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Fast Flexible Bottom-Gated Hydrogen Sensor based on Silicon
Nanomembrane
Minkyu Cho1,2, Incheol Cho1, Kyuyoung Kim1, and Inkyu Park1,*.
1Department of Mechanical Engineering, Korea Advanced Institute of Science and Techno
logy (KAIST), Daejeon, 34141, Republic of Korea
2School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlant
a, Georgia, 30332, USA
*Corresponding Author: [email protected]
Keywords: Flexible Hydrogen Sensor, Silicon Nanomembrane, Palladium Nanoparticle,
Bottom-Gated Sensor, Body Effect Sensing
Abstract
High performance flexible hydrogen sensor using a silicon nanomembrane (Si NM) coated
with palladium nanoparticles (Pd NPs) was developed. After the formation of gate structure on
a released Si NM, selectively pre-doped Si NM was flip-transferred onto a plastic substrate.
Along with Pd NPs deposited on top of the Si channel, the bottom gate structure allows the
sensor to operate in a sub-threshold regime maximizing the response and recovery speed. A
device simulation study revealed that the current change caused by shifting the threshold
voltage upon H2 exposure is the main operating mechanism of the sensor. The fabricated sensor
showed high response (up to 250% @ 0.7% H2 concentration), short response time (τ10-90 =
10s), and short recovery time (τ90-10 = 10s). In addition, the sensor showed low detection limit
(50 ppm) and high mechanical robustness.
Introduction
Hydrogen (H2) is a next generation clean energy source that does not leave carbon footprints.
However, H2 is colorless, odorless, but highly explosive with a concentration above 4%.
Therefore, several types of H2 sensors such as optical[1-7], chemoresistive[8-18], catalytic
combustion type sensors[19-21] have been developed. Specifically, resistive-type H2 sensors are
widely studied among researchers due to their low cost and high sensing performance. Among
many types of chemoresistive H2 sensors, palladium (Pd) nanostructure-based H2 sensors use
the resistance change of Pd as it transforms to palladium hydride (PdHx) upon the absorption
of H2 molecules. Others use the semiconductor-based sensor with Pd decoration, where the
work function of Pd is changed and the carrier distribution in the semiconductor body is
modulated upon the exposure to H2 gas. Flexible gas sensors are light-weight and mechanical
shock-resistive, which make them useful for portable electronics and automobile/aerospace
applications[22]. Various flexible H2 sensors have been reported up to date with a goal of
achieving mechanically robust, highly sensitive, quickly responding/recovering, and highly
selective sensors. Flexible gas sensors based on Pd-functionalized metal oxide H2 sensors
showed high responses to H2. However, they suffer from low response at room temperature and
thus require high temperature for proper sensor operation[23-27]. Flexible H2 sensors based on
low-dimensional materials, such as graphene, transition metal dichalcogenide (TMD), and
carbon nanotube have shown moderate responses to H2 and good mechanical robustness[28-30].
However, further improvement of H2 sensing is needed in terms of response and recovery time.
In this paper, a flexible H2 sensor was demonstrated using Pd nanoparticle (Pd NP)-
functionalized silicon nanomembrane (Si NM) transistor. The sensor structure and operating
mechanism are described in Scheme 1. The sensor body is mainly composed of the Si NM,
source/drain, and gate. As the sensor is exposed to H2, the H2 molecules are diffused into Pd
forming Pd hydride (PdHx), which changes the potential at the bulk substrate modulating the
inversion current across the Si channel. The selectively pre-doped Si NM is released from
silicon-on-insulator (SOI) substrate and transferred to a plastic substrate to form bottom-gated
MOSFET structure. After the transfer, Pd nanoparticles (Pd NP) are evenly deposited on the Si
channel region. The fabricated sensor showed high response (up to 250% @ 0.3V gate bias),
and fast response (τ10-90 = 10s) and recovery time (τ10-90 = 10s). The sensor retained its sensing
characteristics after repeated bending cycles. The sensor tests with various gases showed that
the sensor has a high H2 selectivity over other gases.
