Unpatterned Wafer Inspection for Immersion - KLA

D efect M anagement
Unpatterned Wafer Inspection
for Immersion Lithography Defectivity
Dieter Van Den Heuvel, Frank Holsteyns, Wim Fyen, Diziana Vangoidsenhoven, Paul Mertens, Mireille Maenhoudt – IMEC
Lisa Cheung, Gino Marcuccilli, Gavin Simpson, Roland Brun, Andy Steinbach – KLA-Tencor Corporation
High-yield immersion lithography requires the ability to distinguish between patterning and stack-related defects, such
as wafer and resist-coating/bottom anti-reflective coating (BARC) defects. Extensive optimization of an unpatterned
inspection tool, combined with advanced defect source analysis software, enables clear observation of stack-related
defects through careful partitioning of individual layer inspections.
The switch from dry to immersion lithography has important
consequences regarding wafer defectivity. The immersion
process introduces additional types of defects that are primarily
related to the physical contact of the immersion fluid (water)
with the wafer surface. This article refers to resist coating
defects, as well as defects coming from the silicon wafer or the
BARC, as “stack-related” defects, while other types are referred
to as “immersion-specific” defects. Because the most common
approach in the study of lithography-related defects is to make
use of patterned wafer inspection tools, only patterning-related
defects are revealed.
However, this does not allow distinguishing stack-related
defects from immersion-specific defects. This article investigates wafer defectivity throughout the various process steps
prior to and including lithography, in order to understand and
characterize the origin and propagation of defects (size, class,
location) through each of these process steps. This requires
extensive metrology optimization.
Unpatterned wafer defect inspection was performed using
various darkfield inspection tools including the SurfscanTM
SP1DLS and SP2, and a brightfield inspection tool (KLA-Tencor
2351TM). Defectivity after patterning was evaluated on the
same brightfield tool. The lithographic stacks were based on
commercial 193nm resist with and without immersion-dedicated topcoats. Defect review and classification were performed
by SEM and optical microscopy.
Unpatterned Defect Inspection Technology
The Surfscan SP2 unpatterned inspection system employs a
UV laser (355nm) for scanning across the wafer surface and
detecting any unusual light scattering as defects. As most existing “dry” resist stacks have been well characterized with its
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predecessor, Surfscan SP1, using a 488nm laser for the existing
lithography processes, the benchmarked typical resist defects
are already well understood. With the shorter wavelength and
a higher power laser, the SP2 not only achieves a significant
improvement in the sensitivity for contamination defects but
also resolves the easily overlooked process-induced “flow” type
of defects in the resist stack.
Typically, the smallest characteristic size of photolithographic
structures is in the range of half the wavelength used, targeting
45nm technologies. Defects on the order of a half wavelength
are therefore potential yield killers. The reduced laser spot size
of the SP2 along with its optimized collection angles and faster
signal processing allows the system to achieve the necessary
sensitivity at a production throughput suitable for monitoring
these smaller defects in the litho substrate and films.
Lithography Stack Information
One of the most important concerns when switching from
dry to wet lithography is to overcome the leaching of resist
constituents into the immersion fluid, resulting in possible
contamination of the lens. Previously, the introduction of a
topcoat was the primary approach to making the dry resist
applicable to immersion processing. Today, the introduction of a new generation of low leaching resists, such as the
PAR-IM850 (Sumitomo) makes it possible to process without
a topcoat. This study focuses on the defectivity of the spincoated anti-reflective coating ARC-29A (Brewer Science/Nissan Chemicals) and PAR-IM850 layers. Both layers are organic
polymers with propylene glycol monomethyl ether acetate
(PGMEA) as the primary solvent. The majority of these solvents are removed from the material during a 60s soft bake at
temperatures of 205°C and 105°C respectively. This bake step
also promotes the adhesion and stabilizes the film.
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D efect M anagement
Having the choice of either normal or oblique incidence
enables the detection of defects of specific types at different
detection thresholds. Practically, the two incidence angles lead
to different responses for a PAR-IM850 resist stacked on
ARC-29A with silicon as substrate. Using Klarity DefectTM,
defect source analysis (DSA) can be used to compare defect
locations on the two wafer maps to, in this case, a tolerance
radius of 200µm (Figure 3). This map-to-map technique allows common and added/unique defects to be quantified on
a histogram or identified on a wafer map. This technique was
used throughout the paper to identify differences in capture
rate between normal and oblique modes, and to show common and added/unique defects throughout the resist stack. In
this case normal incidence appeared to give a higher number
Resist Stack, 70nm PSL
BARC
Resist (150nm)
Scattering Intensity (ppm)
1
0.1
SP1 DW-PU
SP1 DN-PU
SP2 DW-PU
SP2 DN-PU
0.01
0.001
0.0001
0
50
100
150
200
250
Resist Thickness (nm)
Figure 1: Scattering intensity model of a 70nm PSL sphere on a resist
stack, at varying resist thickness, comparing Surfscan SP1 and SP2
(DW – Dark Wide, DN-Dark Narrow) collection channels.
