DCUBE-sMIM:
R-V & C-V Spectra

DCUBE-PFM:
Scanning Switching Voltage

DCUBE-TUNA:
Slices of TUNA Current

Application Note #152
Performing Hyperspectral Mappingwith AFM DataCube Nanoelectrical Modes
AFM-based nanoelectrical modes have found applications
in fields ranging from semiconductors to piezoelectricmaterials, energy research, and biology. Modes areavailable to characterize the local conductivity, resistivity,
charge, carrier concentration, carrier-type, or piezoelectric
properties with nanometer-scale spatial resolution, andusually require a direct contact between the AFM tip
and sample. The data produced have traditionally beenin the form of a two-dimensional (2D) map, generated incontact mode, with a single electrical data point per XY
location. At few, carefully selected locations in this map,electrical ramps or spectra are generated to get a deeper
insight in the local electrical properties. This applicationnote introduces a new approach to nanoelectrical imaging
that goes beyond a 2D map, creating an entire electrical
data cube and correlated nanomechanical data cube while
operating at normal imaging speeds. This approach has
the added benefit that it avoids contact mode imaging,
thus extending electrical measurements to soft andfragile samples and improving measurement consistency
through increased tip lifetime. Moreover, this is a generalapproach that is applicable to most nanoelectrical modes
and applications. The more complete data set contains new
information and enables functional imaging on complex
samples as shown in examples of barrier height mappingin heterogeneous metal oxides, semiconductor carrier
profiling, piezoelectric domain switching dynamics, and Li
ion cathode characterization.

Moving Beyond Property Mapping
Atomic force microscopy is generally used to generate
high-resolution (<1-5 nm) topographic images byraster scanning a sharp tip on the sample surface withfeedback-controlled tip-sample force interactions. Bruker
has pioneered AFM technology to simultaneously
capture and extract mechanical properties from thetip-sample interactions. For example, PeakForce
Quantitative Nanomechanics (PeakForce QNM®)1-4 and
FASTForce Volume™ (FFV)5 modes provide an entire
force curve for every pixel of the image, and the contact
resonance mode5 provides a resonance spectrum forevery pixel of the image. From these spectra, mechanicalproperties such as adhesion, stiffness, modulus,
deformation, tan-delta, and loss and storage modulus
can be extracted and visualized in two-dimensional (2D)
maps. For electrical characterization, a range of application
modules is available,6-9 and even electrical measurements inliquid are possible with the recent introduction of insulated
AFM nanoelectrode probes for scanning electrochemical
microscopy (SECM) and nanoelectrical characterization.10-14
Having all of these capabilities contained within a single
instrument provides researchers greater efficiency andexperiment reach in both routine industrial applications
and for highly multidisciplinary research in piezoelectricity,
semiconductor devices, polymeric systems, energy
research, and biological characterization.

AFM Nanoelectrical Modes
Conventional AFM nanoelectrical modes are generally
operated with a fixed set of operating conditions (DCbias, AC bias, frequency, etc.) and a single electricalmeasurement is performed for every XY location,yielding a 2D electrical map. This is also true in PeakForce
Tunneling AFM (PeakForce TUNA™)6 and related
PeakForce Tapping-based electrical modes,7-9 which
overcome the limitations of contact mode. Aside from
2D maps, AFM-based electrical characterization has longincluded point spectroscopy, whereby one of the operating
conditions is swept as the tip is kept stationary, forexample in the acquisition of current-voltage (I-V) curves
at a single or a few selected individual positions. Point
spectra can also be performed in arrays, but until now,
this has remained rather time-consuming and has only
allowed limited spatial sampling. Published application
examples include capacitance-voltage (C-V) spectra applied
for studying pn-junction delineation in Si devices,15 andI-V spectra for investigating humidity effects on nanoscale
electrochemistry in solid silver ion conductors.16
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Figure 1. DCUBE modes operating on FFV approach: (a) height sensor(red) and deflection error (blue open circle) plots with segments
showing extend (1–2), dwell (3), and retract (4–5) cycles; (b) patternof sample bias (red) and corresponding TUNA current (blue);(c) illustration of scan pattern during acquisition of DCUBE-mode
data; and (d) five TUNA current slices from the DCUBE-TUNA results.

DataCube Modes
Bruker's DataCube modes combine imaging and point
spectroscopy, producing an integrated 3D data set. This
multidimensional data cube measures the dependenceof a specific electrical parameter in each XY position as afunction of one of the (electrical) operating conditions.17
The subjective approach of guessing locations of interest(for single-point spectroscopy) is replaced by a big dataapproach, resulting in higher dimensional data that canbe sliced along any axis or plane, and which is conducive
to principal component analysis and machine learning
approaches to data reduction. The high dimensional
electrical data sets allow one to extract high-resolution
2

maps of electrical properties previously not acquired using
AFM. Examples include images of Schottky barrier height,
flat-band voltages, piezoelectric switching voltages, etc.
Rather than employing contact mode, the tip is moved frompixel to pixel in a FFV method.5 An electrical spectrum isacquired during a hold segment inserted into each force
curve in each pixel. The force curve at every pixel embeddedin the FFV map constitutes a set of nanomechanical data
cubes, which are spatially correlated with the electrical data
cubes. Since the FFV map avoids lateral forces, tip lifetime
is drastically improved and the electrical measurements
are extended to polymers, nanoparticles, and other fragile
samples that are impossible to study in contact mode. In
this application note, the data cube principle is illustrated
for tunneling AFM (TUNA), piezoforce microscopy (PFM),
scanning capacitance microscopy (SCM), scanningspreading resistance microscopy (SSRM), and scanningmicrowave impedance microscopy (sMIM), but it canalso be expanded to other electrical modes in both airand liquids.

