Rapelang G Motsoeneng1,2, Ioannis Kortidis1, Suprakas Sinha Ray1,2, David E Motaung1,3. 1. DST-CSIR National Centre for Nano-Structured Material, Council for Scientific Industrial Research, Pretoria 0001, South Africa. 2. Department of Chemical Sciences, University of Johannesburg, Johannesburg, Gauteng 2006, South Africa. 3. Department of Physics, University of the Free State, P.O. Box 339, Bloemfontein ZA9300, South Africa.
Abstract
The application of metal oxide-based sensors for the detection of volatile organic compounds is restricted because of their high operating temperatures and poor gas sensing selectivity. Driven by this fact, we report the low operating temperature and high performance of C3H7OH and C2H5OH sensors. The sensors comprising SnO2 hollow spheres, nanoparticles, nanorods, and fishbones with tunable morphologies were synthesized with a simple hydrothermal one-pot method. The SnO2 hollow spheres demonstrated the highest sensing response (resistance ratio of 20) toward C3H7OH at low operating temperatures (75 °C) compared to other tested interference vapors and gases, such as C3H5O, C2H5OH, CO, NH3, CH4, and NO2. This improved response can be associated with the higher surface area and intrinsic point defects. At a higher operating temperature of 150 °C, a response of 28 was witnessed for SnO2 nanorods. A response of 59 was observed for SnO2 nanoparticle-based sensor toward C2H5OH at 150 °C. This variation in the optimal temperature with respect to variations in the sensor morphology implies that the vapor selectivity and sensitivity are morphology-dependent. The relation between the intrinsic sensing performance and vapor selectivity originated from the nonstoichiometry of SnO2, which resulted in excess oxygen vacancies (VO) and higher surface areas. This characteristic played a vital role in the enhancement of the target gas absorptivity and the charge transfer capability of SnO2 hollow sphere-based sensor.
The application of metal oxide-based sensors for the detection of volatile organic compounds is restricted because of their high operating temperatures and poor gas sensing selectivity. Driven by this fact, we report the low operating temperature and high performance of C3H7OH and C2H5OH sensors. The sensors comprising SnO2 hollow spheres, nanoparticles, nanorods, and fishbones with tunable morphologies were synthesized with a simple hydrothermal one-pot method. The SnO2 hollow spheres demonstrated the highest sensing response (resistance ratio of 20) toward C3H7OH at low operating temperatures (75 °C) compared to other tested interference vapors and gases, such as C3H5O, C2H5OH, CO, NH3, CH4, and NO2. This improved response can be associated with the higher surface area and intrinsic point defects. At a higher operating temperature of 150 °C, a response of 28 was witnessed for SnO2 nanorods. A response of 59 was observed for SnO2 nanoparticle-based sensor toward C2H5OH at 150 °C. This variation in the optimal temperature with respect to variations in the sensor morphology implies that the vapor selectivity and sensitivity are morphology-dependent. The relation between the intrinsic sensing performance and vapor selectivity originated from the nonstoichiometry of SnO2, which resulted in excess oxygen vacancies (VO) and higher surface areas. This characteristic played a vital role in the enhancement of the target gas absorptivity and the charge transfer capability of SnO2 hollow sphere-based sensor.
The
intensification of environmental pollution due to industrialization,
fuel burning, agriculture, and leakage of poisonous gases is a threat
to human life.[1] A timely discovery and
the monitoring of toxic and harmful gases are essential for the environmental
protection.[2] Recently, gas sensors based
on semiconductor metal oxides (SMOs) have become one of the most dominant
research topics owing to their resistance change induced by the interaction
of gas and solid materials on the surface of the semiconductors.[3,4] Additionally, metal oxide (MO) can be readily synthesized with various
methods (e.g., physical and chemical methods). Various MO nanostructure
morphologies have been synthesized, for example, nanobelts, nanowires,
nanoflowers, nanoribbons, and nanosheets.[5,6] However,
the morphology control remains an important problem in the gas sensing
field.[6−8] Among the SMO group (e.g., SnO2, ZnO,
TiO2, Fe2O3, and WO3),
SnO2 is the most commonly used MO for gas sensing applications
owing to its optimal gas sensing properties and excellent chemical
and thermal stability.[5,8,9] The
material is considered to be an n-type SMO because of the surface
oxygen deficit. Thus, the material exhibits sufficient oxygen vacancies
(VO) that act as electron donors.[10]The low selectivity and high operational temperature (≥300
°C) of pure SnO2-based gas sensors[11,12] might result in long-term problems caused by MO grain boundaries.
Recently, much effort has been dedicated to altering the sensing material
through doping or coupling with noble, transitional, or additional
MOs because of their various chemical properties and electronic structures,
which can result in higher sensitivities and selectivities compared
to those of individual MO constituents.[13−18] An additional second constituent that acts as the energetic material
enhances the degree of the redox reaction with the target gases. Hyodo
et al.[14] reported the gas sensing characteristics
of Pd-dopedSnO2 at room temperature for NO2 under UV light. For a UV light of 7 mW cm–2, 0.05Pd-dopedSnO2 exhibited an enhanced response toward the gas. Hu et al.[15] reported the formaldehyde (HCHO)
gas sensing characteristics of Ni-dopedSnO2 materials
synthesized via a one-step hydrothermal route and tested at 200 °C.