Resist Stack, 70nm PSL
Resist (150nm)
Scattering Intensity (ppm)
1
Defect Detection on Resist
Figure 1 shows the scattering intensity model of a 70nm
polystyrene latex (PSL) sphere on a resist stack. A zero resist
thickness, denoted on the graph, essentially represents the
BARC layer on top of a bare silicon substrate. A 150nm resist
thickness was used in the experiment. It is apparent that the
SP2 provided a much higher scattering signal over all thicknesses than the SP1, illustrating better sensitivity of the SP2
for smaller defects. The SP2 was also better at detection of
sub-100nm defects in the litho stacks.
190
0
110
90
80
70
126
60
Common with
oblique
Defect Count
Defect Count
116
120
250
Figure 4 shows the comparison of the SP2 to the 2351 brightfield inspection results. The 2351 system’s 0.25µm pixel-size
inspection of the resist (visible light, avoiding any exposure of
the resist) gave a comparable sensitivity to the oblique illumination of the SP2. Again, a better result was observed using
the normal illumination. The variation in defect counts was
mainly due to the difference in cluster reporting.
60
130
200
90
0001:PAR-IM850_Oblique
0002:PAR-IM850_Normal
70
160
140
150
of additional defects. This is mainly due to a higher number
of randomly distributed unique defects sensitive to the normal
incidence inspection close to the detection limit. A second contribution came from the higher count of defects from clusters.
80
150
100
Figure 2: Scattering intensity model with P-U, S-U and C-U polarizations.
90
Unique normal
170
50
Resist Thickness (nm)
0001:PAR-IM850_Oblique
0002:PAR-IM850_Normal
180
0.001
0.00001
220
200
SP2 DW-PU
SP2 DN-PU
SP2 DW-SU
SP2 DN-SU
SP2 DW-CU
SP2 DN-CU
0.01
0.0001
Besides resist thickness, another parameter that affects the
scattering signal for detection of defects is the choice of
polarization of the incident and scattered light. The polarization configuration of P-U (P-polarized for the incident optics
and Unpolarized for the collection optics) was selected for the
specific resist stack thickness (150nm), as seen in figure 2. The
figure represents the scattering signal of a 70nm latex sphere
at a specific thickness. At any particular film thickness, the
combined constructive and destructive interference effect
requires selection of the appropriate optical configuration to
achieve the best scattering signal for these thin resist stacks,
ARC-29A and the PAR-IM850.
210
0.1
61
50
40
30
Individual LPDs
20
Clusters
50
38.400<=x<= 40.000
36.800<=x<= 38.400
35.200<=x<= 36.800
33.600<=x<= 35.200
32.000<=x<= 33.600
25.600<=x<= 27.200
27.200<=x<= 28.600
1 12 2
11
30.400<=x<= 32.000
11 2 2
28.800<=x<= 30.400
3
24.000<=x<= 25.600
1
20.800<=x<= 22.400
22.400<=x<= 24.000
19.200<=x<= 20.800
3
1 1
17.600<=x<= 19.200
16.000<=x<= 17.600
11
14.400<=x<= 16.000
12.800<=x<= 14.400
11
11.200<=x<= 12.800
23
8.000<=x<= 9.600
0002:PAR-IM850_Normal
1
9.600<=x<= 11.200
0001:PAR-IM850_Oblique
11
6.400<=x<= 8.000
0
1
4.800<=x<= 6.400
10
3.200<=x<= 4.800
0
20
1.600<=x<= 3.200
96
30
10
0.000<=x<= 1.600
40
Defect Count
Figure 3: Comparison of defects for normal versus oblique illumination.
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2351 (0.25µm pixel)
Defect counts: 154
SP2 Oblique (>72nm LSE)
Defect counts: 811
SP2 Normal (>76nm LSE)
Defect counts: 1449
Figure 4: Comparison of different inspection tools/modes.