Experimental Principle and Data Acquisition
Bruker's DataCube (DCUBE) modes are the result of
seamless integration of existing high-performancenanoelectrical modes with the FFV technique. In the FFV
mode, the tip is held in a fixed XY position, while a force
distance cycle with “dwell” segment is executed in the Z
direction. This is illustrated by the height sensor plot andcorresponding force curve shown in Figure 1a. Force ramp
rates up to 300 Hz are possible using Bruker's proprietary
low-force trigger capability. Combined with sub-100 ms
dwell times for the hold segment, good throughput isobtained and one can maintain regular imaging speeds
also when acquiring dense arrays. In Figure 1a, the ramp
rate for the “extend” and “retract” segments is 60 Hz ata normal force (or deflection) trigger level of 15 nN andwith a Z movement of 80 nm. This results in a ramp speedof 9.6 µm/s.
During the “dwell” segment (here 100 ms), the sample
bias is swept from -2 V to +2 V, corresponding to a ramp
rate of 40 V/s, as shown in Figure 1b. The number of data
points for the non-dwell and dwell segments can be set
independently, allowing for high spectral resolution. In thisexample, 256 and 190 data points result in resolutions of
0.625 nm in Z and 21 mV in sample voltage, respectively.
Higher density can be obtained by further increasing theamount of data points. The four spectra (height, deflection
error, sample bias, and TUNA current) are captured
simultaneously. After acquisition of the spectra in one
pixel, the tip moves to the next pixel using the FFV rasterscanning method (Figure 1c), avoiding the shear force
common to contact mode–based scanning. Figure 1dshows five typical current slices extracted from a data cube
acquired using this principle on a γ-Fe2O3 sample. Eachcurrent slice image consists of 256x256 pixels for a sample

1.8

1.8

800 ms (5 V∙s-1)

1.7
1.65

Ramp
Parameter

Distance

OutputChannelForce
Stiffness
Adhesion
Modulus

1.7
1.65

-1.5

-1

1.8

-0.5
0
0.5
Sample Bias (kmV)

1

1.5

-1.5

1.7
1.65

-0.5
0
0.5
Sample Bias (kmV)

1

1.7
1.65

-1.5

-1

1.8

-0.5
0
0.5
Sample Bias (kmV)

1

1.5

-1.5

1.7
1.65

-0.5
0
0.5
Sample Bias (kmV)

1

1.7
1.65

-1.5

-1

-0.5
0
0.5
Sample Bias (kmV)

1

1.5

-1.5

-1

-0.5
0
0.5
Sample Bias (kmV)

1

1.5

Figure 2. A series of C-V spectra of a p-type semiconductor captured
by DCUBE-sMIM. These are raw data without averaging. The dwell
time and the sample bias ramp rate for each spectrum are indicated.

As an alternative to ramping the DC sample bias during
the dwell period, the user can also select to ramp any
other parameter relevant to the electrical mode selected(e.g., the AC voltage, amplitude or frequency). In this way,
one can collect a wide variety of electrical spectra, including
I-V, C-V, dC/dV-V, R-V, dR/dV-V, PFM-amplitude-V, andElectrical
DCUBE-TUNA DCUBE-SSRM

VDC

Current

VDC

log(Resistance)

DCUBE-SCM

DCUBE-sMIM

DCUBE-PFM

VDC
VAC
fAC
Phase

VDC
VAC
fAC
Phase

VDC
VAC
fAC
Phase

dC/dV
Amplitude

dC/dV
Amplitude

dC/dV Phase

dC/dV PhasesMIM-CPFM Amplitude
PFM PhasesMIM-R

Current vs. VDC

Log (resistance) vs. VDC

Table 1. Summary of DCUBE modes and electrical characterizations with FFV.
3

1.5

12 ms (333 V∙s-1)

1.75
Input (V)

1.75

-1

1.8

100 ms (40 V∙s-1)

ExampleSpectraForce vs. Time

1.5

25 ms (160 V∙s-1)

1.75
Input (V)

1.75

-1

1.8

200 ms (20 V∙s-1)

MechanicalForce Volume

50 ms (80 V∙s-1)

1.75
Input (V)

Input (V)1.75

Input (V)In DCUBE modes, the conditions for force curve cycle andthe electrical dwell period are controlled separately. This
allows users to independently fine tune the measurementof force-distance spectra and electrical spectra. The durationof the hold segment for good quality signals depends
on the nanoelectrical mode in use. More specifically, it
depends on the applied AC frequency and/or the bandwidthof the sensor. As sensors normally have a bandwidth in the
kHz range (for example; the PeakForce TUNA application
module has a typical bandwidth of 15 kHz), acquisition
times for capturing the whole electrical spectral down to
ms level are possible. It is worthwhile to note that whenincreasing the electrical ramp speed, the signal/noise
ratio will be compromised. For example, Figure 2 showsa series of capacitance-voltage (C-V) spectra of a p-typesemiconductor captured by DCUBE-sMIM. These are raw
data without averaging. The dwell time and the sample
bias ramp rate for each spectrum are indicated on the
figure. As shown by these results, a dwell time of 50 ms
or a ramp rate of 80 V/s is sufficient to capture all the
spectral features of this sample. Considering both force andelectrical spectra, the time per pixel is typically in the rangeof 20-200 ms. For a 256x256 pixel map, this corresponds toan acquisition time of 22-220 min. Albeit, with this relatively
long spectroscopic mapping duration, one can capture morethan 1000 data points for each electrical spectrum, resulting
in more than 1000 dynamic sequence or slice images at a
capture rate of 1.3-13 s/image.

