1. technology and computing

Nano Research
Nano Res
DOI 10.1007/s12274-015-0729-7
Tunable diameter electrostatically-formed nanowire for
high sensitivity gas sensing
Alex Henning1, Nandhini Swaminathan1 , Andrey Godkin1, Gil Shalev1, Iddo Amit1, and Yossi Rosenwaks 1 ()
Nano Res., Just Accepted Manuscript • DOI 10.1007/s12274-015-0729-7
http://www.thenanoresearch.com on January 28, 2015
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1
TABLE OF CONTENTS (TOC)
Tunable Diameter Electrostatically-formed Nanowire
for High Sensitivity Gas Sensing
Alex Henning, Nandhini Swaminathan, Andrey Godkin,
Gil Shalev, Iddo Amit, and Yossi Rosenwaks*
Department of Physical Electronics, School of Electrical
Engineering, Tel-Aviv University, Ramat-Aviv 69978,
Israel
Page Numbers. The font is
ArialMT 16 (automatically
inserted by the publisher)
Tunable diameter electrostatically-formed nanowire towards a
highly sensitive and robust room temperature gas sensing
device.
1
Nano Res
DOI (automatically inserted by the publisher)
Research Article
Tunable Diameter Electrostatically-formed Nanowire for High
Sensitivity Gas Sensing
Alex Henning1, Nandhini Swaminathan1, Andrey Godkin1, Gil Shalev1, Iddo Amit1, and Yossi Rosenwaks1 ()
1 Department
of Physical Electronics, School of Electrical Engineering, Tel-Aviv University, Ramat-Aviv 69978, Israel
Received: day month year / Revised: day month year / Accepted: day month year (automatically inserted by the publisher)
© Tsinghua University Press and Springer-Verlag Berlin Heidelberg 2011
ABSTRACT
We report on an electrostatically-formed nanowire (EFN) based sensor with tunable diameters in the range of
16 nm to 46 nm and demonstrate an EFN based field-effect transistor as a highly sensitive and robust room
temperature gas sensor. The device was carefully designed and fabricated using standard
integrated-processing to achieve the 16 nm EFN and used for sensing without any surface modification. The
EFN effective diameter was determined using Kelvin probe force microscopy accompanied by
three-dimensional electrostatic simulations. We show that the EFN transistor is capable of detecting 100 parts
per million of ethanol gas with bare SiO2.
KEYWORDS
Gas Sensing, Silicon Nanowires, KPFM, Electrostatic confinement, Multiple gate transistor
Introduction
Field-effect
transistors
(FETs)
based
on
one-dimensional nanostructured materials have
emerged as most promising candidates for miniature
chemical sensors in comparison to the planar FETs
[1]. In particular, Silicon Nanowire (SiNW) based
FETs were demonstrated as highly sensitive and
selective chemical sensors operating at room
temperature (RT) [2–5]. Single crystalline SiNWs are
fabricated via bottom-up or top-down methods with
uniform spatial dimensions and high carrier mobility
[6–11]. Predominantly, FETs based on arrays of
SiNWs, usually modified with molecular groups,
have been reported to be highly sensitive and
selective to volatile organic compounds (VOCs)
[2,4,12–18]. Due to the high surface-to-volume ratio
of Si NWs, surface states have a large impact on the
device performance and often require surface
passivation. Although the top-down approach has
less
severe
integration
issues
with
the
complementary metal-oxide-semiconductor (CMOS)
technology compared to chemically grown NWs
————————————
Address correspondence to Yossi Rosenwaks, Yossir@eng.tau.ac.il
2
[19,20], it involves the
lithographic techniques.
use
of
sophisticated
We present a robust electrostatically-formed
nanowire (EFN) based sensor whose tunable
nanowire diameter was determined by Kelvin probe
force microscopy (KPFM) measurements supported
by three-dimensional (3-D) electrostatic simulations.
Detection of ethanol gas has been used as an
example to demonstrate the application of the EFN
device as a gas sensor. The detection sensitivity
increases by a factor of 27 as the EFN effective
diameter is reduced from 46 nm to 16 nm. We show
that the 16 nm EFN device is capable of detecting
ethanol down to a concentration of 100 parts per
million (ppm), which is among the lowest reported
values for nanostructured gas sensors without
surface modification. Paska et al. demonstrated a
limit-of-detection (LOD) of 60 ppm for ethanol using
SiNW FETs with an organic surface modification [16].
