Inspecting wafers using a
potential difference imaging sensor method
Yang, Jeff Hawthorne, Brandon Steele, Robert Bryant, and David Sowell,
Qcept Technologies; and David Maloney and Katy Ip, DuPont/EKC
and chemical residue are two major causes of reduced yield in semiconductor
fabrication. Wafer cleanliness is becoming increasingly important as minimum
feature sizes shrink below 90 nm, where the thickness of adsorbed layers
and organic contaminants are of the same order as the process tolerances
of functional films in devices. Contamination, whether organic or metallic,
can cause process variation and defects, such as poor coverage, vacancies,
voids, leakage, shorts, and overburdens. For example, a small amount of
metal contamination in the bulk semiconductor substrate can cause the
bulk minority carrier lifetime to decrease because the metal contamination
may assist in the recombination of electrons and holes in the semiconductor
substrate. That effect would have a detrimental impact on the DRAM refresh
rate. To increase yields in semiconductor wafer fabs, it is crucial to
reduce contamination and minimize residues.
and residues can be detected using optical or analytical metrology tools.
Although optical inspection systems are often fast enough to perform in-line
inspection of production wafers, they are not well suited for detecting
film nonuniformities or small amounts of contamination that are not optically
visible. Total x-ray fluorescence (TXRF) or time-of-flight secondary ion
mass spectroscopy analysis tools provide a wealth of information on wafer
surface chemistry, but they are expensive, slow, or destructive and do
not provide information on the entire wafer surface.
and controlling contamination effectively during wafer processing requires
a fast, in-line, nondestructive method of detecting minute chemical changes
on the wafer surface. This capability would lead to cost savings by minimizing
the time required to detect contamination, thereby reducing the number
of wafers affected and the associated costs of scrap or reduced device
reliability. This article describes a new sensor technology and system
developed by Qcept Technologies (Atlanta) for imaging and detecting chemical
contamination on IC wafers. The system operates by detecting variations
in work function across the surface of the wafer.
Kelvin Probe versus Nonvibrating CPD Probe
Kelvin Probe. The work function of an electronic conductor is
defined as the minimum amount of work required to move an electron from
the Fermi level of the bulk material to the vacuum level. In other words,
it is the energy required to move an electron from the interior of the
conductor to a noninteracting point outside the surface (beyond the image
work function is a fundamental property of a material surface, it is of
interest in a wide range of surface phenomena. The work function of a
particular material varies if contaminants or coatings are present. Such
variations can be analyzed to determine the cleanliness of a surface,
the uniformity or thickness of a coating, and other information about
the condition of the material surface. Work-function measurement can be
used to study semiconductor doping, organic semiconductors, organic monolayers,
surface reactivity, biological systems, heterogeneous catalysis, and corrosion.
work function of a surface is typically measured using a vibrating Kelvin
probe. This probe operates by measuring contact potential difference (CPD),
which is the electric potential that forms between two materials with
different work functions when they are electrically connected. CPD is
proportional to the work-function difference between two surfaces.
1: Schematic diagrams showing the energy and contact potential difference
of two metals (a) before and (b) after contact.
concept of CPD is illustrated in the schematic diagrams shown in Figure
1. In Figure 1a, two different metals, with different work functions and
Fermi levels, are placed in close proximity to each other but are not
connected. The figure shows the electron energy levels along with the
work functions Φ1 and Φ2.
If the two metals are then electrically connected, as shown in Figure
1b, electrons flow from the material with the smaller work function (Φ1)
to the material with the larger work function (Φ2),
resulting in an accumulation of charge on the two metals and the formation
of an electric field between them. The amount of charge that is formed
is equal to the product of the capacitance between the two metals and
vibrating Kelvin probe operates by measuring the CPD between a probe of
known work function and a surface of unknown work function. The probe
is vibrated over the surface to be measured. This vibration causes a periodic
variation in capacitance between the two materials, which results in a
time-varying current into the probe. This current is measured and nullified
by applying an opposing voltage on the probe or surface. This voltage,
known as the backing potential, results in zero current when it is equal
to the CPD between the two materials.