Input (V)area of 3x3 µm2. The 190 spectral data points from thedwell segment provide 190 of these current slice images.
At the same time, the “extend” / “retract” segments ofthe deflection plot construct a complete force-distancecurve and allow one to extract quantitative nanomechanicalimages for modulus, adhesion, deformation, and stiffness.

dC/dV vs. VDC

Capacitance vs. VDC

PFM vs. VDC

dC/dV vs. VAC

dC/dV vs. VDC

PFM vs. Frequency

PFM-amplitude-frequency spectra. Table 1 summarizes theavailable electrical DCUBE modes.
The electrical conditions can also be held constant during
the dwell period, which can be short (milleseconds) or long(tens of seconds). In this way, the electrical signal can beaveraged over a user-defined period, resulting in improved
signal/noise ratios as compared to the equivalent contact
or PeakForce electrical mode. During the dwell period,
the electrical parameter is measured as a function oftime, opening up the possibility to study time-dependent
phenomena. Examples include mapping of time-dependent
conductivity or photoconductivity after an external stimulus,
such as a light pulse or electrical pulse; observing timedependent dielectric breakdown in dielectrics; investigating
charging or discharging effects after applying a voltage
pulse; etc.
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Figure 3. Processing, analysis, and visualization of DCUBE data.
Slices of the spectroscopic maps can be extracted for regularprocessing of AFM images in NanoScope Analysis software:(a) surface topography; (b) quantitative nanomechanical properties—
adhesion map; (c) a slice map from TUNA current—sample bias
(I-V) spectra at -1 V (cover image of a movie created from 130 slices
available on the Bruker website); (d) slices of TUNA current maps atselected voltages; and (e) scanning barrier height images created byanalyzing all I-V spectra. The color bar displays from ohmic (zero) toinsulating (one). NanoScope Analysis software goes with a MATLAB
toolbox that allows one to extract the whole cube of data for further
analysis in MATLAB. Image (e) was created by MATLAB.

4

Data Analysis
DCUBE modes provide simultaneous capture ofnanometer-scale electrical and mechanical characteristics
in high-density data cubes. For materials scientists
and engineers, this breaks long-standing efficiency andcharacterization barriers. Processing such information-rich,big data results stimulates and encourages creative data
mining. Bruker's standard NanoScope® analysis offline
software provides a suite of data tools for basic processing
and visualization, such as the extraction of individual
slices and spectra. Figures 3 and 4 illustrate some of thecore functions for handling DCUBE data (here, applied to
DCUBE-TUNA data acquired on a γ-Fe2O3 sample).
First, slices of the spectroscopic maps can be extracted
for further processing, as one would do with regular AFM
images. This allows surface topography and quantitative
nanomechanical maps to be extracted, as shown in
Figure 3a and 3b. Figure 3c shows a current slice at a
fixed sample bias of -1 V, while Figure 3d shows morecurrent slices at nine selected voltages. Figure 4a showsa current slice at +2 V collected in a different area on
the γ-Fe2O3 sample.
Second, one can select, display and export any of thespectra through single or multiple point selection in thesurface topography, nanomechanical, or nanoelectricalimages. One can also display and overlay all spectra from aselected region. Such a dense collection of spectra can also
be visualized through statistical methods with the built-in
density plots. An example is shown in Figure 4c createdfrom 1890 spectra in the dashed-yellow-square region in
Figure 4a. The darkness in this plot corresponds to the
population density of the spectrum in this region of interest.
In this particular example, the three visible curves in
Figure 4c indicate three distinct electrical domain behaviors:
insulating, low barrier, and high barrier.
Third, the NanoScope Analysis software also provides
electrical contour plots along a user-defined line. Figure 4dshows the TUNA current changes over sample bias acrossthe dashed-yellow line in Figure 4a. This is a 2D slice ofthe data cube at a fixed Y position, as indicated by thecoordinates on the image. Each vertical line contains
spectral information rendered by the false color of TUNA
current. The (dark) blue-to-yellow stripes indicate thelocation along the line in Figure 4a where TUNA current
changes with sample bias. The white plot on Figure 4d isthe corresponding surface profile along the dashed-yellow
line in Figure 4a, with a range of 150 nm in height. Thisshows that the nanoelectrical properties have no clear
correlation with the surface topography and are only
randomly varied among different particles.
Further in-depth analysis and data handling can also be
performed using dedicated external analysis packages,
such as MATLAB- or Python-based tools. For this purpose,

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Figure 4. Processing, analysis, and visualization of nanoelectrical
data from DCUBE-TUNA mode with NanoScope Analysis software:(a) current slice at +1 V; (b) point-selected I-V spectra as numberedin (a); (c) density plots based on 1890 I-V spectra from thedashed-yellow-square region in (a); and (d) TUNA current changes
over sample bias across the dashed-yellow line in (a) where the white
plot on the image is the corresponding surface profile with a range of
150 nm in height. This is a two-dimensional slice of the data cube at a
fixed Y position as indicated by the coordinates on the image.

a toolbox is provided that allows one to directly import the
DCUBE raw data files, and extract the channels of interest.
These raw data files can be converted and also fed to otherprogramming languages, such as Python. For example,
one can create movies to show the electrodynamic of
the materials. The TUNA current map in Figure 3c is thecover image of a movie created from 256 slices extracted
from the data cube.18 The sample bias ramping for thismeasurement is from -1 V to +1 V.
In a second example, MATLAB was used to perform abatch analysis of all I-V spectra in this data cube: Fitting
the I-V spectra with a thermionic emission model allowed
us to extract the barrier height of the metal tip / γ-Fe2O3
semiconductor Shockley junction. The resulting barrierheight map is shown in Figure 3e and shows heterogeneity
among different γ-Fe2O3 nanoparticles. The color bar
represents from ohmic (zero) to insulating (one). Thisconfirms previous studies by PeakForce TUNA and sMIM
showing distinct electrical properties at the particle level.8
This is a typical example of how the vast amount of data
combined with in-depth analysis allows one to extract
new, quantitative, nanoelectrical information previously
unattainable by conventional AFM modes.

