Monitoring slurry stability to reduce process variability

13 Pages·00.377 MB·English

by  John P. Bare, Travis A. Lemke

TECH FOCUS — CMP
Monitoring slurry stability to reduce process
variability
John P. Bare and Travis A. Lemke, FSI International

As chemical mechanical planarization (CMP) becomes more widely used for polishing during
microcircuit manufacture, increasingly sophisticated process control procedures are being
developed and implemented. One of the key areas is measurement of slurry quality. Regardless
of the slurry type or source, maintaining consistent slurry quality or "health" is crucial to
maximizing device yields.1 A slurry's health refers to its stability and contamination level. A
healthy slurry, therefore, is one that maintains its polishing performance while resisting changes
in settling and agglomeration tendencies and is free of contamination, including slurry particle
aggregates and agglomerates, foreign particles, absorbed carbon dioxide, and ionic
contaminants. Dynamic measurements of slurry properties, coupled with defined control limits,
can be used to monitor and control health.
The multipart slurries used by the semiconductor industry often require mixing or dilution
before use. Oxide polishing slurries are commonly purchased in concentrated form and diluted
with water on-site to minimize shipping and labor costs, while some multipart tungsten
polishing slurries must be combined shortly before use because of their short postmix lifetime.
In addition, settling characteristics of the abrasive may change after it is combined with the
oxidizer. Occasionally slurry users or manufacturers measure some physical property unique to
a specific slurry, but normally pH, specific gravity, percent solids by weight, and slurry particle
size distribution are measured after mixing for both oxide and tungsten slurries as part of CMP
process control. Some of these properties are more relevant than others as a monitor of slurry
health, and other parameters not commonly monitored may be more useful. After presenting an
overview of the relevant instrumentation, this article describes a study that evaluated the use of
density, pH, zeta potential, and particle-size distribution as indicators of slurry health.
Slurry Analysis Instrumentation
In addition to choosing which properties to monitor, slurry users must decide whether to use
on-line or off-line measurement instruments. On-line monitoring sounds attractive because it
provides real-time data. Unfortunately, many analytical instruments are not easily adapted to
on-line sampling, requiring rigorous maintenance and calibration for proper operation in such
applications. The analytical instruments used for slurry quality control range from simple and
inexpensive to complex and costly. Table I lists some of these instruments along with their
capabilities.
Measurement Instrument Analysis
Location
Density/specific Densitometer On-line
gravity or off-
line
Percent solids Balance and Off-line
oven
Component Titrator Off-line
assay
pH pH probe and On-line
meter or off-
line
Viscosity Viscometer Off-line
Ionic ICP-MS and Off-line
contamination GFAA
Zeta potential Zeta potential Off-line
analyzer
Particle-size Particle-size Off-line
distribution analyzer