They observed that the appropriate incorporation of Ni into SnO2 led to ten times improved sensing of HCHO. Kim et al.[19] reported a near room working
temperature and fast response triethylamine gas sensor using Au-loaded
ZnO/SnO2core–shell nanorods. Jeong et al.[20] reported improved sensing response for 0.3 wt
% Pt-dopedSnO2 hollow nanospheres toward 30 ppm ethanol.
The response was approximately seven times greater than that of pristine
SnO2. Motaung et al.[21] observed that when the Co3O4 hollow
spheres synthesized by ultrasonic spray pyrolysis was converted into
Co3O4–SnO2core–shell
hollow spheres by galvanic replacement, the gas selectivity could
be tuned by varying the amount of SnO2 shells (14.6, 24.3,
and 43.3 at. %) and operating temperatures. According to Motaung et
al.,[21] Co3O4 sensors
retain a capability to selectively distinguish ethanol vapor at 275
°C. By increasing the amount of SnO2 shells to 14.6
and 24.3 at. %, very selective detection of xylene and methylbenzenes
(xylene + toluene) was realized at 275 and 300 °C, respectively.
Previous reports[21−23] have indicated that VO has a crucial impact
on the gas sensing properties. By enhancing the relative concentration
of VO (i.e., providing more active sites), superior sensing
performances can be achieved. The VO surface defects can
considerably improve the absorptivity for the target gas and the charge
transfer capability of SnO2.[22−58]Despite the amount of work existing on the
SnO2 hollowsphere
gas sensing, however, to the best of our knowledge, no reports exist
on the C3H7OH sensing properties of SnO2 hollow spheres at low operating temperatures (75 °C).
Few or no studies exist, showing a clear correlation between the vapor
gas sensing and point defects extracted using electron spin resonance.
Accordingly, we report for the first time the unique C3H7OH sensing characteristics of SnO2 hollow
sphere nanostructures prepared via a hydrothermal method. Moreover,
the C2H5OH gas sensing properties were investigated
for a SnO2 nanoparticle-based sensor. In a controlled manner,
nanostructures with different morphologies such as hollow spheres,
nanoparticles with two different sizes, nanoplatelets, nanorods, and
fishbones were prepared. More importantly, this study explains how
to determine the organic vapor sensing characteristics of these nanostructures
in detail. Further, the relation between the defect type, SnO2 structure, and vapor selectivity was studied. The intrinsic
sensing performance of the SnO2 hollow spheres was investigated
via X-ray photoelectron spectroscopy (XPS) and electron paramagnetic
resonance (EPR). The EPR, XPS, and photoluminescence (PL) analyses
reveal that VO is the dominant structure defects. Extraordinarily,
the intensity of the paramagnetic signal related to VO is
enhanced for the hollow spheres, which is in good agreement with the
sensing response.
Results and Discussion
SnO2 Nanostructure Characterization
Scanning
electron microscopy (SEM) was used to determine the morphology
and structure of the as-prepared SnO2 nanostructures. Figure shows the SEM images
of the SnO2 nanostructures prepared with sodium hydroxide
(NaOH) and hexamethylenetriamine (HMT). At lower temperatures (Figure a), the nucleation
stage occurred, Sn (OH)62– nuclei were
created, and the greatest number of nuclei were formed in the solution
in which the nuclei attracted species and other surrounding nuclei
to form bigger spheres (hollow spheres). Between 24 and 48 h at 200
°C, the hollow spheres decomposed to small nanoparticles (Figure b), which later agglomerated
to form bigger clusters of nanoparticles (Figure c).
Figure 1
SEM images of SnO2 nanostructures
after (a) 24 h hydrolysis,
(b) 24 h in an autoclave, (c) 48 h in an autoclave at 200 °C,
and (d) 12 h and (e) 24 h with HMT.
SEM images of n class="Chemical">SnO2 nanostructures
after (a) 24 h hydrn class="Chemical">olysis,
(b) 24 h in an autoclave, (c) 48 h in an autoclave at 200 °C,
and (d) 12 h and (e) 24 h with HMT.
Because of the size of the nanoparticles, we, therefore, labeled
them as less agglomerated (LA) nanoparticles and more agglomerated
(MA) nanoparticles. The addition of HMT as a surfactant at 200 °C
for 12 h resulted in self-assembled nanoparticles, that is, the formation
of flower-like SnO2 nanorod bundles (Figure d) disclosing a square-shaped structure.
