Figure 3a. Amplitude and phase detection and frequency modulation(FM) techniques for EFM.

frequency modulation (FM). Amplitude
and phase detection and FM modes
are depicted in the block diagram in
Figure 3a. In the amplitude and phasedetection modes, there is no feedback
during the LiftMode scan; i.e., the drive
signal that oscillates the cantilever hasconstant frequency. The 3-D EFM image
is generated by plotting the cantilever’s
phase or amplitude versus the in-plane
coordinates. In the FM mode, the phaseof the cantilever oscillation is measured
relative to the phase of the drive signal
from a high-resolution oscillator. The
phase difference is used as an error
signal in a feedback scheme; i.e.,
the frequency of the drive signal ismodulated (“Frequency Control lines”
in Figure 3a) to maintain the cantilever
oscillation at a constant phase relative
to the drive signal. The modulations of
the drive signal frequency are thenplotted versus the in-plane coordinates,
creating the 3-D EFM image.
The preferred methods of EFM arephase detection and FM, because thecantilever’s phase response is 1) fasterthan its amplitude response to changes
in the tip-sample interactions and, 2)
less susceptible to height variations on
the sample surface.

Figure 3b. Surface Potential (SP) imaging.

Surface Potential Imaging
Surface Potential (SP) imaging maps
the electrostatic potential on the sample
surface with or without a voltage
applied to the sample.1 SP imaging isa nulling technique. As the tip travels
above the sample surface in LiftMode,
the tip and the cantilever experiencea force wherever the potential on thesurface is different from the potential of
the tip. The force is nullified by varying
the voltage of the tip so that the tip is
at the same potential as the region of
the sample surface underneath it. The
voltage applied to the tip in nullifying
the force is plotted versus the in-plane
coordinates, creating the surface
3-dimension potential image.
Figure 3b depicts the SP imaging
technique. During the LiftMode scan,
the piezoelectric element thatmechanically drives the cantilever in
TappingMode™ height imaging is idle.
Instead, an adjustable AC electric
signal at, or near, the cantilever’s
fundamental resonance frequency isapplied directly to the tip. In thepresence of a DC potential difference
between the tip and the sample, theAC signal gives rise to a periodic
Coulomb force which has the rightfrequency to drive the cantilever into
resonant mechanical oscillation. The

DC voltage of the tip is then adjusted
by feedback electronics until the tip
and the sample are at the samepotential, where the frequency ofthe periodic Coulomb force on the
cantilever is now twice the fundamental
resonance frequency.

Examples of Applications
In the topography image (Figure 4a)
the shallow pit near the center would
be indistinguishable from the many
similarly sized features in view. Yet, thecorresponding SP image (Figure 4b)
clearly singles out this pit, about
160mV higher in potential than thesurrounding area. This locally highpotential region was one of many on
this aluminum sample. The cause of thehigher potential was unknown.
SP imaging can sometimes detectmaterial contamination and defects in
manufacturing. The regularly-spacedfeatures in the topography scan in
Figure 5a are 200nm-tall tungsten
islands, patterned out of a blanket
tungsten film by etching. The substrate
is silicon. In the SP image (Figure 5b),the randomly sized and spaced dark
regions on the tungsten islands arelower in potential than the surrounding
areas. Their relatively sharp boundaries

a.

b.

a.

Figure 4. Topography (a) and SP images (b) of a sample ofaluminum. Interpretation of the images is not always straight forward(see text). 8.8µm scans.

suggest that the source of the contrast is
right on the surface. Their random
pattern suggests a likely cause for these
low-potential regions: trapped charge
in photoresist residue left over after thetungsten etching process. On the other
hand, the bright, high-potential region
on the lower right of the SP image isdiffuse and largely indiscriminant oftungsten and silicon. This suggeststhat the source of this contrast may
be beneath the surface, perhaps inthe silicon substrate. Note that the
topography is devoid of any features
corresponding to the contrasts visible in
the SP image. Images like those in
Figures 5 can help in early detection ofpotential causes of device failure suchas revealed in Figure 6, discussed next.

b.

Figure 5. Topography (a) and SP images (b) of tungsten islands on
silicon substrate. Darker regions correspond to lower potential in the
SP image. 76µm scans.