Wu et al. showed 40 ppm LOD for ethanol with
Sb-doped SnO2 NWs at RT [21]. Recently, Chu et al.
demonstrated a 0.5 ppm detection limit for ethanol at
RT using NW FETs modified with iron porphyrin
attached to organic linker molecules [5]. Carbon
nanotube (CNT) based FETs are also used as highly
sensitive devices. Someya et al. showed an LOD of
about 1300 ppm for ethanol with bare CNT based
sensors [22]. Mirica et al. demonstrated response to
700 ppm of ethanol with CNT based sensors at RT
modified with various selectors [23]. Liang et al. used
CNTs coated with a thin SnO2 layer to detect ethanol
down to 10 ppm with a sensitivity of 1.8 [24]. Chen et
al. achieved a high sensitivity for 10 ppm of ethanol
at RT for 1-D core/shell nanostructures (CNT/SnO2)
[25].
The EFN device was fabricated using standard
CMOS processing and demonstrates higher
signal-to-noise ratio compared to the conventional
NW based FETs. The EFN concept was first
introduced by Shalev et al. in 2013 [26], who
demonstrated a surface modified EFN (25 nm in
width) based biosensor for the detection of
femtomolar protein concentrations. Basically, the
EFN is a nanowire-like conducting channel that is
tuned to the nanometer size electrostatically post
fabrication by appropriate gate biasing. The EFN
device resembles the silicon-on-insulator (SOI)
four-gate field-effect transistor (G4-FET), developed
in 2002 [27,28] that emerged from the volume
inversion SOI MOSFET [29].
Results and discussion
EFN
FORMATION
AND
ELECTRICAL
CHARACTERIZATION. The EFN device (Fig. 1 a) is
composed of a doped silicon region surrounded by
four gates, a back gate (biased with V BG), two lateral
junction gates (biased with V JG1 and V JG2) and a top
dielectric that functions as a molecular gate. The
electron accumulated channel between the source
and drain is confined to a nanowire by appropriate
biasing of V JG1, V JG2 and V BG. The active area is
passivated with 6 nm thick thermal SiO2 that can be
activated and modified for enhanced analyte
adsorption with a self-assembled monolayer. The
thickness and purity of the top oxide (SiO2) layer are
important parameters for FET based sensors. The
EFN device is a field-effect device where variations
of the drain current with respect to the surface
potential, Φs, define the gain, g s = dID/dΦs =
(W/L)Ctox µeVD, where W and L are the respective
width and length of the channel, Ctox is the top oxide
layer capacitance and µe is the electron mobility.
Therefore, a thinner gate dielectric results in greater
Ctox and thus a higher gain.
The cross-section along the short axis of the device
(Fig. 1 b) depicts a scheme for the electron
accumulated EFN channel (dark blue). Various
nanowire configurations, each with a particular
shape and effective diameter of the cross-sectional
area are obtained with appropriate biasing of the
surrounding gates. No nanometer features are
defined during the fabrication, and the nanometer
scaling of the EFN device is performed
electrostatically post fabrication.
3
Figure 1 Schematic illustration of an EFN device. (a) Different contact regions and the channel region are defined by specific doping
implants, assigned with n+, n and p+. A thermal SiO2 layer with a thickness of 6 nm covers the active sensing area. The EFN device is
biased according to the electrical circuit. (b) Schematic cross-section along the y-axis of the device showing one possible configuration
of the electrostatically shaped nanowire with a volatile organic compound (ethanol) bound to the active area of the device.
Figure 2 (a) depicts a top scanning electron
microscopy (SEM) image of the EFN device
including the contact regions of source, drain and
junction gates. The contact regions were designed
large enough to be contacted with microprobes.
Figure 2 (b) is a high magnification SEM image of the
n-doped path in the center of the device. The
nanowire is formed inside this ≈ 650 nm wide
n-doped area, located in-between the two p-doped
regions that appear bright in the SEM contrast. The
distance between the two p-doped regions is the
critical (spatial) dimension for the photolithography
masks. Secondary electrons are sensitive to the
surface dopant distributions providing a few
nanometers lateral resolution [30] and allowed us to
determine the width of the n-type doped region from
the measured image (Fig. 2 b). The atomic force
microscopy (AFM) topographic profile of the SiO2
surface within the 100 µ m2 sensing area (Fig. 2 c top)
reveals a root mean square roughness of below 1 nm.
The electron conductive channel is formed inside the
n-doped silicon below the gate oxide.
Figure 2 Scanning electron microscopy image of (a) a full EFN device with contact areas and (b) the active area in the center of the
device where the EFN is located. In this square window the 6 nm thick gate dielectric is directly exposed to the analytes while the
surrounding is passivated with a ≈ 40 nm thick dielectric layer. The ≈ 650 nm wide n-doped region appears darker in the SEM image
and corresponds to the distance between the metallurgical junctions of the p-n-p structure. (c) Measured AFM topography (red line) is
added on top of a schematic depth profile of the active area in the square window.
