Gas sensors based on ultrathin porous Co3O4 nanosheets to detect acetone at low temperature

Article abstract of DOI:10.1039/c5ra08536e

Using a facile two-step process, including a hydrothermal technique and subsequently controlled annealing of the precursor, ultrathin porous Co₃O₄ nanosheets can be synthesized. The gas sensor based on the porous Co₃O₄ nanosheets shows a superior acetone gas-sensing performance at a low operating temperature of 150°C. The gas response to 100 ppm acetone reached 11.4, and exhibited good reproducibility. In addition, the detection limit of the Co₃O₄ nanosheet sensor is lower than 1.8 ppm, which is the diagnostic criteria exhaled from diabetes. What's more, the sensor exhibited good stability when tested over 2 months. The outstanding gas-sensing properties were explained by a typical p-type semiconductor behavior with an ultrathin porosity structure as well as a large specific surface area of Co₃O₄ nanosheets.

Full text of DOI:10.1039/c5ra08536e

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Gas sensors based on ultrathin porous Co3O4
nanosheets to detect acetone at low temperature
Cite this: RSC Adv., 2015, 5, 59976
ab
Ziyue Zhang,ab Zhen Wen,ab Zhizhen Yeab and Liping Zhu
*
Using a facile two-step process, including a hydrothermal technique and subsequently controlled annealing
of the precursor, ultrathin porous Co3O4 nanosheets can be synthesized. The gas sensor based on the
porous Co3O4 nanosheets shows a superior acetone gas-sensing performance at a low operating
temperature of 150 ꢀC. The gas response to 100 ppm acetone reached 11.4, and exhibited good
reproducibility. In addition, the detection limit of the Co3O4 nanosheet sensor is lower than 1.8 ppm,
which is the diagnostic criteria exhaled from diabetes. What’s more, the sensor exhibited good stability
when tested over 2 months. The outstanding gas-sensing properties were explained by a typical p-type
semiconductor behavior with an ultrathin porosity structure as well as a large specific surface area of
Co3O4 nanosheets.
Received 8th May 2015
Accepted 25th June 2015
DOI: 10.1039/c5ra08536e
www.rsc.org/advances
testing instruments in the future, due to their advantages, such
as being small, portable and low-cost.
Introduction
Due to the inherent advantages of gas sensors, such as being
portable, cheap and suitable for daily use,13–16 people have
begun to consider using gas sensors in the analysis of exhaled
breath.17,18 For example, Marco Righettoni et al. developed gas
sensors based on Si-doped WO3 to analyse breath acetone for
diabetes detection at 400 ꢀC,19 Li et al. synthesised co-doped
With the increasingly prominent issues concerning food and
the environment, people are placing much more emphasis on
the advanced diagnosis of their health conditions. Regular
physical examinations, consisting of ultrasonication, electro-
cardiography and irradiation as well as testing blood and urine,1
are time and resource consuming and inconvenient. During the
past few years, a testing approach utilizing the analysis of
exhaled breath from human bodies to make an initial judgment
on their physical condition has been proposed by researchers.2
Basically, the exhaled breath of healthy people contains carbon
dioxide, nitrogen, vapour, rare gases and various organic gases
produced during the metabolic process.3,4 If a certain gas
concentration is beyond its normal range, it could mean that
the human is ill.5 For instance, diabetes, asthma, heart disease,
kidney malfunction and chronic obstructive pulmonary disease
are closely related to the concentration of exhaled acetone,
nitrogen monoxide, pentane, ammonia and carbon monoxide,
respectively.6 Among these illnesses, diabetes is the most
common chronic disease at present. If it can be found at an
early stage, people with pre-diabetes can sharply lower their
chances of developing the disease.7,8 Nowadays, gas chromato-
graphic detection technology, selected ion ow tube mass
spectrometry and cavity ring down spectroscopy are the most
common diagnostic techniques used to detect acetone in
exhaled breath.9–12 But, in addition to these detection technol-
ogies, gas sensors have great potential to be used as acetone
ZnO nanober-based gas sensors to detect acetone at 360 C,20
ꢀ
Song et al. produced Ce doped SnO2 hollow spheres as acetone
gas sensors at 250 C,21 and Zhou et al. developed acetone gas
ꢀ
sensors based on porous ZnO/ZnCo2O4 hollow spheres at 275
ꢀC.22 However, in order to achieve their optimal sensing
performances, these sensors usually have low sensitivity and
need higher working temperatures, which not only shortens
sensor lifetime but also increases the cost of practical applica-
tions. Thus, the large-scale application of these sensors in our
daily life to detect diabetes is limited. In our previous work, we
reported a Co3O4 nanorod array-based ethanol gas sensor with a
low operating temperature.23–25 Therefore, we attempted to
prepare a kind of Co3O4 sensor to detect acetone for diagnosing
diabetes at a low operating temperature.