Result and discussion
The sensor fabrication started with the selective doping of source and drain regions with
phosphorous (P) ion implantation on a p-type silicon-on-insulator (SOI) wafer as shown in
Figure 1 (a). After the ion implantation, the top Si layer was selectively patterned and etched
with reactive-ion-etching (RIE) to form etch holes followed by immersion in hydrofluoric (HF)
solution. During the immersion, the HF solution was infiltrated to etch holes and buried-oxide
(BOX) layer underneath the top Si layer as shown in Figure 1 (b). After the BOX removal, the
top Si layer, called silicon nanomembrane (Si NM), was released from the substrate and bonded
to the substrate with weak Van der Waals force as shown in Figure 1 (c). After the Si NM
release, gate dielectric/metal stack and source/drain metal were deposited on the Si NM as
shown in Figure 1 (d). Then, the Si NM was transferred upside down to SU-8 coated plastic
substrate and later permanently cured with flood UV exposure as shown in Figure 1 (e). It
should be noted that the gate dielectric/metal stacks and source/drain metal are transferred
together with SiNM because they are deposited on top of the released SiNM. After the transfer,
devices were isolated with selective RIE process and 1 nm of Pd was deposited to form Pd
nanoparticles (Pd NPs) on top of the Si channel by electron beam evaporation as shown in
Figure 1 (f). Detailed fabrication process can be found in Methods section. Figure 1 (g) shows
a photographic image of the sensor. Figure 1 (h) is an optical microscope image of the sensor
with a bottom-gated structure.
Figure 2 (a) presents the I-V characteristics of the bottom-gate thin-film-transistor before Pd
deposition, which presents both linear and saturation regions of typical MOSFET. After the Pd
deposition, threshold voltage was increased from 0.8 V to 0.9 V which is due to the body
effect31. The H2 sensing mechanism can be explained based on the following equation:
∆𝑉𝑉𝑡𝑡ℎ = 𝛾𝛾(2∅𝐹𝐹 + 𝑉𝑉𝑆𝑆𝑆𝑆 − 2∅𝐹𝐹) (1)
where ∆𝑉𝑉𝑡𝑡ℎ is the change of the threshold voltage, 𝛾𝛾 is the body-effect parameter, 2∅𝐹𝐹 is
the surface potential, and 𝑉𝑉𝑆𝑆𝑆𝑆 is the source-body voltage. As Pd NPs are deposited on the Si
channel region, VSB increases and, therefore, the threshold voltage increases as well. Figure 2
(b) shows the transfer curves of the sensor before and after Pd NP deposition. The graph shows
that Vth was shifted from 0.82 V to 0.92 V after Pd NP deposition. Atomic force microscope
(AFM) scan image of Pd-coated Si surface in Figure 2 (c) indicates that the diameter of Pd NP
size varies from 5 to 30 nm according to the image analysis and they are densely distributed.
The scanning electron microscope (SEM) image in Figure 2 (d) clearly shows the presence of
densely-packed Pd NPs. To investigate the effect of the Pd NPs on the sensor characteristics,
the device structures were simulated in Figure 2 (e). Silvaco ATLASTM simulation software
was used to generate meshes of the sensor structure. The detailed simulation structure is
presented in Figure S2. According to the simulation result, the increase of the current density
in the channel region is clearly shown with the addition of Pd NPs. The formation of the built-
in electric field at the Pd/Si interface resulted in the shift of threshold voltage and the current
increase at zero gate bias.