Case Study: DataCube Tunneling AFM(DCUBE-TUNA) on Li-Ion Battery Cathodes
Battery failure is a result of complex interrelated
phenomena. It depends on battery chemistry, design,
environment, and actual operation conditions.20 Therefore,
understanding, improving, and controlling the lifetime andperformance of a battery requires studies at the component
level. AFM has proven to be a powerful instrument forbattery component studies.21 However, the presence of
5materials with distinct mechanical properties, from soft
(polymer additive), loose (conductive additive), to hard
(Li metal oxide), porous (separator) surfaces, and highvariation in surface topography, can pose challenges forcontact-based scanning modes due to the nature of highnormal imaging force and shear force. Tapping mode issuperior to contact mode surface mapping in this regard.
However, a majority of nanoelectrical characterization isbased on solid tip-sample contact. Recently, PeakForceTapping modes have proved useful for imaging challenging
samples like battery materials,22-26 in particular for in situ
studies of the fragile solid electrolyte interphase layer onboth anodes27-29 and cathodes.30,31 DCUBE modes further
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Figure 5. DCUBE-TUNA study of a battery cathode consistingof Li metal oxide (1), polymer binder (2), and conductive carbon
nanoparticles (3): (a) surface topography; (b) quantitative surface
stiffness differentiating different domains; and (c) a collection of
TUNA current slices from the spectroscopic mapping at selected
sample voltages. The scanning area is 45x45 µm2.

expand the capabilities of PeakForce Tapping modes byenabling the acquisition of multidimensional data cubes
through simultaneous capture of nanometer-scale electricaland mechanical characteristics in high-density data cubes.
The cathode investigated in this example consists ofLi metal oxide, polymer binder, and conductive carbon
nanoparticles. First, we scanned a large area of 45x45 µm2,
which can be challenging for other AFM nanoelectricalmethods on this type of composite sample. Figure 5ashows a high-quality image of surface topography. The
variation in height is over 1 µm, which is typical for a Li-ion
battery cathode. Representative domains of Li metal oxide(1), polymer binder (2), and carbon black (3) are indicatedon the images. These domains are better identified by
Figure 5b, a quantitative map of surface stiffness, as
Li metal oxide is of the hardest materials, and it shows
the highest stiffness, whereas the polymer binder is thesoftest with the lowest stiffness. Figure 5c is a collectionof slices from the spectroscopic mapping, showing the
TUNA current image at selected sample bias, as indicatedto the right. These TUNA current maps clearly show

distinct conductivities over different material domains, aswell as conductivity heterogeneity over different Li metaloxide grains.
Figure 6 shows more details about this sample with a scansize of 15x15 µm2, where the different material domains
and the heterogeneity over different Li metal oxide grains
are further presented. Figure 6a is the surface topography
showing a few large Li metal oxide grains, e.g., regions#1–3. The inter-grain filling materials are difficult to identify
on this morphology map. This is partially addressed by
the stiffness and modulus maps in Figure 6b and 6c,
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volumetric energy density. In addition, the Li metal oxide
also shows inner-grain heterogeneity, as indicated by grain#3 on Figure 6d. Figure 6e is a collection of slices from thespectroscopic mapping showing TUNA current images atselected sample biases as indicated. This series of images
further confirms the electrical properties. More importantly,
it shows the dynamic changes with applied sample biases
from -4 V to +4 V. The current-voltage behaviors of the Li
metal oxide grains deviate from linear Ohmic response.
For example, the cathode is relatively silent to sample bias
from -0.5 V to +0.25 V.
Figure 7 shows the DCUBE-TUNA results of a single Limetal oxide grain on this cathode. Surface topography
in Figure 7a shows that this grain is an aggregate of
sub-micron nanoparticles that have similar mechanicalproperties, as shown in the stiffness (Figure 7b) andmodulus (Figure 7c). The TUNA current slices in Figure 8d
and 8e extracted from the DCUBE-TUNA spectra at sample
biases of +4 V and -4 V show conductivity variations
amongst these particles. This confirms the inner-grain
electrical heterogeneity shown in Figure 6d. Figure 7f plots
all current-time spectra from the area indicated by thewhite square in Figure 7e. During this 125 ms dwell period,

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E

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F

E

Figure 6. DCUBE-TUNA study of a battery cathode consisting of
Li metal oxide (1)-(3), polymer binder (4), and conductive carbon
nanoparticles (5): (a) surface topography; (b) quantitative surface
stiffness differentiating different domains; (c) quantitative modulus
map; and (d)-(e) TUNA current slices from the spectroscopic mappingat selected sample voltages. The scanning area is 15x15 µm2.

where Li metal oxide shows high stiffness and modulus,
respectively. This differentiation is confirmed by the TUNA
current map in Figure 6d, a slice of spectroscopic mapping
at a sample bias of +4 V. Carbon black rich regions (region#5) show high conductivity, while polymer binder regions
are insulating (region #4). For the Li metal oxide domains,
it is interesting that grain #2 only shows backgroundcurrent, which is totally different from other grains. This
could be due to the lack of conduction channel connectedby carbon black additives or by the intrinsic nature of thegrain itself. Such a region needs to be avoided in practicaldesign as it only serves as a redundant weight and volumeburden to the battery, lowering the specific energy or
6