In this work, we present the fabrication of an ultrathin
porous Co3O4 nanosheet-based gas sensor with high-
performance for selective acetone detection at a relatively low
temperature. The characterization techniques used on of the
Co3O4 nanosheets include scanning electron microscopy (SEM),
thermogravimetric analysis (TGA), X-ray diffraction (XRD),
transmission electron microscopy (TEM), high-resolution TEM
(HRTEM) and Brunauer–Emmet–Teller (BET). Subsequently,
the high-performance sensing properties of the gas sensor
based on ultrathin porous Co3O4 nanosheets for acetone and
the related gas-sensing mechanism will also be discussed.
aSchool of Materials Science and Engineering, Zhejiang University, China
bState Key Laboratory of Silicon Materials, Hangzhou 310027, People’s Republic of
China. E-mail: zlp1@zju.edu.cn; Fax: +86 571 87952625; Tel: +86 571 87952625
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Experimental
Co3O4 nanomaterial synthesis
All chemicals were of analytical grade and used as purchased
without further purication. The typical experiments were as
follows: rstly, 0.02 mmol (0.125 g) poly(ethylene glycol)-block-
poly(propylene glycol)-block-poly(ethylene glycol) was dissolved
in a mixing solution with 16.5 mL ethanol and 1 mL high purity
water (18.3 MU cm resistivity) under stirring at room tempera-
ture. Secondly, aer obtaining a claried solution, 0.5 mmol
(0.07 g) hexamethylenetetramine and 0.5 mmol (0.125 g) cobalt
acetate (C4H6O4$Co$4H2O) were added and stirred at 60 ꢀC,
then 13 mL ethylene glycol was added, until its colour changed
from transparent to pink. Thirdly, the precursor solution was
statically aged for 12 h. Fourthly, the homogeneous solution
was transferred into a 50 mL Teon-lined stainless steel auto-
clave, which was sealed and maintained at 170 ꢀC for 2 h inside
an electric oven. Fihly, aer cooling down to room tempera-
ture, the brown muddy solution in the autoclave was washed
with distilled water and ethanol several times, in order to
remove the free nanoparticle debris and the residual reactant. A
light green powder was collected through washing/
centrifugation (10 000 rpm, 3 min) and dried under vacuum
at 60 ꢀC for 12 h. Finally, a series of Co3O4 nanosheets were
fabricated by annealing the as-prepared light green powder at
Fig. 1 (a) SEM image of a section of the sensor; (b) the top view of the
sensor substrate and sample sensors; (c) a schematic structure of the
sensor.
Gas-sensing measurements
The detailed gas-sensing experimental process can be found in
our previous report.26 We measured the gas sensing properties
of the samples using an intelligent gas sensing analysis system
(CGS-1TP, Beijing Elite Tech Co., Ltd, China). Two probes were
pressed onto the sensor electrodes through adjusting their
position in the analysis system. There is an external tempera-
ture control (from room temperature to 500 ꢀC), which could
ꢀ
ꢀ
ꢀ
ꢀ
ꢀ
250 C, 300 C, 350 C, 400 C and 450 C in air for 2 h (corre-
sponding products denoted as S250, S300, S350, S400 and S450,
respectively).
ꢀ
easily adjust the sensor temperature with a precision of 1 C.
First of all, the sensor was preheated at different operating
temperatures for about 1 h to achieve the stable resistances.
