Eleonora Pargoletti1,2, Umme H Hossain3, Iolanda Di Bernardo4, Hongjun Chen4, Thanh Tran-Phu4, Gian Luca Chiarello1, Josh Lipton-Duffin5, Valentina Pifferi1,2, Antonio Tricoli4, Giuseppe Cappelletti1,2. 1. Dipartimento di Chimica, Università degli Studi di Milano, via Golgi 19, Milano 20133, Italy. 2. Consorzio Interuniversitario Nazionale per la Scienza e Tecnologia dei Materiali (INSTM), Via Giusti 9, Firenze 50121, Italy. 3. Department of Electronic Materials Engineering, Research School of Physics and Engineering, The Australian National University, Canberra Australian Capital Territory 2601, Australia. 4. Nanotechnology Research Laboratory, College of Engineering and Computer Science, The Australian National University, Canberra Australian Capital Territory 2601, Australia. 5. Institute for Future Environments (IFE), Central Analytical Research Facility (CARF), Queensland University of Technology(QUT), Brisbane 4000, Australia.
Abstract
The development of high-performing sensing materials, able to detect ppb-trace concentrations of volatile organic compounds (VOCs) at low temperatures, is required for the development of next-generation miniaturized wireless sensors. Here, we present the engineering of selective room-temperature (RT) chemical sensors, comprising highly porous tin dioxide (SnO2)-graphene oxide (GO) nanoheterojunction layouts. The optoelectronic and chemical properties of these highly porous (>90%) p-n heterojunctions were systematically investigated in terms of composition and morphologies. Optimized SnO2-GO layouts demonstrate significant potential as both visible-blind photodetectors and selective RT chemical sensors. Notably, a low GO content results in an excellent UV light responsivity (400 A W-1), with short rise and decay times, and RT high chemical sensitivity with selective detection of VOCs such as ethanol down to 100 ppb. In contrast, a high concentration of GO drastically decreases the RT response to ethanol and results in good selectivity to ethylbenzene. The feasibility of tuning the chemical selectivity of sensor response by engineering the relative amount of GO and SnO2 is a promising feature that may guide the future development of miniaturized solid-state gas sensors. Furthermore, the excellent optoelectronic properties of these SnO2-GO nanoheterojunctions may find applications in various other areas such as optoelectronic devices and (photo)electrocatalysis.
The development of high-performing sensing materials, able to detect n>an class="Chemical">ppb-trace concentrations of volatile organic compounds (VOCs) at low temperatures, is required for the development of next-generation miniaturized wireless sensors. Here, we present the engineering of selective room-temperature (RT) chemical sensors, comprising highly porous tin dioxide (SnO2)-graphene oxide (GO) nanoheterojunction layouts. The optoelectronic and chemical properties of these highly porous (>90%) p-n heterojunctions were systematically investigated in terms of composition and morphologies. Optimized SnO2-GO layouts demonstrate significant potential as both visible-blind photodetectors and selective RT chemical sensors. Notably, a low GOcontent results in an excellent UV light responsivity (400 A W-1), with short rise and decay times, and RT high chemical sensitivity with selective detection of VOCs such as ethanol down to 100 ppb. In contrast, a high concentration of GO drastically decreases the RT response to ethanol and results in good selectivity to ethylbenzene. The feasibility of tuning the chemical selectivity of sensor response by engineering the relative amount of GO and SnO2 is a promising feature that may guide the future development of miniaturized solid-state gas sensors. Furthermore, the excellent optoelectronic properties of these SnO2-GO nanoheterojunctions may find applications in various other areas such as optoelectronic devices and (photo)electrocatalysis.
The development of
ultraminiaturized and low-power pan class="Chemical">consumption
sensors for monitoring of volatile organiccompound (VOC) concentrations
is becoming increasingly important because of the rapid pace of emission
of potentially toxic VOCs in urban areas and their role as biomarkers
in noninvasive medical diagnostics.[1] Many
VOCs are highly toxic with potential carcinogenic, mutagenic, and
teratogenic functions at low concentrations. They can also contribute
to atmospheric pollution, such as photochemical smog and destruction
of the ozone layer.[2] Recently, significant
attention has been devoted to the BTEXcompounds, namely, benzene,
toluene, ethylbenzene, and xylene, because of their increasing release
in various industrial processes.[2−4] Quite a few VOCs are also present
in the humanbreath and correlated with several metabolic processes.
