Introduction
There are various harmful and hazardous matter vapors, which have a major
role in diverse spheres such as environmental protection, industrial
manufacturing, medicine and national defence. As an illustration,
propylene glycol (PG) is an excellent solvent for many organic compounds and
is used as an active ingredient in engine coolants and antifreeze, brakes,
paints, enamels and varnishes, and also as a solvent or surfactant in many
products. It also can be found in cosmetics, perfumes and
pharmaceuticals.
Another example is dimethylformamide (DMF) which is used as a solvent in
vinyl resins, adhesives, pesticide and epoxy formulations. It purifies and
separates acetylene, 1,3-butadiene, acid gases and aliphatic
hydrocarbons. DMF is also used in the production of polyacrylic or cellulose
triacetate fibres and pharmaceuticals or in the production of polyurethane
resin for synthetic leather (Fiorito et al., 1997).
Formaldehyde (FA) is a colorless, water-soluble gas with a pungent odor,
which used in making building materials and in many household products such
as particleboard, plywood and fiberboard, glues and adhesives, textiles,
papers and their product coatings. Besides, formaldehyde can serve an
intermediate product in the manufacture of industrial chemicals. It can also
be found as a preservative substance in some foods and products, such as
antiseptics, medicines and cosmetics (Lefebvre et al., 2012).
DMF, PG and FA have a huge impact on human organs (e.g. liver, skin, eyes
and kidneys) (Fiorito et al., 1997; Lefebvre et al., 2012; Malaguarnera et
al., 2012; Chang et al., 2004). PG can cause nausea and vomiting, headaches,
dizziness and fainting. Moreover, it is known as a combustible liquid,
which can explode in fire. A minimal risk level of 0.009 ppm has been
derived for constant-duration (15–364 days) inhalation exposure to
propylene glycol (Robertson et al., 1947). FA gas can cause burning
sensations in the eyes, nose and throat as well as cause coughing, wheezing, nausea and skin
irritation. Besides, exposure to relatively high amounts of formaldehyde can
increase the risk of leukemia and even cause some types of cancer in humans.
The United States Occupational Safety and Health Administration (OSHA) has
set its short-term exposure limit (15–30 min) at 2 ppm and permissible
exposure limit (up to 8 h) to 0.75 ppm (Salthammer et al., 2010). The
current OSHA standard for dimethylformamide is 10 ppm averaged over an
8 h work shift (Ellenhorn, 1997).
Due to the information noted above, PG, DMF and FA gas sensors are commonly applied for detecting and continuously monitoring these gases in
the spheres where they are used.
Despite our careful analysis of data in the literature, we did not find any
works related to research on and development of resistive-type sensors
for PG and DMF gases. There are only studies on sensors working on other principles
(for example, sensors working on a modification of the color of the
substance), which is incompatible with modern techniques, while resistive
gas sensors, made from metal oxides, have some advantages such as
availability of the electric signal, measurement of gas concentration, small
sizes, low power consumption, high sensitivity and high reliability (Fine
et al., 2010; Korotcenkov et al., 2013). As opposed to this case, there are
various types of FA gas sensors: for instance, FA gas sensors based on
graphene or polymers, which are working at a room temperature (Chuang et
al., 2015; Flueckiger et al., 2009). However, FA gas sensors, which are
based on metal-oxide materials, have benefits that are mentioned above.
Meanwhile, pure metal oxide structures react on FA at higher operating
temperatures (300–400 ∘C) (Xu et al., 2014; Park et al., 2014) or room
temperature with the assistance of UV LEDs (Chung et al., 2014; Li et al.,
2015).
Nanomaterials, such as carbon nanotubes (CNTs), metal-oxide nanoparticles,
nanotubes, nanowires and other various nanopattern formations are widely
used in gas sensing structures due to their excellent responsive
characteristics, mature preparation technology and low cost of mass
production (Aroutiounian, 2015; Arafat et al., 2012; Korotcenkov et al.,
2009; Aroutiounian et al., 2013; Feyzabad et al., 2012; Hieu et al., 2008).