Then through a rubber plug, the target gas was injected into the
test chamber (18 L in volume) using a micro-injector. Our target
liquid, e.g. acetone, was injected into the evaporator to form
acetone vapour. Using the two fans in the analysis system, the
saturated target gas was mixed with air (the relative humidity
was about 50%). Aer the sensor resistance reached a new
constant value, the test chamber was opened to recover the
sensor in air. The gas response was designated as Rg/Ra, where
Rg is the sensor resistance measured in the presence of the
target gas and Ra in air. Response and recovery times were
dened as the time needed to reach 90% of the total resistance
change (Rg-Ra) on exposure to gas and air.
Characterization
The microstructures and morphologies of both the sample
before annealing and the calcined products were examined
using SEM (Hitachi, S-4800) with an accelerating voltage of 5 kV.
The crystal phase identication was investigated using an XRD
(Bede D1) system with Cu-Ka1 radiation (l ¼ 0.15406 nm) over
the 2q range of 10–70ꢀ. TEM and HRTEM images were taken
using a HRTEM analyser with an accelerating voltage of 200 kV.
TGA (SDT Q600) was carried out under an air atmosphere at 10
ꢀC minꢁ1 in the temperature range of 10–900 ꢀC. Specic
surface areas were computed from the results of the N2
adsorption–desorption isotherms at 77 K (Micromeritics ASAP
3020).
Results and discussion
Gas sensor fabrication
Material characterization
The as-prepared powder was mixed with a chitosan solution, in The morphology and structure of the precursor obtained using
the appropriate weight ratio to get a 0.2 wt% CHIT solution, and the hydrothermal method were rstly investigated systemati-
ground in a mortar over time to form a paste. The paste was cally. Fig. 2(a) indicates that the precursor is randomly shaped
coated onto a polycrystalline alumina ceramic plate (8 mm ꢂ 4 nanosheets with a smooth surface and are extremely thin (ꢃ30
mm, 0.5 mm thick) which had been plated with Ag–Pd nger nm). Fig. 2(b) shows the thermodecomposition behavior of the
regions (ve pairs, both the width and distance were 200 mm) as precursor, which implies that three decomposition steps exist:
ꢀ
electrodes to form a sensing lm (with a thickness of ꢃ6 mm, as the rst one appears below 200 C, with a weight loss of about
shown in Fig. 1(a)). Finally, the samples were annealed at 60 ꢀC 5.5%. The weight loss is mainly due to the evaporation of
for 12 h. The top view of the sample sensor is shown in Fig. 1(b), adsorbed water in the sample. The second turning point
ꢀ
and Fig. 1(c) shows the schematic structure of sensor.
appears at 310 C, with a distinct weight loss of about 18.5%
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between 200 ꢀC and 310 ꢀC, which is ascribed to the decom- The pores on the surface were formed during the thermal
position of the precursors, leading to the release of CO2 and treatment, because the generated CO2 and H2O (g) have escaped
H2O. Numerous fractured porous structures are formed during the samples. Comparing these SEM images, it can be found that
this stage, accompanying gas evolution and solid volume both the size of the nanoparticles and pores throughout the
contraction. The third step appears aer 310 ꢀC, with the nanosheets have gradually increased, with the increasing
primary small nanoparticles growing into larger particles and annealing temperature.
the number of fractured porous structures decreasing
gradually.
Further crystallographic properties were examined via TEM.
