (LBNL) and showed substantial similarity of the through-focus imagery between the two tools. Measuring signal and noise levels on the Teron 600 allowed us to determine the signal-to-noise ratios (SNR) of bumps and pits. International SEMATECH provided defect sizes measured with an atomic force microscope (AFM). Comparing the measured signal levels with those calculated by a thin-mask simulation showed good agreement. From these data we estimated that we should be able to detect a 1 nm high x 80 nm FWHM defect with >99% capture probability and 1-10 false defects/mask (142 x 142 mm²) with the Teron 600. Our goal now is to improve the sensitivity so as to detect 1 nm x 50 nm phase defects in future tools. We also reported at the Prague conference that exposure to 193-nm light equivalent to 20-50 inspection scans showed no measurable reflectivity change on Ru-capped or Si-capped ML, either at 193 nm or 13.5 nm, and no ML structural change as measured by X-ray reflectivity (XRR).2 Particle detection at various stages of EUV mask manufacture is also important. Particle detection does require a somewhat different approach than that for phase defects because they, in general, are objects with a combination of phase and amplitude contrast, whereas shallow bumps and pits are almost pure phase objects. In Section 2 we present data on an inspection of a programmed-defect mask, estimates of future sensitivities from simulations, and the principle underlying phase object detection. We also demonstrate that we can inspect quartz (and presumably LTEM) substrates. In Section 3 we discuss preliminary inspections of SiO2 spheres on ML and quartz, commenting on the necessity of obtaining calibrated sphere sizes <40 nm diameter. Using an existing dark-field scattering program we show predicted relative sensitivities for particle detection on ML, ML with an absorber and a 257nm anti-reflection coating (ARC), and quartz.

*stan.stokowski@kla-tencor.com

phone

1-408-875-7501;

fax

1-408-;

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kla-tencor.com

2. PHASE DEFECTS 2.1 Programmed-defect mask We inspected a programmed-defect mask containing bump arrays of known size using the Teron 600 Blank Mode. Figure 1 shows a defect map from that inspection. There are 13 blocks of phase bumps of increasing size from left to right. Block 12 has 1 nm high x 90 nm FWHM defects, with a capture probability of 74%. Block 11 has 1.5 nm x 100 nm FWHM defects with a capture probability of 100%. Blocks 1 through 10 have 100% capture probability. The various colors in the map correspond to different algorithm detectors. The rectangular patches are those which had a number of defects larger than a set limit. The off-grid detections are a combination of real defects and some nuisance/false counts. Nuisance detections are due to ML roughness. Some of the false counts are due to an initial version of our detection algorithm, which has now been improved. We are in the process of inspecting additional programmed-defect masks to continue our development of Blank Mode.

Figure 1. Defect map of an area of an inspected Ru-capped, multilayer, programmed-defect mask.

Figures 2 and 3 respectively show an example of a detected phase bump and a pit on ML. We see here the opposite contrasts of phase bumps and pits, which makes their classification easy.

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Figure 2. An example of a detected bump on a Si-capped ML, both raw and interpolated images. This defect is 2 nm high by 80 nm FWHM and was captured at 100%.

Figure 3. An example of a detected pit on a Si-capped ML, both raw and interpolated images. Independent sizing information was not available, but the optical image suggests it is similar to the bump shown in Figure 2.

2.2 Sensitivity estimates As part of this development we are implementing additional improvements to the special algorithms we use for the Blank Mode. Because multilayer surface roughness is a substantial contributor to the image noise we are characterizing roughness on several mask blanks. Image noise from ML roughness can lead to nuisance detections, whereas system noise can result in false positive detections. Figure 4 shows the relative contributions of roughness and system noise power to the total noise. Our measured (observed) values fall within the range of the first two bars in Figure 4. The last two bars are predicted noise powers based on planned improvements to the system and a 2.5 x lower ML rms roughness. This noise power is, from simulations, required to detect 1 nm high x 50 nm FWHM phase bumps or pits.

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We plan improvements to the Teron system that will lower the system noise. If in addition, ML surface roughness decreases as the mask manufacturing process improves, we can expect a significant reduction in noise power. Relative noise power, observed and future

Observed higher value of roughness/system noise

Observed lower value of roughness/system noise Roughness System

System improvements planned

ML rms roughness lowered by 2.5 x

0.0

0.2

0.4

0.6

0.8

1.0

Relative noise power

Figure 4. Noise power in our images due to ML roughness and system noise. The first two bars are observed noise powers, high and low. The last two bars are predicted based on planned improvements to the system and a 2.5 x lower ML rms roughness, which is required to detect 1 nm high x 50 nm FWHM phase bumps or pits.