The width of the nanorods is approximately 120 nm. When the time was
increased from 12 to 24 h at 200 °C, the formation of fishbone
structures was observed (Figure e), which resulted from the growth of the flower-like
nanorod bundles.To validate the SEM results, low-resolution
transmission electron
microscopy (TEM) analyses were conducted. As shown in Figure a, hollow spheres with average
diameters of 150 nm and wall thicknesses of approximately 20–40
nm are observed. Figure b,c reveals tiny and slightly bigger nanoparticles. Nanorods with
flower-like structures are presented in Figure d, and fishbone-like structures exist in Figure e. The trunk diameter
is approximately 80 nm, and the rod connected to the trunk has a diameter
of approximately 20 nm.
Figure 2
TEM images of SnO2 nanostructures:
(a) hollow spheres,
(b) LA nanoparticles, (c) MA nanoparticles, (d) nanorods, and (e)
fishbones, after (a) 24 h hydrolysis, (b) 24 h in autoclave, (c) 48
h in autoclave, and (d) 12 h and (e) 24 h with HMT.
TEM images of SnO2 nanostructures:
(a) hollow spheres,
(b) LA nanoparticles, (c) MA nanoparticles, (d) nanorods, and (e)
fishbones, after (a) 24 h hydrolysis, (b) 24 h in autoclave, (c) 48
h in autoclave, and (d) 12 h and (e) 24 h with HMT.The high-resolution (HR)-TEM images and selected area electron
diffraction (SAED) patterns of various synthesized SnO2 nanostructures are shown in Figure a–e. The Debye rings of the hollow spheres and
LA nanoparticles are more diffused compared to those of the other
nanostructures. However, with increasing particle sizes, the Debye
rings become brighter according to Figure c. Moreover, the nanorods exhibit single-crystal
properties in Figure d. By contrast, the nanostructures of the fishbones and nanoplatelets
are highly polycrystalline. The observed d-spacing
of approximately 0.3347 nm is attributed to the (110) plane of tetragonal
rutile SnO2.
Figure 3
TEM images and SAED patterns of SnO2 nanostructures:
(a,a′) hollow spheres, (b,b′) LA nanoparticles, (c,c′)
MA-nanoparticles, (d,d′) nanorods, and (e,e′) fishbones
after (a) 24 h hydrolysis, (b) 24 h in autoclave, (c) 48 h in autoclave,
and (d) 12 h and (e) 24 h with HMT.
TEM images and SAED patternpan>s of SnO2 nanostructures:
(a,a′) hollow spheres, (b,b′) LA nanoparticles, (c,c′)
MA-nanoparticles, (d,d′) nanorods, and (e,e′) fishbones
after (a) 24 h hydrolysis, (b) 24 h in autoclave, (c) 48 h in autoclave,
and (d) 12 h and (e) 24 h with HMT.The crystalline structure and phase purity of the products were
determined with the X-ray diffraction (XRD) technique. The crystal
orientation plays an imperative role in surface-related applications
such as gas sensing owing to the high density of atomic steps, edges,
and ample unsaturated coordination sites. In Figure , the XRD patterns of the samples obtained
under different hydrothermalconditions display the peak positions
that match well with the standard data with a = b = 0.4738 nm and c = 0.3188 nm (JCPDS
card no. 041-1445). No other phases can be observed for SnO2. Hence, the as-prepared nanomaterials had a pure rutile SnO2 structure. All diffraction peaks can be indexed to the tetragonal
rutile SnO2 phase with a = b = 0.4748 nm and c = 0.3817 nm. The most prominent
peaks of these nanostructures correspond to the (110), (101), and
(211) crystal lattice planes. It is further evident in Figure b that XRD patterns shift depending
on the structure of SnO2.
Figure 4
(a) XRD patterns of various as-prepared
SnO2 nanostructures.
(b) Magnified at the (101) diffraction peak. LA nanoparticles, less
agglomerated nanoparticles; MA nanoparticles, more agglomerated nanoparticles.
(a) XRD patterns of various as-prepared
SnO2 nanostructures.
(b) Magnified at the (101) diffraction peak. LA nanoparticles, less
agglomerated nanoparticles; MA nanoparticles, more agglomerated nanoparticles.Regarding the tetragonal rutile structure of SnO2, the
interplanar space d( is related to the lattice parameter viaWith a and c being lattice
constants.
The lattice constants can be calculated withAs listed in Table , various nanostructures depending on the morphology show
different
sizes of the crystallites, where then nanoparticle reveals smaller
crystallites compared to the rest of the samples.