Specifically, the monitoring of VOCs spontaneously released by the
body is increasingly considered as a promising path for noninvasive
medical diagnostics and health monitoring.[5,6] For
instance, abnormal concentrations of acetone (>1800 ppb) can be
related
to type 1 diabetes, where the standard concentrations in people not
affected by this illness are 300–900 ppb.[7] Similarly, a marked presence of ethanol and acetone are
related to nonalcoholic fatty liver disease and hepatic steatosis.[8] Ethylbenzene as well, apart from being a BTEXcompound, has been recently recognized as one of the potential biomarkers
for lung cancer detection (0.04 ppb in healthy humans vs 0.11 ppb in ill patients).[9−11] Hence, the need for frequent
VOC monitoring with deployable, portable, or wearable detectors has
attracted a widespread interest in the development of few millimetres
in size wireless sensor devices.[5]
pan class="Chemical">Chemoresistive n>an class="Gene">gas sensors, based on nanostructured metal oxide
semiconductors (MOS), are a promising technology for low-concentration
detection of VOCs with superior miniaturization potential to established
analytical techniques such as proton-transfer reaction mass spectrometry
and gaschromatography.[12] Development of
MOS sensors is held back from few fundamental challenges related to
the sensing material, including high operating temperatures (OT) (200–400
°C)[13−15] and their difficulty in achieving selectivity in
multiple gas environments.[1] Much effort
is focused to address the above challenges. Various recent studies
report the design and fabrication of MOS (e.g., ZnO,[16−18] NiO,[13] and WO3[19]) with unique nanoarchitectures that enable low-temperature
sensing.[13−15] However, the lower limit of detection is often at
the ppm level and thus very high for many applications, including
detection of important biomarkers for breath analysis.[14,15]
The use of heterojunctions between n>an class="Chemical">metal oxides[13] or by coupling them with carbonaceous materials[20,21] has been reported as a path to improve the gas sensing performance
of MOS, with particular merits for room-temperature (RT) detection
under light irradiation. Notably, graphene materials possess several
promising features such as thermoelectricconductivity and mechanical
strength,[9] which can enhance the sensing
behavior of MOS by formation of nanoscale heterojunctions. Reduced
graphene oxide (rGO) has been widely investigated for electrochemical
applications and offers some potential for gas sensing.[22−24] For instance, Meng et al.[25] recently
described a ternary sensing materials made of ZnO–rGO sensitized
with graphiticcarbon nitride that exhibits superior ethanol vapor
sensing, reaching a 9-fold higher response than pure ZnO. Similarly,
a newly ternary nanocomposite material comprising Au, SnO2, and rGO has been reported to successfully detect low ppm concentrations
of ethanol at OT down to 50 °C. This was attributed to the synergistic
effects arising between SnO2 and rGO that were further
enhanced by decoration with gold nanoparticles.[26] Ultimately, Yuan et al.[27] synthesized
a sandwich-like composite consisting of a double layer of Co3O4 and rGO, reporting a 5-fold increase in response to
100 ppm of triethylamine with respect to a conventional bare Co3O4 semiconductor. In contrast, pure graphene oxide
(GO) has been scarcely reported for this application[24,28,29] because of its less defective
structure and surface chemistry.[28,30] Nevertheless,
its oxygen-rich functional groups can be the anchor points that help
the further growth of MOS nanoparticles. Particularly, if the adopted
metal oxide behaves as an n-type semiconductor, the conceivable formation
of p(GO)[31,32]–n(MOS) heterojunction may be hypothesized.
Here, we report the fabripan class="Chemical">cation of an ultrapn>orous nanoheterojunction
network of SnO2 and GO, demonstrating the effective engineering
of their chemical sensing and photoresponsive properties tuning the
p- and n-type nanodomain fraction. The photo- and chemical sensing
features of these nanoheterojunctions were systematically investigated,
achieving new insights into the role played by the GO in the enhancement
of the RT sensor response and the selectivity toward a particular
VOC. Specifically, three different volatile compounds, i.e. ethanol
(EtOH), acetone and the less-studied ethylbenzene (EtBz), were adopted
as target molecules. Notably, we observed that a small amount of GO
leads to the formation of electron-depleted nanoheterojunctions with
superior electron–hole separation efficiency. These nanocomposites
are able to selectively detect ethanolconcentrations down to 100
ppb at RT. Conversely, the increase of GOcontent hinders ethanol
sensing and favors ethylbenzene detection, providing for the first
time a mechanism to tailor MOS sensor selectivity. We demonstrated
that this optimal nanocomposite structure provides excellent photo-
and chemical responses, showcasing their applicability as both visible–blind
UV photodetectors and selective RT VOC solid-state sensors.
Experimental Section
All the
chemicals were of reagent-grade purity; Milli-Q water was
utilized. All the adopted reagents were purchased from Sigma-Aldrich.
Synthesis
of Pristine Oxides and Hybrid SnO2–GO
Compounds
pan class="Chemical">GO was prepn>ared through modified Hummers method
already repn>orted in the literature.[29,33] For the composite
materials, SnO2–GO, the adopted synthetic route
was the same described in our previous works[28,29] with different starting salt precursor-to-GO weight ratios (i.e., 4:1 and 32:1 SnO2–GO since with
the other intermediate ratios, lower sensing performances were obtained,
as deeply discussed in our previous study).[29] For the sake of comparison, pure SnO2 was prepared through
the same synthetic route, without the addition of GO.
Powder Physicochemical
Characterizations
X-ray diffraction
(XRD) analyses were performed on a Philips PW 3710 Bragg–Brentano
goniometer as described elsewhere,[29] collecting
spectra between 10 and 80° with a step size of 0.1°.Raman spectra were collected on a Renishaw inVia micro-Raman spectrometer,
as reported in our previous study.[29]The Brunauer–Emmett–Teller (BET)-specific surface
area was determined by a multipoint BET method. Desorption isotherms
were used to determine the total pore volume using the Barrett–Joyner–Halenda
(BJH) method, as stated elsewhere.[29]The morphology was investigated by using a Zeiss Ultraplus (field-emission
span class="Chemical">canning electron microscopy, FESEM) at 3 kV coupled with an energy-dispersive
X-ray (EDX) spectrophotometer for elemental analysis. Transmission
electron microscopy (TEM) analyses were carried out on Hitachi H7100FA
at 100 kV. The TEM grids were prepared as already described.[29]
Thermogravimetric analyses were carried
out by means of a Mettler
Toledo Star and System TGA/DSC 3+ under air atmosphere (5 °C
min–1 from 30 to 800 °C).X-ray photoemission
spectrosn>an class="Chemical">copy (XPS) data were collected in a
Thermo Fisher Kratos Axis Supra photoelectron spectrometer at the
Central Analytical Research Facility of the Queensland University
of Technology (Brisbane, Australia). The apparatus is provided by
a monochromated Al kα source (1486.7 eV), and the spectra were
calibrated with respect to their Fermi level. Survey spectra were
acquired at pass energy 160 and high-resolution spectra at pass energy
20.
pan class="Chemical">Powder optical band gaps were evaluated by Kubelka–Munk
elaboration. Diffuse reflectance spectroscopy (DRS) spectra were measured
on a UV/vis spectrophotometer Shimadzu UV-2600 equipped with an integrating
sphere; a “total white” BaSO4 was used as
a reference. The porosity of SnO2 nanoparticle networks
of the films was estimated from the optical density and SEM visible
thickness as suggested by Bo et al.[34] adopting
an absorption coefficient of 3.08 × 107 m–1 (at 312 nm for all the powders).