To estimate what we might expect for sensitivity once we implement algorithm improvements and the mask suppliers produce even smoother ML surfaces, we calculated the capture probabilities and false count rate per mask using our image simulator. Our simulations match the data obtained from natural defects on a multilayer substrate, as reported at the 2009 EUVL conference in Prague. Figure 5 shows simulation results of the expected capture probability of a 1-nm high phase defect as a function of FWHM and ML surface roughness, assuming a nuisance/false count rate of 1/mask. Note that sensitivity depends on how many false counts per 142 x 142 mmÂ˛ mask are allowed. The detection threshold is lower for a higher false count rate, resulting in a slightly higher sensitivity, which can be initially useful. A false count rate higher than 1/mask will suffice for mask development, but in production a rate of 1/mask is more desirable. We calculate the signal using our image simulator. The noise values input to the signal-to-noise analysis are those shown in Figure 4. If the root-mean-squared (rms) ML roughness decreases by 2.5 times, sensitivity such that we could detect 1 nm high by 50 nm FWHM phase defects. We have seen ML roughness vary by at least 40% in a small sample of only three masks. We are currently working with partners to confirm these predictions.

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Capture probability (%)

100

Current rms roughness/system noise Improved system noise rms roughness 2.5 x lower

0 40

Full width half maximum (FWHM, nm)

Figure 5. Expected capture probabilities from simulations of a 1-nm high phase defect as a function of FWHM, with varying ML surface roughness and system noise, assuming 1 nuisance/false count/mask. The system and roughness noise values inputted to the simulation are from those shown in Figure 4.

2.3 Optical principle for detecting phase defects Detecting phase defects relies on a well-established optical technique for making them visible. However, we need special algorithms and image processing to take full advantage of the low noise of the Teron system. Figure 6 illustrates the phase character of bumps or pits on a surface. Because the defects are relatively shallow and the multilayer is conformal to a first approximation, the reflectance of the defect and its surround are approximately the same. Therefore, there is almost no amplitude contrast present, only a phase contrast.

Figure 6. Schematic diagram illustrating the phase character of bumps and pits

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Mathematically, for defects small in lateral extent, the defect optical amplitude (D) and the amplitude of the surround (S) are

D = exp(iφ )

S =1

(1)

The intensity of each of these regions separately is one. Rigorously the phase φ corresponds to the mean defect phase integrated over the point spread function of the optical system. The smaller the lateral extent of the defect, the smaller this phase is. Image contrast comes from the mixing of these optical amplitudes through the optical point spread function of the system. Maximum contrast arises from a mixing of D and S with approximately equal amplitudes. Thus, the defect intensity contrast is 2

S+D 1 1 Contrast ≈ S − = − [1 − cos(φ )] = − sin 2 (φ / 2) 2 2 2 2

(2)

For small φ, we can expand the sine. The contrast is thus

Contrast ≅ −

φ2

(3)

This quantity is small. To increase image contrast for small phase defects, we can use defocus to shift the relative phase between S and D. At focus, the amplitude point spread function of the optical system has only a real part (Figure 7a). However, under a defocus condition the point spread function has an imaginary part with a ring shape. The image contrast will now come from a mixing of the central spot and the ring, which are 90° out of phase with respect to each other. The contrast becomes 2

Contrast ≈ S −

S + iD = sin(φ ) ≈ φ 2

(4)

We have now made the contrast linearly proportional to the phase. Thus, bumps and pits have opposite contrast signs, and the contrast sign flips in going from positive to negative focus (Figure 7b). Note that the contrast is nearly zero at focus.

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(a)

(b)

Figure 7. (a) Real and imaginary parts of the optical point spread function when defocused and when at focus. (b) Contrast of bumps and pits through focus

2.4 Quartz substrate inspection We have concentrated our effort on ML phase defects; however, the above principle works just as well for any surface, including the quartz substrate and the absorber with ARC. The main difference between sensitivities of the various surfaces is the amount of light reflected from the surface and the surface roughness. Because the quartz substrate has relatively low reflectance, considerably more illumination power is needed to lower the detector shot-noise relative to the signal. We did successfully inspect a quartz substrate with obvious natural defects, including bumps, pits, and particles. Figure 8 shows two typical defect images from that inspection. Note the meandering line in the right image (b); this line could be due to a contamination film on the quartz.

