Vol.3, No.6, 471-477 (2011) Natural Science
http://dx.doi.org/10.4236/ns.2011.36065
Conversion of ethanol to acetone & other produces
using nano-sensor SnO2 (110): Ab initio DFT
Leila Mahdavian
Department of Chemistry, Doroud Branch, Islamic Azad University, Doroud, Iran; [e-mail], Mahda-
Received 3 February 2011; revised 18 March 2011; accepted 2 April 2011.
ABSTRACT
The material considered in this study, SnO2
(110), has a widespread use as gas sensor and
oxygen vacancies are known to act as active
catalytic sites for the adsorption of small mo-
lecules. In the following calculations crystal line
SnO2 nano-crystal have been considered. The
grains lattice, which has the rutile structure of
the bulk material, includes oxygen vacancies
and depositing a gaseous molecule, either
ethanol, above an atom on the grain surface,
generates the adsorbed system. The conduc-
tance has a functional relationship with the
structure and the distance molecule of the na-
no- crystal and its dependence on these quanti-
ties parallels the one of the binding energy. The
calculations have quantum mechanical detail
and are based on a semi-empirical (MNDO me-
thod), which is applied to the evaluation of both
the electronic structure and of the conductance.
We study the structural, total energy, thermo-
dynamic and conductive properties of absorp-
tion C2H5OH on nano-crystal, which convert to
acetaldehyde and acetone.
Keywords: Ethanol; Gas Sensor; SnO2 (110);
Electrical Resistance; Semi-Empirical (MNDO).
1. INTRODUCTION
The products of the ethanol dehydrogenation reaction
(C2H5OH  H
2 + products) depend upon the ensem-
ble size of SnO2 [1]. Isolated SnO2 (110) catalyze only
the dehydrogenation to acetaldehyde, whereas multiple
Cu ensembles show high yields of ethyl acetate in addi-
tion to acetaldehyde for surface. Many reactive gases
know metal oxides of gas sensors for their sensitivity but
they are also ill famed for their cross-sensitivity. A well
recognized way for distinguishing gases is using the fact
that different kinds of gases tend to react with different
ease at the sensor surface and that these therefore give
rise to differently shaped gas sensitivity/surface tem-
perature characteristics [2]. In fact, the results obtained
using the nano-spheres clearly demonstrate only the
products of mono atomically dispersed Cu (only acetal-
dehyde is observed) with an apparently improved effi-
ciency [3]. For this reason, it has become popular to ap-
ply temperature modulation techniques to metal oxide
gas sensors in which the surface temperature is rapidly
scanned through a range of temperatures in which there
is a strong variation of the gas sensitivity with surface
temperature [4-7].
Accordingly, it is important to understand the role of
alcohol vapor in the sensing mechanism. The goal of this
work is to improve the detection of surface species of
SnO2 thick film gas sensors under their working condi-
tions using computer calculation, and to correlate the
sensor signals with the relative changes of the electrical
resistance (Ω). Development of ethanol sensors based on
thin film technology offers the advantages of greater
sensitivity, shorter response time and lower costs.
The SnO2 (110) are showed in Figure 1 that primitive
tetragonal unit cell of the bulk SnO2. That is orthorhom-
bic super cell of the slab model. The ethanol reactions on
SnO2 (110) show that basic sites participate in alcohol
dehydrogenation and 3-hydroxybutanal condensation
steps leading to 3-oxobutanal (aldol) and acetone. Chain
growth occurs by condensation reactions involving a
metal-base bi-functional aldol-type coupling of alcohols.
Reactions of C2H5OH–C2H4O mixtures show that di-
rect condensation reactions of ethanol can occur without
requiring the intermediate formation of gas phase acet-
aldehyde [8]. In this work, gas sensors based on SnO2
nano-crystal were fabricated and we report on the etha-
nol sensing properties of the sensors at various mecha-
nisms in room temperature.
All the calculations were carried out using Gaussian
program package. Density Functional Theory (DFT)
calculations interaction between them. The results show
a sensitivity enhancement in resistance and capacitance
when ethanol is near the surface so converted different

L. Mahdavian / Natural Science 3 (2011) 471-477 472
(c)
Figure 1. (a) Primitive tetragonal unit cell of the bulk SnO2, (b)
Optimized configuration Side-view of SnO2 (110) and (c) the
surface adsorption sites for interaction with ethanol.
products.
2. THE COMPUTATIONAL METHODS
The geometry optimizations were performed using an
all-electron linear combination of atomic orbital density
functional theory (DFT) calculations using the Gaussian
program package. In density function theory the exact
exchange Hartree-Fock (HF) for a single determinant is
replaced by a more general expression the exchange
correlation functional which can include terms account-
ing for both exchange energy and the electron correla-
tion which is omitted from Hartree-Fock theory:
() ()
12( )
KSj C
EhpPEE