Kelvin probes have been used in a wide variety of applications, including
the measurement of dielectric layer thickness and contamination inside
the dielectric layer.1,2 While they can be used to form images
of work-function variation across surfaces, the need to vibrate the probe
and adjust the backing potential results in limited data acquisition rates
that are not compatible with fast-cycle-time, high-resolution imaging
CPD Probe. The nonvibrating contact potential difference (nvCPD)
measurement technique is a variant of the traditional vibrating Kelvin
probe method. Instead of vibrating the probe, the nvCPD sensor detects
work-function variations by translating the probe relative to the sample
surface. Variations in work function across the surface result in variations
in CPD and the associated voltage between the probe and the surface. These
voltage variations produce a small current into the probe that can be
amplified and sampled. The use of translation instead of vibration results
in a dramatic improvement in the data acquisition rate.
vibrating Kelvin probes typically acquire data at several samples per
second, the nvCPD probe can acquire data at millions of samples per second,
making it suitable for high-speed imaging applications. In fact, the faster
relative motion between the nvCPD probe and the surface of the wafer results
in an increase in signal strength (within the bandwidth limits of the
amplifier). The sensor's increased scanning speed makes it useful as an
in-line tool for contamination detection.
both the vibrating and nonvibrating CPD sensors, the sensor probe and
the measured surface form a capacitor. The well-known formula for the
charge on a capacitor is simply
Q is charge, C is capacitance, and V is voltage.
The current i into a capacitor is obtained by differentiating the first
both vibrating and nonvibrating sensors, the voltage across the capacitor
is the CPD resulting from the difference in work function between the
probe and surface. The vibrating probe determines the CPD by applying
a backing voltage (Vb) to zero the current during
vibration (i = 0 when Vb = –Vcpd).
The resulting backing voltage is equal in magnitude, and opposite in sign,
to the CPD:
contrast, the nonvibrating probe detects changes in voltage across the
capacitor while the probe moves relative to the surface. If the surface
is relatively smooth and the gap between the probe and surface is relatively
constant, the capacitance is constant. The resulting current into the
probe is given by:
v is the relative velocity of the probe and underlying surface,
and dx represents the change in relative position. Any variation
in CPD generates a current into the probe. Since the work function of
the probe is fixed, the probe signal is proportional to the work-function
variation across the surface.
Technologies has developed the Chemetriq wafer-scanning system for mapping
the work-function variation on silicon wafers. Based on a patented nonvibrating
nvCPD sensor and proprietary imaging software, the system produces information
that can be used to assess chemical variation across wafer surfaces.
in Figure 2, the system measures the electric potential difference between
the sensor probe tip and the silicon wafer surface, quickly generating
whole-wafer images of work-function variation. Sensitive to minute traces
of contaminants and residues, the sensor detects surface chemical and
geometric nonuniformities that cannot be detected easily using other metrology
tools. Contamination on the wafer surface, including bulk contamination
and submonolayer surface residues, can be mapped.
2: The core module of the nvCPD wafer-scanning system.
time, which depends on the required resolution, can vary from less than
one minute to several minutes for entire 200- or 300-mm wafers. The sensor
and system are well suited for performing nondestructive, real-time contamination
inspection and characterization. The stand-alone inspection tool can be
integrated as an in-line metrology tool in the fab for performing in situ
monitoring, providing a go/no-go assessment of wafer cleanliness.
wafer-scanning system includes a spindle and a three-axis linear motion
system. The nvCPD sensor and the scan- height sensor are mounted on the
linear motion stages. The wafer is mounted on a vacuum chuck attached
to the spindle. When the wafer is spun, a sensor measures the wafer height
and adjusts the gap between the nvCPD sensor probe tip and the wafer surface.
After the linear motion system positions the nvCPD sensor above the wafer
surface, concentric, circular tracks of data are acquired as the sensor
scans the wafer from the outer edge to the center. Data are collected,
stored in a computer, and then processed with software to generate images
and quantitative data on wafer nonuniformity.
3: Work-function image of (a) a full 200-mm postcopper CMP process
wafer with a Sematech 831AZ pattern, and (b) an enlarged section of
the same wafer showing the work-function variation on the copper/dielectric
surface inside a die after CMP processing.