Comparing the typical TEM images shown in Fig. 4(a)–(e), we
In order to nd the most suitable annealing temperature for can see that the cracked particles gradually grow, and the size of
ideal ultrathin porous Co3O4 nanosheet-based gas sensors, the these particles become bigger as the annealing temperature
ꢀ
samples were annealed at different temperatures (from 250 C increases from 250 ꢀC to 450 ꢀC, which is in agreement with that
ꢀ
to 450 C). The XRD patterns of S250–S450 shown in Fig. 3(a) shown in the SEM images. What’s more, the differences also
indicate that all of the samples are pure cubic Co3O4 phase. inuence the porosity of these Co3O4 nanosheets, including
With the increasing annealing temperature, the intensity of the pore volume and pore density. From the HRTEM image shown
diffraction peaks increased, meaning that the grain size in Fig. 4(f), the lattice fringe of d ¼ 0.466 nm agrees well with the
increased. The mean crystallite sizes were estimated from the (111) crystallographic plane of the cubic Co3O4 phase.27–29
(311( peak using the Scherrer formula, the grain sizes from S250
N2 sorption measurements were evaluated for characteriza-
to S450 are 4.9 nm, 6.4 nm, 9.1 nm, 19.4 nm and 28.9 nm, tion of the textural properties and inner architectures of the
respectively. Fig. 3(b)–(f) show the high-magnication SEM ultrathin Co3O4 nanosheets and gathering information about
images of the ultrathin Co3O4 nanosheets obtained at different the specic surface area and pore size distribution. Fig. 5(a)
annealing temperatures. We can see that all of these samples displays the nitrogen adsorption and desorption isotherms of
are also random-shaped nanosheets, but compared with S250–S450, all of which reveal a typical type IV adsorption
samples before annealing, these products have porous surfaces. isotherm with a H3-type hysteresis loop at different relative
pressure ranges. When elevating the annealing temperature,
the corresponding specic surface areas of samples from S250
to S450 gradually decrease, and are 76.06 m2 gꢁ1, 68.73 m2 gꢁ1
,
46.85 m2 gꢁ1, 21.58 m2 gꢁ1 and 19.49 m2 gꢁ1, respectively. The
pore diameter of the samples signicantly increases with the
increasing annealing temperature. However, according to
Fig. 2 Morphological and structural characterization of the precursor: Fig. 3 (a) XRD patterns of S250–S450; (b)–(f) SEM images of Co3O4
(a) SEM images of the Co3O4 nanosheets; (b) TGA/DTG curves under nanosheets annealed at 250 ꢀC, 300 ꢀC, 350 ꢀC, 400 ꢀC and 450 ꢀC,
air with a ramp of 10 ꢀC minꢁ1
.
respectively.
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Fig. 4 TEM images of the porous Co3O4 nanosheets prepared at
different annealing temperatures: (a) 250 ꢀC; (b) 300 ꢀC; (c) 350 ꢀC; (d)
400 ꢀC and (e) 450 ꢀC. (f) HRTEM image of the Co3O4 nanostructure
annealed at 300 ꢀC.
Fig. 5 (a) Nitrogen adsorption and desorption isotherms of the porous
Co3O4 nanosheets with different annealing temperatures; (b) pore
diameter distribution curves of the porous Co3O4 nanosheets with
different annealing temperatures.
Fig. 5(b), it is obvious that the distribution of the pore diameter
of S300 is more concentrated than others. These results indicate
that the morphologies of the Co3O4 nanosheets largely depend
on the annealing temperature, and controlling the annealing
conditions could regulate their microstructures.
escape from the Co3O4 surfaces before the reaction because of
the strong thermal motion owing to high temperature, thus
responses decrease correspondingly.30 Therefore an appro-
priate operating temperature is the precondition of the good
gas sensing property. The relation curves between the sensors
response versus acetone with concentrations ranging from 1
to 100 ppm were measured at 150 ꢀC, as shown in Fig. 6(b). As
is reported, acetone at concentrations greater than or equal to
1.8 ppm is exhaled from diabetes patients, which are 2–6-fold
higher than the 300–900 ppb of acetone exhaled by healthy
people.19 Thus, the acetone detection limit of the sensor was
lower than 1.8 ppm and is an important parameter for the
applications aimed at the diagnosis of diabetes. This result
indicates that this kind of gas sensor can be used to analyse
breath acetone for diabetes detection. With the increase of the
concentration of acetone, the response also improved rapidly.
The response to 100 ppm acetone gas reached ꢃ11.4, which
illustrates that the ultrathin Co3O4 nanosheet-based sensor
not only can be used to detect diabetes but also is useful for
other elds which need to detect acetone with high
concentration.