Table 1
2θ, Crystal Size, and d-Spacings of Various
Nanostructures for the (110) Diffraction
Peak
SnO2
2θ (deg)
D (nm)
a = b (nm)
c (nm)
hollow spheres
26.684
10.80
0.4720
0.3346
LA particles
26.566
6.80
0.4692
0.3123
MA particles
26.849
7.73
0.4680
0.3155
rods
26.711
19.60
0.4715
0.3170
fishbones
26.701
12.60
0.4737
0.3188
It is well known that
the gas sensor properties are also dependent
on the surface area and porosity of the SMO. Thus, nitrogen adsorption–desorption
analyses were carried out. The results are shown in Figure . According to the IUPAC classification,
the nitrogen adsorption–desorption isotherms of the hollow
spheres and MA nanoparticles exhibit type IV isotherms.[25] The LA nanoparticles and nanorods have typical
type III isotherms. At a relative pressure (P/P0) of 0.5–1.0, the presence of large
mesopores or macropores is observed. The amount of absorbed N2 increases with increasing pressure. Hence, the nanostructures
possessed mesoporous structures. It evident that the desorption curves
are slightly lower than the adsorption curve, especially for the fishbones,
and such behavior could be due to poor pore volume. The pore size
distribution investigated with the Barrett–Joyner–Halenda
(BJH) method is shown in the insets of Figure . The pore sizes differ for the different
morphologies of the nanostructures. Regarding the hollow spheres,
high specific surface areas of 195.86 m2 g–1 and pore volumes of approximately 0.2625 cm3 g–1 are observed. These findings suggest that the higher surface area
and pore volume found for hollow spheres make them possible candidates
for use in gas sensors.
Figure 5
Nitrogen adsorption–desorption isotherm
and BJH pore size
distributions (insets) of various SnO2 nanostructures.
(a) Hollow spheres, (b) LA nanoparticles, (c) MA nanoparticles, (d)
fishbones, and (e) nanorods.
Nitrogen adsorption–desorption isotherm
and BJH pore size
distributions (insets) of various SnO2 nanostructures.
(a) Hollow spheres, (b) LA nanoparticles, (c) MA nanoparticles, (d)
fishbones, and (e) nanorods.The HR XPS spectra for Sn 3d in Figure exhibit two peaks at approximately 486.9–4877
and 495.4–496.1 eV, which are assigned to Sn 3d5/2 and Sn 3d3/2, respectively.[26,27] These two symmetric peaks are associated with the spin–orbit
coupling of the 3d state with a spin–orbit separation of 8.4
eV and a spin–orbit branching ratio of 1.34. This observation
is in good agreement with Lee et al.[28] The single peak observed in the Sn 3d5/2 region
(486.9–4877 eV) of all different nanostructures indicates that
the samples have a Sn(IV) (Sn4+) state with no visible
Sn2+, which is anticipated to appear at 485.8 eV. The observed
peak shift is related to the morphology change as observed in Figure
S1a (Supporting Information).
Figure 6
Sn 3d spectra
of various SnO2 nanostructures: (a) hollow
spheres, (b) LA nanoparticles, (c) MA nanoparticles, (d) nanorods,
and (e) fishbones.
Sn 3d spectra
of various SnO2 nanostructures: (a) hollow
spheres, (b) LA nanoparticles, (c) MA nanoparticles, (d) nanorods,
and (e) fishbones.The XPS spectra were
produced to determine the chemicalcomposition
of the materials. Figure illustrates the HR XPS spectrum of oxygen. Based on the measured
binding energy, the asymmetric shape of the spectrum indicates several
chemical states. Therefore, the O 1s peaks can be deconvoluted into
three peaks, as shown in Figure . For instance, the hollow spheres have three peaks
at 531.4, 532.4, and 533.1 eV, whereas other morphologies including
the nanoparticles and nanorods have three peaks centered at 530.9,
531.4, and 532.5 eV. The lower binding energies of 530.9 and 531.4
eV, respectively, correspond to O2– ions in the
SnO2 lattice (OL) and O2– ions
in the oxygen deficiency region within the SnO2 matrix
(Ov), which corresponds to VO.[29,30] The peak at 533 eV is accredited to chemisorbed and dissociated
oxygen species (i.e., O– and O2–) in the surface of the SnO2 nanostructures (OS).[31] From the Supporting Information, Figure S1b, it is observed that O 1s peaks shift
depending on the structure of SnO2, and such shifting was
previously observed from the XRD patterns in Figure b.
Figure 7
O 1s XPS spectra of various SnO2 nanostructures:
(a)
hollow spheres, (b) LA nanoparticles, (c) MA nanoparticles, (d) nanorods,
and (e) fishbones.
O 1s XPS spectra of various SnO2 nanostructures:
(a)
hollow spheres, (b) LA nanoparticles, (c) MA nanoparticles, (d) nanorods,
and (e) fishbones.To further confirm the
creation of the VO and oxygen
deficiency centers in the sensing and response mechanism of SnO2, an EPR analysis was conducted (Figure ). The hollow spheres, LA nanoparticles,
MA nanoparticles, and fishbones in Figure show a single broad resonance peak located
at the g-factors of 1.8991, 2.0041, and 2.0161, respectively.
The nanorods show two peaks located at the g-factors
of 2.0023 and 2.1418. The signal at approximately 2.1 is related to
superoxide radical O2–, which forms owing
to the transfer of electrons trapped in VO to the adsorbed
oxygen molecules in the SnO2 surface.[29] The observed resonances at 1.8991–2.0 are attributed
to unpaired electrons trapped in singly ionizedVO.[30−34] The hollow spheres show the highest signal. Thus, they possess high
quantities of defects, as confirmed by the PL (see the Supporting Information, Figure S2) and XPS measurements.