The sensor response (%) is defined as:
𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅 (%) = 𝐼𝐼𝐻𝐻2−𝐼𝐼𝑎𝑎𝑎𝑎𝑟𝑟𝐼𝐼𝑎𝑎𝑎𝑎𝑟𝑟
× 100 (2)
where IH2 is the current during H2 exposure and Iair is the current in air environment. Upon H2
exposure, Pd NPs are transformed to PdHX lowering the built-in electric field at the Pd/Si
interface, and VSB is changed. This results in the threshold voltage shift toward negative side
increasing the drain current. Figure 3 shows the sensor response versus different H2
concentrations and gate bias. The result showed reproducible sensor response to different H2
concentrations in the range of 0.1 – 0.7%. The response starts to reduce with a gate bias more
than 0.3V. However, the response and recovery time became much shorter at the gate bias of
0.5V and above. This may be attributed to the switching time delay from off-state to sub-
saturation upon exposure to H2. Further investigation is needed to understand the reason of
slow response speed in off-state. More detailed analysis for the gas sensing result is presented
in Figure 4 (a-c). Figure 4 (a) shows the response versus H2 concentration at different gate bias
(0.3V, 0.5V, 0.6V, 0.7V, 0.8V and 0.9V). At the gate bias of 0.3V, the average sensor responses
were 38%, 98%, 169% and 250% to 0.1%, 0.3%, 0.5% and 0.7% of H2 concentrations,
respectively. The relationship between sensor response and concentration can be defined by
the equation according to Langmuir isotherm absorption theory[32]: ∆I/𝐼𝐼𝑎𝑎𝑎𝑎𝑎𝑎 ∝ 𝜃𝜃 =
𝑘𝑘1/𝑘𝑘−1𝑃𝑃𝐻𝐻2 where 𝜃𝜃 is the absorption coverage, 𝑘𝑘1 is absorption constant, 𝑘𝑘−1 is
desorption constant, and 𝑃𝑃𝐻𝐻2 is H2 partial pressure. The sensor response is linearly
proportional to the square root of the partial pressure at 0.5V bias with R2 ~ 0.99. Figure 4 (b)
shows a graph of response time versus H2 concentration with different gate bias. The response
time was defined as the time between 10% and 90% of the current change after H2 exposure.
At 0.3V gate bias, the response times were 169 s, 168 s, 204 s and 287 s to 0.1%, 0.3%, 0.5%
and 0.7% of H2 concentration respectively. However, for > 0.5V, the response time became
much faster. At 0.5V gate bias, the response times were 28 s, 13 s, 11 s and 10 s to 0.1%, 0.3%,
0.5% and 0.7% of H2 concentration respectively. Figure 4 (c) shows the recovery time versus
H2 concentration with different gate bias. The recovery time is defined as the time between 90%
and 10% of the current change during the air purge cycle. Similar to the response time, the
recovery times at 0.5V and above were much faster than those at 0.3V. At 0.3V gate bias, the
recovery times were 68 s, 39 s, 34 s and 42 s to 0.1%, 0.3%, 0.5% and 0.7% of H2 concentration
respectively. At 0.5V gate bias, the recovery times were 35 s, 19 s, 12 s and 10 s to 0.1%, 0.3%,
0.5% and 0.7% of H2 concentration respectively. Figure 4 (d-f) show the response, response
and recovery time under different H2 concentrations. Figure 4 (d) indicated that the responses
at 0.3V gate bias showed highest responses. However, the response recovery time was much
slower than those at 0.5V bias and above as shown in Figure 4 (e, f). This discernable
differences in response/recovery time between 0.3 V and 0.5 V voltage bias indicate that the
sensor speed is fastest when it is operated in sub-threshold regime. In this regime, the inversion
layer is not fully formed, therefore, it is less sensitive to the Schottky barrier change at the
interface between Pd and Si NM upon H2 exposure. The limit of detection (LOD) of the sensor
was 50 ppm as shown in Figure S3. To show the sensor uniformity, we randomly chose seven
sensors and plotted ID vs. VG curves. Overall, the sensors show uniform I-V characteristics as
shown in Figure S4. The eight repeated cycle tests at 0.7% H2 concentration in Figure S5 shows
a base current drift was with an average - 3.67 nA/cycle and 117% of response with standard
deviation of 2.24 % demonstrating reliability of the sensor.
For reliable sensor operation, it is indispensable to consider the temperature effects on the sensing
characteristics. The ambient temperature change may affect the sensor characteristics by two major
factors: 1) solubility change and 2) threshold voltage change of MOSFET. According to Sievert’s law,
H2 solubility is proportional to the inverse of the temperature. Absorbed H2 molecules gain enough
kinetic energy to desorb from Pd surface as temperature increases. This phenomenon was demonstrated
with experiments in our previous work[13, 33]. The second major temperature effect is the threshold
voltage shift due to the surface potential change (∅𝐹𝐹 ), which is proportional to the temperature.
Therefore, the temperature effect should be absolutely considered for palladium/semiconductor gas
sensors. This is a common practice for every chemo-resistive gas sensor. In order to resolve this problem,
temperature should be also measured simultaneously, and temperature effect should be compensated by
temperature calibration methods such as machine learning algorithm.