When CNTs' walls are covered with metal-oxide nanoparticles, the specific
surface area of sensitive gas material enlarges. Furthermore, nanochannels in
the form of hollows of CNTs promote penetration of gas molecules deeper down
in the nanocomposite sensitive layer (Bai et al., 2014). Hence, it can be
expected that application of nanocomposite structures composed of metal
oxide functionalized with CNTs in the technology of gas sensors should
improve gas sensor parameters, such as gas response, response, recovery
times and operating temperature.
Our recent works related to the study of gas sensors based on multiwall
carbon nanotubes/tin oxide (MWCNTs/SnO2) nanostructures are also
supported by Aroutiounian et al. (2013, 2015) and Adamyan et al. (2016). The choice of tin-oxide as
a component of SnO2/MWCNT nanocomposite structure is conditioned by
the fact that SnO2 is a well-known basic material for metal-oxide gas
sensors (Korotcenkov et al., 2009; Aroutiounian, 2007; Shankar et al.,
2015). We expected that coating of functionalized MWCNTs with SnO2
nanoparticles with admissible (close to double Debye length) sizes (Xu et
al., 1991; Adamyan et al., 2003, 2007) should provide the
improved performance of the gas sensor and lower its operating temperature.
Here, we present the characteristics of the PG, DMF and FA vapor sensors
based on ruthenated thick films of MWCNT/SnO2 nanocomposite structures.
The choice of corresponding processing technique, treating conditions and
regimes for CNTs functionalization, as well as the modification of thick films
surface with Ru catalyst, are described below in Sect. 2. Results of the
measurements of PG, DMF and FA vapor sensors and their discussions are given
in Sect.3.
Materials and methods
Materials preparation
MWCNT membranes, which were used for the preparation of nanocrystalline
MWCNTs/SnO2 powder, were kindly provided to us by our colleagues from
the University of Szeged, Hungary. MWCNTs were prepared by the decomposition
of acetylene (CVD method) using a Fe, Co/CaCO3 catalyst (Couteau et al.,
2003; Magrez et al., 2010). This growth procedure using a CaCO3 catalyst
enables a highly efficient selective formation of clean MWCNTs, suitable for
efficient bonding between CNT and metal oxide, particularly for SnO2
precursors.
For functionalization of nanotube walls with oxygen-containing hydroxyl
(OH), carbonyl (C=O) and carboxylic (COOH) functional groups, MWCNTs from
the membranes were transferred to slurry in HNO3/H2SO4 acid
mixture over the course of 1 . Such functionalization of the CNTs is vital for the
following synthesis of SnO2 nanoparticles on the MWCNT walls since
these oxygen-containing groups act as sites for the nucleation of
nanoparticles. After rinsing with distilled water and drying at 80 ∘C,
MWCNTs were poured and treated in deionized water in the ultrasonic bath for
5 min.
The preparation of nanocomposite materials with a hydrothermal method was
carried out in two steps. Firstly, purified MWCNTs were dispersed in water
via sonication. Then, a calculated amount of precursor of the
SnCl2⚫2H2 was dissolved in another beaker in water,
after which 3 cm3 HCl was added to the solution. The choice of water as
a solvent, instead of ethanol for example, is connected with the expectation to
improve gas sensing characteristics (Nemeth et al., 2014b). In the next
step, the MWCNT's suspension and the solution of the precursor were mixed
and sonicated for 30 min. To prepare the nanocomposites, we poured
solutions mentioned above into autoclaves, where hydrothermal synthesis was
carried out at 150 ∘C for 1 day. At the end of this procedure, all
obtained nanocomposite powders were filtered and dried at 90 ∘C for 5 h. The final mass ratio of the nanocomposite MWCNTs/SnO2 obtained
with the hydrothermal method in this study was 1 : 200. The
hydrothermal synthesis process is presented in detail again in articles
mentioned above (Aroutiounian et al., 2013, 2014;
Nemeth et al., 2014a).