Electrochemical impedance
spectroscopy (EIS) experiments were carried
out as reported in our previous study.[29]
Deposition on Pt-Interdigitated Electrodes
Powders
were deposited on glass substrates topped with Pt interdigitated electrodes
(Pt-IDEs) by a simple hot-spray method reported elsewhere.[28] Therefore, the tested IDEs were prepared by
adopting pristine SnO2, hybrid 4:1, and 32:1 SnO2–GO powders.
Photodetector Measurements and Gas Sensing
Tests
For
photodetector tests, photo- and dark-n>an class="Chemical">currents were measured at 25
°C with an LCS-100 Series Small Area Solar Simulator (Newport
Co.). The electrode active surface was equal to 0.4 cm–2, and the irradiation power at 312 nm was 1.5 μW cm–2. The responsivity and detectivity were, then, calculated according
to the equations reported elsewhere.[34] Regarding
NO2, ethanol (EtOH), acetone and ethylbenzene (EtBz) sensing,
O2 (BOC Ltd), and N2 (BOC Ltd) were controlled
by a mass flow controller (Bronkhorst), with a total gas flow rate
of 0.5 L min–1. The target gas (10 ppm in N2, Coregas) was diluted to 1 ppm and lower concentrations by
using the simulated air (0.1 L min–1 O2 + 0.4 L min–1 N2, BOC Ltd) before purging
into the chamber, keeping the total flow rate constant. The temperature
of the hot plate in the gas sensing chamber (Linkam) was controlled
by a temperature controller and, when the OT was lowered (equal or
below 150 °C), UV light was also exploited. The samples were
illuminated through a quartz window by a solar simulator (NewSpec,
LCS-100) with an FGUV5-UV–Ø25 mm UG5 Colored Glass Filter
(AR Coated: 290–370 nm, Thorlabs Inc). For the gas sensing
tests, the adopted experimental procedure is finely described in previous
works of some authors of the present paper.[28,29] Furthermore, tests conducted under controlled relative humidity
(RH of ca. 80%) were carried out by exploiting a
bubbler through which the target gas evaporated.
To shed light
on the intrinsipan class="Chemical">c materials electrical features, Figure S1 displays both the resistance variations upon purging
a representative VOC as ethanol for pure and hybrid compounds, adopting
the same operative conditions used during sensing measurements (temperature,
UV, and applied bias). Besides, Figure S1c shows the resistance of pure GO.
Results and Discussion
Synthesis
of a SnO2–GO Nanoheterojunction
Network
The graphiteconversion into the GO material and
the subsequent formation of nanoheterojunctions with a three-dimensional
SnO2 network have been verified by a combination of physical
and chemical characterizations. Two different relative GOconcentrations
of SnO2–GO 4:1 and 32:1 were investigated to evaluate
the potential optoelectronic and chemoresistive performances of the
SnO2–GO nanoheterojunctions. These SnO2–GO ratios were selected with respect to the previous study
on ZnO–GO nanoscale heterojunctions.[29]Figure a,b
shows a compn>arison of the XRD patterns and Raman spn>ectra of the pristine
graphite and GO, along with the structural data of bare SnO2 and the synthesized SnO2–GOcomposites. The effective
transformation of graphite material into GO was assessed by both the
main GO diffraction peak (at 2θ value of 12°) and the intensity
increase of the ratio between the D and G Raman bands up to 1.01 of
GO versus 0.25 of the precursor graphite (Figure a,b, red spectra).[28,29] Indeed, during the oxidation process, oxygen functional groups are
introduced into the graphiticchain, causing either an increase of
the D band intensity[28,35] or a small shift (ca. 25 cm–1 upward for G band and 45 cm–1 downward for D band) of the band positions,[28] because of the achievement of a highly defective structure.[36,37] Moreover, the gradual integration of GO nanodomains into the SnO2 matrix was revealed by both the presence of Raman bands relative
to the GO material (Figure b, blue and violet spectra) and the very small XRD crystallite
diameter (ca. 5–8 nm; Figure a and Table , fourth column). Indeed, the crystallite size of the
SnO2–GO nanoheterojunctions resembles much more
the GO one (11 nm, Table ), underlining the effective integration of the carbonaceous
material into the metal oxide network.
Figure 1
(a) XRD patterns of graphite,
GO, pure SnO2, and hybrid
SnO2–GO samples. (b) Raman spectra of all the investigated
samples. (c) TGA spectra of GO, pure, and hybrid nanopowders. (d)
EDX spectra of 4:1 SnO2–GO and 32:1 SnO2–GO. XP spectra of (e) C 1s and (f) O 1s regions of graphite,
GO, 4:1, and 32:1 SnO2–GO.
Figure 2
(a–c)
TEM images of pristine SnO2 and hybrid
SnO2–GO compounds. (b) Presence of GO was highlighted
in red. (d–i) Top-view FESEM micrographs and (j–l) cross-sectional
images of both pure and composite samples. Insets: photos of the relative
IDEs.
