Controlling Wafer Contamination Using Automated
On-Line Metrology during Wet Chemical Cleaning
Jason Wang, Skip Kingston, Ye Han, Harmesh Saini, Robert McDonald, and
Rudy Mui
Metara Inc. 1225 East Arques Ave., Sunnyvale, CA 94085, USA
Abstract. The capabilities of a trace contamination analyzer are discussed and demonstrated. This analytical
tool utilizes an electrospray, time-of-flight mass spectrometer (ES-TOF-MS) for fully automated on-line
monitoring of wafer cleaning solutions. The analyzer provides rich information on metallic, anionic, cationic,
elemental, and organic species through its ability to provide harsh (elemental) and soft (molecular) ionization
under both positive and negative modes. It is designed to meet semiconductor process control and yield
management needs for the ever increasing complex new chemistries present in wafer fabrication.
what is actually happening in the wet baths in the
process line and how this impacts the yield and
performance of the final product. We give a
couple of examples that discuss potential
contamination mechanisms for Cu and Fe to
illustrate the complexity of the models that have
been proposed.
It has been shown that Cu ions present in
aqueous HF solution adsorb on Si wafer surface
in the form of reduced metallic particles [4]. This
electrochemical process can be expressed by the
chemical equation:
INTRODUCTION
Sub-micron device technologies are highly
sensitive to chemical impurities which may be
present during wafer cleaning. Metallic
contamination is a major source of performance
failure in IC devices including increased p-n
junction leakage, degradation of gate oxide
breakdown voltage and reduced carrier lifetime.
As critical device geometries continue to shrink
below 0.13 µm, strict control of contaminants in
wet chemical cleaning baths to ppt (parts per
trillion) levels has become increasingly
necessary.
In a 1999 publication, Shive et. al., discussed
the benefits of on-line monitoring for metallics
in wafer cleaning processes [1]. In that paper, a
key assumption was that there was a relationship
between the amount of metal on a wafer and the
amount of metal in the last cleaning solution in
which the wafer was immersed. In general this
is true, however not in a simple fashion. Work
by Helms [2], Poliak and Gupta et. al. [3] and
others have demonstrated that the amount of
contamination deposited on the wafer is a strong
function of the specific contamination
mechanisms involved, the process chemistry in
the particular process step and the wafer
treatment in prior steps.
There are literally hundreds of papers
postulating contamination mechanisms as a
function of the contaminant and the process
chemistry involved. However most of these
results are based on measurements made in the
laboratory environment and may or may not
simulate manufacturing process conditions. To
this day there is only limited understanding of
2Cu 2+ + Si + 6HF <=> 2 Cu + SiF62- + 6H+.
As a result, measurements of UPW (ultrapure
water) as a final rinse may not establish a
correlation between Cu in the final UPW rinse
solution to that on the wafer surface. Cu may be
on the wafer surface, but it may not be detectable
in the final rinse bath.
Mouche et. al. studied the mechanism of
metallic impurity deposition on silicon substrates
by dipping wafers in solutions [5]. They found
that the number of Fe particles deposited on the
wafer surface increased according to the increase
of Fe concentration in SC-1 solution (0.5:1:5,
T=70°C). This was confirmed by two
experiments: particle counts by light scattering
and characterization of the deposited particles by
x-ray microanalysis. Because of the presence of
Fe(OH)3 (solid) in SC-1, it was believed that the
precipitation of iron hydroxide Fe(OH)3
physically absorbed on the wafer surface. Helms
[2] also showed a correlation between the Fe
contamination in SC-1 bath and on the wafer.
SC-1 bath concentrations ranging from 100 ppt
CP683, Characterization and Metrology for ULSI Technology: 2003 International Conference,
edited by D. G. Seiler, A. C. Diebold, T. J. Shaffner, R. McDonald, S. Zollner, R. P. Khosla, and E. M. Secula
© 2003 American Institute of Physics 0-7354-0152-7/03/$20.00
300
to 1 ppb leads to surface concentrations of 1011
to 1012 atoms/cm2. The results are similar to that
reported by Mouche et. al. [5]. However Helms
[2] points out that Fe transfer to the wafer
surface reaches a saturation point in SC1
solutions containing greater than 1000 ppt Fe
contamination.