  (1)
where, () E


is the exchange function and ()C E

is
the correlation functional. The correlation unction of Lee,
Yang and Parr includes both local and nonlocal term. For
the Minimum energy structures and cluster size, we em-
ploy commercial soft ware from MSI [9] and carry out
both linear combinations of atomic orbital (LCAO) and
plane wave pseudo potential (PWPP) calculations at the
DFT± GGA level. The LCAO basis functions are
one-electron orbital of free atoms and free ions [10].
Another advantage is that for specific and well-parame-
terized molecular systems, these methods can calculate
values that are closer to experiment than lower level ab
initio techniques.
Semi-empirical quantum mechanics method used for
calculation all thermodynamic parameters of this inter-
action. Because, we can use the information obtained
from semi-empirical calculations to investigate many
thermodynamic and kinetic aspects of chemical pro-
cesses. Energies and geometries of molecules have clear
relationships to chemical phenomena.
The accuracy of semi-empirical quantum mechanics
method depends on the database used to parameterize
the method. Configuration Interaction (or electron cor-
relation) improves energy calculations using CNDO,
INDO, MINDO/3, MNDO, AM1, PM3, ZINDO/1, and
ZINDO/S for these electron configurations. The heat of
formation is calculated for these methods by subtracting
atomic heats of formation from the binding energy.
MNDO has been used widely to calculate heats of for-
mation, molecular geometries, dipole moments, ioniza-
tion energies, electron affinities, and other properties [11,
12]. MNDO gives better results for some classes of mo-
lecule, such as some phosphorus compounds.
 Closed-shell singlet ground states
 Half-electron, excited singlet states
 Half-electron, doublet, triplet, and quartet open-
shell ground states.
MNDO is a Modified Neglect of Diatomic Overlap
method based on the neglect of diatomic differential
overlap (NDDO) approximation. In order to compute the
average properties from a microscopic description of a
real system, one shall evaluate integrals over phase
space. It may be calculated for an N-particle system in
an ensemble with distribution function P(rN), the ex-
perimental value of a property A(rN) from:



 
N
NNN
A
rArPrdr (2)
The problem with direct evaluation of this mul-
ti-dimensional integral (apart of the huge number of
phase space points as a sample) is that most of the con-
figurations sampled contribute nothing to the integral.
Having energy is so high that the probability of their
occurrence is vanishing small [13,14].
The RMS gradient that is reported is just the root-
mean square average of the Cartesian components of the
gradient vector. For multi-dimensional potential energy
surfaces a convenient measure of the gradient vector is
the root-mean-square (RMS) gradient described by RMS
Gradient:

12
22 2
1
3
AAA A
EEE
NXYZ















 (3)
For a molecular mechanics calculation the energy and
the gradient are essentially the only quantities available
from a single point calculation. Ball-and-stick models of
the (110) surface are showed in Figure 1 that converting
of ethanol to other products on SnO2 (110) simulated by
program package and the adsorption, electric, binding
nuclear energy, RMS gradient, heat of formation and
Gibbs free energy are calculated by MNDO methods in
semi empirical quantum by Gaussian program package.
The electric resistance for them is following as:

L. Mahdavian / Natural Science 3 (2011) 471-477 473
elec
ERI (4)
where, elec
Eis electric energy (V), R () is electric re-
sistance and I (A) is electric intensity that is q
It

and
q(C) is electric charge and t is time interaction, in ex-
perimental data, it is so:
elec
Et
RnF  (5)
where, n, F and t are electron number of conversion,
faraday constant and time (h) respectively.
3. RESULTS AND DISCUSSION
Therefore, the surface energies of several low-index
facets of SnO2 also known as rutile or tetragonal phase,
space group P42mnm, lattice parameters are a = b =
4.7374 oA and c = 3.1864 oA. In the bulk all Sn atoms
are six fold coordinated to threefold coordinated oxygen
atoms. The surface energies of low index SnO2 surfaces
with a termination that maintains the bulk composition
have been calculated (Figure 1) [15-20].
Semi conducting sensors offer an inexpensive and
simple method for monitoring gases. The change of the
electrical conductivity of semi conducting materials
upon exposure to reducing gas C2H5OH has been used
for gas detection. Therefore, SnO2 have been used util-
izing as the sensing material in pressure, flow, thermal,
gas, optical, mass, position, stress, strain, chemical, and
biological sensors [21-23]. Ethanol near SnO2 surface
was converted other products such as: acetaldehyde,
ethyl acetate, acetone and etc, which is shown in Figure
2. The mechanism conversion ethanol to other produces
on nano-crystal SnO2 (110) are investigated with MNDO
methods. The other methods in DFT can not calculate
these parameters for SnO2 with 24 Sn atoms and theirs
calculation are most heavy.
3.1. The Interaction of Ethanol with SnO2
3.1.1. Formation of Acetaldehyde
It by the oxidative dehydrogenation of ethanol de-
pends critically upon the reaction step that requires the
oxide surface to acquire a negative charge. It is well ac-
cepted that upon adsorption, the O–H bond of the alco-
hol dissociates hydrolytically to yield an ethoxide and a
proton as follows in Figure 3.
This type of interaction is more known as an acid-base
interaction, where the H atom of the acid (in this case
ethanol) interacts with one surface O2– (the base). Si-
multaneously, the Sn4+ site (acting as Lewis acid) inter-
acts with the O (2p) orbital of the oxygen of the ad
sorbed ethanol molecule.
A sequential reaction scheme, where ethanol dehy-
drogenates to form gas phase acetaldehyde, which then
undergoes self-condensation reactions into products, is
not considered, because it is not consistent with the
Figure 2. Products of interaction: Ethanol+ SnO2.