Table 1
Surface Area (SBET), Total Pore Volume (Vtot. pores), Crystallite Domain Size by XRD Analysis (⟨dXRD⟩), Optical Band Gap (Eg, by Kubelka–Munk Extrapolation), Film Thickness
(by
Cross-Sectional SEM), and Film Porosity Percentage (Obtained by Means
of UV/vis Spectroscopy Technique)
sample
SBET (m2 g–1)
Vtot. pores (cm3 g–1)
⟨dXRD⟩
(nm)
Eg (eV)
film thickness
(μm)
% film porosity
graphite
11
0.030
27
-
-
-
GO
30
0.020
11
-
-
-
SnO2
67
0.210
15
3.6
1.8 ± 0.2
93 ± 1
4:1 SnO2–GO
29
0.070
5
3.0
1.2 ± 0.4
97 ± 1
32:1 SnO2–GO
55
0.133
8
3.4
1.4 ± 0.4
94 ± 2
(a) XRD patterns of graphite,
GO, pure SnO2, and hybrid
SnO2–GO samples. (b) Raman spectra of all the investigated
samples. (c) TGA spectra of GO, pure, and hybrid nanopowders. (d)
EDX spectra of 4:1 SnO2–GO and 32:1 SnO2–GO. XP spectra of (e) C 1s and (f) O 1s regions of graphite,
GO, 4:1, and 32:1 SnO2–GO.(a–c)
TEM images of pristine SnO2 and hybrid
SnO2–GOcompounds. (b) Presence of GO was highlighted
in red. (d–i) Top-view FESEM micrographs and (j–l) cross-sectional
images of both pure and composite samples. Insets: photos of the relative
IDEs.Thermogravimetripan class="Chemical">c analysis reveals that the hybrid sampn>les are
very stable (Figure n>an class="Chemical">c) with a mass loss of only ∼4% up to temperatures of 800
°C, resembling the typical behavior of the pristine SnO2. This indicates that the presence of metal oxide prevents the decomposition
of the underneath GO. On the contrary, pure GO (Figure c, red line) decomposes in several stages,
ascribable to different processes, such as (i) the loss of moisture
and interstitial water between 60 and 110 °C; (ii) the pyrolysis
of labile oxygen-containing groups with the generation of CO, CO2, and water[38] at 200 °C; and
(iii) the breakage of sp2carbon bonds at around 480 °C.[29,37] Furthermore, the presence of tin in the hybrid samples was confirmed
by EDX data (Figure d). The surface composition of the SnO2–GO materials
was further investigated by XPS and BET–BJH analyses. The C
1s and O 1s core-level high-resolution spectra of the GOcompound
(Figure e,f, red spectra)
were discussed recently.[28,29,39] Besides, the C 1s region of both pure and SnO2–GOcompounds shows three components, referable to C–C sp2 (284.75 eV), C–O/C–OH (286.20 eV), and O–C=O
(289.00 eV) bonds.[40,41] While the last two carbon peaks
are mostly attributed to adventitious CO2, its enhanced
presence in the nanoheterojunctions is indicative of the presence
of GO.[28,29]Figure f shows the O 1s core-level high-resolution spectra,
which can be deconvoluted into three components centered at around
530.75, 531.40, and 532.60 eV. These bands correspond respectively
to (i) lattice oxygen anions (O2–) in the cassiterite
lattice, (ii) oxygen ions (O2– and O–) in the oxygen-deficient regions, caused by oxygen vacancies, and
(iii) adsorbed oxygen species (especially water molecules).[42,43] The relative amount of oxygen vacancies in the SnO2–GOcompounds is higher than in the pure SnO2, suggesting a
more defective structure as a result of the GO integration into the
metal oxide matrix. Furthermore, the specific surface areas (Table , second column) of
the nanoheterojunctions increases with decreasing GOcontent (29 and
55 m2 g–1 for 4:1 and 32:1 SnO2–GO, respectively), approaching that of the pure SnO2 (67 m2 g–1).[28] The same trend was observed for the total pore volume data (Table , third column), where
4:1 SnO2–GO has a value (0.070 cm3 g–1) comparable to that of pure GO (0.020 cm3 g–1), whereas 32:1 SnO2–GO exhibits
a larger pore volume and size distribution (Figure S2b and inset of Figure S2a), because
of the increasing amount of tin dioxide. Figure S2b shows a rise in pore numbers with diameter above 20 nm.
Besides, by evaluating the hysteresis loop of the BET desorption isotherms
(Figure S2a), we can observe the presence
of slit-shaped pores for the GO and the hybrid materials, while bare
SnO2 possesses bottleneck pores, in line with previous
studies on SnO2–GO.[28]
Figure shows
the
morphology of the prispan class="Chemical">tine and composite samples by TEM and FESEM.
Notably, both the 4:1 and 32:1 SnO2–GO ratios seem
to be composed of spherical nanoparticles with dimensions of around
8–10 nm (Figure b,c), which are larger than the pure oxide ones, having a size of
∼4–6 nm (Figure a).[28] Interestingly, with 4:1 lowest
ratio, the presence of underneath GO is still clearly observable (Figure b). Also scanning
electron micrographs display the presence of spherical agglomerates
with dimensions of hundreds of nanometers for all the three SnO2-based samples (Figure g–i).
Overall, this set of pan class="Chemical">characterizations
indicates that the gradual
coverage of the GO sheets by SnO2 is achieved, creating
strong bonds between the graphene and the metal oxide nanoparticles.
This tunable coverage can influence the structural and surface properties,
the morphology, and crystal size of the as-prepared powders, thus
affecting their behavior as photo- and chemical sensing materials.
Optoelectronic and Chemical Sensing Properties
The
formation of nanospan class="Chemical">cale heterojunctions is a promising approach to
improve chemical sensing at low temperatures by photoexcitation and
separation of reactive electron/hole couples.[13,28,44−46] The optical properties
of the tin dioxide-containing compounds were initially investigated
by DRS. Figure a shows
the Kubelka–Munk conversion of the DRS spectra, revealing similar
values of 3.0 and 3.4 eV for the 4:1 and 32:1 nano-SnO2–GO, respectively. These values are lower than the band gap
of pure SnO2 of about 3.6 eV.[28,47] Such decrease is attributable to the coupling between the white
tin dioxide and the brownish GO sheets.