The paste for the thick film deposition made by mixing powders with α-terpineol (Sigma Aldrich) and methanol was printed on the chemically
treated surface of the alumina substrate over the ready-made Pt
interdigitated electrodes. The thin-film Pt heater was formed on the back of the substrate. Then, the obtained composite structures were cut into
3 mm×3 mm pieces. After that, the drying and annealing processes of
the resulting thick films were carried out in two stages: the first step is
the heating of thick films up to 220 ∘C with the 2 ∘Cmin-1 rate of temperature rise, holding for 3 h and then
increasing in temperature to (but not including) 400 ∘C with the
1 ∘Cmin-1 rate and holding for 3 h. In the second
step, the thick-film specimens were cooled down as the oven cooled.
After annealing and cooling processes, the surface of MWCNTs/SnO2 thick
films was ruthenated by dipping samples into the 0.01 M RuOHCl3 aqueous
solution for 20 min, after which they were dried at 80 ∘C for 30 min. Then, the
annealing treatment was carried out again by the same method noticed above.
The choice of the ruthenium as a catalyst was determined by the advantages
outlined in Aroutiounian et al. (2013, 2014) and Adamyan et al. (2016). At the final stage, ruthenated MWCNT/SnO2 chips were
arranged in TO-5 packages, and the gas sensors would be ready for
measurements after the bonding of leads.
Material characterization
The morphologies of the prepared SnO2/MWCNT nanocomposite powders with
diverse compounds were studied by scanning electron microscopy using a Hitachi
S-4700 Type II FE-SEM equipped with a cold field emission gun operating in
the range of 5–15 kV. The presence of an oxide layer was confirmed by
SEM-EDX. Furthermore, the crystalline structure of the inorganic layer was
also studied by an X-ray diffraction method using the Rigaku Miniflex II
diffractometer (angle range: 2θ = 10–80∘, utilizing
characteristic X-ray (CuKα) radiation). Results of these
investigations were presented in detail in the Aroutiounian's articles
(Aroutiounian et al., 2013, 2014). Here, we
are only noting that the average crystalline size of SnO2 nanoparticles,
estimated from SEM images and XRD patterns, is less than 12 nm, but the
average diameter of non-covered SnO2 nanoparticles CNTs was about 40 nm.
Results and discussions
Some results of the nanocomposite sensors have been presented during the
international conference in Nuremberg (Adamyan et al., 2017). In this paper,
we introduce the extended version of our investigations (surface morphology
studies, as well as characteristics of a gas sensor), but the performances of
PG, DMF and FA sensors are discussed separately. Also, the dependence of
electrical resistance of the sensors on operating temperature, as well as
values of responses, response and recovery times of the sensors at various
operating temperatures or target gas concentrations, is shown here.
Measurement method
In order to measure the testing of the semiconductor gas sensors'
performances and parameters in the real-time mode faster and more reliably, we
developed a similar automated measurement setup. The presence of such a
measurement setup with automated DAQ system facilities makes the search of
the sensor's optimal operation regime and the action of receiving reliable
data about the experiment more accessible.
The developed automated setup leads to measure resistive type gas sensor parameters and allows to display the changes of the resistance of the sensor, which are taking place as a result of fast-acting processes (∼0.1 s)
as well as possible long-term drifts. By using this setup, it
is possible to get the reliable information about all parameters of the
investigated sensors (sensitivity, response and recovery times, sensor's
operation temperature, etc.).
Automated gas-sensor parameter-measurement system flowchart.
The system flowchart in Fig. 1 shows the electromagnetic valve K1 with the
limited-flow faucet as well as the MPX5010DP Motorola pressure sensor connected
to the test chamber by leakless passage. The valve control is fulfilled via
one of the digital outputs of a PCL-818HG data acquisition (DAQ) card.