Table I: Slurry analysis instruments and their capabilities.
As the table indicates, densitometers are used to measure density or specific gravity. Off-line
measurement is easy to perform, while on-line measurement requires periodic instrument
maintenance to ensure reliable results.
Percent solids is normally analyzed off-line. For oxide slurries, the principal component of
which is silica, this is a straightforward measurement following evaporation to dryness.
However, because they contain dissolved solids with low decomposition temperatures, many
tungsten slurries require a high-temperature drying procedure that completely decomposes
these components in order to achieve repeatable results.2
Component assays monitor the concentration of dissolved solids (potassium iodate, ferric
nitrate, and so forth) in the chemical component of slurries. The most common technique is off-
line titration for some specific ingredient. Unfortunately, many commercial slurries contain
proprietary ingredients whose composition and concentration are not made available to users,
making measurement, and thus monitoring, more challenging.
Another commonly measured slurry property is pH, although such data may not provide
meaningful information for slurries that are chemically buffered. Even in unbuffered oxide
slurries, silica can act as a buffering agent. However, pH measurements can indicate
contamination levels in slurry. Oxide slurries in contact with air absorb carbon dioxide, and the
resulting decrease in pH can affect the CMP process. The precision and reliability of a pH meter
can be affected by several factors. The potential unreliability of standard pH probes for on-line
monitoring is due in part to clogging of the porous probe membrane by small abrasive particles
and in part to the amount of calibration and maintenance required. Since pH is dependent on
temperature, pH readings also must be temperature compensated.
Significant changes in pH can reduce the absolute charge on slurry particles, leading to particle
agglomeration. Consequently, the relationship between zeta potential and pH can provide useful
information for monitoring slurry health. Other properties, such as viscosity and ionic
contamination, appear on most slurry suppliers' product information sheets. They are
occasionally measured by slurry users as well but rarely are used as routine monitors of slurry
health.
Particle-size distribution is the most recent focus area for monitoring slurry health.
Unfortunately, different particle-size analyzers generate different distributions for the same
slurry. There are three major factors that contribute to these differences: (1) the various
commercially available instruments use different physical principles to measure particle size;
(2) slurry particles are irregularly shaped, in contrast to the polystyrene spheres used to calibrate
many of the instruments; and (3) each instrument uses a different algorithm or statistical
treatment of the raw data. Such differences make it difficult to compare data from the various
analyzers available to the CMP community. Furthermore, there is no consensus on whether
average particle size is more or less important than the number of large agglomerated particles.
Generally, larger particles increase removal rates during CMP processing, but very large
agglomerates may contribute to wafer scratching.3,4
Experimental Procedures
Four commercially available slurries (listed in Table II) were used in the evaluation of density,
pH, zeta potential, and particle-size distribution as indicators of slurry health. The four products
represent the main categories of oxide and tungsten slurries used in volume wafer production.
All are two-part slurries, which provided an opportunity to measure the ability of the various
analytical techniques to detect mixing error. In order to test this capability, "high-solids" and
"low-solids" slurries were prepared such that the percentage of abrasive was 20% higher or 20%
lower than the recommended ratio. (Since some slurries contain dissolved solids in the oxidizer
component, their total percent solids may vary.)
Slurry Manufacturer Active Abrasive
Type/Trade Chemical
Name
Oxide polishing
slurries
Cab-O-Sperse Cabot Potassium Silica
SC-1 hydroxide
Klebosol Solution Ammonium Silica
30N50 Technology hydroxide
Tungsten polishing
slurries
Semi-Sperse Cabot Ferric nitrate Alumina
W-A400/FE-
400
Granite 14 Rodel Potassium Alumina
iodate

Table II: Slurries used in the evaluation of density, pH, zeta potential, and particle-size
distribution as indicators of slurry health.
In addition to the high- and low-solids samples, a sample of each slurry was prepared at the
volumetric mix ratio recommended by the manufacturer (Table III). The diluent (water) or
oxidizer was added slowly. Physical properties were measured within 30 hours of sample
preparation. Density was determined using a volumetric flask: A tared 100-ml flask was filled
with slurry and weighed to the nearest 0.001 g. The pH levels were measured on samples that
had been equilibrated in a constant-temperature bath at 20°C using a meter that was calibrated
by the standard two-point technique before each session and checked for drift after each session.
Percent nonvolatile solids was measured following evaporation to dryness. For three of the
slurries, samples weighing ~2 g were weighed to the nearest 0.001 g and evaporated to dryness
in an oven at 105°C for 1 hour. High-temperature evaporation was used for the W-A400 and
FE-400 slurry components and the W-A400/FE- 400 slurry mixture. After being heated for 1
hour at 105°C, these samples were heated at 500°C for 1 hour to decompose the ferric nitrate
to ferric oxide.2

Slurry Trade Abrasive Diluent or
Name Component Oxidizer
Cab-O-Sperse 1 part SC-1 1.8 parts H2O
SC-1
Klebosol 30N50 2 parts 30N50 1 part H2O
Semi-Sperse 1 part W-A400 1 part FE-400
W-A400/FE-400
Granite 14 1 part Granite 14A 5.5 parts Granite
14B

Table III: Volumetric mix ratios recommended by slurry suppliers.
Particle-size distribution measurements were made by the four analyzer vendors listed in Table
IV. In all cases, 400-ml samples of dilute slurry were shipped to the instrument manufacturers
or their representatives for analysis. The five analyzers used for the study are based on different
operating principles and use different algorithms to develop a profile of a sample's particle-size
distribution. Some characterize the main distribution or the distribution of particles over a wide
range of sizes, while others measure only larger particles. These differences present problems
in comparing results from the analyzers.
Analyzer Manufacturer Analysis Analysis
Model Method Range
(µm)
CHDF- Matec Applied Capillary 0.015—
2000 Sciences hydrodynamic 1.1
fractionation
LA-910 Horiba Classical light 0.02—
scattering 1000
Nicomp Particle Sizing Dynamic light 0.003—5
370 Systems scattering
AccuSizer Particle Sizing Single-particle 0.5—400
770 Systems light extinction
and
light scattering
LiQuilaz- Particle Single-particle 0.5—20
SO5 Measuring light scattering
Systems

Table IV: Particle-size distribution analyzers used in the study.
Another difference between the particle-size analyzers is the channel width, or range of sizes
in each particle count. Instruments with several narrow sizing channels will have fewer particles
in each channel than those with fewer and wider channels. Thus, when distribution profiles
show the percentage of particles in each channel, the analyzers with narrow channels will have
lower peaks than analyzers with wide channels. Channel width is somewhat adjustable on each
of the analyzers used for testing.