Figure 3
(a) Band gap values determined
by Kubelka–Munk elaboration.
(b) Dynamics of photodetector responsivity for all the Sn-based compounds
(λ = 312 nm, light power density = 1.5 μW cm–2, and applied bias = +1.0 V). (c) Schematic illustration of VOC sensing
by hybrid SnO2–GO nanomaterials.
(a) Band gap values determined
by Kubelka–Munk elaboration.
(b) Dynamipan class="Chemical">cs of photodetector responsivity for all the Sn-based compounds
(λ = 312 nm, light power density = 1.5 μW cm–2, and applied bias = +1.0 V). (c) Schematic illustration of VOC sensing
by hybrid SnO2–GO nanomaterials.
In order to investigate the powder performanpan class="Chemical">ces, the nanopn>owders
were depn>osited on n>an class="Chemical">Pt-IDEs via a scalable air-spraying method, obtaining
highly homogeneous micrometric-thick films (Figures d–f). The cross-sectional FESEM images
(Figure j–l)
reveal a layer thickness of around 1.5–2.0 μm for both
the SnO2 and the two SnO2–GO nanoheterojunctions
(Table , sixth column).
The estimated film porosities[29] are above
90% for all materials (Table , seventh column), in line with the values expected for aerosol
self-assembly processes.[48] Insights into
the optoelectronic properties and sensing mechanism of the nanoheterojunctions
SnO2–GO were first obtained by investigating the
photoresistive behavior under UV illumination. Lan et al.[49] proposed a high-performance UV photodetector
design by combining SnO2 semiconductors with three-dimensional
graphene nanoflakes. The as-prepared nanocomposite films showed strong
absorption in the wide UV region, owing to the presence of the three-dimensional
(3D) network that efficiently suppresses the recombination of the
photo-induced electron–hole pairs and resulted in a significant
enhancement of the graphene–SnO2 photoresponse over
that of pure SnO2. Notably, the responsivity of a 3D graphene–SnO2 photodetector was reported to be as high as 8.6 mA W–1 at a bias voltage of 1.0 V, which is around 8 times
higher than that of pristine tin dioxide. Here, starting from this
report, the current response was acquired by applying a bias potential
of 1.0 V and by UV light irradiation at 312 nm with a light power
density of 1.5 μW cm–2 (Figure b). The principal figures of merit for photodetectors
are the magnitude of the photo-/dark-currents, responsivity, and detectivity
(Table ). Especially,
the last parameter quantitatively characterizes the photodetector
performances.[34] Among the investigated
samples, the 32:1 SnO2–GO shows the highest detectivity
of 1.4 × 1015 Jones followed digressively by SnO2 and 4:1 SnO2–GO (Table , eighth column). The photocurrents, together
with Iphoto/Idark ratios, follow the same trend (Table , third and fourth columns), showing a very high Iphoto/Idark value
of around 2400 for the 32:1 SnO2–GO. Furthermore,
the rise and decay times (Table , fifth and sixth columns) were comparable to some
of the best performing SnO2-based UV photodetectors.[34,50] Here, the responsivity of the 32:1 SnO2–GO ratio
is 400 A W–1 and is thus very high (Table and Figure b) with respect to the recent literature.[49] Similarly, the 32:1 SnO2–GO
nanoheterojunction detectivities (Table , eighth column) are greater than those of
some of the most performing materials.[49,51,52] This photoresponsivity trend (32:1 > SnO2 > 4:1) and the very high responsivity/detectivity measured with
the 32:1 ratio suggest a potential mechanism for the enhancement of
the UV light sensing.[53] In line with the
previous literature,[13,28,29,54] we suggest that a p–n-type nanoheterojunction
is formed between the GO, showing a p-type behavior, and the n-type
SnO2.[31]
Table 2
Figures
of Merit of Sn-Based Photodetectors
(λ = 312 nm, Light Power Density, 1.5 μW Cm–2, and Applied Bias, +1.0 V)
sample
dark-current (nA)
photocurrent
(μA)
IPhoto/IDark
rise time
(s)
decay time
(s)
responsivity (A W–1)
detectivity (jones)
SnO2
540
58
108
≈160
≈130
100
1.5 × 1014
4:1 SnO2–GO
1
0.057
52
≈130
≈110
0.100
3.4 × 1012
32:1 SnO2–GO
100
240
2380
≈120
≈100
395
1.4 × 1015
Upon UV light illumination, photogenerated electron–hole
pairs are formed, whin>an class="Chemical">ch are rapidly separated by the SnO2–GO nanoscale heterojunctions, which is a disadvantage for
their recombination. This results in a higher photocurrent response
especially for the 32:1 ratio, where an optimal distribution of the
GO in the metal oxide nanoparticles matrix may be obtained (Figure ). The above mechanism
may also be exploited to achieve high chemical sensing at RT under
light illumination. Once generated, the photoelectrons (e–) are mostly trapped on
the metal oxide surface, giving rise to reactive photoinduced oxygen
ions (as O2–). Hence, when reducing VOC molecules are purged into the chamber,
they can be oxidized by these oxygen ions releasing electrons back
to the conduction band of SnO2 and thus increasing the
film conductivity. A schematic illustration of such mechanism is reported
in Figure c.