Connection of the power supply to the sensor's electrodes and heater as well as outputting
of the electric signals from the testing specimen is ensured by utilizing the
hermetic power socket. The signals proceed to the DAQ card through the
PCLD-8115 wiring terminal board. The software control gives the possibility
to change the composition, temperature and gas pressure as well as to tune
the investigated sensors' surface temperature. The channel of the sensors
resistance measurements connects to the DAQ card via a buffer preamplifier. This ensured the size of the resistance and its change over time in the full
range of the resistance values from 10 to 1012 Ω with sufficient
accuracy. The software ensures an automatic adjustment of the measured
resistances and time intervals depending on the entrance of the sensor
signal. The interface of software control allows automatical control of the
environment of the test chamber (letting the flow of a necessary amount of
gas or gas mixture into the chamber). The pressure sensor is providing the
flow of the required amount of gas concentration into the chamber.
The operation temperature is maintained by connection of the electric
voltage to the thin-film resistive heater of the sensor by the power supply
through the DAQ card. The temperature is controlled by the heater resistance
measurements with additional recalculations, taking into account the
temperature efficiency of the heater material. The monitor screen displays
any of the real-time measured parameters, both in digital and graphical
forms, which makes the measurement process transparent and provides the
information for interpreting the measurements. Simultaneously, all received
data are written to an Excel file as a table. The window of the program's
measurements is shown in Fig. 2.
The window of the control program.
Gas sensing properties of the MWCNTs/SnO2 nanocomposite structures were
measured by an in-house-developed and computer-controlled static gas sensor
test system (Adamyan et al., 2007). The sensors were reheated and studied at
different operating temperatures. When the electrical resistance of all
studied sensors was stable, the necessary assigned amount of compound in the
liquid state for testing sensors was injected by a microsyringe into the
measurement chamber. Moreover, the target matter was introduced into the
chamber on the special hot plate designed for the quick conversion of the
liquid substance to its gas phase. After its resistance reached a new
constant value, the test chamber was opened to recover the sensors in the
air.
The measurement chamber with the large volume (45 L) was used in this work
in order to avoid possible vapor condensation on the chamber walls. The
temperature of the gas environment within the chamber was kept near room
temperature and controlled by the thermocouple with digital output.
Thus, the possibility of the developed software-programmable automatic setup
for gas sensor parameters measurements allows the following conditions to be met:
PC control of the electromagnetic valve for generation of gas mixtures
GAS sensor data acquisition and logging
on-screen monitoring of the station
monitoring of the gas composition in real time in parts per million
(ppm)
tracking of the sensor response in real time
robustness allowing measurements spanning months
the different artificial atmosphere variations during a measurement
a graphically improved user interface
monitoring of the operating temperature or voltage applied by the heater
(utilizing the developed-software-controlled power supply)
possibility of controlling the statistical error of the measurements in real
time
on-screen monitoring of the surrounding temperature value
on-screen tracking of the total gas pressure within the measurement
chamber.
A schematic circuit diagram of the apparatus and its parameters is presented
in Adamyan et al. (2007).
The primary measurement circuit, similar to those used by many manufacturers,
is elementary. Generally speaking, the sensor requires two voltage inputs:
heater voltage (VH) and circuit voltage (VC). The VH is applied to
the integrated thin-film heater. Circuit voltage is applied to the voltage
divider consisting of the resistance of the sensor and the load resistance
connected in series. In our case, standard power supply (5.0 ± 0.2 V DC
or AC) is used for both VC and VH to fulfil the sensor's electrical
requirements. Heater resistance (RH) is about 73 Ω at room
temperature. At that, heater current is 63 mA. Heater power consumption is
approximately 315 mW.
Gas sensing characteristics
The sensing characteristics were studied in the 20–300 ∘C operating
temperature range, and the gas response of the sensors determines
Ra/Rg, where Ra and Rg are the electrical resistance in
the air and target gas–air atmosphere, respectively. The response and
recovery times are determined when the time required for reaching the 90 %
resistance changes from the corresponding steady-state value of each signal.
Dependence of electrical resistance change in MWCNTs/SnO2 structures on
operating temperature measured in air at 50 % RH is shown in Fig. 3.
Dependence of electrical resistance change in MWCNTs/SnO2
sensors on operating temperature in the air.