(a)

(b)

Figure 8. Defect images from a quartz substrate inspection: (a) pits (bright) and a bump (dark), (b) pits with a boundary of perhaps film contamination.

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3. PARTICLES Particles have significantly different characteristics from phase defects. Figure 9 is a correctly-proportioned schematic illustrating a 1 nm high x 70 nm FWHM shallow phase defect and a sphere of the same volume. A particle in general has significant height. It scatters more light outside of the imaging aperture, thus it is both an amplitude and phase object. Therefore, the best signal-to-noise ratios for particles and phase defects will be at different focal positions. As amplitude objects particles are best seen near focus; however, they still have significant modulation even under a defocused condition.

Figure 9. Scaled schematic of a 1 nm x 70 nm FWHM phase bump and a spherical particle of the same volume on a Ru-capped multi-layer (Ru is green color; Si is magenta; Mo is cyan)

We have difficulty in obtaining SiO2 spheres that are not agglomerated smaller than 40 nm deposited on ML or quartz. On ML and quartz we do see 40-nm diameter SiO2 spheres at high capture and expect better results, certainly on ML. Until we have a calibrated deposition of spheres <40 nm diameter, however, we can not say anything beyond this. We are still in an early phase of determining our particle sensitivity and the best mode for achieving it. Simulation is part of this investigation. We are modifying a Mie-scattering program that calculates scattered fields for spheres on layered substrates. This program has successfully matched the data for dark-field scattering of particles on unpatterned substrates over six orders of magnitude in scattering cross section and has been in use since 1990. Although we do not have bright field capability on this simulation just yet, we can make an estimate of the relative signal levels of SiO2 particles on the various EUV materials based on dark-field cross sections. Table. Estimated signal levels for SiO2 spheres on EUV materials relative to 50-nm diameter on ML (calculated)

Diameter (nm)

Quartz

EUV ML

ML with absorber and 257-nm ARC

0.015

0.03

0.02

0.06

0.14

0.1

0.16

0.44

0.29

0.34

0.68

The greatest particle sensitivity is on multilayer. When comparing the values in the Table, note that the signal for bright field imagery scales approximately as the volume of the sphere. Thus, a factor of three in signal level translates to a 1.44 factor in sphere diameter. The highlighted values in the Table correspond to those observed

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near the sensitivity limit in our initial inspections, thus supporting the validity of our estimates. We expect to improve on our particle sensitivity in the near future. In the past the semiconductor industry has used polystyrene latex (PSL) spheres as a standard for measuring sensitivity of an inspection tool for detecting particulate defects. Under DUV exposure however, PSL is not stable, thus SiO2 spheres are now in use and likely will become the de facto standard. We must note that PSL has a higher refractive index than SiO2 and as such, scatters more light than an equivalent SiO2 sphere. When comparing a PSL equivalent diameter to a SiO2 equivalent diameter, one must use a factor of ~0.88. Therefore, a sensitivity of 30 nm for SiO2 corresponds to an equivalent PSL diameter of 26.4 nm.

4. CONCLUSIONS We expect to release Blank Mode on the Teron 600 using 193-nm illumination in the near future. It is designed to meet the requirements for development of 32 nm hp EUV blanks. As EUV blank defectivity is one of the critical issues gating insertion of EUV into mainstream lithography, the early availability of Blank Mode should provide unique new capability to help the industry make progress in this important area. Blank Mode is expected to be available as a field upgrade on existing Teron 600 systems, as well as an option on the next-generation Teron. Blank Mode can be used to inspect quartz or LTEM substrates, a ML-deposited mask, as well as an ARC-coated absorber blank. To meet the requirements of the 22 nm hp node, we plan to extend the Teron platform further, including a Blank Mode option along with the usual optical and EUV patterned mask capability options. This capability is expected to be released with timing consistent with the general industry roadmap for EUV pilot line production.

ACKNOWLEDGMENTS KT would like to acknowledge the assistance of Sematech and Intel who have provided test samples, analyzed data, or provided information to us in this development.

REFERENCES [1] Stokowski, S. and Wack, D, â&#x20AC;&#x153;Using a 193-nm inspection tool for multi-layer mask blank inspection,â&#x20AC;? 2009 International EUVL Symposium, Prague, Czech Republic, 18-21 Oct 2009, SEMATECH and ISMI Proceedings Archives: Lithography [2] C. C. Lin, SEMATECH MBDC, private communication (October 2009)

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