3a shows a typical full-wafer nvCPD scan of a 200-mm copper wafer that
has undergone a two-step CMP process. The image contains more than 10
million data points and can be manipulated to examine an enlarged area
of interest. Figure 3b shows a sample area of interest consisting of a
experiments were conducted to test the sensitivity of the nvCPD sensor
at detecting contamination on silicon wafers. Two types of wafers were
prepared. In the first experiment, different types of thin metal films
were deposited on the same silicon-substrate wafer to compare the nvCPD
signal with the work function of the metal materials. In the second experiment,
a wafer with copper contamination was tested. Both wafers were scanned
using the sensor/software system.
between CPD and Work Function. In this experiment, the wafer
was divided into quadrants, and each quadrant underwent unique deposition
processing. Using dc sputtering, four different materials were deposited
onto different quadrants of a silicon substrate through a shadow mask.
The first quadrant was sputtered with copper, the second with chromium,
the third with titanium, and the fourth with aluminum. Sputtering time
was set to achieve a film thickness of 100 Å in all quadrants.
4: Wafer images of four different metal thin films taken using the
image of the wafer is shown in Figure 4. The lines and dots indicate the
areas where metal films were deposited. In all four quadrants, features
were detected by the nvCPD sensor with different intensities and contrasts.
The CPD signal intensity was the voltage change measured by the probe
as it passed from over a silicon substrate region to a deposited-metal
region. Signal intensity can be extracted from either a trackwise line
plot or straight line plot. In this case, trackwise line data were used
for characterization. Figure 5 shows that the peak-to-peak intensity of
the CPD signal varied with the four metals. The copper film generated
the lowest peak intensity and the titanium the highest.
5: CPD peak-to-peak intensity versus four metals.
signal intensity can be compared with the work function of materials.
Table I lists the electronic work function Φ of the silicon substrate
and the four metals deposited on the wafer surface. The work-function
difference (ΔΦ) between the deposited film and the silicon substrate
is also calculated. The table indicates that there is a good correlation
between the CPD signal intensity (Vcpd) and ΔΦ. The higher the
work-function difference, the higher the CPD signal intensity. This correlation
is shown in Figure 6, where the CPD signal intensity increases linearly
with the work-function difference between the deposited film and silicon
I: Work function (Φ) and work-function difference (ΔΦ),
which is determined by ΦFilm – ΦSi.
Contamination. In the second experiment, the sensitivity of the
nvCPD sensor to copper residue was tested. The copper contamination was
intentionally introduced onto a silicon wafer with a solution containing
copper sulfate pentahydrate. First, the solid Cu (II) sulfate pentahydrate
was diluted in methanol to different concentrations ranging from 10–2
mol/L to 10–7 mol/L. Then a drop of each solution about
12 mm in diameter was dispensed onto a specific location on the wafer
surface. A total of six spots were deposited on the wafer at a radius
of 30 mm. The wafer was allowed to dry through evaporation and then measured
using the wafer-scanning system.
6: CPD signal intensity versus the work-function difference.3
7 shows a work-function map of a doughnut-shaped section of the test wafer.
As seen in the image, all six contaminated spots were detected. TXRF analysis
was subsequently performed on the wafer to measure the atomic concentration
of surface copper at all six spots. The copper concentration at site 1
was found to be 2.4 X 1011 atoms/cm2. The CPD signal
intensity at that spot was about 150 mV. This experiment demonstrates
that even very low surface concentrations of copper can be detected using
the nvCPD technique.
7: Wafer images of various copper residue concentrations taken using
the nvCPD system.
8 demonstrates the correlation between the work-function variation and
copper surface concentration as measured by TXRF. It can be seen that
the signal intensity increases gradually with the increasing copper concentration
but then levels off at still higher concentrations. This phenomenon is
in agreement with the theoretical prediction. Work function is an inherently
surface phenomenon. Once a surface layer is contiguous and unbroken, piling
more of the same kind of atom on the surface will not affect the work
function. For reference, one monolayer of copper has a surface density
of approximately 2 X 1015 atoms/cm2. As the atomic
concentration of the contaminant film approaches a contiguous atomic monolayer,
the addition of more atoms has a diminishing effect.