Slurry Percent Density at pH at
Component Nonvolatile 20°C (g/ml) 20°C
Solids
SC-1 30.51 1.194 10.26
30N50 30.14 1.185 10.92
FE-400 W- 2.03 5.97 1.045 1.039 1.19
A400 4.39
Granite 14A 25.78 6.56 1.221 1.037 4.18
Granite 14B 3.92

Table V: Physical properties of slurry components as received from suppliers.
Density and pH Results
Table V shows the measured density and pH of the individual slurry components as received
from the manufacturers; Table VI shows the same properties after preparation of the dilute
slurries. In order for density and pH to be used to monitor the concentration of a slurry's
nonvolatile abrasive solids, the change in these parameters with a change in percent abrasive
concentration must be large enough to be detected reliably by the analytical instruments being
used. A linear variation with abrasive concentration was assumed for the dilution range
examined. Figure 1 demonstrates the sensitivity of density to abrasive concentration by
comparing all four slurries, showing a normalized change in delta density as a function of
change in percent abrasive. (Delta density is defined as the deviation in density from the
standard mix ratio density.) As the figure shows, the four test slurries behaved very differently.
The W-A400/ FE-400 slurry showed almost no change in density as abrasive concentration
changed, whereas the 30N50 (dilute) density was very sensitive to changes in abrasive
concentration. The other two slurries had intermediate sensitivities.
Figure 1: Normalized change in density as a
function of percent abrasive for all four test
slurries.

The relationship of delta density to change in percent abrasive can be explained by the
differences between (or similarity of) the densities of the slurry components (see Table V).
Because the W-A400 and FE-400 slurry components have nearly identical densities, 1.045 and
1.039 g/ml, respectively, the density of the mixutre does not vary significantly with mix ratio.
The densities of the 30N50 slurry concentrate, 1.185 g/ml, and its diluent (water), 1.00 g/ml,
are very different; therefore the density of the dilute slurry is very sensitive to the mix ratio. In
general, because they are diluted with water, oxide slurries show greater density sensitivity to
concentration changes than do tungsten slurries, which are mixtures of an abrasive component
and an oxidizer with similar densities.
Slurry Percent Density pH Zeta
Nonvolatile at at Potential
Solids 20°C 20°C (mV)
(g/ml)
ESA- ZLS-
8000 370
SC-1 12.24 1.066 10.29 —28 —31
(dilute)
30N50 21.10 1.121 10.80 —32 —31
(dilute)
W- 4.09 1.042 1.87 5 7
A400/FE-
400
Granite 14 9.80 1.066 4.06 0.3 16

Table VI: Physical properties of slurries after mixing.
Although monitoring the density of slurries such as W-A400/FE-400 is not a useful way to
monitor mix ratio, for other slurries the change in density might be sufficient to do so. The
ability of density to indicate changes in abrasive concentration depends on both the slurry and
the precision of the analytical instrument used. Factors that can reduce the reliability of the
measurements include the presence of bubbles in the slurry; instrument calibration,
repeatability, and drift; and slurry temperature. All of these must be taken into account when
determining the useful precision of the instrument. The relationship between instrument
resolution, slurry type, and minimum detectable change in abrasive concentration is graphed in
Figure 2. As indicated in the figure, a densitometer with a precision of 0.001 g/ml would not
effectively detect small changes in the W-A400/FE-400 slurry; the smallest detectable change
in percent alumina would be ±0.8%, or ±27% relative error for a nominal 3% abrasive slurry.
The densities of the other slurries are more sensitive to changes in abrasive concentration. Using
the same densitometer to monitor a Granite 14 slurry with 4.6% abrasives, the resolution of the
abrasive concentration would be 4.6% ± 0.2%, or ±4% relative error. Use of a densitometer
with higher precision would improve the ability to detect abrasive concentration changes.
Figure 2: The effect of densitomter resolution
on the minimum detectable change in abrasive
concentration.
Figure 3: Normalized change in pH as a
function of percent abrasive for all four test
slurries.