Gas sensing properties
The gas sensing properties of the Co3O4 mesocrystals with
different annealing temperatures were studied with acetone
as the probe gas. The Co3O4 nanosheets have been uniformly
coated on the Ag–Pd nger regions, which provides an elec-
trical path between the neighbouring ngers. Firstly, the
acetone sensing characteristics of the above Co3O4
nanosheet-based sensors were investigated for an optimum
operating temperature. As shown in Fig. 6(a), the optimum
operating temperature for both S250 and S300 is 150 ꢀC, while
that of S350, S400 and S450 is 170 ꢀC. Among the sensors,
S300 exhibited superior sensitivity. The sensitivities of the
present sensors were found to increase with the increasing
operating temperature, attaining the maximum value (ꢃ11.4),
then decreasing with further increase of the operating
temperature. The gas adsorption and desorption kinetics on
the surface of Co3O4 can be used to explain this behaviour.
When the operating temperature is relatively low, the chem-
ical activity of the Co3O4 nanosheets is consequently low,
leading to a low response. But if the operating temperature
increases too much, some adsorbed gas molecules may
Another important parameter of the sensor properties is the
response–recovery time, which is calculated under 100 ppm
ꢀ
acetone at 150 C for all samples. Fig. 7(a) shows the response
time of S250–S450, decreasing from 150 s to 41 s. And the
recovery time of S250–S450 decreases from 300 s to 65 s, as
shown in Fig. 7(b).
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Fig. 6 (a) Gas responses of five samples as a function of different
working temperatures to 100 ppm acetone concentration; (b) the
response and recovery curves of S300 between different concentra-
tions of acetone gas and air at the operating temperature of 150 ꢀC.
Fig. 7 (a) Response time and (b) recovery time of the samples S250–
S450.
Gas sensing mechanism
The gas sensing mechanism for Co3O4 widely consists of the
change in electrical conductivity when accounting for the
chemical interaction of gas molecules with the surface involving
gas adsorption, surface reaction, and desorption processes. The
schematic diagram of the acetone gas sensing mechanism is
illustrated in Fig. 10. Herein, Co3O4 is a typical p-type semi-
conductor, where holes are the main charge carrier. When
exposed to air, the oxygen molecules adsorbed on its surface
transform to ionized oxygen species (O2ꢁ, O2ꢁ, or Oꢁ) by trap-
ping electrons from Co3O4, forming the depletion layers. When
Fig. 8 presents the acetone-selective characteristics of S300
with respect to other typical interfering gases such as ethanol,
ammonium, methanol, toluene, and p-xylene with response
values toward each gas at 150 ꢀC. The gas response to 100 ppm
acetone vapour is signicantly higher than all the other gases
at the same concentration, which demonstrates that the
sensors based on ultrathin porous Co3O4 nanosheets show a
high anti-interference performance that is a precondition for
becoming a useful sensor to detect breath acetone for diabetes
detection. The adsorption ability of ultrathin porous Co3O4
nanosheets to some gas molecules, such as acetone, is
comparatively stronger than others, which enables it to achieve
selective detection.31–33
To conrm the stability of the samples, the responses of
ꢀ
S300 at 150 C to 100 ppm acetone (RH ꢃ 50%) were investi-
gated 20 times over two months. The results shown in Fig. 9
illustrate that there was almost no apparent signal attenuation
during the 20 tests. Therefore, we can conclude that the
stability of this material is good enough to detect acetone over
a long time. However, even though this device showed good
performance for acetone detection, it does not mean that this
device can be directly put into clinical use. There are lots of
realistic issues which should be solved rst, such as the high
humidity levels in breath, uctuations in humidity and
temperature, counteracting volatile compounds in breath, and
more.34
Fig. 8 The gas responses of S300 to several reducing gases with
concentrations of 100 ppm at 150 ꢀC.
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surface of S300 and promote the diffusion of target gases, which
are the key factors for the gas sensing properties. Generally, the
ultrathin porous structure is benecial for gas sensing perfor-
mances, allowing the gas molecules to easily penetrate and
adsorb on the surface of the nanosheets and leading to fast
response–recovery times as well as high sensitivity.