Figure 7. DCUBE-TUNA studies of a Li metal oxide grain on a battery
cathode consisting of Li metal oxide, polymer binder, and conductive
carbon nanoparticles: (a) surface topography; (b) map of quantitative
surface stiffness differentiating different domains; (c) quantitative
modulus map; (d)-(e) two slices from spectroscopic mapping showing
TUNA current image at a sample bias of +4 V and -4 V, respectively;and (f) all current-time spectra from the area indicated by the whitesquare in (e). During this 125 ms dwell period, the sample bias
sweeps linearly from -4 V to +4 V, or at a rate of 64 V·s-1.

the sample bias sweeps linearly from -4 V to +4 V, or at a
rate of 64 V/s. The square area is across two nanoparticles
with different conductivities, as shown in Figure 7e. Withineach particle, the conductivity is relatively homogeneous.
This results in two distinct groups of spectra, as shown in
Figure 7e.
This DCUBE-TUNA example nicely demonstrates theimportance of dynamic, multidimensional information forclearly differentiating and analyzing the performance of acomplex system constructed from functional materials with
distinct physical properties.

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Case Study: DataCube Scanning
Capacitance Microscopy (DCUBE-SCM) of
Semiconductor Devices
SCM provides a method for direct measurement ofactivated carrier concentration with nanometer-scaleaccuracy in two dimensions. In SCM, the variation in carrier
concentration inside semiconductor structures can beimaged through measurement of the dC/dV signal of themetal-oxide-semiconductor (MOS) capacitor formed by theprobe and the semiconductor sample. In this mode, theprobe is scanned in contact mode, and topography andelectrical data are acquired simultaneously, enabling thedirect correlation of a sample location with its electricalproperties. Applications of SCM include failure analysis ofsemiconductor devices and two-dimensional carrier profilingof cross-sectioned semiconductor devices.
Conventional SCM has two limitations: first, as it operates
in contact mode, it can suffer from high imaging and shear
forces, which links directly to tip lifetime, especially on
structures with substantial topography variations. Second,
it is operating at a fixed DC bias voltage between the tip
and the sample, while lots of information becomes visible
only when operating at a variety of voltages. In fact, cycling
DC bias on every pixel has been a topic of interest forquite some time.15 DCUBE-SCM overcomes these twolimitations by providing high spatial and spectral resolution
spectroscopic mapping data without the use of contact
mode. By further analysis of the resulting data cubes,
researchers can obtain additional information on oxide
thickness, oxide charges, threshold voltages, contaminationfrom mobile ions, and interface trap densities.
Figure 8 shows a DCUBE-SCM example from a SRAM
transistor. In this measurement, the DC sample voltage was
swept from -2 V to 2 V. The scan size was 2x2 µm2 with
128x128 pixels. Each pixel took 100 ms and we collected
the complete whole data cube in 27 min. Both the SCM
dC/dV amplitude (displayed in Figure 8) and dC/dV phasedata were also stored, in addition to the force-distancedata. Visualization of the dC/dV amplitude data cube in athree-dimensional (3D) space of X, Y and VDC was createdin MATLAB, shown in Figure 8a. The vertical plane shownin Figure 8b is a slice displaying the dynamic change of7

Figure 8. DCUBE-SCM study of two adjacent SRAM pnp transistors.
This collection of images displays the SCM dC/dV amplitude data:(a) data cube in a 3D space of X, Y and VDC; (b) a slice of the data
cube at a fixed Y position; (c)-(k) slices at selected, fixed DC biases
along the VDC coordinate. DC sample voltage was swept from -2 V to+2 V. The scan size is 2x2 µm2 with 128x128 pixels.

dC/dV amplitude with VDC along the line in the X direction.
This slice shows how the pnp junction carrier profile varies
with the DC sample voltage and is a demonstration of
the movement of “apparent junction,” that is, effective
channel length with DC voltage. Slices extracted at fixed
DC voltages are shown in Figure 8c to 8k, where the fixed
DC voltage is indicated on each image. Figure 8e and 8ishow a defect on the right pnp junction. Interestingly, thisdefect is only visible at certain voltages, as shown in thisseries of data. This defect is better displayed by a movie ofthe whole collection of 128 slices.18 This example illustrates
that DataCube imaging allows one to observe effects easily
missed when using conventional electrical modes operated
at only a few discrete operating conditions.

Case Study: DataCube Scanning Microwave
Impedance Microscopy (DCUBE–sMIM) on
Delicate Samples
In sMIM, a microwave signal reflected from the tip-sample
interface holds information of the electrodynamic propertiesof the sample surface underneath the tip apex.8 Detecting
and processing the reflectance in real time allows sMIM
to directly access the permittivity and conductivity of thematerial. When an AFM-type sMIM probe is scanning
across the sample surface, sMIM is capable of imaging
variations in resistive (sMIM-R) and capacitive (sMIM-C)
properties. This detection approach does not require making
electrical contact between the sample and the substrate,
as sMIM is based on the capacitive coupling between
the tip and the sample. By AC-biasing the sample, sMIM
also provides carrier profiling (dC/dV) capability similarto traditional SCM. In the same way, it also uniquelyoffers mapping of nonlinear resistive properties (dR/dV).
With both DC and AC sMIM signals, sMIM is suitable forstudying surfaces with complex composition and over abroad dynamic range, e.g., metallic, semiconducting andinsulating domains. As a near field method, the resolutionof sMIM is limited by the tip radius of the probe and it caneasily achieve a lateral resolution of <30 nm for electricalmapping. Sub-aF sensitivity and high signal/noise ratios
are realized by using waveguide tips with coaxial shielding.
When combined with PeakForce Tapping, it is possible
to obtain sMIM results on delicate samples such ascarbon nanotubes, and simultaneously acquire mechanicalsample properties such as modulus and adhesion.8 With
DCUBE-sMIM one can acquire the same properties at avariety of sample voltages, in a single scan and get the“full picture” at once.
Doped Si Device
Figure 9 shows a DCUBE-sMIM example collected
on a series of doped Si devices. The adhesion map is
extracted directly from the force-distance spectra available
in each pixel, and can, for example, be used to identify
contamination. Both C-V and dC/dV-V spectra werecollected in each pixel resulting in C, dC/dV amplitude, anddC/dV phase maps for voltages ranging from -2 V and +2 V.
As an example, the dC/dV amplitude voltages at somediscrete sample voltages are displayed, illustrating how theobserved contrast strongly varies with applied voltage andcarrier type and concentration.