8: Correlation between the nvCPD signal and the concentration of copper
surface contamination on a silicon wafer.
article has presented data characterizing the ability of a novel wafer
inspection technique to detect metal contaminants on a silicon wafer surface.
Signal strength has been shown to be proportional to the difference in
work function between the contaminant metal species and the underlying
silicon. Signal strength has also been shown to be proportional to the
surface concentration of the contaminant species in the range of 2 X 1011
to 1 X 1014 atoms/cm2.
the nvCPD imaging technique can scan the entire wafer surface and is fast
and sensitive to submonolayer amounts of surface contamination, it is
useful for process characterization and control applications throughout
the fab. While the data presented here deal with metal detection, the
technique is also sensitive to minute amounts of other surface contaminant
species, such as solvent and photoresist residues.
authors would like to thank Chris Huntley of DuPont EKC for his help in
conducting the experiments discussed in this article. They also wish to
acknowledge Mark Schulze for his assistance in processing the images,
and Allen Vance and George Deltoro of Qcept Technologies for their valuable
Miller, "A New Approach for Measuring Oxide Thickness," Semiconductor
International 18, no. 8 (1995): 147–148.
Weinberg, "Tunneling of Electrons from Si into Thermally Grown SiO2,"
Solid-State Electronics 20, no. 1 (1977): 11–18.
Ley and M Cardona, eds., Photoemission in Solids (Berlin: Springer,
Yang, PhD, is a senior research engineer at Qcept Technologies
(Atlanta), where he is responsible for the application of nvCPD technology
for wafer inspection and metrology. Before joining the company in 2004,
he was a senior process development engineer at BEI Technology. Yang has
published more than 20 scientific papers. He received a PhD in materials
science and engineering from Tsinghua University in Beijing. (Yang can
be reached at 404/526-6081 or firstname.lastname@example.org.)
Hawthorne is VP of product development at Qcept Technologies.
Before joining the company in 2001, he was North American product manager
at Machine Vision Technology. He also worked for eight years at the Motorola
Corporate Manufacturing Research Center, where he was a research engineer
and manager of a group working on process monitoring and control technologies.
Before that, Hawthorne was at IBM's Entry Systems Division, where he designed
ICs for personal computer products. He received a BS in electrical engineering
from Auburn University in Auburn, AL, and an MS in electrical engineering
from Georgia Institute of Technology in Atlanta. (Hawthorne can be reached
at 404/ 526-6073 or email@example.com.)
Steele is a senior design and research engineer at Qcept Technologies,
where he focuses on contact potential difference sensing and imaging technologies.
Before joining the company, he was a research engineer in the electronic
materials lab at the Georgia Institute of Technology in Atlanta. He received
a BS in mechanical engineering from the Georgia Institute of Technology.
(Steele can be reached at 404/526-6076 or
Bryant is director of business development at Qcept Technologies.
Before joining the company, he held various product and marketing management
positions at nLine, Cymer, and Air Products and Chemicals. Before that,
he was a process engineer and manager at Texas Instruments. He received
a BS in material science engineering from Cornell University in Ithaca,
NY, and an MBA from the University of Texas at Austin. (Bryant can be
reached at 512/470-0830 or firstname.lastname@example.org.)
Sowell, founder of Intellimetrics, is a consultant for Qcept
Technologies. As software leader, Sowell defined the overall software
architecture for the Chemetriq wafer-imaging tool and is responsible for
most of its implementation. He is interested in high-performance computing
and wrote the first multiprocessor operating system kernel for Apple Computer.
He received BA degrees in mathematics and computer science from East Carolina
University in Greenville, NC, and an MS in information and computer science
from the Georgia Institute of Technology. (Sowell can be reached at 404/909-3193
Maloney, PhD, is R&D manager at DuPont/EKC Technology (Danville,
CA), where he is responsible for new product development and applications
support. He has been with the company for eight years. Maloney has coauthored
more than 25 publications and holds a number of patents. He received a
BS in chemistry from McGill University in Montreal and a PhD in chemistry
from Texas A&M University in College Station. (Maloney can be reached
at 510/780-5626 or email@example.com.)
Ip was an applications engineer at DuPont/EKC Technology for
three years. She earned a BS in biological sciences from the University
of California at Davis. (Ip can be reached at firstname.lastname@example.org.)
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