4
The complete EFN device process was simulated
with a 3-D device simulator (Synopsys TCAD
Sentaurus, Mountain View, CA, USA) taking into
account all the fabrication processes including the
actual ion implantations and thermal annealing steps.
For each of the simulation mesh points, the Poisson
and continuity equations are numerically solved.
Electron acceptor and donor type interface trap
states located at the gate-silicon interfaces with a
concentration of 1 × 10 12 cm−2 were taken into account,
whereas the contact resistances and the ambient air
were neglected in the simulations.
Figure 3 (a) shows the measured (black squares) and
simulated (red circles) drain current, and the
extracted effective diameter, De ff, (blue triangles) as a
function of the side gate voltages, ID−V JG12, where
V JG12 = V JG1 = V JG2. De ff of the EFN channel is defined
as the full width at half maximum (FWHM) of the
electron density distribution, ρ(r), within the
n-doped Si across the p-n-p junction (Fig. 3 b) and
was obtained by comparing the measured and
simulated I−V characteristics (Fig. 3 a). By gradually
applying more negative bias, V JG12, on both side gates,
the drain current, ID, of the electron accumulated
channel formed between source and drain is reduced
and its De ff decreased (Fig. 3 a).
Figure 3 The EFN effective diameter, Deff, is reduced to a few nanometers by reversed junction gate biasing. (a) Simulated and
measured drain current-side gate bias (ID − VJG12) characteristics for the EFN is shown in a semi-logarithmic plot. Deff was estimated
from 3-D electrostatic simulations. (b) The electron density distributions across the EFN correspond to 3 possible configurations and are
extracted from 3-D simulations. (c) Measured drain current-drain voltage (ID − VD) characteristics are depicted in a semi-logarithmic
plot; the dashed line represents the pinch-off voltage, VP . It is evident that the EFN transistor on/off ratio, ION/IOFF, is about 1 ×106.
Below V JG12 ≈ −1.2 V, the current sharply decreases
as the depletion regions span the entire conduction
channel leaving a small electron accumulation
region. De ff of the EFN cross-sectional area is found
to be 46 nm for V JG12 = 0 V and 16 nm for V JG12 = −1.6
V. For V JG12 < −1.6 V, the electron density in the EFN
drops below 3 × 10 15 cm−3 which corresponds to the
detection limit of our measurement system. With
more negative side gate voltages (V JG12 < −1.6 V) the
electron-accumulated channel is pushed towards the
device surface. In this case, the circular EFN shape
turns to be elliptical maintaining a constant De ff of 16
nm, which corresponds to the transverse diameter of
the elliptical cross-sectional area. We define the EFN
as fully depleted when the electron density inside
the channel drops by two orders of magnitude, from
3 × 10 17 cm−3 to 3 × 10 15 cm−3 with a corresponding
current below the detection limit ( ≈ 5 pA).
Accordingly, the EFN is fully depleted below V JG12
≈ −1.6 V corresponding to De ff ≈ 16 nm as evident
from Figure 3 (a). Pinch-off occurs due to the tapered
shape of the electron-conducting path, which is a
consequence of the drain-source potential drop along
the channel. In a regular junction gate FET, the
pinch-off voltage, VP , is the applied drain-source
voltage for a certain gate voltage at which the drain
current saturates. In the EFN device, V P is the
source-drain voltage V D, for a particular V JG12 at
which ID saturates because the two depletion regions
from both sides of the channel are crossing each
other as shown in the CPD measurement of an EFN
device under operation (Fig. 4a, V JG12 = -1 V).
5
Depending on V JG12, the pinch-off voltage (indicated
by dashed line Fig. 3 c) is in the range of V D = 0.1 to
0.8 V. It is evident from the ID-V D characteristics that
the transistor operates in the linear Ohmic regime for
V D below V P while for V D above VP , the transistor
operates in the saturation regime and its current is
nearly constant.
4 b, V JG12 = −2 V) the measured current also drops to
zero (Fig. 3 a). At V JG12 = 0 V, the current linearly
increases as a function of V D (Fig. 3 c) and the
nanowire can be treated as a cone-shaped and
uniformly doped conductor. The cross-sectional area,
A, and resulting De ff are estimated using Ohm’s law
(Eq. 1) [33]:
KELVIN PROBE FORCE MICROSCOPY OF AN
EFN DEVICE. KPFM measures the contact potential
difference (CPD) between the AFM tip and a sample
with nanometer spatial resolution and meV
sensitivity [31,32] where the CPD is a direct measure
of the sample Fermi level energy. Figure 4 (a)
represents the CPD images of an EFN under
operation for three different biasing configurations:
V JG12 = 0 V, −1 V and −2 V at V D = 1 V and V BG = 0 V.