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Figure 9. DCUBE- sMIM data acquired while ramping the sample bias
from -2 V to +2 V. As an example, slices of the dC/dV amplitude datacube at selected voltages are displayed and show voltage dependent
contrast for some regions. Adhesion and Height are measured
simultaneously and also displayed.

Si with Staircase Carrier Profile
Figure 10 shows typical data extracted from a
DCUBE-sMIM study. In this example, we used a Si sample
with a n-type and p-type staircase carrier profile, whichforms a candidate sample for quantification of AFM-based
carrier profiling methods.32 Both the C-V spectra (sMIM-C
vs sample bias) and R-V spectra (sMIM-R vs samplebias) were collected within 100 ms per pixel, covering abias range of -2 V to +2 V. Having images over this bias
range helps to differentiate and locate all carrier levels
8

A

D

B

E

C

F

G

Figure 10. DCUBE-sMIM study of a Si sample with n-type and p-typestaircase carrier profile: (a)–(c) ‘sMIM-C’ capacitance image slices atselected sample biases; (d)–(f) eleven spectral sets of force, sMIM-R
and sMIM-C, respectively, collected at user-selected positions
marked on (b); (g) slice image representing the sMIM-C signal vssample bias and X position at a fixed Y location.

and regions in the sample. This is seen in the sMIM-C
data in Figure 10a-c. The negative bias in Figure 10a drives
the p-type regions into depletion regime, enhancing theircontrast. The n-type regions are in the inversion regime,
depressing their contrast, while the positive bias in
Figure 10c has the opposite effect. Figure 10g combines
this information in a single spatio-spectral slice.
DCUBE-sMIM provides valuable nanoelectrical information
not only during the surface hold time, but also during
the “approach” and “retract” processes. This is seenin Figure 10d-f, which are spectra taken at the locations
marked by X in Figure 10b. First, during the hold time,
the sMIM-C signals in Figure 10e show a gradual change
in slope with carrier density. Most curves were takenin the p-type region. At negative bias, the sample is in
the accumulation regime, causing equally high sMIM-C
signal, which then drops as the bias turns positive andthe sample goes into depletion. The signal drops further
for lower doped regions. Second, Figure 10e and 10f also
capture the sMIM signals before the probe touches andbefore bias is applied, thus automatically capturing the
distance dependence.
Fitting of the sMIM-C versus distance spectra allows
extraction of tip-shape information. One can easily extract
the capacitance image at a given, fixed height above thesample. This image represents the “background” or stray
capacitance, and can be subtracted from all capacitancedata to remove background effects. This enhances thesMIM-C data, removes any stray capacitance effects, andprovides a path for quantification of the sMIM-C data.

Detailed analysis and comparison of the sMIM signal during
the “extend” and “retract” period also provides additional
information. For example, asymmetric behaviors indicate achange of the sample surface after the dwell time.
Maghemite (γ-Fe2O3)
Figure 11 is an example of a DCUBE-sMIM study on a
γ-Fe2O3 sample, where the electrical conditions were
held constantly during the measurement and the sMIM
signals were measured over time during the dwell period.
Figure 11a shows γ-Fe2O3 spindle-like nanoparticles(100x500 nm in size) deposited into a continuous film.
The corresponding adhesion map extracted from eachforce ramping cycle is shown in Figure 11b. This sample
A

C

B

D

E

Figure 11. DCUBE-sMIM study of a γ-Fe2O3 sample: (a) surface
topography; (b) quantitative adhesion map; (c) a slice of sMIM-C fromthe DCUBE results; (d) a slice of sMIM-R from the DCUBE results.

has conductivity inhomogeneity across the surface,and has been used as a reference sample in conductive
AFM modes as already illustrated in Figures 3 and 4.
The local impedance of the sample varies across the
sample surface and shows contrast on both the sMIM-C
and sMIM-R channels, as shown in Figures 11c and 11d.
Figure 11e shows sMIM-C spectra at locations withdifferent dielectric constants. As the probe approaches thesurface, the sMIM-C signal shows the expected increase.
Upon the snap-in contact at ~8 ms, the sMIM-C signal
abruptly increases. Following this, as the force increases
or tip indents into the sample for <1 ms, the tip-sample
interaction interface area increases, resulting in further
signal increase. During the dwell period, the sMIM signals
are detected for 50 ms, while all electrical conditions are9

kept unchanged, allowing one to average over a relatively
long period, achieving excellent signal/noise ratios inthe sMIM maps.