PG, DMF and FA vapor sensor characteristics
As a result of measurements of the sensor resistance in air and an air–gas
environment, the maximal response to 650 ppm PG vapor was revealed at
200 ∘C operating temperature (Fig. 4). Dependence of the response of the
sensor on operating temperature in the presence of 500 ppm DMF and 1160 ppm
FA vapors in the air are also presented in Fig. 4. As demonstrated,
the maximal response to FA and DMF vapors are revealed to be in the range of 200–225 ∘C operating temperatures.
Response vs. operating temperature at 650 ppm PG, 500 ppm DMF and
1160 ppm FA vapor exposure.
Changes in the resistance of the structure depending on PG and FA gas
concentrations are presented in Figs. 5 and 6, respectively. Dependence of
the response of MWCNTs/SnO2 sensors on PG, DMF and FA vapor
concentration are shown in Figs. 7 and 8, respectively. As it is obvious
from the figures, the sensor response occurs down to small target gas
concentrations (13 ppm of PG and 5 ppm of DMF) and the response
depends approximately linearly (on a double logarithmic scale in Fig. 7 and in a
half logarithmic scale in Fig. 8) on the gas concentration in all
cases.
The response–recovery curves observed at different PG
concentrations measured at 200 ∘C operating temperature.
The response–recovery curves observed at different FA
concentrations measured at 200 ∘C operating temperature.
Dependence of the response of MWCNTs/SnO2 PG and DMF vapor
sensor on gas concentration measured at 200 ∘C operating temperature.
Dependence of the response of MWCNTs/SnO2 FA vapor sensor on
gas concentration measured at 200 ∘C operating temperature.
Good repeatability of the sensor response can be seen from Fig. 9, where the
electrical resistance change in PG sensor vs. time measured upon cyclic
exposure of 650 ppm PG vapors in air at 200 ∘C operating temperature is
presented.
The electrical resistance change in
MWCNTs/SnO2 thick-film PG sensors vs. time measured
upon cyclic exposure of 650 ppm PG vapors in air at
200 ∘C operating temperature.
Changes in the response and recovery times of the sensors depending on PG,
DMF and FA vapor concentration are presented in Figs. 10, 11 and
12, respectively.
Dependence of response and recovery times of MWCNTs/SnO2 PG
vapor sensor on gas concentration measured at 200 ∘C operating
temperature.
Dependence of response and recovery times of MWCNTs/SnO2 DMF
vapor sensor on gas concentration measured at 200 ∘C operating
temperature.
Dependence of response and recovery times of MWCNTs/SnO2 FA
vapor sensor on gas concentration measured at 200 ∘C operating
temperature.
Changes in the response and recovery times of the PG and FA vapor sensors
depending on operating temperature are presented in Figs. 13, 14 and
15. Comparison of responses of MWCNTs/SnO2 sensors to 650 ppm PG,
500 ppm DMF and 1160 ppm FA vapor exposure vs. operating temperature is
shown in Fig. 16.
Dependence of the response time of MWCNTs/SnO2 PG vapor
sensor on operating temperature.
Dependence of the recovery time of MWCNTs/SnO2 PG vapor
sensor on operating temperature.
Dependence of the response and recovery times of MWCNTs/SnO2
FA vapor sensor on operating temperature.
Comparison of responses of MWCNTs/SnO2 sensors to 650 ppm
PG, 500 ppm DMF and 1160 ppm FA vapor exposure at various operating
temperatures.
As shown in Fig. 16, sensors demonstrate the best response
against PG and FA vapors at 200 ∘C operating temperature and against DMF
vapor at 225 ∘C operating temperature.
On possible mechanisms of gas sensitivity
It is known that attachment of carboxyl groups on the surface of MWCNTs is
useful in nucleation and trapping of other materials including tin-oxide
nanoparticles. Earlier it was shown that COOH groups, attached on the
surface of MWCNTs, have strong interactions with alcohol vapors, which
result due to the formation of hydrogen bonds between COOH groups and OH
groups of alcohol molecules (Aroutiounian et al., 2013; Adamyan et al.,
2016). This hydrogen bond should be removed by increasing the temperature,
which contributes to long recovery times in MWCNTs/SnO2 sensors.