The extracted CPD profiles along the EFN channel
(Fig. 4 b) from source to drain (indicated by the
dashed arrow) emphasize the effect of a more
negative V JG12: a CPD increase in the conductive
channel indicates a larger potential barrier between
the source and drain. For negative V JG12, the
conductive channel is more depleted of electrons and
therefore the measured CPD is higher (more p-type).
At V JG12 = −2 V the EFN is fully depleted and the
depletion regions on either side of the EFN overlap
(Fig. 4 a). As the energy barrier between the source
and drain of a depleted EFN becomes too large (Fig.
J = q µe n(x) ·d|CPD|/dx
(1)
J = ID/A is the current density, Ex = d|CPD|/dx is the
local electric field, n(x) is the free carrier density
inside the EFN, µ e is the electron mobility and q is
the elementary charge. By differentiating the
measured CPD profile along the EFN, Ex is obtained.
The doping density was measured by time-of-flight
secondary ion mass spectrometry (TOF-SIMS) and
equals n = 4.0 ± 0.2 × 10 17 cm−3 which corresponds to
µ e = (430 ± 10) cm2/Vs. ID was measured during each
CPD measurement. Hence, all parameters except
from A are known and the diameter was calculated
along the EFN axis (Fig. 4 c). The error bars result
from the measurement uncertainties for doping
density, mobility, and CPD (± 5 mV). Due to the
source-drain potential difference that causes
pinch-off, the diameter decreases along the nanowire
axis resembling a cone-like shape as schematically
shown in Figure 4 c.
6
Figure 4 (a) CPD images of the EFN active area and (b) CPD profiles along the EFN channel from source to drain for three different
cases: undepleted, partially depleted and fully depleted. VBG was maintained at 0 V. (c) The EFN diameter in axial direction along the
nanowire was extracted from the measured CPD profile at V JG12 = 0 V.
In order to demonstrate the reliability of this method
to estimate the diameter, we have characterized an
EFN device with a larger channel. Figure 5 (a) shows
the ID-V D characteristics of the large EFN for four
different side gate voltages, V JG12 = 0 V, -0.5 V, -1 V
and -1.5 V. Compared with the I-V characteristics of
the narrow EFN device (Fig. 3 c), the saturation (at
VP ) is reached for higher source-drain-voltages. De ff
was determined for four side gate voltages while
applying a constant drain bias (V D = 0.5 V) indicated
by the red circles in Figure 5 (a). The effective width
was calculated from the CPD profiles from source to
drain along the NW (Fig. 5 b) by using the slopes of
the CPD profiles between 2 and 3 µ m in Eq. 1. In this
manner, the values of De ff are equal to 105 nm, 85 nm,
67 nm and 40 nm for V JG12 = 0 V, -0.5 V, -1 V, -1.5 V,
respectively.
Figure 5 (a) ID-VD characteristics for a large channel EFN device for 4 different side gate voltages and corresponding (b) CPD profiles
along the EFN channel from source to drain at VD = 0.5 V and VBG = 0 V.
ETHANOL VAPOR SENSING WITH AN EFN
DEVICE. The sensitivity of the EFN device for
ethanol detection is quantified through the drain
current change here defined as ∆I/I0 = (I0 - Ie th)/I0,
where I0 and Ie th are the drain currents in pure
nitrogen and ethanol with nitrogen as carrier gas,
respectively. Figure 6 (a) shows the sensitivity of the
device as a function of ethanol concentrations for
side gate voltages, V JG12 = 0 V, −0.9 V, −1.2 V and −1.5
V and a back gate voltage of V BG = −6 V. These side
gate voltages correspond to an effective EFN
diameter varied from 46 nm to 16 nm, as represented
by the schematic NW cross-sections to the right of
Figure 6 (a).
7
Figure 6 Sensitivity plot as a function of ethanol concentration in ppm range at VBG = −6 V and VD = 1 V. Different curves correspond
to VJG12 = 0 V, −0.9 V, −1.2 V and −1.5 V each voltage is equivalent to a different effective diameter represented by the semi-spherical
cross-sections on the right. The Inset shows the logarithmic plot of the ID−VBG characteristics for different V JG12. Dotted curves
correspond to the N2 atmosphere and the solid curves correspond to 1100 ppm ethanol exposure on the EFN device. (b) The plot of the
drain current as a function of the ethanol concentration shows a linear behavior within the measurement uncertainties.
The sensitivity increases with the concentration for
all curves (for each V JG12). Furthermore, at each
concentration, the sensitivity increases with
decreasing V JG12 corresponding to a narrower
channel. It is evident from Figure 6 (a) that the EFN
device is sensitive to ethanol concentrations as low as
100 ppm when V JG12 < −0.9 V and V BG = −6 V. Figure 6
(b) shows the sensor response as a function of the
ethanol concentration for the narrowest EFN (16 nm)
showing a linear behavior. The error bars result from
the device noise current and uncertainty of the
adjusted ethanol vapor concentration. The EFN
device can be reused following mild heating after
which the ethanol molecules are desorbed. Figure 7
shows the drain current - backgate characteristics
(ID-V BG) for three different cases: before sensing,
after
sensing
and
after
heating.