Figure 3 shows the change in pH (delta pH) as a function of change in abrasive concentration
for all four slurries tested. Comparing the two oxide polishing slurries, the 30N50 (dilute) has
a greater pH sensitivity to concentration change than the SC-1 (dilute), which indicates that
using pH monitoring as a measure of mix ratio would be more effective for 30N50 than for SC-
1. For the tungsten polishing slurries, the pH change with abrasive concentration for Granite 14
is small because the slurry's two components have a very similar pH, 4.18 and 3.92. In contrast,
FE-400 and W-A400 differ by 4 pH units, making the pH sensitivity of that mixture greater.
Figure 4: The effect of pH meter resolution on
the minimum detectable change in abrasive
concentration.

Regardless of the pH sensitivities of the slurries, the usefulness of pH monitoring is highly
dependent on the precision and reliability of the pH probe and meter. Furthermore, pH stability
over a wide range of abrasive concentrations is as important as pH sensitivity to changes in
abrasive concentration. The effect of meter resolution on the ability to detect abrasive
concentration changes using slurry pH is shown in Figure 4. The SC-1 slurry, the least pH
sensitive of those tested, is typically mixed to a nominal 12% silica. If a pH meter with a
precision of ±0.01 pH units were used to monitor the dilute slurry, the smallest detectable
change in percent silica would be 12% ± 1%, or ±8% relative error. The W-A400/FE-400 slurry
is the most pH sensitive; for a slurry mixture with 3% alumina, pH meter resolution would be
3% ± 0.1%, or ±3% relative error.
Zeta Potential Results
Zeta potential is a measure of the surface charge on a slurry particle. In theory, the higher the
absolute zeta potential, the better the slurry stays in suspension. The results of zeta potential
measurements by both PSS's ZLS-370 and Matec's ESA-8000 instruments (shown in Table VI)
support this theory since the oxide slurries, which are better suspended than the tungsten
slurries, exhibited higher absolute zeta potentials (28—32 mV compared with 0.3—16 mV).
Particle-Size Distribution Results
Figures 5 through 7 show the respective particle-size distribution profiles of the four test slurries
from the three analyzers that characterize the main distribution. Because the profiles are
displayed in the formats preferred by the analyzer manufacturers, the figures differ in their
presentation of the particle data and in the scale of the x-axis (log versus linear).
Figure 5: Particle-size distribution analyses of
all four test slurries using the CHDF-2000
analyzer.

Figure 6: Particle-size distribution analyses of
all four test slurries using the LA-910 analyzer.
Figure 7: Particle-size distribution analyses of
three test slurries using the Nicomp 370
analyzer. (Granite 14 could not be analyzed
successfully.)

The data in Figure 5 from the CHDF-2000 analyzer are mass weighted. In a mass weighting of
a particle-size distribution the masses of all particles in the sample are summed and the
percentage of the total mass in each channel calculated. The channels are spaced evenly on a
non-log scale, and the data are normalized so that the largest channel percentage is always
100%. However, this does not mean that the number of particles in each slurry's most-populated
channel is the same.
In Figure 6, the LA-910 analyzer distribution profiles are displayed as the volume-weighted
frequency plotted against particle diameter. Similar to mass weighting, volume weighting is
accomplished by adding the particle volumes and normalizing the data for the volume in each
channel. The channels are spaced equally on a log scale. The data shown in the figure were
obtained with the analyzer operating in its standard mode. The LA-910, like some of the other
instruments mentioned, can operate in various modes, which allows the detection of smaller
peaks, such as particle agglomerates. This multimode operation is accomplished by collecting
more data to fit a particular distribution model or by changing model assumptions.
The data from the Nicomp 370 analyzer are displayed in Figure 7 as a plot of particle diameter
versus volume percent. No results are given for the Granite 14 slurry because the attempted
analysis was unsuccessful. Since slurries contain large amounts of solids, they must be diluted
in order for most instruments to develop a particle-size distribution. The diluent used should be
pH-adjusted to preserve the slurry's stability.
Analyzer
Slurry CHDF-2000 LA-910 Nicomp 370
Meana Meanb Medianb Meana Mediana Meana Meidana
SC-1 128 186 183 175 167 158 135
(dilute)
30N50 74 91 89 85 86 74 67
(dilute)
W- 129 204 211 120 110 431 316
A400/FE-
400