Conclusions
In conclusion, a gas sensor based on ultrathin porous Co3O4
nanosheets has been successfully synthesized through a
hydrothermal technique and a subsequent controlled anneal-
ing route, showing excellent performances for acetone detection
at a much lower operating temperature. The response to 100
ppm acetone reached 11.4 at 150 ꢀC. What’s more, the detection
limit of Co3O4 nanosheet-based sensors is lower than the 1.8
ppm that is exhaled from diabetes patients, and exhibited good
reproducibility and stability. Its high-performance is due to the
ultrathin structure, meso-porosity, and large specic surface
area. These results indicate that the gas sensor based on
ultrathin porous Co3O4 nanosheets is very promising for
making a daily life initial judgment on diabetes in human
beings. However, it must be mentioned that there are lots of
problems which should be overcome before putting the sensor
into practical use.
Fig. 9 The response of the Co3O4 sensor at 150 ꢀC to 100 ppm
acetone (RH ꢃ 50%) investigated 20 times over two months.
reductive gas molecules, such as acetone, are introduced into
the test chamber, these chemisorbed oxygen species will be
released,9,35 thus, the charge carrier accumulation layer near the
surface is thinned by the electrochemical interaction between
Oꢁ and gas molecules, as in the following reaction (1), which
releases free electrons and neutralizes the holes in Co3O4,
leading to the increase of the baseline resistivity until dynamic
equilibrium conditions are obtained. Aer the acetone ow
stopped, oxygen molecules in the air are adsorbed on the
surface of the sensors again, and the resistance decreases to its
initial value.
Notes and references
(1)
CH3COCH3 (gas) + 8Oꢁ / 3CO2 + 3H2O + 8eꢁ
1 P. Spanel and D. Smith, Med. Biol. Eng. Comput., 1996, 34,
409–419.
2 L. Pauling, A. B. Robinson, R. Teranishi and P. Cary, Proc.
Natl. Acad. Sci. U. S. A., 1971, 68, 2374–2376.
3 W. Miekisch, J. K. Schubert and G. F. Noeldge-Schomburg,
Clin. Chim. Acta, 2004, 347, 25–39.
4 A. Damico, C. Dinatale, R. Paolesse, A. Macagnano,
E. Martinelli, G. Pennazza, M. Santonico, M. Bernabei,
C. Roscioni and G. Galluccio, Sens. Actuators, B, 2008, 130,
458–465.
5 D. Hill and R. Binions, Int. J. Smart Sens. Intell. Syst., 2012, 5,
401–440.
In our experiment, we believe that the difference in sensing
properties among samples with different annealing tempera-
tures is related to the specic surface chemical composition and
microstructure of these gas sensors. As TEM images show in
Fig. 4(a)–(e), the nanoparticles in S250 and S300 are smaller
than that of S350, S400 and S450, and the pore density of S300 is
higher than that of S250. From Fig. 5(a), we can see the corre-
sponding specic surface area of S250 is slightly higher than
that of S300. However, from Fig. 5(b), it is obvious that the pore
diameter of S300 is bigger than that of S250, and the distribu-
tion of the pore diameter of S300 is more concentrated than that
of S250. Hence, more oxygen molecules can be adsorbed on the
6 D. Guo, D. Zhang, N. Li, L. Zhang and J. Yang, IEEE Trans.
Biomed. Eng., 2010, 57, 2753–2763.
7 C. Ortiz-Lopez, R. Lomonaco, B. Orsak, J. Finch, Z. Chang,
V. G. Kochunov, J. Hardies and K. Cusi, Diabetes Care,
2012, 35, 873–878.
8 A. American Diabetes, J. P. Bantle, J. Wylie-Rosett,
A. L. Albright, C. M. Apovian, N. G. Clark, M. J. Franz,
B. J. Hoogwerf, A. H. Lichtenstein, E. Mayer-Davis,
A. D. Mooradian and M. L. Wheeler, Diabetes Care, 2008,
31(suppl. 1), S61–S78.
9 J. F. Dummer, M. K. Storer, W. P. Hu, M. P. Swanney,
G. J. Milne, C. M. Frampton, J. M. Scotter, G. K. Prisk and
M. J. Epton, J. Breath Res., 2010, 4, 046001.
10 A. Kachanov, A. Charvat and F. Stoeckel, J. Opt. Soc. Am. B,
1995, 12, 970–979.
Fig. 10 Schematic diagram of the acetone gas sensing mechanism.