The International Technology Roadmap for
Semiconductors (ITRS), 2001 Edition [6]
highlights the critical need for better
understanding of contamination and yield
correlation as devices scale below the 65nm
process node. This is discussed in Table 88 titled
“Yield Enhancement Difficult Challenges” and
the specific wording is as follows:
“Correlation of Impurity Level to Yield –
Methodology for employment and correlation of
fluid/gas types to yield of a standard test
structure/product. Establish an employment
methodology for each material type. Define a
standard test for yield/parametric effect.”
Historically, wafer contamination has been
measured and controlled in two ways: (1) offline periodic testing of samples from wet station
process baths using an approved laboratory [7,8];
(2) or by the examination of residues on test
wafers which have been exposed to process
solutions using either TXRF (total reflection xray fluorescence) or VPD-ICP/MS (vapor phase
decomposition-inductively coupled plasma/mass
spectrometry) [8,9].
Although it is possible to perform TXRF at
the process line, TXRF’s inability to detect
critical light elements such as Na, B and Al at
trace contamination levels means that the results
are not sufficient for comprehensive detection
and control of process contamination. Off-line
lab or VPD-ICP/MS measurement is still
required if these critical species are to be
measured. Also, the analysis area measured by
TXRF, approximately from 0.5 to 0.8 cm2, may
also not be representative of the contamination
across the entire wafer surface unless full wafer
scans are performed [9]. However, these full
wafer scans take many hours.
VPD-ICP/MS has excellent detection limits
for all key elements on the wafer surface. It does
measure the cumulative contamination across the
entire wafer surface unless special local area
methods are used. As in TXRF unpatterned test
wafers are required.
The cost of both TXRF and VPD-ICP/MS
measurements are relatively high since they
require unpatterned test wafers that occupy
valuable production wafer slots. This problem
will get significantly worse with the conversion
to the 300 mm wafer size.
Off-line chemical analysis is severely
compromised as a process control tool by the
long turn-around times ranging from hours to
days and the inherent risk that contamination
may be introduced during manual sampling from
a cleaning bath. The accuracy of results and the
time in which they become available is critical
since a single contamination excursion in a 300
mm fab can cost upwards of $5 million per day
in scrap wafers alone. This does not include the
additional expertise, testing and labor required to
troubleshoot and resolve contamination problems
and to ultimately disposition the affected
material. This estimate also ignores the potential
delay in time to market, lost revenues, idle
capacity, and the cost of recovering and requalifying contaminated equipment.
There is only limited understanding of the
correlation between contamination in the process
bath, contamination which is deposited on the
surface of test wafers and the actual impact on
device yields, performance and reliability
problems. The overall complexity of the wafer
process creates a large part of this problem,
however the larger roadblocks are the
uncertainties due to sampling artifacts and the
high costs associated with the off-line and test
wafer techniques discussed here. These costs
and uncertainties are major barriers in obtaining
statistically valid process chemistry data for
correlation to process performance parameters.
We would submit that the in-line measurement
of process chemistry will lead to major progress
in the understanding of contamination, its
sources and yield correlation, particularly if it
can be done cost-effectively with statistically
valid basis.
We first announced a new in process mass
spectrometry tool that has been designed to
address this measurement need last year [10]. In
this paper we present the results of the first trace
contamination measurement results.
IPMS TCA TECHNOLOGY
In this paper, the capabilities of an in-process
mass spectrometry trace contamination analyzer
(IPMS TCA) will be discussed. This tool was
specifically designed to enable real-time on-line
quantitative measurement of contamination
present in wet station process baths as well as
other process chemistries [11,12]. Wet process
measurement results are presented including
301
signal intensity over relatively short periods of
time. This presents the need for frequent
recalibration using standard solutions between
unknown runs and subsequent adjustment of the
calibration curve. In contrast to this, the TCA
uses IDMS and SIDMS methods to correct for
spectrometer instabilities as well as matrix
effects. This enables accurate automated and
unattended quantitative measurement of wet bath
contamination levels and other process
chemistries.