The higher operating temperature of the gas response is observed up to the
temperature at which the response achieves to its maximal value. With the
subsequent increase in operating temperature, desorption of chemisorbed
oxygen ions takes place, and the gas response decreases. The recovery times
are decreasing.
When there is relatively more content of SnO2 in a nanocomposite, as in our case,
MWCNT nanochannels play a smaller role since nanotubes are entirely closed
by plenty of SnO2 nanoparticles. Accessibility of gas-molecule
penetration to MWCNT nanochannels through the metal-oxide thick film is
very difficult. Therefore the response is mainly determined by the number of
metal-oxide nanoparticles and a considerable amount of surface adsorption
sites. MWCNTs only prevent the formation of SnO2 agglomerates and
thereby ensure the developed surface, due to repulsive forces between the
carboxyl groups adsorbed on it.
The oxidation reaction of PG and DMF vapors on the nanocomposite surface
could be represented as follows, respectively:
C3H8O2(g)+8O-→3CO2(g)+4H2O(g)+8e-
and
4C3H7NO(g)+42O-→12CO2(g)+4NO2(g)+14H2O(g)+42e-.
At the temperature corresponding to the highest response, the reactivity of
the target gas molecules is proportional to the speed of diffusion into the
sensing layer. Hence, the target gas has the chance to penetrate
sufficiently into the sensing layer and react with an appropriate speed. The
competition between the amount of adsorbed target gases and their oxidation
rate supports the maximum response and its sharp decline. With the resulting
increase in operating temperature, desorption of the adsorbed oxygen ions
from the surface of the sensor is growing. It follows that at higher
operating temperatures, fewer oxygen ions are present on the surface of
SnO2, which might be taking part in reaction to target gases. Therefore
the response falls at high operating temperatures. Moreover, the temperature
has an impact on the physical properties of the semiconducting sensor
material. To demonstrate, at higher temperatures the carrier concentration
increases (owing to releasing electrons back to the conduction band in
consequence of desorption of adsorbed oxygen) and the Debye length
decreases. This, in turn, may be one of the possible reasons for the rise in
Rg curve in Fig. 3, which leads to the decrease in response at higher
temperatures.
Although the molecular weight of both considered target gases are close to
each other, the quantity of carbon atoms is just the same. Response from DMF-vapor exposure is smaller because the adsorbed oxygen ions demand the full
oxidation reaction. Therefore a chemical decomposition occurs. Nevertheless,
the 1 : 200 weight ratios of the nanocomposite sensor components, with the
relatively large amount of SnO2 particles, promote an initiation of
the sufficiently large quantity of ionized adsorption centers which, in
turn, ensures a relatively high response to DMF gas exposure.
At exposure to low concentrations of both PG and DMF gases, recovery times
become shorter than response times (Figs. 5, 6). We explain this phenomenon
by the fact that the chemisorption process is developing slower and on a larger scale than desorption of products, obtained in the course of the
chemical reaction. That is due to the necessity of having many adsorption
centers for implementation of the oxidation reaction, as well as because of
desorption after the exposure by low concentrations of gases, which takes
place from the relatively shallow depth of the near-surface layer. Moreover,
the loose structure of the sensitive thick film is obtained because of the
presence of carbon nanotubes in the nanocomposite facilitates and outlet
gaseous products formed by the reaction that leads to a decrease in recovery
times.
At the high-impact gas concentrations, after filling adjacent to the
surface adsorption sites the remaining target gas molecules, only
after overcoming of SnO2 clusters by diffusion and penetrating more
rooted in the nanocomposite layer, are adsorbed there. This leads to
an increase in response time. The same factors affect the rise in recovery
time too.
As Fig. 10 shows, the response and recovery times are highly dependent on
the concentration of propylene glycol. Why do response and recovery times rise
with an increase in concentrations of propylene glycol?