This journal is © The Royal Society of Chemistry 2015
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11 N. Makisimovich, V. Vorotyntsev, L. N. Nikitin, O. Kaskevich, 23 Z. Wen, L. Zhu, W. Mei, L. Hu, Y. Li, L. Sun, H. Cai and Z. Ye,
P. Karabun and F. Martynenko, Sens. Actuators, B, 1996, 36,
419–421.
12 M. Phillips, K. Gleeson and R. N. Cataneo, Lancet, 1999, 353,
1930–1933.
13 G. F. Fine, L. M. Cavanagh, A. Afonja and R. Binions, Sensors,
2010, 10, 5469–5502.
14 T. Akamatsu, T. Itoh, N. Izu and W. Shin, Sensors, 2013, 13,
12467–12481.
15 K.-I. Choi, H.-R. Kim, K.-M. Kim, D. Liu, G. Cao and J.-H. Lee,
Sens. Actuators, B, 2010, 146, 183–189.
16 B. Ding, M. Wang, X. Wang, J. Yu and G. Sun, Mater. Today,
2010, 13, 16–27.
Sens. Actuators, B, 2013, 186, 172–179.
24 Z. Wen, L. Zhu, W. Mei, Y. Li, L. Hu, L. Sun, W. Wan and
Z. Ye, J. Mater. Chem. A, 2013, 1, 7511.
25 Z. Wen, L. Zhu, Y. Li, Z. Zhang and Z. Ye, Sens. Actuators, B,
2014, 203, 873–879.
26 Z. Wen, L. Zhu, Z. Zhang and Z. Ye, Sens. Actuators, B, 2015,
208, 112–121.
27 X. Xiao, X. Liu, H. Zhao, D. Chen, F. Liu, J. Xiang, Z. Hu and
Y. Li, Adv. Mater., 2012, 24, 5762–5766.
28 X. Liu, J. Zhang, S. Wu, D. Yang, P. Liu, H. Zhang, S. Wang,
X. Yao, G. Zhu and H. Zhao, RSC Adv., 2012, 2, 6178.
29 Y. Teng, L. X. Song, L. B. Wang and J. Xia, J. Phys. Chem. C,
2014, 118, 4767–4773.
17 G. Konvalina, Acc. Chem. Res., 2014, 47, 66–76.
18 H. Haick, Y. Y. Broza, P. Mochalski, V. Ruzsanyi and 30 S. Wang, C. Xiao, P. Wang, Z. Li, B. Xiao, R. Zhao, T. Yang
A. Amann, Chem. Soc. Rev., 2014, 43, 1423–1449. and M. Zhang, Mater. Lett., 2014, 137, 289–292.
19 M. Righettoni and A. Tricoli, J. Breath Res., 2011, 5, 037109. 31 L. Li, S. He, M. Liu, C. Zhang and W. Chen, Anal. Chem.,
20 L. Liu, S. Li, J. Zhuang, L. Wang, J. Zhang, H. Li, Z. Liu, 2015, 87, 1638–1645.
Y. Han, X. Jiang and P. Zhang, Sens. Actuators, B, 2011, 32 M. Hakim, Y. Y. Broza, O. Barash, N. Peled, M. Phillips,
155, 782–788. A. Amann and H. Haick, Chem. Rev., 2012, 112, 5949–5966.
21 P. Song, Q. Wang and Z. Yang, Sens. Actuators, B, 2012, 173, 33 B. Wang, J. C. Cancilla, J. S. Torrecilla and H. Haick, Nano
839–846. Lett., 2014, 14, 933–938.
22 X. Zhou, W. Feng, C. Wang, X. Hu, X. Li, P. Sun, 34 G. Konvalina and H. Haick, ACS Appl. Mater. Interfaces, 2012,
K. Shimanoe, N. Yamazoe and G. Lu, J. Mater. Chem. A,
2014, 2, 17683–17690.
4, 317–325.
35 L. Qin, J. Xu, X. Dong, Q. Pan, Z. Cheng, Q. Xiang and F. Li,
Nanotechnology, 2008, 19, 185705.
59982 | RSC Adv., 2015, 5, 59976–59982
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