The TCA provides identification and
quantitative measurement of metallic, anionic,
cationic, elemental, and organic species present
in semiconductor process solutions. Molecular
information is preserved through use of the
unique electrospray ionization system that is able
to perform either “soft ionization” of molecular
species for complete chemistry analysis or
“harsh” elemental ionization for improved
detection limits. The change from one mode to
another is accomplished by simple computer
controlled adjustment of electrospray parameters.
No operator intervention is required.
In the IDMS method, an enriched isotope
solution is prepared and mixed with the natural
isotopes in the sample solution. Because the ratio
of enriched isotope to natural isotopes does not
change during the measurement, the calculation
of concentrations can now be completed
comparing signal intensities in the mass
spectrum vs. comparison to a calibration curve
generated using system standards. Specifically,
poly-isotopes are quantified using IDMS with
the formula shown below where Cs is the
element concentration in sample solution:
those obtained during the first on-line application
in a manufacturing fab. For a more detailed
discussion of the IPMS TCA design and its
operational features, please see Ref. 11 from the
proceedings of this conference.
In summary the IPMS TCA capability
includes automated sample extraction, sample
preparation and analysis. The sample preparation
system includes dilution capability and a mixing
module for the introduction of isotopic
calibration standards.
The TCA automatically samples wet station
process solutions via a narrow sample probe
mounted vertically on the inside edge of the bath.
The tip of the probe extends below the surface of
the liquid. It draws 2 mL of sample into a
reservoir through vacuum suction. After closing
a valve to the bath, pressurized nitrogen gas is
used to transport the sample through a fully
encapped HP Plus Teflon tube to the TCA
system. The TCA can be located up to 30 meters
away from the wet station that is being sampled
and incorporates five sample extraction and
preparation modules so that up to five wet baths
can be sampled simultaneously.
After transfer into the automated TCA
sample preparation system, the sample is mixed
with enriched isotopes, equilibrated, introduced
into the electrospray ionizer and the time-offlight mass spectrometer (ES-TOF-MS).
Quantitative analysis is completed using isotope
dilution mass spectrometry (IDMS) and
speciated isotope dilution mass spectrometry
(SIDMS) methodologies [12-16].
The TCA system is fully clean room
compatible, runs under computer control
including sample extraction and preparation and
interfaces with standard fab data systems. The
fundamental nature of TOF-MS is similar to that
of other mass spectrometers in that it utilizes
electric and/or magnetic fields to separate
charged species in space by their mass-to-charge
ratio (m/z). The TOF-MS has an average 2000
M/∆M resolution power and is presently
configured to operate in a mass range from 18 to
230 m/z in positive ion mode (cations). The
system allows accurate mass measurements,
resulting in precise determination of the intact
molecular and/or atomic components of the
sample.
Traditionally
each
elemental
measurement is quantified by comparison to a
calibration curve that has been generated by the
measurement of standard solutions.
Under
normal
operating
conditions,
a
mass
spectrometer instrument has significant inherent
“drifts” which cause unpredictable changes in
( As Cs Vs + Asp Csp Vsp )
Ratio
=
( Bs Cs Vs + Bsp Csp Vsp )
Where:
As = Fraction of isotope A in sample (natural)
Bs = Fraction of isotope B in sample (natural)
Asp = Fraction of isotope A in spike (altered)
Bsp = Fraction of isotope B in spike (altered)
Cs = Concentration of element in sample
Csp = Concentration of element in spike
Vs = Volume of the sample
Vsp = Volume of the spike
Quantification of mono-isotopic elements
such as 27Al, 23Na, and 59Co relies on ratio
methods applying spikes of elements with
neighboring
mass
to
determine
their
302
concentrations. For example, 25Mg is used for the
quantification of sodium 23Na, and aluminum
27
Al; 62Ni is used for the quantification of cobalt
59
Co. Figure 1 shows the quantification of
mono-isotope 59Co at various concentrations by
use of a 62Ni internal standard. These results
were generated by measuring ultra pure water
(UPW) spiked with a NIST multi-element
traceable “stock” solution at blank, 200 ppt, 500
ppt and 1000 ppt concentrations. In the next
section, we will show measurement results for
other mono-isotopic elements present in the
multi-element standard.