Therefore, to highlight the intimate interaction between n>an class="Chemical">GO and
MOS nanoparticles, proving the existence of optimally integrated p–n
heterojunctions, EIS measurements were performed (Figure and Table ), investigating the glassy carbon/MOS/electrolyte
interfaces. The computed equivalent circuits are shown in Figure c. Remarkably, for
all the studied materials, a series resistor (RΩ, ca. 15–20 Ω cm2) was introduced to describe the electrolyte resistance and a Rct/constant phase element (CPEDL)
parallel circuit was necessary to model the electrode/electrolyte
double layer (Rct is the charge-transfer
resistance, whereas CPEDL represents a nonideal double-layer
capacitance). A CPE was used instead of a real capacitance because
of the presence of defects that introduce inhomogeneities in the electrical
material properties. Going into detail, the charge-transfer resistance
(Rct) at the solid–liquid interface
has similar values for the 32:1 SnO2–GO (0.90 kΩ
cm2) and GO (0.03 kΩ cm2), and it is much
smaller with respect to either the SnO2 (around 3.90 Ω
cm2) or the mechanically mixed, SnO2 +GO (ca. 3.76 Ω cm2, Table ) ones. Besides, the CPEDL is
very high for the conductive GO material (14 mF cm–2) and quite low for the bare SnO2 (ca. 0.2 mF cm–2). Interestingly, the hybrid materials
exhibit an intermediate behavior, resulting in capacitance of about
4 mF cm–2, which is higher than that of SnO2 +GO (2 mF cm–2, Table ). As already reported in previous works,[29,55,56] the impedance spectroscopy technique
can provide information about the actual presence of a p–n
heterojunction, modeling it as a parallel combination of resistance
(RHJ) and CPEHJ. In particular,
the former is connected to the leakage and recombination paths through
the p/n-type MOS interface, whereas the latter results from the nonideal
capacitance due to the depletion region of the p–n junction.
Remarkably, only for the 32:1 SnO2–GO, an additional RHJ/CPEHJ circuit was added to better
fit the EIS data. Finally, a third circuit (R1/CPE1, i.e., the polarization
capacitance) is present due to the interface between the powders and
the glassy carbon support. CPE1 values similar or higher
than that of the bare glassy carbon indicate the easiness of the polarization
processes, as in the case of GO and the hybrid material. Furthermore,
an open Warburg element (RW) was added
in the fitting circuits of GO, 32:1 SnO2–GO, and
mechanically mixed SnO2 +GO to take into account the probe
mass-transfer process. Hence, we can infer that 32:1 SnO2–GO EIS behavior is quite different from the one obtained
with the mechanically mixed SnO2 +GOcompound, thus resulting
in a peculiar and specific feature.
Figure 4
Impedance (a) Bode and (b) complex plane
plots recorded for glassy
carbon, GO, pure SnO2, 32:1 SnO2–GO,
and mechanically mixed SnO2 + GO recorded in 0.1 M phosphate-buffered
saline (PBS) at −0.15 V (potential at which the adopted probe,
[Ru(NH3)6]Cl3, is oxidized). Points
are the experimental values, while continuous lines are the simulated
data according to the equivalent circuits, shown in (c).
Table 3
EIS Fitting Parameters According to
the Computed Equivalent Circuits at −0.15 V. Supporting Electrolyte:
PBS 0.1 M, pH 7.4. Adopted Probe: [Ru(NH3)6]Cl3, 3 mM
modified-GCE
RΩ (Ω cm2)
Rct (kΩ cm2)
CPEDL (mF cm–2)
RHJ (Ω cm2)
CPEHJ (mF cm–2)
R1 (kΩ cm2)
CPE1 (mF cm–2)
RW (Ω cm2)
bare
21.9
2.95
1.4
-
-
2.0
2.0
-
GO
15.7
0.03
13.7
-
-
4.5
2.0
0.02
SnO2
20.2
3.90
0.2
-
-
2.4
2.1
-
32:1 SnO2–GO
20.5
0.90
4.0
3.6
0.03
2.5
2.2
0.05
SnO2 + GO
19.7
3.76
1.2
-
-
3.7
2.1
0.11
Impedanpan class="Chemical">ce (a) Bode and (b) complex plane
plots recorded for glassy
carbon, GO, pure SnO2, 32:1 SnO2–GO,
and mechanically mixed SnO2 +GO recorded in 0.1 M phosphate-buffered
saline (PBS) at −0.15 V (potential at which the adopted probe,
[Ru(NH3)6]Cl3, is oxidized). Points
are the experimental values, while continuous lines are the simulated
data according to the equivalent circuits, shown in (c).
Then,
to investigate the use of opan class="Chemical">ptoelectronic properties of the
SnO2–GO nanoheterojunctions for gas sensing, here,
ethanol, acetone, and ethylbenzenegases were chosen as VOC model
molecules. Figure a,d,g shows the sensor responses of the pure SnO2 and
the optimal 32:1 SnO2–GO nanoheterojunction as a
function of both OT and UV irradiation. Notably, at a high temperature
(350 °C) without UV light, both the pure and hybrid samples can
detect ethanol in air below to 2 and 10 ppbconcentrations, respectively.
Remarkably, for an ethanolconcentration of 1 ppm, the signal intensity
of 32:1 SnO2–GO is about 3 times higher than that
of SnO2 (Figure a,d). By decreasing the temperature to 150 and 25 °C,
only the nanoheterojunction was able to sense ethanol, even if light
irradiation was required (Figures g and S3a), whereas no response
was obtained for the bare oxidecompound at RT with and without light
irradiation. Notably, the 32:1 SnO2–GO had a very
good signal-to-noise ratio (SNR) down to 100 ppb at RT. Furthermore,
the selectivity of the materials was investigated using different
VOC molecules. Acetone and ethylbenzene were used as alternative VOCs
(Figures b,c,e,f,h,i
and S3). An analogous sensing behavior
was observed for these species, achieving detection at RT of 100 ppb.