Noise Suppression
The choice of polarization and collection angles is important
for suppressing the noise contribution from surface roughness
(source of N) induced by the wafer processing. Organic films
typically contribute a high level of surface scattering at UV
wavelengths, depending on the film-specific chemical composition. A built-in optical filter on the SP2 can suppress this
surface scatter from photons carrying higher energy at the UV
wavelength than ones at 488nm on SP1. Up to 50% of suppression of the background signal (haze) can be obtained.
The SP2 allows the selection of either 10% or 100% of the full
laser power in the recipe to minimize any potential for material
damage at UV wavelengths and high power dosage, for resists
and other organic films. In order to compare the potential
damage to the resist, and to try and understand the mechanism
behind any changes, wafers with PAR-IM850 were scanned
ten times using normal incidence with the optical filters off for
10% and 100% laser power. Figure 5 shows the average haze
for the wide and narrow channels after each scan. 100% power
was shown to change the haze by 7% and 5% for the wide and
narrow channels respectively after 10 scans. The 10% level resulted in a minor change in the haze signal. The change in haze
may be a surface modification due to solvent outgassing from
the surface, a minor reflowing of the top surface or a chemi-
To check for modifications of the chemical bonding at 10% or
100% power, FTIR was used. The wafers, scanned with the
SP2 (one scan and 10 repeated scans) were compared to a reference wafer that had not been scanned. No evidence was found
for any SP2-induced change in photoresist composition or bond
structure. These results indicated that probably some solvents
were evaporating from the resist during the laser exposure.
Recipe Summary
Recipes for all resist stack layers in the study were optimized
with the above considerations to achieve the best signal to
noise. Table 1 summarizes the best available defect threshold
(Latex Sphere Equivalent, LSE) with two sensitivity-determination methods. In all cases, the sensitivity achieved on the SP2
was better than that of the SP1, demonstrating the need for
the use of SP2 for immersion lithography resist monitoring as
design rules shrink. All scans on the SP2 were performed with
the 10% laser power mode and the use of optical filters for both
channels (wide and narrow).
ARC-29A
S/N = 1.5
Capture rate >95%
SP2 Wide Oblique
83nm
80nm
Narrow Oblique
94nm
84nm
SP1 Wide Oblique
95nm
64nm
105nm
101nm
SP2 Wide Oblique
75nm
71nm
Narrow Oblique
72nm
65nm
SP2 Wide Normal
76nm
69nm
Narrow Normal
76nm
69nm
SP1 Wide Oblique
90nm
87nm
-7
Narrow Oblique
82nm
78nm
-8
SP1 Wide Normal
81nm
81nm
149nm
145nm
1
Average haze: percentage change (%)
cal change in the resist. All inspections were for this reason
performed at 10% laser power.
10% laser power
0
Narrow Oblique
PAR-IM850
-1
-2
-3
100% Wide
100% Narrow
-4
10% Wide
10% Narrow
-5
100% laser power
-6
0
1
2
3
4
5
6
7
8
9
10
Narrow Normal
Run No.
Figure 5: Change in average haze of PAR-IM850 over 10 scans for 10%
and 100% laser power, measured in wide and oblique channel of the SP2.
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Table 1: Signal to noise versus capture rate for the different layers, comparing
SP1 and SP2 versus normal and oblique for the ARC and resist. SP2 recipes were
set at 10% laser power and optical filters for both channels.
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D efect M anagement
Defect Analysis: Stack-Related vs.
Immersion-Specific Defects
When monitoring an immersion lithography tool (ASML
XT:1250Di) or process with particle per wafer pass (PWP)
tests, a typical tool monitoring technique, it is important to be
able to understand whether the defects are related to the resist
stack or they are intrinsic to the immersion process itself. A
clear distinction allows one to continue the ongoing improvement in defect reduction. Thus, a partitioning experiment was
performed to allow the calculation of the impact of each layer
on total defectivity, and determine the impact of these defects
on the overall pattern formation. An overview of the partitioning experiment is given in figure 6. Note that specific patterning defects were excluded from this study.
Si
SP2
ARC-29A
2351:
0.16µm pixel
Finally, defect maps before and after scan/development were
compared, and a defect source analysis was performed on the
results to distinguish between stack-contributed defects and
immersion-specific defects.
Scan at zero dose
In the experiment, the unpatterned wafer inspected area was
660.5cm2, using high sensitivity mode, with 5mm edge exclusion. The patterned inspection used a different inspection area,
determined by the number of available die on the wafer that
could be inspected using the 2351 (556.18 cm2). This would
have affected the results if defects had been found at the edge
of the wafer; however, the SP2 inspection results showed that
the majority of the defects were not from this region.