100 ppt Ni, Cu, Zn
400
63
A m p litu d e
300
1p
pb
0.0
1p
pb
64
62
66
Zn+
+
Ni
58
59
60
61
62
63
64
65
66
67
Figure 2 presents the typical spectrum
obtained for the 100 ppt level solution. The TCA
was operated in positive “harsh” ionization mode
in this analysis. Because of the high mass
resolution of the TOF-MS, the elemental peaks,
such as Ni, Zn and Cu, are clearly resolved from
the adjacent organic peaks. Figure 3 shows the
average quantitation results for the three
solutions (100ppt, 50ppt and 20 ppt). Elements
present can be quantified at the 100 ppt level,
independently of whether they are poly-isotopic
or mono-isotopic. Some elements can also be
quantified at lower concentrations, i.e., 50 ppt
and 20 ppt. Missing data in Figure 3 occur where
the species cannot be measured with sufficient
accuracy under current measurement conditions.
0.2
1p
pb
65
Cu+
Zn+
Ni+
FIGURE 2. Mass spectrum of 100 ppt NIST traceable
solution with the TCA operated in positive “harsh”
ionization mode.
0.4
1p
pb
60
m /z
0.6
bla
nk
20
0p
pt
20
0p
pt
20
0p
pt
20
0p
pt
50
0p
pt
50
0p
pt
50
0p
pt
50
0p
pt
Ni
200
57
0.8
bla
nk
100 ppt
UPW
Cu+
0
1.0
bla
nk
+
100
1.2
bla
nk
58
FIGURE 1. Quantification of mono-isotopic
element Co solutions at blank, 200ppt, 500ppt
and 1000 ppt concentrations by using 62Ni as an
internal standard (UPW). The vertical axis is
concentration in ppb.
TCA analysis of 100, 50 and 20 ppt NIST in UPW
TCA MEASUREMENT OF
METALLIC CONTAMINATION
95% CI, n = 3 different solutions
200
180
160
Concentration (ppt)
In order to characterize the performance of
the TCA in trace contamination analysis over a
broad range of elements, measurements were
conducted on UPW containing NIST traceable
multi-element solutions diluted to concentrations
of 100, 50, and 20 ppt. The UPW used in the
dilution was produced by a Nanopure
purification system.
During analysis each
sample was spiked with appropriate amounts of
enriched isotopes (25Mg, 41K, 44Ca, 46Ti, 53Cr,
57
Fe, 62Ni, 65Cu, 68Zn, 124Sn, 136Ba, and 206Pb) for
IDMS quantification.
140
120
100
80
60
40
20
0
Na Mg Al
K Ca Ti
V
Cr Mn Fe Co Ni Cu Zn Sr Ag Cd Sn Sb Ba Tl Pb
FIGURE 3. TCA analyses of ultrapure water (UPW)
spiked with NIST standard “stock” solution to 20, 50
and 100 ppt. levels. Quantification preformed Isotope
Dilution Mass Spectrometry (IDMS).
303
The quality of the facility and the UPW used
in this work were major limitations in our ability
to perform successful quantification at the lower
levels for a number of species.
A high
background concentration of Ca was observed in
the 100 ppt analysis. The contamination source is
unknown but believed to be human or facility
related.
In another series of measurements, SC-1
(NH4OH:H2O2:H2O=1:1:5) and DHF (dilute HF,
1:50) solutions were prepared with 100 and 200
ppt concentration levels using the same methods
as described above. The results are presented in
Figures 4 and 5.
t = student’s “t” values at 95% confidence
intervals = 4.3
σ = standard deviation of the measurements
n = numbers of measurements
Work is underway to optimize system
detection limits and measure ultimate
performance under conditions that are not
limited by the current tool environment and
UPW water purity.