Case Study: DataCube Piezoresponse (Piezoforce)
Microscopy (DCUBE-PFM) on Piezoelectric Films
Piezoresponsive materials are substances that
undergo mechanical deformation in response to an
applied voltage. The properties of piezoresponsive
materials make them useful in a wide range of areas,from microelectromechanical systems (MEMS) tobiosensors. Ferroelectric materials are a subset of
piezoelectrics that have particularly advantageous
functional properties. As process control improves andfabrication of small volume ferroelectrics becomes morecommon, researchers have discovered that the physicalcharacteristics of these materials change as they shrink.
PFM enables high-resolution nanoscale characterizationof piezoresponsive materials and topographical imaging.
PFM is a contact AFM technique to measure sample
displacement in response to an applied AC bias. The
resulting cantilever deflection of the probe in contact
with the sample is detected then demodulated by use of
a lock-in amplifier, such that topography and ferroelectricdomains can be imaged simultaneously with highresolution. PFM has also been widely used for domain
writing and ferroelectric switching studies.33-35 Integration
with the data cube technique, DCUBE-PFM enables
simultaneous acquisition of nanomechanical mapping and
PFM amplitude/phase spectra in every pixel, revealing theswitching behavior of each individual domain in a single data
set. In addition, DCUBE-PFM overcomes artifacts, sample
damage, and complexity of data analysis associated withthe conventional contact mode based approach.
Figure 12 shows an example of DCUBE-PFM studies ofa BiFeO3 (BFO) piezoelectric film. In this experiment, thesample voltage is ramped from -6 V to 0 V during the dwell
period while collecting the PFM amplitude and phasesignals. Figure 12a shows the surface topography; a flat filmwith roughness of 0.37 nm. A PFM amplitude slice at -4.5 V
B

A

C

D

F

E

Figure 12. DCUBE-PFM studies of a BiFeO3 (BFO) piezoelectric film:(a) height; (b) PFM amplitude image; and (c) 50 of the selected 110
spectra along a 1.2 µm long line as indicated in (a) and (b), crossing
multiple domains in a BFO ferro-electric sample; (d) and (e) plots of
those 110 spectra show both PFM amplitude and PFM phase vs.
bias during a ramp from -6 V to 0 V; (f) map of switching voltages
extracted from the data cube.

differentiates different piezoelectric domains (Figure 12b).
Figure 12c shows the first 50 of the selected 110 spectra
along a 1.2 µm long line, as indicated by the white dashedlines in Figure 12a and 12b, crossing multiple domains
in this BFO ferroelectric sample. These spectra indicate
distinct switching voltages among different domains
as the minimum of each spectrum spreads from about-5.0 V to -2.0 V on Figure 12c. These switching voltages
can be extracted for each individual domain by the analysisof the spectra. Figure 12d and 12e are color plots of those
110 amplitude and phase spectra, respectively. The abruptchanges in color along the voltage (vertical) direction
show the locations of the switching voltages. Further
analysis of the data cube enables the extraction of theswitching voltage at every pixel. These switching voltages
can be plotted in a new map (Figure 12f) that showsthat heterogeneous piezoelectric properties are present
between domains and also within some single domains.

Figure 13 presents the same data cube results in a different
format. Figure 13a and 13b respectively show two set of
amplitude and phase spectra from two domains. Sample
biases for the minimum of the amplitude spectra or the riseof the phase spectra indicate the switching voltages for thecorresponding pixel on the XY plane. Figure 14c and 14dshow the amplitude and phase data cubes, respectively.19
The horizontal directions, X and Y, correspond to the scan
area of the sample, which is 1x1 µm2. The vertical direction,Z, from bottom to the top, is following the time of the holdsegment while the sample bias was linearly applied from
-6 V to 0 V. The size of this cube is 128x128x833 pixels. The
four horizontal planes correspond to the slices of amplitude
or phase at different sample biases. To better show thedomain boundaries, the middle slice in the phase cube
is shown as a set of contours over the range of values
appearing at this bias. The two vertical slices along the XZ
direction represent amplitude or phase changing over the

C

D

A

B

E

F

G

H

I

J

K

L

M

N

Figure 13. DCUBE-PFM studies of a BiFeO3 (BFO) piezoelectric film: (a) two sets of amplitude spectra from two different domains inside thered circles in (f) and (h); (b) corresponding phase spectra to those in (a); (c) and (d) are cubes of the amplitude and phase data, respectively. X
and Y correspond to the 1 µm x 1 µm scan area. The vertical direction, Z, from bottom to the top, is the sample bias from -6 V to 0 V. The cube
color represents the amplitude or phase in the cube space, i.e., the measured PFM signal at a specific XY location and applied bias. The cube
size is 128x128x833 (or 1x1 µm2 x 6 V). The four horizontal planes correspond to the slices of amplitude or phase at different sample bias. The
middle slice in the phase cube is shown as a set of contours over the range of values appearing at this bias. The two vertical slices along the
XZ direction represent amplitude or phase changing over the sample bias (Z direction) along two line positions in the XY plane. (e)-(i) are slices
of amplitude at different sample bias; and (j)-(n) are slices of phase at different sample bias.

10

sample bias (Z direction) along two line positions in the
XY plane. Figure 13e-13i are slices of amplitude at different
sample bias, extracted from data cube.

resonance frequency and quality factor can be extractedwith a real-time fit of the spectrum, and can be calculated
into loss modulus, storage modulus, and loss tangent
when applying the proper mechanical model;

Case Study: DCUBE – Contact Resonance (CR) PFM
on a LiTAO3 Sampleadhesion, stiffness and modulus are extracted out of theforce-distance spectrum; andIn PFM, the applied AC bias of a certain frequency results
in a periodic AC deformation of the sample surface atthe same frequency. Operation at or near the contact
resonance has been exploited in PFM to provide enhanced
piezoelectric response signal.36,37 For a single-frequency
PFM measurement, the implementation of this technique islimited, as the contact resonance shifts with the nature of
the tip-sample contact as well as with the sample material
properties. DCUBE-CR PFM overcomes this challenge,
where during the dwell duration the frequency is swept
to collect a complete contact resonance spectrum. Thishybrid mode inherits all advantages from the FASTForce
Volume Contact Resonance mode (FFV-CR) developed forcharacterization of viscoelastic mechanical properties5:

piezoelectric properties can be extracted out of thephase and amplitude signals, in particular at theresonance frequency.