However, the signal intensity was quite different (Figure S4a), thus resulting in a possible selective detection
of ethanol among the studied VOCs. Outstandingly, at RT, ethanol results
in the highest signal response intensity of ca. 2
at 1 ppm, while acetone and ethylbenzene showed a lower value of about
0.3 and 0.8, respectively. This trend may follow the VOCchemical
structure, that is, the presence of polar groups (such as hydroxyl
groups) or steric hindrance (as the phenyl ring), thus leading to
different affinities and reactivities with the oxide surface.[57−60] It has been previously reported that alcohols are highly sensed
by metal oxides rather than aldehydes or ketones and to a greater
extent with respect to nonpolar/low polar analytes, such as ethylbenzene.[59−62]
Figure 5
(a–c)
Pure SnO2 and (d–f) hybrid 32:1
SnO2–GO sensors response when exposed to different
low-ppm concentrations of ethanol, acetone, and ethylbenzene at 350
°C without UV light. (g–i) Same tests performed with hybrid
32:1 SnO2–GO materials at RT, UV-assisted. All the
measurements were carried out in simulated air (20% O2–80%
N2). OT = operating temperature.
(a–c)
Pure SnO2 and (d–f) hybrid 32:1
SnO2–GO sensors response when exposed to different
low-ppm concentrations of ethanol, acetone, and ethylbenzene at 350
°C without UV light. (g–i) Same tests performed with hybrid
32:1 SnO2–GO materials at RT, UV-assisted. All the
measurements were carried out in simulated air (20% O2–80%
N2). OT = operating temperature.Moreover, both SnO2 and 32:1 SnO2–GO
readily respond and recover upon purging these three analytes with
response and recovery times below 80 s at 350 °C (Figure S4b,c). Reducing the OT increases the
response time by three/four times, depending on the VOC molecule.Additionally, as pan class="Chemical">clearly visible in Figure g–i, notwithstanding the worst opn>erative
conditions (RT and UV light), the profile of the sensing curves is
satisfactory. To clarify this point, we computed the SNR for 32:1
SnO2–GO, as a representative example, toward the
three VOCs at RT. SNRs were calculated using the following equation[63]where signalmax is the maximum
intensity of the signal and σbaseline is the standard
deviation in the resistance baseline before the analyte flux (calculated
on at least 10 data points). Considering the limit of detection of
100 ppb (as the lowest detectable concentration at 25 °C), the
SNRs values of 65, 70, and 40 toward ethanol, acetone, and ethylbenzene,
respectively, were obtained.
Hence, we can conclude that our
results are robust and fully in
agreement with those already reported in the literature[63] for optimal VOC sensing materials, evidencing
that a very low detection limit can be reached toward the three investigated
VOCs, even at RT, by using our nanoheterojunctions.A comparative
summary of the SnO2–GO sensing
performances with literature data about SnO2-based chemoresistors[2,14,15,64,65] is reported in Table . Interestingly, all the nanoheterojunctions,
synthesized here, have superior performance than some of the best
already reported. In particular, the 32:1 SnO2–GO
exhibits significantly higher signal intensity with a very low limit
of detection and high sensitivity even at RT.[15,65]
Table 4
Comparison of SnO2-Based
Material Sensing Performances toward the Three Investigated VOCs
material
operating
temperature (°C)
VOC
signal response, (Rair/Ranalyte)–1b
LODa (ppb)
refs
hollow SnO2
300
EtOH
28.2 (100 ppm)c
5000
(18)
rGO–SnO2
300
EtOH
42.0 (100 ppm)c
5000
(15)
acetone
11.0 (100 ppm)c
–
(15)
0.1 wt % GO/SnO2 nanocomposite
250
EtOH
22.5 (50 ppm)
1000
(17)
SnO2 hollow spheres
200
acetone
15.0 (50 ppm)c
5000
(19)
Rh-doped SnO2 nanofibers
200
acetone
59.6 (50 ppm)c
1000
(64)
3% CuO/SnO2
280
EtBz
7.0 (50 ppm)c
2000 of BTEX
(4)
SnO2
350
EtOH
2.0
2
this work
acetone
1.8
10
this work
EtBz
1.5
10
this work
32:1 SnO2–GO
350
EtOH
5.1
10
this work
acetone
12.5
5
this work
EtBz
7.2
20
this work
RT
(UV)
EtOH
2.0
100
this work
acetone
0.4
100
this work
EtBz
0.8
100
this work
4:1 SnO2–GO
350
EtOH
0.1
100
this work
acetone
0.6
100
this work
EtBz
0.4
100
this work
RT (UV)
EtOHd
0.006
1000
this work
acetone
–0.1
100
this work
EtBz
–0.6
100
this work
LOD, limit of detection.
Always referred to 1 ppm, otherwise
stated.
Calculated from
data reported in
the reference.
Ref (28).
LOD, limit of detepan class="Chemical">ction.
Always referred to 1 ppm, otherwise
stated.Calculated from
data reported in
the reference.Ref (28).The feasibility of tuning the pan class="Chemical">chemical response of
the nanoheterojunctions
by engineering their composition was further obtained correlating
their sensing response at a constant VOCconcentration. Figure shows a comparison of responses
at 1 ppm relative to different nanoheterojunctions composed of 32:1
SnO2–GO, 32:1 ZnO–GO, previously reported,[29] and 4:1 SnO2–GO. Interestingly,
the 32:1 SnO2–GO has significantly higher ethanol
selectivity than the other species, showing a response of about 4
times higher than that of acetone. These results show that at a constant
relative GO amount, tin dioxide is more selective to ethanol and has
significantly higher sensitivity than zinc oxidecontaining the nanoheterojunction.
This may be attributed to the grain boundary density of the two nanoheterojunctions.