ON-LINE MEASUREMENT OF
PROCESS CHEMISTRY
USING TCA
TCA Analysis of SC1 Spiked with 100ppt & 200ppt NIST
A TCA has been installed in a production
wafer fab to provide on-line monitoring of wet
station chemical baths. As first verification of
on-line performance, the TCA was used to
measure a serious of spiked UPW, SC-1 and
DHF solutions.
The results are compared
against those of the lab ICP/MS used by the fab.
Figure 6 shows a comparison of results between
TCA and ICP/MS in a 200ppt (0.2ppb)
multielement DHF solution. The results from
TCA represent the average of 60 continuous
measurements and those for the ICP/MS 3-4
measurements. The number of samples that can
be sent for lab ICP/MS measurement was limited
by time and cost constraints.
90%C.I. n=3
Concentration ppt
250
200
150
100ppt
200ppt
100
50
0
Na Mg
Al
Ti
K
Ca Cr
Mn Fe
Co
Ni
Cu Zn
Sn
Ba
FIGURE 4. TCA analyses of SC-1 spiked with NIST
standard “stock” solution to 100, and 200 ppt levels.
Quantification performed by IDMS.
Analytical Result Comparison between TCA & ICP/MS in 200ppt DHF
TCA Analysis of 1:50 HF Spiked with 100ppt & 200ppt NIST
1.20
90% C.I. N=3
1.00
Concentration (ppb)
Concentration (ppt)
250
200
150
100ppt
200ppt
100
50
TCA
0.80
ICP-MS
0.60
0.40
0.20
0
Na Mg Al K Ca Ti V Cr Mn Fe Co Ni Cu Zn Sn Ba Pb
0.00
Na
FIGURE 5. TCA analyses of DHF spiked with NIST
standard “stock” solution to 100, and 200 ppt levels.
Quantification performed by IDMS.
Mg
Al
K
Ca
Ti
Cr
Mn
Fe
Co
Ni
Cu
Zn
Sn
Ba
FIGURE 6 A comparison of analytical results
between TCA and ICP/MS in 200ppt DHF solution
Figure 7 shows the first measurement results
of an SC1 bath being used to process production
wafers. This trend plot illustrates the volume of
on-line data that can be cost-effectively achieved
in a few hours (concentrations of select elements
in the SC-1 bath are plotted against time in
hours). In this case, one single production SC-1
bath is being sampled for 15 elements
The error bars shown in Figures 3 to 5 are
calculated using the following formula:
µ = X ± tσ/(n)1/2
where
µ = analytical results;
X = average of three measurements;
304
The chelate additions also improve SC-1 bath
stability by minimizing the metal catalyzed
decomposition of hydrogen peroxide. One of the
commercial chelating agents, such as Titriplex
(ethylene-diamine-tetra-acetic acid, EDTA) is
commonly used for this purpose.
The TCA enables quantitative analysis of the
process chemistry present in standard cleaning
processes as well as these modified approaches.
It is anticipated that the additional process
chemistry
information
will
speed
up
development and implementation of these new
and improved cleaning processes.
simultaneously and 3 elements are shown in the
trend plot. Up to five baths could have been
sampled at one-fifth the frequency per bath. The
rate
of
quantitative
measurement
is
approximately 5 complete multi-element analysis
results per hour. These results demonstrate the
volume of quantitative measurement data that
can be routinely and cost-effectively generated in
just a few hours. These results also demonstrate
the potential for statistically valid process control
decisions based on actual process chemistry.
120
Mass
100
RET (00:04:36)
3000000
Curve 1
80
2500000
Cu
Mn
60
2000000
Amplitude
Ni
40
1500000
1000000
20
500000
0
0:00
2:24
4:48
7:12
9:36
12:00
14:24
16:48
19:12
21:36
0:00
T i me
0
100
125
150
175
m/z
200
225
250
FIGURE 8. Spectrum of 1 ppm of the surfactant
CH3(CH2)7SO3Na in SC-1 solution; TCA operated in
soft ionization and negative mode.