Figure 14a to 14c shows some typical DCUBE-CR PFM
force ramping, PFM phase, and PFM amplitude spectraof a LiTaO3 (LTO) sample. In this measurement, thefrequency was ramped from 250 to 400 kHz in every pixel
during a 100 ms dwell period. Figure 15d and 15e shows
the phase and amplitude data cubes, respectively.19 The
size and the space pixel density of these two cubes are
3x3 µm2 x 150 kHz and 256x256x260. The horizontal planes
show phase (Figure 14d) or amplitude (Figure 14e) maps at
specific frequencies, where different piezoelectric domains
are well differentiated at and near contact resonance.
Vertical planes are phase (Figure 14d) or amplitude(Figure 14e) changing with the sweep frequency, whichfrequency sweeps can be performed over a broad range(up to 5 MHz) enabling observation and tracking ofmultiple eigenmodes at once;

D

E

A

B

C

F

G

H

I

J

Figure 14. DCUBE-CR PFM studies on a LiTaO3 sample: (a)-(c) typical DCUBE-CR PFM force ramping, PFM phase, and PFM amplitude
spectra, respectively, frequency swept from 250 to 400 kHz during the 100 ms dwell period; (d)-(e) visualization of the phase and amplitude
data cubes, respectively, where XY are the scan area and z is the frequency sweep. Size is 3x3 µm2 x 150 kHz, and the pixel density is
256x256x260. Horizontal planes show phase or amplitude maps at specific frequencies. Vertical planes are phase or amplitude changing overthe sweep frequency. (f) Surface topography, at scan 1x1 µm2 scan size; (g) number of valid solutions found for the characteristic equationfrom which stiffness and damping are determined; (h)-(i) maps of contract resonance frequency, amplitude, and quality factor found uponfitting the hold sweep spectra.
11

demonstrates shifts in the contact resonance frequency
between different domains. Figure 14f-14j shows the
DCUBE-CR PFM data on the same LiTaO3 sample witha smaller scan size of 1x1 µm2. Figure 14f is the surface
topography with a roughness (Rq) of ~1.5 nm. Figure 14g
shows the number of peak that the algorithm foundduring the fitting. At the domain boundaries and in somecontaminant positions, this signal becomes zero indicatingthat the material does not show piezoelectric response. The“CR Frequency,” “CR Amplitude,” and “CR Q” channels in(h)-(i) are maps of contact resonance frequency, amplitude,and quality factor found upon fitting the hold sweep
spectra. This example demonstrates that DCUBE-PFM
in conjunction with contact resonance provides the full
benefits of DCUBE-PFM with the added benefits ofproviding a frequency ramp at every pixel, providing a full
spectrum and the peak sensitivity at the contact resonance.

between electrical and mechanical properties; eliminationof contact mode, resulting in longer tip lifetime, and thecapability to measure soft and fragile samples; and mappingof new nanoelectrical properties, such as schottky barrierheight, flatband voltages, piezoelectric switching voltages,
etc. Finally, each individual nanoelectrical mode is improved
with the DataCube approach, including, for example, thecapability to measure and subtract background capacitancecontributions in sMIM and PFM data acquisition at thehighest sensitivity using a contact resonance approach.

Authors
P. De Wolfa, Z. Huangb, B. Pittengerc, A. Dujardina,b, M. Febvrea,
D. Mariollec, N. Chevalierca.

Bruker Nano Surfaces, 112 Robin Hill Road, Santa
Barbara, CA 93117, USAb.

Cellular Microbiology and Physics of Infection Group– Lille Centre for Infection and Immunity, CNRS
UMR8204, INSERM U1019, Lille Regional Hospital
University Centre, University of Lille, Institut Pasteur deLille, F-59021 Lille, Francec.

Univ. Grenoble Alpes, CEA, LETI, 3800 Grenoble, France

Conclusions
DCUBE-based nanoelectrical modes represent a general big
data approach with the potential to provide new information
in a wide range of applications, especially on samples withhigh complexity. Extracting image slices, spatio-spectral
slices, or spectra at every pixel opens the door to reveal
sample properties that are either not accessible or are
easily missed in conventional nanoelectrical modes, whereimages at only one or a few discrete settings are acquired.
Table 2 shows the favorable comparison of DCUBE modes
to contact and PeakForce Tapping modes.

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Pittenger, B., Erina, N. and Su, C., “Quantitative
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2.

Pittenger, B. and Yablon, D. G., “Improving the
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Contact Mode

PeakForce Tapping

DataCube

Challenging on
soft and fragile
sampleAll samples

All samples

Correlation to
Mechanical properties

No

Integrated

Integrated

High dimensional
electrical data (= atdifferent electricalsettings)

No

No

Yes

Maps of new electricalproperties (flat-band
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No

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Slightly slower

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Tip lifetime

Limited on
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Excellent

Excellent

Samples

Table 2. DCUBE-based electrical modes are compared to contact
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13

©2019 Bruker Corporation. FASTForce Volume, NanoScope, PeakForce QNM, PeakForce Tapping, and PeakForce TUNA are trademarks of Bruker Corporation. All other trademarks are

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Santa Barbara, CA · USA
phone +1.805.767.1400
productinfo@bruker.com

www.bruker.com/nanothe property of their respective companies. All other trademarks are the property of their respective companies. All rights reserved. AN152, Rev. A0.

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