EFM is a useful failure analysis toolon the device, wafer, or chip level—
even on packaged IC’s. The images
in Figures 6 are from a region ona packaged SRAM IC with thepassivation layer still on and with
voltage applied to select bus lines. Allof the devices along this region had
voltages applied in the three-pronged
arrangement seen in the right half of the
EFM image in Figure 6b — all except
for the device shown on the left half of
this image. The electric signal between
the second and third prongs from theleft shows that the transistor on the left isin saturation. The topography image in
Figure 6a shows no hint of this failure.
Using emission microscopy first, adefect was detected in the vicinity of

a.

b.

a.

b.

Figure 6. Topography (a) and EFM image (b) of a live packaged IC with passivation
layer on. EFM image detects transistor in saturation. 80µm scans.

Figure 7. Topography (a) and SP image (b)(with cross-section) across the boundary
between aluminum and copper. CPD
measures ~400mV. Sample courtesy of
P. Schmutz and G. Frankel, Ohio State
University. 20µm scans.

a.

Figure 8. (a) SP image of ZnO-based varistor
with no voltage applied across the device. (b)in-situ SP image with +4V applied across thevaristor from left to right. (c) SP image with
–4V applied. 10µm scans.

this transistor, but the cause and theexact location of the defect were not
identifiable until the EFM image wascaptured. With the passivation
removed, and then reactive ion etch
strip-back to the gate oxide, AFM
topography images of another defective
transistor very close to this area
revealed an ESD (electrostatic
discharge)-induced rupture hole in thegate oxide of that transistor (not shown).
SP imaging can be used to detect andquantify contact potential differences(CPD) on the surface. In Figures 7 thetopography (a) and the SP (b) images
are shown across a boundary that
separates aluminum from copper.
Topography shows the copper on theright has polished differently than thealuminum on the left. The contrast in the
SP image is due to the CPD across thetwo metals. An average cross section
measurement on the SP image returns avalue of about 400mV, which is close
to the difference of the work functions of
the two metals—but not equal to it since
the imaging was performed in air,rather than vacuum.

Grain boundary potential barriers inpolycrystalline materials play importantroles in the electronic properties ofdevices such as solar cells, gas sensors,
variable-temperature-coefficient resistors,
and varistors (variable resistors or surge
protectors). The applied-voltage
dependence and spatial variation ofgrain boundary potential barriers canbe quantified using SP imaging, asshown by Huey and Bonnell(University of Pennsylvania), whohave studied the resistance acrossboundaries of electrically active grains
in-situ; i.e., on varistors and similar
devices in operation.
In a varistor, the electrical resistanceacross a grain boundary can be up
to 1000 times larger than that acrossa grain, thus becoming the major
impediment to current flow. Figure 8ashows the SP image of a region on thesurface of a zinc oxide(ZnO)-based
varistor device with no applied bias
voltage across the device. The image
depicts two low-potential islands and afaint boundary that runs from upper left
to lower right. EDS (Energy Dispersive
Spectroscopy) chemical data using a
SEM showed the low-potential islands
to be second phases rich in Ti and Bi.

b.

c.

The island near the top is approximately
100mV lower in potential than theregion to the left of the faint boundary.
The potential drop across the faintboundary itself is only about 15mV. The
contrasts in this image are attributable
to differences in work function acrossthe boundaries. Figures 8b and c show
the SP images of the same area when(b) +4 volts and, (c) -4 volts are
externally applied to the varistor fromleft to right. Electron back scattering
pattern microscopy (EBSP) confirmedthat the voltage steps in these images
mark the location of a grain boundary
in the zinc oxide. The tall potential steps
in these images reveal the resistive
nature of the grain boundaries. SP
images not only pinpoint the locationof the grain boundary—absent in the
topography image (not shown)—
but also enable measurement of thepotential drop across it (approximately
350mV). With knowledge of the carrier(donor) concentration in the ZnO grains
and of the magnitude of the current
flowing through the varistor during in-situ
AFM imaging, measurements of thesevoltage steps can be used to calculate
the grain boundary potential barrier.

Figure 9. Topography (left) and FM-EFM (right) images of aferroelectric film with electrical bits written onto it. The four bits were
written with a metal-coated AFM tip at +3,-3,+2, and -2volts from
top to bottom. The images were captured with the same tip,
moments after polarizing the central region. Carrying +1V, the tip
failed to polarize this ferroelectric film. 2µm scans.