Scan (nominal dose)+PEB+develop
Scan at Zero Dose
SP2
PAR-IM850
SP2:
normal
ing part of the stack consisted of a photoresist PAR-IM850
coating and soft bake. This layer was also inspected by the
SP2 in normal mode at LSE>76nm. In some practical cases
the intermediate inspection of the ARC layer was skipped.
The next lithography processing step on the ASML 1250i was
either a scan at zero exposure dose (simulating an immersion
lithography process) or full exposure plus post-exposure bake
and development to give the printed pattern.
PAR-IM850
SP2
ASML
XT:1250Di
Figure 6: Pathway of partitioning experiment with intermediate
inspection steps.
The starting material, bare silicon (MEMC – p Mon F130),
was first inspected with a SP2 recipe at LSE >52nm including
a crystal originated particle (COP) classification to determine
incoming baseline defectivity. An ARC layer was coated on the
silicon wafer, followed by a soft bake. This layer was inspected
by the SP2 in the oblique mode for LSE >83nm. The follow-
After the stack formation, the wafer was scanned with water (in
the ASML XT:1250Di) at zero dose to mimic a typical wafer
passing under the immersion head, and determine the effect
of the water flow over the wafer during exposure. The wafer
was then re-measured on the SP2 to isolate immersion-related
defects from the stack defects.
From the results in figure 7, the impact of each layer during
the stack formation was observed. A map-to-map coordinate
comparison at each step allowed the close examination of defects contributed from each specific process step with a
800
700
Immersion induced defects
0001:Silicon
0002:PAR-IM850
0003:PAR-IM850-latent
600
672
365
Defect Count
500
400
Substrate / Coating defects
171
300
139
200
100
216
211
PAR-IM850
PAR-IM850-latent
0
Silicon
Figure 7: Defects reported throughout the stack: Silicon, ARC-29A/PAR-IM850 (post ARC/resist coat) and PAR-IM850 (latent: post scanning
at zero dose) for LSE >76nm. It is clear that a significant number of defects were added during the immersion step.
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800
700
Patterning defects
0001:Silicon
0002:ARC-29A
0003:PAR_IM850
0004:2351_UV_0.16
600
Defect Count
500
400
674
382
Resist / Coating defects
300
200
184
100
112
0
Silicon
20
55
9
53
2
ARC29A
ARC-29A
PAR_IM850
2351_UV_0.16
Figure 8: Defect reported throughout the stack: Silicon, ARC-29A, PAR-IM850 (post resist coat) and PAR-IM850 after exposure/patterning.
comparison stack tolerance set at 200µm (ARC and resist comprised one measurement). It was clear that a significant number
of defects (>76nm LSE (optimized recipe)) were added during
the immersion step. However, the various types of stack-related
defects were not to be neglected. They were typically embedded in the resist. The final impact of these defects (stack-related or immersion-related defects) on the lithographic process
is not known; a detailed study on the impact on patterning is
required.
Exposed Wafer Tests (Regular Patterning), Example 1
To study the impact of stack-related defects on patterning
defects, and distinguish them from immersion-related defects,
the wafers were exposed and parallel lines were patterned in
the resist. A parallel study was conducted using a wafer in
which the stack was formed and measured in the same manner
as above, except that the wafer was exposed with a small die
(10x10mm2) reticle, using exposure conditions to produce
100nm line/space features.
Defects originating from the
incoming silicon wafer were
traced through the ARC-29A
coat step and the PAR-IM850
coat step, as illustrated in
figure 8. The influence of the
ARC-29A-defects was traced
through the resist coat step
and also the final develop and
rinse steps. In this case ~30%
of the defects inspected after
pattern formation were attributed to the previous layer,
with the resist layer having
the highest influence. The
remainder of the defects were
attributed to current-layer
patterning.
2351 patterned inspection
a.
b.
Figure 9: a) Inspection and optical review of the wafer after patterning; b) StreakTM inspected by the
Surfscan SP2 SURFimage.
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As indicated by the optical review results (Figure 9),
the majority of the defects
added during the resist coat
step were particles in or on
the surface of the resist. The
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D efect M anageMent
a.
b.
Figure 10: a) SURFimage of PAR-IM850 from the normal narrow channel, and b) the corresponding flow defect
(originated from a cluster defect) captured by algorithm.