Figure 7 Drain current - backgate characteristics (ID-VBG) for the
EFN device before (green triangles) and after long-term exposure
to 1000 ppm of ethanol (black squares), and after regeneration
(red circles), achieved by heating to 70 °C.
The surface charge density can be estimated by using
the basic relation of the threshold voltage shift, ∆V th =
− (QSS tbox)/(ε0εox), for a standard MOS capacitor
where QSS is the surface charge density, tbox is the
back oxide layer thickness, ε0 is the vacuum
permittivity and εox is the relative dielectric constant
[34]. The measured threshold-voltage shift, ∆V th = 2.1
V, following ethanol adsorption (exposure to 1000
ppm), corresponds to QSS = 2.5 × 10 11 cm-2. Figure 8
shows the transconductance, gm, and sensitivity as a
function of V JG12 obtained in the following two cases:
(a) measurements with the EFN device at 1100 ppm
ethanol exposure (b) simulation for 10 trapped
electrons fixed on top (center) of the EFN channel
surface representing a charged analyte molecule. In
this work, gm is calculated as: ∂ID/∂V BG| VD=1V. As a
consequence of the narrower channel due to more
negative side gate voltages, the absolute change in ID
becomes smaller. Hence, gm decreases with higher
reversed side gate voltages (Fig. 8).
8
voltage where the transconductance curve is peaked.
But this is not the case for the EFN device; here, the
enhanced sensitivity is a direct result of the vertical
and lateral size and shape of the channel tuned by
appropriate biasing of V BG and V JG12, respectively.
Conclusions
Figure 8 Transconductance and logarithmic plot of sensitivity as
a function of Deff controlled with reversed gate voltages V JG12 for
VD = 1 V and VBG = 2.8 V and 10.8 V for (a) experimental
results of the EFN sensing towards 1100 ppm ethanol and (b)
simulated results for 10 electrons placed in the center of the
EFN.
Comparing the measurements with simulations, it is
observed that the influence of the adsorbed ethanol
molecules on the EFN characteristics is equivalent to
that of the localized negative charges at the channel
center. The negative surface charge causes electron
depletion in the EFN hence reducing the drain
current. The order of magnitude difference in the
y-axis of Figure 8 (a) and Figure 8 (b) is due to two
reasons: First, the surrounding medium for the
EFN in the simulations is vacuum while in
experiments, it is nitrogen; Secondly, trapped oxide
charges in the top dielectric screen the electric field
and were not taken into account in the simulations.
The increase in the sensitivity with smaller De ff (more
negative V JG12) can be explained by the influence of
the adsorbed ethanol molecules on the electron
density distribution of the EFN (Fig. 3 b). Adsorbed
molecules modify the surface charge distribution
and consequently induce a change in the surface
potential; the smaller the EFN, the more it is affected
by such a surface potential change. Hence, the
increase in the sensitivity is a direct result of a
smaller conducting channel when V JG12 is decreased.
In addition, Figure 8 indicates that while sensitivity
is high for more negative values of V JG12, gm is
maximal at 0 V. Typically, the sensitivity of a
FET-type sensor strongly depends on gm of the
transistor. The device is most sensitive for the gate
In summary, we have demonstrated an
electrostatically formed nanowire with a tunable
effective width down to 16 nm. The electrical
properties of the device and the nanowire channel
dimensions were simulated using a 3-D electrostatic
simulator and were found to be in excellent
agreement with KPFM and I − V measurements. The
device was capable of detecting 100 ppm of ethanol
vapor with a bare SiO2 surface. The EFN device
being a low-cost (CMOS-compatible), robust and
highly sensitive gas sensor, paves the way for future
ultra-compact electronic devices. Work is in progress
to achieve selectivity and increase the device
sensitivity by surface modifications, using EFN
arrays and signal processing.
Materials and Methods
EFN DEVICE FABRICATION. The EFN transistors
were fabricated by a semiconductor foundry
(TowerJazz, Israel - Migdal Haemek) in a CMOS
process with 4 masks to implant the different dopant
regions for the channel, source-drain and junction
gate contacts. The actual doping densities, blanket
Arsenic of 4 × 10 17 cm−3, junction gate Boron of 2 ×
1020 cm−3 and source-drain Arsenic of 7 × 10 19 cm−3,
were determined post fabrication by time-of-flight
secondary ion mass spectrometry (TOF-SIMS). Boron
doped 8 inch SOI wafers with a doping density of 1.5
× 10 14 cm2 and an SOI thickness of 150 nm were used.