Various gases were tested for the sensor to investigate the gas selectivity as shown in Figure
5. The gas concentration for each gas type was set according to the permissible exposure limits
(PELs) by Occupational Safety and Health Administration (OSHA). The result shows that the
sensor does not respond or negligibly respond to nitrogen dioxide (NO2) and carbon monoxide
(CO) since intrinsic Si without any surface functionalization is inert to these gases. The sensor
showed response to hydrogen disulfide (H2S) as well as H2 because both H2S and H2 are
dissociated into H atoms, and these atoms are diffused into Pd and changing its work function.
The low gas selectivity of hydrogen to hydrogen disulfide or water vapor is one of common
problems to solve in room temperature hydrogen sensor. According to the literature, Pd itself
has low sensitivity to hydrogen radicals[34]. However, it has been reported MOS structure with
Pd shows some sensitivity to hydrogen radicals due to impurities in the metal / at the interfaces.
We believe that, with adoption of the micro heaters, filters, sensor array, different sensor
operating regime with various reaction material, and pattern recognition, the gas selectivity
issue can be improved.
To investigate the mechanical robustness of the sensor, the sensor has gone through several
cycles of repeated bending and the sensing test afterward. The sensor response was measured
after 1000 and 5000 bending cycles with curvature radii varying from infinite to 20 mm. The
mechanical strain of the sensor during the bending is 0.5%[8]. The sensor was bent along the Si
channel direction. After 1000 bending cycles, the sensor did not show significant degradation
of its sensing capability. Even after 5000 bending cycles, the sensor still retained the responses
as compared to those before bending. However, the response time was increased after 5000
bending cycles. This slow response after 5000 bending is similar to what is observed when the
sensor was operated in transistor off regime meaning at Vg << Vth when inversion current is not
formed along the Si channel. The increased response time after 5000 bending is attributed to
the threshold voltage shift due to increased electron traps in SiO2 [35]. Although the response
time was increased after 5000 bending cycles, the sensor was still able to detect H2 with
different concentrations. The sensor responses under static bending were also presented in
Figure S6. The result shows that the sensor retained its sensing performance under static
bending. This robustness after repeated bending may be due to the thin SiNM layer which
corroborates the flexural rigidity of the sensor. In addition, the sensor response under various
humidity conditions was tested (RH=0%, 20%, and 80%) as shown in Figure S7. The test result
shows that the response time is increased in high humidity condition. The increased response
time in high humidity condition is due to the condensed water molecules that occupy the
absorption sites and prevent the diffusion of H atoms into Pd lattice. The response also changed
with humidity which may be attributed to the base current change in high humidity conditions.
This issue may be resolved by using water absorbing filters36, humidity sensors and machine
learning algorithm to compensate for the H2 sensing data.
Conclusion
In this work, flexible H2 sensor was developed based on Pd NP coated Si NM enabled by
flip-transfer method. The prompt built-in electric field change of Pd NP upon the intake of H2
and bottom-gated Si NM transistor that operates in sub-threshold regime result in fast response
and recovery, which is explained by body effect-induced threshold voltage shift. Both
simulation and measurement result suggested that the decoration of Pd NP and its
transformation into PdHx changes the channel current by shifting the threshold voltage. The H2
gas response test demonstrated high response (up to 250% @ 0.7% H2 concentration) and fast
response (10s) and recovery (10s) time under the operation in sub-threshold regime. Moreover,
the sensor showed excellent linearity to tested H2 concentration range with R2 > 0.99. Gas
selectivity test showed that the sensor has high selectivity to other gas such as CO and NH3.
Repeated bending test was performed and showed the mechanical robustness of the sensor. The
fabrication process is easily applicable to wafer scale and can be integrated with electronic
circuitry and other silicon-based sensors. The presented flexible sensor would be useful for
wearable electronics and IoT that requires detection of H2 in hazardous environment.
Acknowledgement
This research was supported by Basic Science Research Program through the National
Research Foundation of Korea(NRF) funded by the Ministry of Science, ICT & Future
Planning (2018R1C1B6006338).