As we pointed out above, propylene glycol in the gas phase is obtained by
vaporization of the liquid, dripping it on the heated metal plate or by
using the temperature resistor (coil). The issue is that a large amount of
the liquid will vaporize if heat transfer occurs very quickly. When it is heated slowly, a portion of PG vapors is lost, condenses or absorbs on the chamber
walls or in other places. Rapid heating is necessary for other areas, as
having a small amount of heat in a confined space of the measurement chamber
and, above all, for ensuring the possibility of the sensor firm performance
determination. Moreover, very high-temperature heat source provides plenty
of oxygen compared with a liquid state (Walter Jr. et al., 1985). This promotes
that at least part of the liquid can attain ignition temperature by heating
(flash temperature is only just 64 ∘C) instead of plain vaporization.
When combustion is complete, and there is plenty of oxygen pieces, as in
this case, the chemisorption reaction happens according to Eq. (1) with
formation just enough volatile CO2 and water to release the conduction
electrons. If the combustion is incomplete and there is not enough oxygen,
intermediate formaldehyde is formed along with the most thermodynamically
stable CO2 and water (Jensen et al., 2015). The oxidation of PG to
formaldehyde (CH2O) happens as follows:
CH2OH-CHOH-CH3+4O-→2CH2O+2H2O+CO2+4e-.
In this case, we explain the sharp rise in PG response and recovery times at high PG
vapor concentrations (beginning from about 300 ppm and higher) by
intermediate formaldehyde formation. It is known that formaldehyde molecules are more stable than PG, but less stable than carbon dioxide (Ertl and
Tornau, 1977). So, decomposition of formaldehyde at high temperatures but
below 300 ∘C occurs very slowly (rate of decomposition is about 0.44 %
per minute). The main products of the decomposition are carbon monoxide and
hydrogen. We suppose that at least part of the formaldehyde gas molecules is
adsorbed on the Ru catalyst. Based on the data of works (Ertl and Tornau,
1977; Vannice, 1975; Borowiecki and Barcicki, 1979) where decomposition of
formaldehyde on Pt, Pd and Ru has been studied, we can assume that the
catalytic decomposition of formaldehyde in our case on ruthenium also occurs
as follows:
.
Here, the dotted lines indicate the weak attraction. Oppositely charged
adsorbed molecules of hydrogen and carbon monoxide are reacted in the
adsorption layer. The primary product of this interaction can be adsorption
complex of formaldehyde. The formation of such complexes occurs at low speed
and goes with a decrease in the work function (Vlasenko and Yuzefovich,
1969). In the presence of carbon monoxide and carbon dioxide gases under
hydrogenation simultaneously, these gases are competing for active
adsorption centers. Since the carbon monoxide molecules will interact with
active sites faster, the hydrogenation of CO occurs, but not as carbon
dioxide (Vlasenko and Yuzefovich, 1969). According Ertl and
Tornau (1977) the process
for carbon dioxide, in this case, occurs sufficiently slowly. The time of formaldehyde decomposition at high concentrations
of PG is close based on the order of magnitude to the response and recovery
times demonstrated in the Figures. At that, more
concentrations of PG and more parts of formaldehyde are involved in Eq. (3) as
more extended response and recovery times of the sensor. The dominant
contribution of the adsorption of formaldehyde or incomplete combustion with
an increase in PG concentration is started, apparently, with about 300 ppm.
Following Ertl and Tornau (1977), the presence of CO and its attractive interaction
with H2 causes a lowering of hydrogen adsorption energy and an increase in
H2 desorption energy, respectively. At lower
concentrations of PG, the proportion of adsorbed complex of formaldehyde is
negligible, and both response and recovery times are relatively short and
defined by the speed of chemisorption and desorption of the Eq. (1)
products. As mentioned, the amount of response and recovery times differs based on
DMF vapor concentrations (Fig. 11). Smaller gas concentrations require less
recovery time than the response time. Practically, in the whole studied
concentrations range, with the rise of gas concentration, the response time
is decreasing whereas recovery time is increasing.