300
Defect Length (mm)
Defect Area (mm2)
250
Defect feature
200
a. Normal Narrow
150
100
50
0
1
2
3
4
5
6
7
Defect ID
b. Multiple defects captured
c. Example of two extracted parameters: defect length and area.
Figure 11: a) SURFimage of PAR-IM850 from normal narrow, and b) all flow defects captured by the algorithm,
c) with the defect length and area parameters displayed for each defect.
500
Defect Count
400
Patterning defects
0001:Silicon COP Classified
0002:ARC-29A
0003:PAR-IM850
0004:2351 Patterned
300
674
200
379
342
Stack related defects
125
100
86
10
0
Silicon COP Classified
ARC-29A
PAR-IM850
2351 Patterned
Figure 12: Defects reported throughout the stack: Silicon, ARC-29A, PAR-IM850 (post resist coat) and PAR-IM850
after exposure/patterning.
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critical patterning defects
(Figure 10) which later were
found to originate at the resist
steps were clearly mapped to
a streak defect by the Surfscan
SP2 SURFimage map — an
enhanced haze capability on
the Surfscan SP2 — earlier in
the inspection steps. The defect
cluster with its “comet tail”
caused a high defect count.
More important, the small
variation in resist uniformity
can lead to a more significant
effect of subsequent variation
in line width due to a thinnerthan-nominal resist layer, or a
missing pattern in the worstcase scenario for patterned
wafers. These defects were captured by a prototype algorithm
outputting a defect feature
vector of over 20 attributes
(such as length, area, intensity,
haze statistics, orientation, etc.)
which was used for classification and defect binning.
The streak defect feature was
extracted and displayed as
figure 10b. This extraction of
feature-only representation
allows the defect to be exported
for display in Klarity as a
clustered, extended defect. The
attributes are then available
for Paretos, decision making,
process control, etc. Figure
11 shows a different PARIM850 wafer with multiple
streak defects, all of which
were captured by the algorithm, although one streak was
captured as two different defect
segments. The length and area
calculated by the algorithm
for each defect are displayed in
figure 11c.
Exposed Wafer Tests
(Regular Patterning),
Example 2
A second case, shown in
figure 12, showed an improved
defectivity level. In this case
the influence of the stack-related defects was lower: ~5%
of the defects originated from
the substrate. Defects from the
substrate appeared to be COPs
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detected during the brightfield inspection.
Conclusions
In this inspection the capture rate of the silicon defects in the
ARC-29A was lower than that seen in the resist inspection or
in the previous example. This was due to a slight change in
the sensitivity in the ARC-29A recipe; however, the impact
of the COPs/particles could be clearly seen during the resist
inspection (Figure 13).
For successful and efficient process control during immersion
lithography, the capability to distinguish immersion/patterning-related defects from stack-related defects is very useful.
The stack-related defects were observed only after careful
partitioning of individual layer inspections and defect source
analysis using Klarity.
The defects seen as small, dark dots on the patterned inspection map were common to the defects seen during the SP2
silicon wafer initial inspection, mostly matching the spatial
patterns of the COPs. The majority of defects observed on the
BARC and resist were particles, as seen in figure 14.
The optimization of the unpatterned inspection tool, SP2, was
central. Improved sensitivity at adequate signal-to-noise ratio
was easily obtained on the resist stacks by using the shorter
wavelength, UV-laser light of the SP2. For bare Si and BARC,
oblique-incidence illumination gave better sensitivity and
captured more defects. However, monitoring of the resist,
and stacks with resist, required
normal-incidence illumination
for best scattering intensity.
The use of an optical filter and
the 10% laser power setting
also contributed to establishing
a low, stable background signal
for each inspection.
As immersion tool development is improved and immersion-specific defectivity
is reduced, the proportion of
stack-related defects will
become a significant fraction of
the overall defect count. A detailed method has been shown
for the accurate monitoring of
these stack-related defects. This
includes point defects (embedded particles) or flow defects
(streaks) identified and classified using SURFimage.
Figure 13: Silicon defects in final pattern, filtered using Klarity.
BARC
This information was used to
identify the defect origin(s) for
ultimate elimination of defects
in the stacks. Stack defects continue to be important for either
dry or wet lithography steps, as
they have direct implications
to the subsequent processing
steps. However, determining
the direct impact of individual
stack defects on the final defectivity of the immersion process
will require additional studies
as the immersion process further improves and matures. F
Figure 14: BARC and resist defects, filtered using Klarity.
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