Such higher defect concentrations could be beneficial for gas sensing
applications.
Figure 8
(a) Electron spin resonance spectra of various SnO2 nanostructures
and (b) magnified spectra.
(a) Electronspin resonpan>ance spectra of various SnO2 nanostructures
and (b) magnified spectra.
Electrical and Gas Sensing Properties
The
MO gas sensor response is predominantly governed by the interaction
between the analyte gas and oxygen species on the sensor surface.
Therefore, the morphology, surface area, and defect states severely
impact the sensing properties. Moreover, the responses of gas sensors
based on MO materials are intensely affected by the operating temperature.[35] To determine the optimal operating temperature,
the performance of various SnO2 nanostructures was tested
with various gases (e.g., CO, CH4, NO2, and
NH3) and volatile organic compounds (e.g., C3H7OH, C2H6O, and C3H6O) at 75, 150, and 225 °C.Among the tested sensors,
the hollow spheres have the strongest response toward C3H7OH at a low operating temperature (75 °C). The
hollow spheres exhibit a response value of 15, which is five times
higher than those of the others at this temperature. Previous studies[36,37] have indicated that alcohols with increased −CH2– groups are effortlessly decomposed and oxidized compared
to those with lesser one. Consequently, C3H7OHcontaining the maximum number of −CH2–
groups is simply decomposed. Therefore, it reacts efficiently with
the adsorbed oxygen molecules, resulting in a release of electrons,
consecutively, enhancing the sensing response. This explains the high
response of the film in the presence of propan-2-ol, followed by ethanol
and methanol, respectively. To the best of our knowledge, a response
value of 15.8 of pure SnO2 for C3H7OH vapor at 75 °C is one of the highest response values that
have ever been reported.[38] The sensors
with low operating temperatures not only reduce costs but also increase
the life span of sensors without compromising stability. However,
for an operating temperature of 150 °C, the nanorod-based sensor
reveals a higher response toward C2H5OH. This
clearly indicates a shift in the optimal temperature among sensors
with varying morphologies. Thus, the optimal temperature is morphology-dependent.
As a result, the operating temperatures of 75 and 150 °C were
selected for SnO2 hollow spheres and nanorod-based sensors
for various concentrations of C3H7OH and C2H5OH vapors.The resistance change of the
various SnO2-based sensors
with respect to C2H5OH is shown in Figure . All sensors display
the typicaln-type gas sensing behavior. The different morphologies
have substantial effects on the baseline resistance of the gas sensors.
The resistances of the nanorods and fishbones are higher in the air
in comparison to those of the other nanostructures. Furthermore, regardless
of the C2H5OHconcentration, the resistance
of the SnO2-based sensors recovers to the baseline level
after the C2H5OH flow stops. The response and
recovery times of 110 and 90 s were noticed for the hollow spheres
toward C3H7OH, while the response and recovery
times of 105 and 100 s were witnessed for the LA nanoparticles toward
C2H5OH, respectively.
Figure 9
(a) Response vs operating
temperatures of SnO2-based
sensors exposed to 40 ppm of C3H7OH and C2H5OH. (b) Dynamic resistance curves of various
SnO2-based sensors upon exposure to 10–100 ppm C2H5OH at 150 °C. (c) Real-time response of
various SnO2-based sensors toward C2H5OH vapor.
(a) Response vs operating
temperatures of SnO2-based
sensors exposed to 40 ppm of C3H7OH and C2H5OH. (b) Dynamic resistance curves of various
SnO2-based sensors upon exposure to 10–100 ppm C2H5OH at 150 °C. (c) Real-time response of
various SnO2-based sensors toward C2H5OH vapor.Figure shows
the responses versus the C3H7OH and C2H5OH gas concentrations at 75 and 150 °C, respectively.
The SnO2 hollow spheres exhibit an exponential increase
in the response to 10–40 ppm of C3H7OH.
It is well known that SnO2 exhibits a great response at
elevated temperatures (>200 °C).[37−40] Nonetheless, the presented performance
of the pure SnO2 hollow spheres at 75 °C is even better
than in other reports (Table ). Tan et al.[39] reported response values of approximately 19 for pure SnO2 nanoparticles at 300 °C toward 100 ppm ethanol.
Figure 10
Response
vs gas concentrations of (a) C3H7OH and (b)
C2H5OH at 75 and 150 °C, respectively.