The thickness of the buried SiO2 is 1 µ m. The thermal
SiO2 gate dielectric was formed at 1200 °C. The
lowest spatial dimension in the process ((540 ± 20)
nm) was given by the distance between the two
metallurgical junctions within the active area.
Devices were diced to 1 cm2 squares and Ti/Au
contacts were manufactured by optical lithography
and subsequent metal evaporation.
ELECTROSTATIC DEVICE SIMULATIONS. A
three-dimensional (3-D) finite-element device
9
simulator (Synopsys TCAD Sentaurus, Mountain
View, CA, USA) was used in order to solve the
Poisson equation, and the hole and electron
continuity equations for each mesh. The measured
doping density depth profiles (TOF-SIMS) within the
silicon served as input for 3-D electrostatic
simulations. Drift-diffusion transport model together
with Boltzmann statistics were assumed throughout
the device and the Masetti model for
doping-dependent mobility was used in order to
account for impurity scattering [35]. Drain, source,
backgate and side gate contacts were defined and
forced the respective biasing as boundary conditions.
The material constants of silicon were taken from the
literature [36]. The source-drain current was
simulated for different configurations of backgate,
sidegate and drain voltages. For the qualitative
charge sensing, 10 elementary charges were placed
on top of the SiO2 gate dielectric in the lateral and
transversal center of the channel. The elementary
charges were placed inside an imaginary cube with
side dimensions of 10 nm. The charged cube should
emulate the effect of a big sized molecule. This
simplifies the problem as in reality molecules rather
represent dipoles.
ELECTRICAL CHARACTERIZATION AND GAS
SENSING. Current-voltage characteristics, both as a
function of drain electrode bias (ID−VD), backgate
electrode bias (ID−V BG) and junction gate electrodes
(ID−V JG12), were performed using semiconductor
parameters analyzer (B1500A, Agilent). Sensing of
volatile ethanol was done in a controlled nitrogen
(99.999 % purity) atmosphere in a sealed metallic gas
chamber connected to a gas dilution system.
Ethanol gas was generated in a bubbler system and
diluted with N2 and mass flow controllers. A
reference sensor (ppbRAE 3000, RAE Systems) was
connected to the gas chamber in order to verify the
analyte concentration inside the chamber down to
100 ppb level. Sensing was performed by measuring
and comparing the I−V characteristics with and
without different concentrations of ethanol. The EFN
device was cleaned and hydroxylated by the SC-1
treatment that involves immersion of the device in
NH4OH:H2O2:H2 O (1:1:5, v/v/v) at 70 °C for 10 min.
The device was then rinsed thoroughly in DI water
several times and blow dried with N2.
KELVIN
PROBE
FORCE
MICROSCOPY.
Amplitude modulation KPFM was carried out with a
commercial AFM (Dimension Edge, Bruker Inc.)
inside a nitrogen glove box with less than 1 ppm
H2O. The CPD was measured simultaneously with
the topographic signal at an effective tip sample
distance of 5 to 10 nm during scanning. The
topographic height was obtained by maintaining
the amplitude of the first cantilever resonance (f 1st ≈
75 kHz) at a predefined amplitude set point of
approximately 5 to 20 nm. The CPD was determined
by compensating the ac component of the
electrostatic force, FES, at angular frequency ω with
an applied dc voltage (= CPD) in a feedback control
loop. To separate topographic from CPD signal,
increase the sensitivity, and minimizing probe
convolution effects, the ac electrostatic force
component was generated at the second resonance
[37,38], f2nd ≈ 450 kHz, of the cantilever by applying
an ac voltage of about 500 mV. Highly conductive
cantilevers with Pt/Ir coating (PPP EFM,
Nanosensors) were used for KPFM.
TOF-SIMS. Doping depth profiles with a surface
sensitivity of 2 nm were obtained with a TOF-SIMS
instrument (2100 TRIFT II, PHI). Briefly, a pulsed
primary ion beam is used to desorb and ionize
species from a sample surface. The resulting
secondary ions are accelerated into a mass
spectrometer, where they are mass analyzed by
measuring their time-of-flight from the sample
surface to the detector.
Acknowledgements
We are very grateful to Yakuv Roizin, Alexey
Heiman, Miriam Buchbinder and Noel Berkovitch
from TowerJazz for device fabrication and helpful
discussions. We acknowledge the ’Pearl of Wisdom’
foundation. AH acknowledges the support of the Tel
Aviv University Center for Nanoscience and Nanotechnology.
References
[1]
Zhou, K. B.; Wang, X.; Sun, X. M.; Peng, Q.; Li, Y. D.