By locally polarizing ferroelectricmaterials, an AFM can create what
is tantamount to electrical bits. At
Advanced Surface Microscopy, Don
Chernoff uses TappingMode AFM witha metal-coated tip to “write” onto aferroelectric thin film and then uses thesame tip in LiftMode to “read” thepolarization just induced.2 Figure 9
illustrates this. The background patternwhich appears in both images is due tothe grain boundaries on the surface ofthe ferroelectric film. At the center of the
EFM image, four polarized regions are
identified with a metal-coated AFM tip,
the same tip which was biased with a
DC voltage to induce the polarization
just moments earlier. With the polarityof the tip reversed from 700mV to –1500mV during imaging (i.e., during
the “reading”), the contrast of the four
bits was reversed (not shown). This
verified that the electrical bits wereindeed stored in the ferroelectric film.
The size of a bit is determined in partby the sharpness of the AFM tip, and inpart by the properties of the ferroelectric
film and the voltage required to achieve
the desired level of polarization. The
typical radius of curvature at the apex

Figure 10. On the surface of a conductor-insulator composite,
topography (left), EFM image (right) allows easy identification andmeasurement of carbon black network (dark regions) leading tocalculation of fractal dimension and correlation length incorroboration with SEM-based results. 16µm scans.

of a metal-coated TappingMode AFM
tip is 25-50nm. (See also images in
Figures 1a,b)
The electrical transport propertiesof disordered conductor-insulator
composites are closely tied to thestructure of their “percolation network,”
which enables the movement of charge
carriers through the composite. Figure
10 shows the topography (left) andthe EFM image of an area on thesurface of a 250µm-thick sample ofa disordered conductor-insulator
composite, with small islands ofconductive carbon-black randomly
dispersed within the non-conductive
high-density polyethylene matrix. Someof the carbon-black islands are isolated
from one another, while others areconnected in a continuous network—an“infinite cluster”—so that they create a
conductive path through the thickness ofthe composite. The EFM image wascaptured with a 3V potential difference
between the tip and the sample. The
dark areas in the EFM image are partsof the carbon-black infinite cluster. The
lighter colored areas depict the material
not in the infinite cluster; i.e., the nonconductive polymer and the isolatedislands of carbon-black. The EFM

image was quantified using grain
analysis, enabling calculation of thefractal dimension (2.6±0.1) andestimation of the correlation length(~3µm) for the percolation network.
These numerical results corroborated
findings from electron microscopy
image analysis on other similar carbon
black composites.3 It is known that suchcomposites do not conduct electricity(i.e., the infinite cluster does not form), if
the volume fraction of the conducting
material is less than a certain“percolation threshold.” For thiscomposite, the percolation threshold isreported in other literature to be 0.170+/- 0.001.4 EFM images of a sampleof this composite with carbon black
volume fraction of 0.168 (slightly lessthan the percolation threshold) did notshow any contrast even when the tip
voltage was increased. On the other
hand, a sample with carbon black
volume fraction of 0.179 (slightly larger
than the percolation threshold) revealed
contrast, but with a correlation length
larger than that of the 0.1978-volumefraction sample, which is shown in the
figures here. This work was done by
Ravi Viswanahtan and Michael
Heaney at Raychem Corporation,
Menlo Park, California.5

a.

Figure 11. Topography (left) and phase detection EFM (right) imagesof the surface of a thick-film resistor (TFR). EFM image depicts the
conductive RuO2 network (dark) exposed at the surface. 56µm scans.

EFM has also proven useful in similar
studies on thick-film resistors (TFR). TFR
are composites used in hybrid thick-film
microelectronics and sensors; forexample, as heating elements inprinting heads of equipment such as
facsimiles and printers. As an electric
current is forced through it, a TFR heats
up and makes a permanent mark on aheat-sensitive paper. The uniformity ofheat generation in the TFR and thetransfer of the heat to the paper (andthus the quality of print marks producedon paper) depend on a number ofparameters, including the sub-micron
structure of the percolation network
in TFR. RuO2-glass composites arecommonly used as TFR heating elements
in printing heads, and have beenstudied by Andreas Alessandrini andb.

Figure 12. Secondary electron (SE) SEM image (a) and sample
current (SC) image (b) identify the same areas distinguished as
conductive (green) in the EFM image in Figure 11. Images are~56µm square.