Table 2
Comparison of Gas Sensing Performances
of SnO2-Based Sensors for C3H7OH
and C2H5OH
sensing element
synthesis
method
gas
gas concentration
(ppm)
operating
temperature (°C)
response
refs
SnO2 hollow spheres
hydrothermal
C3H7OH
40
75
20.1
this work
SnO2 LA nanoparticles
hydrothermal
C2H5OH
40
150
59.6
this work
SnO2 nanoparticles
hydrothermal
C3H7OH
500
100
9.8
(41)
SnO2 nanoparticles
hydrothermal
C3H7OH
17
220
32
(42)
1.7
6
SnO2 nanoparticles
hydrothermal
C2H5OH
500
100
14.6
(43)
SnO2 nanoparticles
quasi-molecular cluster
C2H5OH
100
300
8.9
(38)
SnO2 nanowires
quartz tube method
C2H5OH
50
400
7.1
(44)
Response
vs gas concentrations of (a) C3H7OH and (b)
C2H5OH at 75 and 150 °C, respectively.Table (41−44) compares the results of the current study with those
reported in
the literature for SnO2 sensors tested on C3H7OH and C2H5OH, respectively. Please
note that most reported SnO2-based sensors were prepared
via the hydrothermal method, which allows a clear comparison with
our results. The gas response of the SnO2 hollow spheres
and nanoparticles toward C3H7OH and C2H5OH is higher than those of the sensors listed in Table for a low operating
temperature.The selectivity of the SnO2 sensors
with respect to
various target vapors and gases (e.g., C3H7OH,
C2H5OH, CO, NH3, CH4,
and NO2) is shown in Figure . All sensors were tested with similar gas
concentrations (40 ppm) and at two different working temperatures
(75 and 150 °C). At 75 °C, the SnO2 hollow sphere-based
sensor exhibits a significantly higher response to C3H7OHcompared with the other sensors (see Figure a). However, at 150 °C,
the SnO2 nanoparticle-based sensor reveals an improved
response toward C2H5OH vapor. Thus, the operating
temperature affects the selectivity of the MO gas sensor (Figure b). The high response
to C3H7OH might be due to the highest number
of (−CH2−) groups, which decompose more easily
and result in greater changes in the free-carrier density within the
SnO2 structure.[45]
Figure 11
Selectivity
histograms of SnO2-based sensors exposed
to various gases at (a) 75 and (b) 150 °C; (c,d) response ratio
for C3H7OH and C3H5OH
with respect to other five interfering gases (40 ppm) at various operating
temperatures.
Selectivity
histograms of SnO2-based sensors exposed
to various gases at (a) 75 and (b) 150 °C; (c,d) response ratio
for C3H7OH and C3H5OH
with respect to other five interfering gases (40 ppm) at various operating
temperatures.For quantification, the cross
selectivity was calculated using
the equation: S = Sa/Sb, where Sa and Sb are the responses of a sensor toward a target
and the interfering gases, respectively.[46−48]Figure c,d illustrates the cross
selectivity of the SnO2 hollow sphere- and LA nanoparticle-based
sensors for C3H7OH and C2H5OH with respect to the interference gases, respectively. The response
ratios of the hollow spheres of C3H7OH to C2H5OH and of the LA-nanoparticles of C2H5OH to NO2 are relatively large (1450 and
1140, respectively). In this study, NH3 and NO2 act as prospectively strong interfering gases. Therefore, the respective
response ratios are considered as the influence parameters to evaluate
the cross selectivity of the hollow spheres.To study the stability
of the hollow sphere- and nanorod-based
sensors, repeatability and long-term stability analyses were carried
out. Figure a shows
the repeatability performance of the sensor for eight successive cycles
toward 40 ppm C3H7OH for three weeks. On day
one, the fresh sensor exhibits evident repeatability of six consecutive
periods for 40 ppm C3H7OH. However, after seven
days, the repeatability performance remains constant, whereas the
response decreases, as confirmed by the stability plot in Figure b. This behavior
is also observed after 23 days, where the response decreases by 88.1%
with respect to the original value. It is further observed that the
LA nanoparticle response decreases rapidly by 37% after 7 days, while
after 23 days, the response dropped by 86.7%. However, we have found
that upon incorporating the p-type NiO on the surface of the hollow
spheres, the stability improved, and such results are not shown here
because they fall under our future work.
Figure 12
(a) Repeatability (b,c)
long-term stability of hollow spheres under
response to 40 ppm C3H7OH; (d,e) response vs
RH (0, 40, and 60%) under 40 ppm C3H7OH and
C2H6OH at 75 and 150 °C, respectively.