The change in material resistance depends mainly from the ratio between
the grain size (d) and the Debye length (δ).[66] If d is slightly lower or equal
to 2δ, the whole grains are depleted and change in the surface
oxygen speciesconcentration can affect the entire grain, resulting
in higher sensitivity. Here, the particle sizes of both SnO2–GO (∼5–8 nm) and ZnO–GO (∼50
nm[29]) compounds are very close to twice
the Debye length of tin dioxide (∼3 nm[65,67,68]) and zinc oxide (∼30 nm[69]), respectively. Therefore, an improvement of
the sensing behavior is expected. However, in the case of zinc oxide,
Bo et al.[34] recently reported that the
further increase of ZnO nanoparticle dimensions beyond 42 nm does
not help to enhance the optoelectronic features. This is mainly ascribed
to the slightly greater backscattering phenomena, causing reduced
photosensing performances. Furthermore, in the case of acetone and
to a greater extent for ethylbenzene, we observed a reversed change
in conductance with the 4:1 SnO2–GO sample. This
phenomenon is reported to be typical of MOS operating at low temperatures
because of a greater amount of adsorbed oxygen species,[70] leading to a more hydrophilic surface. In this
sample, indeed, the incomplete GOcoverage results in a greater adsorption
of oxygen species and moisture with respect to the 32:1 SnO2–GO. In order to demonstrate the conductivity switching at
low temperature, tests at high temperatures were carried out (Figure S5). We observed that the signals both
for acetone and ethylbenzene switch from negative to positive values
by rising up the OT above 150 °C, along with an increase in the
relative intensities. Because this behavior was observed for ethylbenzene
molecules only in the case of 4:1 SnO2–GO nanoheterojunction,
it can be used as a tool to selectively sense this species at RT.
Figure 6
Comparison
among 32:1, 4:1 SnO2–GO, and previously
reported 32:1 ZnO–GO sensors[29] in
terms of signal response intensity to 1 ppm of NO2, ethylbenzene,
acetone, and ethanol at 25 °C under UV irradiation.
Comparison
among 32:1, 4:1 SnO2–GO, and previously
reported 32:1 ZnO–GO sensors[29] in
terms of signal response intensity to 1 ppm of NO2, ethylbenzene,
acetone, and ethanol at 25 °C under UV irradiation.Moreover, to further investigate both the selectivity of
our hybrid
materials to VOCcompounds and the interference of water vapor molecules,
sensing tests at RT toward NO2gas on the one hand and
at RH on the other hand were carried out.pan class="Chemical">Concerning the former,
as shown in Figure S6, all the three best
performing compounds, 32:1 SnO2–GO,
32:1 ZnO–GO, and 4:1 SnO2–GO, exhibited a
response to 1 ppm of NO2. As expected for oxidizing species,
we observed a current decrease in the presence of nitrogen dioxide.
Notably, the signal intensity is at least around 4 times lower than
the one achieved toward VOC species, confirming the higher selectivity
(Figure ). By using
the best performing 32:1 SnO2–GO material composition,
sensing measurements toward the three VOCs were performed at RH of ca. 80%. Figure S7 exhibits a
significant decrease (50% at most) of the sensor response to all the
three target gases. However, the relative selectivity toward ethanol
was preserved, indicating that with an appropriate parallel measurement
of the humidity level, these materials have potential for translation
into commercial devices.
As a result, tailoring of the GOcontent
in a 3D SnO2 network enables to achieve high sensitivities
and selectivities
toward different VOCs at RT.
Conclusions
Herein,
we supan class="Chemical">cceeded in engineering the optoelectronic performance
of SnO2–GO nanoheterojunctions for the selective
and sensitive measurement of VOCs at RT. The effective integration
of the carbonaceous material into the metal oxide network was confirmed
by XRD, Raman, XPS, and high-resolution TEM analyses. Highly porous
film structures, with an average thickness of around 1.5 μm,
were obtained by depositing the SnO2–GO nanodomains
onto Pt-IDEs by a scalable air-spraying method. The enhancement of
the sensing performance over that of the bare SnO2 is attributed
to the relative fraction of p(GO)–n(SnO2) nanodomains,
which promotes the electron–hole separation. Hence, by exploiting
impedance measurements, an additional RHJ/CPEHJ circuit was introduced to verify and corroborate
this unique behavior. Notably, we observed that the fine control of
the GO amount in the SnO2 nanoparticle network is a potential
path to tune the selectivity to VOCs. A low GOcontent results in
an enhanced UV light responsivity of ca. 400 A W–1, with short 120 and 100 s rise and decay times, and
RT detection of below 100 ppb of ethanol, with good selectivity against
other VOCs such as acetone and ethylbenzene. Conversely, a high amount
of GO hinders the ethanol response at RT, enhancing an opposite change
of conductivity and selectivity to ethylbenzene. We proposed that
selectivity switching mechanism is mainly due to the different surface
compositions of the 4:1 SnO2–GO nanoheterojunction.
The latter has a highly more hydrophilic surface than that of 32:1
SnO2–GO, resulting in the adsorption of moisture
and hydroxyl groups at RT, which can compete with the target VOCs
for adsorption sites. Moreover, further tests were carried out to
investigate both the selectivity toward other interfering gases, such
as nitrogen dioxide, and the role played by water vapor molecules.
We observed a significantly decreased response to NO2,
which is at least 4 times lower than the one obtained toward VOC species.
Second, a RH of about 80% led to a remarkable decrease of response
intensity, even if both sensitivity and selectivity were preserved.
We believe that these findings provide guidelines for the engineering
of miniaturized chemoresistive sensors for selective RT detection
of various VOCs. The excellent performance of the SnO2–GO
nanoheterojunctions as UV photodetectors also provides a tunable low-cost
material for the fabrication of optoelectronic devices for various
applications.
Authors: Amel Bajtarevic; Clemens Ager; Martin Pienz; Martin Klieber; Konrad Schwarz; Magdalena Ligor; Tomasz Ligor; Wojciech Filipiak; Hubert Denz; Michael Fiegl; Wolfgang Hilbe; Wolfgang Weiss; Peter Lukas; Herbert Jamnig; Martin Hackl; Alfred Haidenberger; Bogusław Buszewski; Wolfram Miekisch; Jochen Schubert; Anton Amann Journal: BMC Cancer Date: 2009-09-29 Impact factor: 4.430