FIGURE 7. Cu, Ni and Mn concentrations vs.
time in hours in a production SC-1 bath
POTENTIAL APPLICATIONS: TCA
ANALYSIS OF ORGANIC SPECIES
AND ELEMENTAL SPECIATION
IN WET CLEAN PROCESSES
Mass
GEN( 00:05:40 : 00:08:19 )
650000
Curve 1
600000
C7F15CO2-
550000
500000
450000
400000
Amplitude
ppt
CH3(CH2)7SO3-
The semiconductor industry is in the process
of investigating more environmentally friendly
and cost-effective cleaning chemistries. One
approach is the use of highly diluted versions of
existing cleaning solutions such as modified SC1 (NH4OH:H2O2:H2O). In these new versions of
SC1, the relative concentration of solution
components is changed from 1:1:5 to 1:4:20 or
even more extremely to 1:2:80. Combinations of
anionic and non-anionic surfactants, as well as
chelating agents [17-19] are added in an attempt
to maintain cleaning effectiveness. Surfactants
enable more effective particle removal and the
addition of chelating agents can prevent metal
precipitation/re-precipitation on the silicon wafer
surface. These changes are also used to enable
the elimination of the usual SC-2 clean that
normally follows the standard SC-1 clean.
350000
300000
250000
[CuCl(C7F15CO2)]-
200000
150000
[CuF(C7F15CO2)]-
100000
50000
0
400
425
450
475
500
525
m/z
FIGURE 9. Spectrum of 1 ppm surfactant C7F15CO2H
in BOE solution (300x dilution); TCA operated in soft
ionization and negative mode.
For example, “soft ionization” TCA analyses
was used to identify the molecular species
present in a SC-1 solution with the addition of 1
ppm of the surfactant CH3(CH2)7SO3Na, as
shown in Figure 8. The mass spectra of
surfactant C7F15CO2H in BOE (buffered oxide
etch) and a chelating agent EDTA, are shown in
Figures 9 and 10, respectively. The two Cu
305
species present in the BOE case, Figure 9, are
from an unknown source. The spectrum in
Figure 10 shows organic species with 12C or 13C
combined with various Fe isotopes, i.e. 54Fe, 56Fe
and 57Fe.
Fe(EDTA)
GEN( 00:02:51 : 00:03:11 )
343.994
1000000
Curve 1
56
Fe and all 12C
Unregistered
100
900000
90
80
800000
70
60
50
700000
40
30
20
Amplitude
600000
10
0
342
500000
344
346
348
400000
54
Fe and one 13C
300000
57
Fe and all 12C,
Fe and one 13C
56
200000
54
12
Fe and all C
57
Fe and one 13C,
Fe and two 13C
56
344.998
100000
341.994
0
341
342
344.270
342.993
343
344
345
346.001
346
m/z
347
348
349
350
351
FIGURE 10. Spectrum of Ferric EDTA, TCA
operated in soft ionization and negative mode.
There are some areas that have not yet been
explored that are now enabled by the TCA, such
as the measurement of elemental speciation. For
example, we know that many transition metals
likely form complex compounds in SC-1
solution. This may also be true for metals in
DHF solution. How do those metal complexes
undergo absorption or desorption on the wafer
surface? May equilibrium be species dependent?