(a) Repeatability (b,c)
long-term stability of hollow spheres unpan>der
response to 40 ppm C3H7OH; (d,e) response vs
RH (0, 40, and 60%) under 40 ppm C3H7OH and
C2H6OH at 75 and 150 °C, respectively.The responses of the sensors exposed to 40 ppm
C3H7OH in the presence of 40 and 60% relative
humidity (RH) are
shown in Figure c,d. The responses of both sensors decrease with RH. The performance
of the SnO2 hollow sphere-based sensor decreases by 87.3%
toward 40 ppm C3H7OH in the presence of 60%
RH. The response of the SnO2 LA nanoparticle-based sensor
decreases by 91.8% toward C2H6O in the presence
of 60% RH. Based on the above findings, it is evident that the current
sensors are not stable either in an actual environment or in dry air
after long exposure to C3H7OH or C2H5OH vapor.Usually, the gas sensing mechanism of
an n-type SnO2 SMO can be determined according to the radial
modulation in the
electron depletion layer and the potential barrier modulation. The
oxygen species that are adsorbed on the SnO2 surface capture
the electrons in the conduction band, thereby increasing the resistance
because of the increasing electron depletion layer. When the sensor
is exposed to a target gas (e.g., C3H7OH), the
gas molecules interact with the preadsorbed oxygen species (O2–). The electrons that are captured are
released back into the SnO2conduction band, thereby decreasing
the electron depletion layer and the resistance.[49]To determine the reason for the different sensitivities
and selectivities
of the gas sensors, we analyzed different types of paramagnetic defects
existing on the nonstoichiometric layers of the SnO2 sensors
and compared them with the sensing responses. According to the EPR,
PL, and XPS analyses, VO is the dominant defect on the
SnO2 surface. VO is considered as an active
site for oxygen adsorption. Therefore, the hollow spheres exhibit
improved oxygen adsorption. To relate the paramagnetic defects to
the gas sensing response, we calculated the number of spins (Figure a). Remarkably,
the sensing response fluctuates with the EPR intensity. Therefore,
a clear constructive relationship between the electrical response
and paramagnetic VO is revealed, which is also confirmed
by the PL and XPS results (see the Supporting Information). These results agree well with those reported
in previous studies. Thus, the quantity of paramagnetic VO identified via ESR is related to the number of electrons reaching
the SnO2conduction band. This result agrees well with
the improved sensing performance.[34,49,50] From the XRD analysis, the hollow spheres displayed
higher lattice strain, which resulted in the formation of more structural
defects within the system as validated by PL, EPR, and XPS analyses.
Figure 13
Gas
sensing response toward 40 ppm C3H7O
at 23 °C vs (a) number of spins related to paramagnetic defects
and (b) BET surface area. Fundamentally, each VO offers
two electrons. Therefore, a larger concentration of VO in
the hollow spheres results in a higher number of electrons, which
can be absorbed.[34,52,53]
Gas
sensing response toward 40 ppm C3H7O
at 23 °C vs (a) number of spins related to paramagnetic defects
and (b) BET surface area. Fundamentally, each VO offers
two electrons. Therefore, a larger concentration of VO in
the hollow spheres results in a higher number of electrons, which
can be absorbed.[34,52,53]Furthermore, to understand the
sensing behavior occurring on the
current sensing layer, we correlated the response versus the active
surface area of various nanostructures, and the results are presented
in Figure b. As
shown in Figure b, as the surface area increases, the response also increases, whereby
the hollow spheres reveals higher surface area, correlating well with
the higher response they revealed. Remarkably, the hollow sphere structure
containing the inner and outer shell layer can broaden the contact
area existing between the sensing layer and analyte gases as observed
in the current work. The high surface to volume ratio and density
of surface active sites are supportive of the adsorption and desorption
of C3H7OH gas molecules and surface interaction.[51−54] The hollow sphere structure reduces the path of gas diffusion and
enables the penetration of gas molecules.Besides, Morazzoni
et al.[49,55] proposed new radicalSn4+–O2–, which is
paramagnetically active and plays a vital part in the gas sensing
mechanismWhen the SnO2 hollow sphere- and nanoparticle-based
sensors are exposed to C3H7OH (see Scheme ) and C2H5OH at 75 and 125 °C, respectively, they will react
with the adsorbed oxygen species (O2–), while, at temperatures of <300 °C, they will react with
the adsorbed oxygen species (O–) through the following
reactions 6 and 7,[56,57] thereby resulting in a decrease in the sensor resistance
Scheme 1
Schematic Diagram of the Oxygen Chemisorption and the Reaction between
C3H7OH Gas and the Preadsorbed Oxygen Species
Conclusions
Various
SnO2 nanostructures were successfully synthesized
using a simple hydrothermal one-pot method. In a controlled manner,
nanostructures with different morphologies such as hollow spheres,
nanoparticles with two different sizes, nanoplatelets, nanorods, and
fishbones were synthesized. The defect analyses via EPR, PL, and XPS
revealed that the hollow spheres contained the most defects (e.g.,
VO). Further, the relative concentration of VO is morphology-dependent. The SnO2 nanostructure-based
gas sensors were fabricated and characterized for different gases
(CO, NH3, CH4, and NO2) including
volatile organic compounds (C3H7OH, C3H5OH, and C2H5OH) at various operating
temperatures. The SnO2 hollow spheres exhibited an improved
sensing response for C3H7OH gas at a low operating
temperature (75 °C). At a high operating temperature (150 °C),
the SnO2 nanoparticle-based sensor showed the highest response
value. This variation in the optimal temperatures among sensors with
different morphologies implied that the gas selectivity and sensitivity
are morphology-dependent.
Experimental Section
Materials
All reagents were of analytical
grade and used without further purification. Tin chloride dihydrate
(SnCl2·2H2O), sodium hydroxide (NaOH),
HMT [H2N (CH2)6NH2], and
absolute ethanol were purchased from Sigma-Aldrich, Johannesburg,
South Africa.