Methods
Sensor Fabrication
20 nm of SiO2 was grown on n-type SOI wafer with resistivity of 1-20 Ω‧cm (200 nm / 375
nm thicknesses for top silicon and buried oxide layer, respectively). After the thermal oxidation,
source/drain regions were selectively opened with a photoresist patterning. For the ion
implantation, phosphorous (P) ion was ion-implanted with 20 keV energy and 5×1015 cm-2 dose.
After the ion implantation, the photoresist and thermal oxide was removed by organic solvents,
piranha solution and hydrofluoric acid (HF) to remove photoresist and thermal oxide. Etch
holes were formed on the top silicon layer with a photoresist patterning and reactive-ion etching
(RIE). After the etch hole formation, the sample was immersed in HF. During the HF immersion
process, the buried oxide layer was etched away, and silicon nanomembrane (Si NM) was
released from the substrate and bonded to the substrate by Van der Waals force. After the Si
NM release, gate dielectric/metal stack and source drain metal were selectively deposited. After
the deposition, the Si NM was flip-transferred to SU-8-coated poly (ethylene terephthalate)
substrate followed by flood UV exposure. After the transfer, 1 nm Pd was deposited on the
channel region by an e-beam evaporator to form Pd nanoparticles on the Si channel.
Gas Sensing Test
The flexible bottom-gate H2 sensor was tested inside a sealed chamber with gas inlets and
outlets. Gate and source-drain voltages were applied by a DC voltage supply and current source,
while the current across the source and drain of the sensor was monitored in real time. A gas
sensing test was performed in a dry air environment, and the gas flows were controlled by mass
flow controllers (MFCs) that were connected to a computer with a LabVIEW interface. The
total gas flow rate was kept at 500 sccm. The H2 test was conducted in synthetic air base by
mixing N2 and O2 in 4:1 ratio. For the humidity test, the relative humidity (RH) was adjusted
by changing the proportion of the humid air generated by saturated salt solution.
Mechanical Bending Test
The mechanical bending test was performed with a linear stage. The sensor was repeatedly
pressed and released at two end points of the sensor while the center point was fixed at a
cylindrical fixture, similar to three points bending. The radius of curvature was 20 mm during
the bending state.
Scheme 1. Graphic illustrations of flexible bottom gate thin-film-transistor H2 Sensor
Figure 1. (a-f) Illustrations of the sensor fabrication process, (g) photographic picture of the
complete sensor (scale bar: 1 cm), (h) optical microscope image of the sensor (scale bar: 50µm)
Figure 2. (a) Measured I-V characteristics of the flexible bottom-gated MOSFET, (b) measured
transfer characteristic before and after Pd decoration, (c) atomic force measurement (AFM)
scan images of Pd nanoparticles on silicon, (d) scanning electron microscope (SEM) image of
Pd nanoparticles (scale bar: 30 nm), (e) device simulation of the sensor without (up) and with
(bottom) Pd layer
Figure 3. Real-time H2 sensing characteristics with different H2 concentration and gate bias.
The right axis and the brown bar graphs indicate H2 concentrations. The base current is
increased as higher gate bias was applied which corresponds to ID-VG curve. The response
(∆I/Iair × 100) when VG = 0.3V is the highest because of low base current. However, the
response time is lowest due to slow saturation of the current after H2 exposure.
Figure 4. (a-c) response (%), response time (τ10-90) and recovery time (τ90-10) vs. H2 concentration,
(d-f) response (%), response time (τ10-90) and recovery time (τ90-10) vs. gate bias (V). the response
time is clearly reduced as the gate bias ≥ 0.5V.
Figure 5. The sensor response to various gases: (a) Hydrogen Sulfide (H2S), (b) Carbon
Monoxide (CO), and (c) Nitrogen Dioxide (NO2). The concentrations for each test gases are
based on permissible exposure limits (PELs) by Occupational Safety and Health
Administration (OSHA).
Figure 6. H2 response after repeated bending: (a) before bending, (b) after 1000 times, and (c)
after 5000 times. The sample was bent in linear stage with 20mm of radius curvature. The
repeated bending test was performed on a linear stage with two tips mounted at the end that
press both end of the sensor while the middle part of the sensor was fixed at a cylindrical chuck
with 40 mm diameter.
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