Enhanced catalytic activity of ceria nanorods from well
defined reactive crystal planes. J. Catal. 2005, 229,
206–212.
[1]
Patolsky, F.; Lieber, C. M. Nanowire nanosensors. Mater.
Today 2005, 8, 20–28.
[2]
Cui, Y.; Wei, Q.; Park, H.; Lieber, C. M. Nanowire
10
nanosensors for highly sensitive and selective detection of
biological and chemical species. Science 2001, 293,
1289–1292.
[3]
[4]
[5]
[6]
[7]
[8]
[9]
Zheng, G.; Patolsky, F.; Cui, Y.; Wang, W. U.; Lieber, C. M.
Multiplexed electrical detection of cancer markers with
nanowire sensor arrays. Nat. Biotechnol. 2005, 23,
1294–1301.
Paska, Y.; Stelzner, T.; Christiansen, S.; Haick, H.
Enhanced sensing of nonpolar volatile organic compounds
by silicon nanowire field effect transistors. ACS nano 2011,
5, 5620–5626.
Chu, C. J.; Yeh, C. S.; Liao, C. K.; Tsai, L.-C.; Huang,
C.-M.; Lin, H.-Y.; Shyue, J.- J.; Chen, Y.-T.; Chen, C.-D.
Improving nanowire sensing capability by electrical field
alignment of surface probing molecules. Nano Lett. 2013,
13, 2564–2569.
Morales, A. M.; Lieber, C. M. A laser ablation method for
the synthesis of crystalline semiconductor nanowires.
Science 1998, 279, 208–211.
Cui, Y.; Zhong, Z.; Wang, D.; Wang, W. U.; Lieber, C. M.
High performance silicon nanowire field effect transistors.
Nano Lett. 2003, 3, 149–152.
Elibol, O.; Morisette, D.; Akin, D.; Denton, J.; Bashir, R.
Integrated nanoscale silicon sensors using top-down
fabrication. Appl. Phys. Lett. 2003, 83, 4613–4615.
Yang, C.; Zhong, Z.; Lieber, C. M. Encoding electronic
properties by synthesis of axial modulation-doped silicon
nanowires. Science 2005, 310, 1304–1307.
Ultraselective Detection in the Gas Phase. Nano Lett. 2014,
14, 933–938.
[19] Stern, E.; Klemic, J. F.; Routenberg, D. A.; Wyrembak, P.
N.; Turner-Evans, D. B.; Hamilton, A. D.; LaVan, D. A.;
Fahmy, T. M.; Reed, M. A. Label-free immunodetection
with CMOS-compatible semiconducting nanowires. Nature
2007, 445, 519–522.
[20] Park, I.; Li, Z.; Pisano, A. P.; Williams, R. S. Top-down
fabricated silicon nanowire sensors for real-time chemical
detection. Nanotechnology 2010, 21, 015501.
[21] Wu, J. M. A room temperature ethanol sensor made from
p-type Sb-doped SnO2 nanowires. Nanotechnology 2010,
21, 235501.
[22] Someya, T.; Small, J.; Kim, P.; Nuckolls, C.; Yardley, J. T.
Alcohol vapor sensors based on single-walled carbon
nanotube field effect transistors. Nano Lett. 2003, 3,
877–881.
[23] Mirica, K. A.; Azzarelli, J. M.; Weis, J. G.; Schnorr, J. M.;
Swager, T. M. Rapid prototyping of carbon-based
chemiresistive gas sensors on paper. Proc. Natl. Acad. Sci.
2013, 110, E3265–E3270.
[24] Liang, Y.; Chen, Y.; Wang, T. Low-resistance gas sensors
fabricated from multiwalled carbon nanotubes coated with
a thin tin oxide layer. Appl. Phys. Lett. 2004, 85, 666–668.
[25] Chen, Y.; Zhu, C.; Wang, T. The enhanced ethanol sensing
properties of multi-walled carbon nanotubes/SnO2
core/shell nanostructures. Nanotechnology 2006, 17, 3012.
[11] Schmidt, V.; Wittemann, J.; Gösele, U. Growth,
thermodynamics, and electrical properties of silicon
nanowires. Chem. Rev. 2010, 110, 361–388.
[26] Shalev, G.; Landman, G.; Amit, I.; Rosenwaks, Y.; Levy, I.
Specific and label-free femtomolar biomarker detection
with an electrostatically formed nanowire biosensor. NPG
Asia Mater. 2013, 5, e41.
[27] Cristoloveanu, S.; Blalock, B.; Allibert, F.; Dufrene, B.;
Mojarradi, M. The four-gate transistor. In Proceedings of
the European Solid-State Device Research Conference.
2002, pp 323–326.