Synthesis of SnO2 Nanostructures
The SnO2 hollow spheres were
produced by mixing 0.4
g SnCl2·2H2O and 0.5 g NaOH in 20 mL deionizedwater and 0.5 M HNO3, under magnetic stirring for 20 min.
Next, 40 mL ethanol was slowly added to the solution to form a white
precipitate. The mixture was stirred for 24 h, washed with distilled
water and ethanol, and dried at 80 °C for 24 h. The SnO2 nanoparticles were synthesized using 0.4 g SnCl2·2H2O and 0.5 g NaOH in 20 mL deionizedwater and 0.5 M HNO3. The solution was stirred for 20 min and transferred into
a 45 mL Teflon-lined stainless-steel autoclave, which was sealed tightly
and kept at 200 °C in an oven for 12–48 h. After the hydrothermal
step, the autoclave was allowed to cool down to room temperature.
The flower-rod bundle, fishbone platelet, and hierarchical flower-like
platelet nanostructures were synthesized by mixing 0.4 g SnCl2·2H2O, 0.5 g NaOH, and 0.84 g HMT in 20 mL
deionizedwater under continuous magnetic stirring. Next, 60 mL ethanol
was added slowly to the white precipitate. The mixture was transferred
into a 45 mL Teflon-lined stainless-steel autoclave and kept at 200
°C for 12–48 h. We should point out that to form different
morphologies, different synthesis times had to be adopted. While with
the MA nanoparticles, the synthesis reaction time prolonged in order
to form larger sizes of the nanoparticles to have a comparison with
smaller ones. Finally, the white precipitates were collected through
centrifugation and washed thoroughly with distilled water and ethanol.
Afterward, they were dried at 80 °C for 24 h.
Characterization
The SnO2 crystal structure
was analyzed with a PANalytical X’pert
PRO PW 3040/60 X-ray diffractometer with Cu Kα radiation and
λ = 0.154178 nm at an acceleration voltage of 45 kV and a current
of 40 mA (PANalytical, the Netherland). The nanostructures and surface
morphologies were determined with a scanning electron microscope (SEM,
Zeiss Auriga, Germany) and JEOL-2100 transmission electron microscope
(TEM, JEOL, Japan). The analysis of the pores, surface area, and nitrogen
adsorption–desorption isotherms were conducted with the Brunauer–Emmett–Teller
(BET) and BJH methods with a Micromeritics TRISTAR 3000 instrument,
USA. The point defects and crystal quality were investigated with
a Jobin-YvonNanoLog PL spectrometer (Jobin-Yvon, France). Further,
the chemical state of the nanostructures was studied via XPS with
a PHI 5000 VersaProbe Scanning ESCA Microprobe (USA). To study paramagnetic
defects, a JEOL X-band EPR spectrometer (JEOL, Japan) was used. The
analyses were carried out at 25 and 75 °C to mimic the sensing
conditions.
Sensor Fabrication and
Sensing Characterization
The vapor and gas sensing properties
were measured using the KSGAS6S
gas sensing station (Kenosistec, Italy). Inpan> the typical sensor fabrication
procedure, an appropriate amount of sample powder was placed in an
agate mortar and grounded adding terpineol to form slurry. Afterward,
the paste was carefully coated onto alumina substrates. The sensor
units were placed in a sealed chamber at a controlled temperature
under different conditions (i.e., in dry air and under RH values of
40 and 60%). The gas sensing studies were conducted exposing the fabricated
sensors to different concentrations (10–100 ppm) of various
reducing gases (e.g., CO, CH4, and NH3), volatile
organic compounds (C2H5OH, C3H6O, and C3H7OH), and an oxidizing gas
(NO2) in a background of synthetic dry air. The gas/organic
compound concentrations in the test chamber were precisely mixed with
synthetic air. The measurements were carried out at various operating
temperatures 25 °C (i.e., room temperature), 75, 150, and 225
°C. The sensor resistance was continuously monitored using a
Keithley 6487 picoammeter/voltage source meter. We define the gas
response as Ra/Rg – 1 for reduced gas and Rg/Ra – 1 for oxidized gas, where Ra and Rg are the
resistances of the sensors in air and gas/organic vapor, respectively.
The response recovery times were calculated as the time intervals
between the time at which the response has achieved 90% of its maximum
and the time at which it has decreased to 10% of its maximum.[12]
Authors: Xiao Ming Yin; Cheng Chao Li; Ming Zhang; Quan Yi Hao; Shuang Liu; Qiu Hong Li; Li Bao Chen; Tai Hong Wang Journal: Nanotechnology Date: 2009-10-13 Impact factor: 3.874
Authors: Won Seok Chi; Chang Soo Lee; Hu Long; Myoung Hwan Oh; Alex Zettl; Carlo Carraro; Jong Hak Kim; Roya Maboudian Journal: ACS Appl Mater Interfaces Date: 2017-10-16 Impact factor: 9.229