There remain open questions. Mori et. al [20]
investigated the adsorption of Fe(III), Ni(II) and
Zn(II) on wafer surface in SC-1 solution (1:1:5,
T=80°C) and concluded that the main adsorption
species was the dissolved neutral hydroxide
complexes, i.e. M(OH)nz-n, where M = Fe, Ni,
and Zn. This conclusion was based on the
calculated distribution of hydroxide complexes
as a function of pH. For example, in the
calculation, Fe(III) forms Fe(OH)3 (aq) in SC-1
solution at pH =10.6. The dissolved neutral
hydroxide species is then adsorbed on the wafer
surface, i.e. trapped inside the silicon oxide
layer. This thin film Fe contamination (not
Fe(OH)3 particles) was confirmed by TXRF
angle scan profiling. However, this conclusion is
completely different from Mouche’s as discussed
earlier [5]. Furthermore, based on another
calculation, the total concentration of ammonia
complexes of Ni(II), e.g. Ni(NH3)62+, Ni(NH3)52+
Ni(NH3)42+ …, is 1010 times higher than
hydroxide complexes, e.g. Ni(OH)42-, Ni(OH)3-,
Ni(OH)2. Why do only the neutral hydroxide
species deposit on the wafer surface? Why not
ammonia complexes which are in much higher
concentration? In addition, it has been known
that the zeta potential of wafer surfaces is
negative in a SC-1 solution with pH ≈10.6 [21].
Because of the attraction of opposite charges, the
positive species such as Ni(NH3)x2+ and
Zn(NH3)x2+ or Cu(NH3)x2+ seem more likely to
deposit on the negative wafer surface than
neutral species do. The explanation that has been
given [5] is that in SC1, the Cu ions are totally
complexed by the ammonia molecules which can
decrease their reactivity and mobility due to the
steric factor; resulting in one more theoretical
hypothesis and postulate for debate. These
questions may be better answered by measuring
the exact species present in the process chemistry
as enabled by the IPMS TCA.
The detailed in-bath reactions associated with
organic additives such as surfactants or chelating
agents is also not understood. The theoretical
hypotheses involve calculation of pKs, ionic
strengths, and reactivities but soon this approach
becomes very complicated and any conclusion
based on the calculation is questionable.
Although metallic contaminant analysis may
remain a primary target in the bath chemistry
measurement, the information provided by direct
elemental speciation and species measurement
and identification will enable a better
understanding of the contamination mechanisms
involved.
The bottom line of this discussion is that
there is much that is unknown about process
chemistry and the new cleaning approaches are
generating additional complexity.
Better
understanding of the actual mechanisms present
will lead to the design and successful
implementation of more effective cleaning
solutions.
CONCLUSIONS
We have demonstrated that the new IPMS
TCA capability enables identification and
quantification of metallic and organic species,
both in cationic or anionic forms in wet clean
process solutions. In this case we have applied
this capability to UPW and standard BOE, SC-1,
and DHF semiconductor process solutions. We
have also shown organic and specie
measurement capabilities in analytes of the
relatively new dilute SC-1 chemistries which
include surfactants and chelating agents.
The capabilities of the trace contamination
analyzer (TCA) include operator unassisted
306
6. 2001 International Technology Roadmap for
Semiconductors,
Semiconductor
Industry
Association.
7. Balazs, M.K., Wet Chemical Analysis for the
Semiconductor Industry A Total View,
Characterization and Metrology for ULSI
Technology: 1998 International Conference, D. G.
Seiler, A. C. Diebold, W.M. Bullis, T.J. Shaffner,
R. McDonald, and E. J. Walters, AIP Conference
Proceedings CP449, Melville, New York, pp. 703712.
8. Gupta, P., Pourmotamed, Z., Tan, S.H., and
McDonald, R., Ultra Sensitive Methods for
Microcontamination Analysis in Semiconductor
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automated on-line operation. The tool provides
real-time process chemistry measurements and
has the capability to provide elemental and
molecular species information.
It is expected that this new high volume costeffective measurement capability will provide
statistically
valid
process
chemistry
characterization and yield correlation for the first
time. The tool produces real-time statistically
valid process information that will enable
excursion avoidance and required corrective
action. Bath refresh or changeout requirements
can be determined based on actual process
chemistry and contamination levels as well as the
need for unanticipated equipment preventative
maintenance. Overall these capabilities will
enable better and more cost-effective
semiconductor process control and yield
management.
ACKNOWLEDGEMENTS
The authors wish to thank the Metara
scientific team for their contribution in
generating the data and analyses used in this
paper. The authors would particularly like to
thank Dr. Michael West for providing spectra of
surfactant and chelating agents.
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