[12] McAlpine, M. C.; Ahmad, H.; Wang, D.; Heath, J. R.
Highly ordered nanowire arrays on plastic substrates for
ultrasensitive flexible chemical sensors. Nat. Mater. 2007,
6, 379–384.
[28] Blalock, B. J.; Cristoloveanu, S.; Dufrene, B. M.; Allibert,
F.; Mojarradi, M. M. The multiple-gate MOS-JFET
transistor. Int. J. High Speed Electron. Syst. 2002, 12,
511–520.
[13] Engel, Y.; Elnathan, R.; Pevzner, A.; Davidi, G.; Flaxer, E.;
Patolsky, F. Supersensitive detection of explosives by
silicon nanowire arrays. Angew. Chem. Int. Ed. 2010, 49,
6830–6835.
[29] Balestra, F.; Cristoloveanu, S.; Benachir, M.; Brini, J.;
Elewa, T. Double-gate silicon- on-insulator transistor with
volume inversion: A new device with greatly enhanced
performance. IEEE Electron Device Lett. 1987, 8,
410–412.
[30] Grunbaum, E.; Barkay, Z.; Shapira, Y.; Barnham, K.;
Bushnell, D.; Ekins-Daukes, N.; Mazzer, M.; Wilshaw, P.
The electric field and dopant distribution in p-i-n structures
observed by ionisation potential (dopant contrast)
microscopy in the HRSEM. In Microscopy of
Semiconducting Materials. Cullis, A. G., Hutchison J. L.,
Eds.; Springer: Berlin Heidelberg, 2005, pp 503–506.
[10] Tong, H. D.; Chen, S.; van der Wiel, W. G.; Carlen, E. T.;
van den Berg, A. Novel top-down wafer-scale fabrication
of single crystal silicon nanowires. Nano Lett. 2009, 9,
1015–1022.
[14] Niskanen, A.; Colli, A.; White , R.; Li, H.; Spigone, E.;
Kivioja, J. Silicon nanowire arrays as learning chemical
vapour classifiers. Nanotechnology 2011, 22, 295502.
[15] Cao, A.; Sudhölter, E. J.; de Smet, L. C. Silicon
Nanowire-Based Devices for Gas-Phase Sensing. Sensors
2013, 14, 245–271.
[16] Paska, Y.; Stelzner, T.; Assad, O.; Tisch, U.; Christiansen,
S.; Haick, H. Molecular gating of silicon nanowire
field-effect transistors with nonpolar analytes. ACS Nano
2011, 6, 335–345.
[17] Wang, B.; Haick, H. Effect of functional groups on the
sensing properties of silicon nanowires toward volatile
compounds. ACS Appl. Mater. Interfaces 2013, 5,
2289–2299.
[18] Wang, B.; Cancilla, J. C.; Torrecilla, J. S.; Haick, H.
Artificial Sensing Intelligence with Silicon Nanowires for
[31] Nonnenmacher, M.; Oboyle, M.; Wickramasinghe , H.
Kelvin probe force microscopy. Appl. Phys. Lett. 1991, 58,
2921–2923.
[32] Glatzel, T. In Kelvin Probe Force Microscopy; Sadewasser,
S., Glatzel, T., Eds.; Springer Series in Surface Sciences;
Springer: Berlin Heidelberg, 2011; pp 289–327.
[33] Koren, E.; Rosenwaks, Y.; Allen, J.; Hemesath, E.; Lauhon,
L. Nonuniform doping distribution along silicon nanowires
11
measured by Kelvin probe force microscopy and scanning
photocurrent microscopy. Appl. Phys. Lett. 2009, 95,
092105.
[34] Shaya, O.; Shaked, M.; Usherenko, Y.; Halpern, E.; Shalev,
G.; Doron, A.; Levy, I.; Rosenwaks, Y. Tracing the
mechanism of molecular gated transistors. J. Phys. Chem.
C 2009, 113, 6163–6168.
[35] Masetti, G.; Severi, M.; Solmi, S. Modeling of carrier
mobility against carrier concentration in arsenic-,
phosphorus-, and boron-doped silicon. IEEE Trans.
Electron Devices 1983, 30, 764–769.
[37] Kikukawa, A.; Hosaka, S.; Imura, R. Silicon pn junction
imaging and characterizations using sensitivity enhanced
Kelvin probe force microscopy. Appl. Phys. Lett. 1995, 66,
3510–3512.
[38] Glatzel, T.; Sadewasser, S.; Lux-Steiner, M. C. Amplitude
or frequency modulation- detection in Kelvin probe force
microscopy. Appl. Surf. Sci. 2003, 210, 84–89.
[36] Palik, E. D. Handbook of optical constants of solids;
Academic press, 1998; Vol. 3.
12