Giovanni Valdrè at the Physics
department at the University of Bologna,
Italy. In Figure 11 the topography (left)
and EFM (phase detection) images areshown for such a composite with a 20V
DC potential applied to the sample
relative to the grounded tip. Small
protrusions speckle the topography
image and are also convoluted into the
EFM image. The contrast between
lighter and darker red areas in the EFM
image depends on the applied voltage;
the green areas are part of thepercolation network. These same areas
are also depicted in a secondary
electron (SE) SEM image (Figure 12a)as well as in a sample current (SC)image (Figure 12b). Secondary electron
and EDS analysis revealed that thesegreen areas were indeed RuO2 crystals.

Figure 13 shows TappingMode AFM
topography and EFM images of across-section of a nanowire bundle
embedded in a matrix of the dielectric
Al2O3 (alumina). The cross-section waspolished and some of the dielectric wasetched; the nanowires are protruding
out of the matrix slightly and showing
up as lighter colored regions (taller) in
topography (left). Nanowire composites
such as these may be used in making
high-density electrical multi-feedthroughs
and photosensing arrays. An external
voltage (~7V relative to the groundedtip) was applied to the other end of thebundle, and the electric field gradient
was monitored in LiftMode using
amplitude detection at this end of thebundle. One of the nanowires (marked
by x in the topography image) is not

X

Figure 13. Topography (left) and EFM (right) images of cross-section of
a nanowire bundle embedded in an alumina matrix. EFM image locatesa broken nanowire (marked by “X”) and some trapped charge (darker,
upper left). 1.7µm scans.

Figure 14. Topography (left) and Surface Potential image (right) ofalternating TiO2 and SiO2 regions. SP image shows the CPD anddebris on the surface. 40µm scans.

showing contrast in the EFM image,indicating discontinuity in the wire. The
EFM image also detects a region ofhigh electric field gradient on the upper
left (dark region). The source of this highfield gradient is unknown, but possibly
trapped charge in a particle (indicatedby an arrow), which is resting on thesurface as revealed in the topography
image. This work was done by Tito
Huber and his colleagues at Polytechnic
University, New York; Howard
University, Washington DC; Naval
Surface Warfare Center, Silver Spring,
MD; and Veeco Instruments.6
Figure 14 shows the topography andthe SP image captured on the crosssection of a multi-layer of alternating
SiO2 and TiO2, which wasmechanically polished (using colloidal
alumina particles) at a shallow angle
to expose the different layers. The twomaterials polished differently, giving rise
to topographic contrast. The SP image
shows the contact potential difference(CPD) between the TiO2 (lighter color)
and the SiO2. In addition, the SP
image depicts small regions oflocally-higher potential dispersed overthe entire image. These are debris(likely SiO2) left over from thepolishing process.

Summary

References

Electric Force Microscopy (EFM) and
Surface Potential (SP) imaging are nondestructive AFM techniques for detecting
electric field gradients and surface
potential variations on insulating,conducting and semiconducting
materials. Requiring little or no sample
preparation, characterization is done
in air on test structures and materials
in research – on chip- or wafer-level
devices, and even on completed,powered ICs. Applications range frommonitoring fabrication processes, tofailure analysis, to quantifying electricalproperties of materials. In addition to
imaging, a conductive AFM tip witha controlled voltage can be used tomodify electrical properties of materials
locally, e.g., polarization offerroelectric films.

1. Surface Potential imaging issometimes referred to as Scanning
Kelvin Probe Microscopy (SKPM)

Figure 15. Topography (left) and Surface Potential (right) images of an
I-P-based nanowire between two metal contacts with biased applied
between them. 2µm x 1µm scans. Sample courtesy of Philips Corp.,
The Netherlands.

2. Advanced Surface Microscopy,
Indianapolis, IN, USA.
3. F. Ehrburger-Dolle and M. Tence,
Carbon, Volume 28, p. 448,
1990.
4. M. B. Heaney, Physical Review B,
Volume 52, 12477, 1995.
5. R. Viswanathan and M. B. Heaney,“Direct Imaging of the Percolation
Network in a Three-Dimensional
Disordered Conductor-Insulator
Composite,” Physical Review Letters,
Volume 75, Number 24, pp. 44334436, 11 December 1995.
6. C. A. Huber, T.E. Huber, M.
Sadoqi, L. A. Lubin, S. Manalis, andC. B. Prater, “Nanowire Array
Composites,” Science, Volume 263,
pp. 800-802, 11 February 1994.