L. Mahdavian / Natural Science 3 (2011) 471-477 474
Figure 3. The mechanism converted ethanol to acetaldehyde on SnO2 (110) by seven steps.
sharp initial increase in product site-yield curves (Figure
1). The proposed mechanism involves the initial dissoci-
ate adsorption of ethanol on SnO2 to form ethoxide and
hydrogen species. Hydrogen species can then is removed
by migration to surface sites, recombination with another
hydrogen ad atom, and adsorption as H2. Additional C–H
bond cleavage events in ethoxide species can then occur
and the hydrogen atoms formed are transferred to oxy-
gen ions and form surface acetaldehyde species. Ball-
and-stick model of this interaction for DFT calculation is
seen in Figure 4. We calculated that the conductance and
thermodynamic properties this interaction on SnO2 sam-
ples that could be substantially increased or decreased in
exposure to ethanol by DFT, which the results are
showed Table 1. After adsorption of ethanol on surface
and transition electron between them, the electric resis-
tance to time (h) decreased that showed in Figure 5.
A current versus voltage curve recorded with a SnO2
sample after time exposure to ethanol showed an up-fold
of conductance depletion (Figure 4). Exposure to etha-
nol molecules increased the conductance of the SnO2
sample (Figure 5). The SnO2 is a hole-doped semicon-
ductor, as can be gleaned from the current versus gate
voltage curve (middle curve in Figure 5), where the
electric resistance of the SnO2 is observed to decrease.
In Table 1, the adsorption of energy is negative, which
this interaction is exothermic, when ethanol is converted
to acetaldehyde; it is –71.13 MJ/mol. Their heat of for-
mation is increased for this conversion on surface be-
cause electrons are translated between surface and etha-
nol molecule in transient state. The heat of formation is
enhanced for intermediates (1433.78 MJ/mol) and tran-
sient state (1208.01 MJ/mol) and then it is reduced for
product (442.85 MJ/mol). That for binding energy and
nucleic energy is too. Suitable default values for ending
Figure 4. The adsorption ethanol and formation of surface
(SnO2 (110)) ethoxides so converted acetaldehyde.
Figure 5. Electrical resistance (Ω) of from Ethanol to acetal-
dehyde with SnO2 (100).

L. Mahdavian / Natural Science 3 (2011) 471-477 475
Table.1. The properties thermodynamic of interaction ethanol
with SnO2 (110).
Ethanol on SnO2 (110) - based sensor to acetaldehyde
Time(h) E ads
(MJ/mol)
RMS
Kcal/mol.oAEelec(V) E bin (MJ /mol)
1 –297.27 1699 –1489.79 963.60
4 –292.09 1357 –1437.89 1433.78
6 –268.30 1546 –1526.91 992.56
8 –71.13 1421 –1507.98 1189.73
10 –83.66 1363 –1601.32 424.57
11 –153.89 1665 –1444.12 1106.97
Time(h) H
(MJ /mol)
Gele
(MJ /mol)
E nuc
(MJ /mol)
1 981.88 –10142.46 9845.20
4 1452.07 –9789.16 9962.09
6 1010.85 –10395.19 10126.89
8 1208.01 –10266.33 10195.19
10 442.85 –10901.73 10065.43
11 1125.25 –9831.54 9677.64
an optimization calculation are either an RMS gradient
of 0.1 Mcal/mol. Å or a maximum number of cycles that
is 15 times the number of atoms involved in the calcula-
tion. In general, we must use a gradient limit. For im-
proved precision, use a lower gradient limit. For most
organic molecules, this will result in an acceptance ratio
of about 0.9, which means that about 50% of all moves
are accepted. This result shows why surfaces that pro-
mote oxidative dehydrogenation reactions tend to be
those containing reducible and reoxidisable cations. The
residual hydrogen from ethanol adsorption generally
desorbs either as H2.
3.1.2. Formation of Ethyl Acetate
Now, in environment of reaction, there are ethanol and
acetaldehyde that ethyl acetate represents the second
most important reaction product in our calculations. The
intermediates and transient states for this interaction are
seen in Figure 6. In this reaction requires H transfer
from one adsorbed acetaldehyde, which becomes oxi-
dized to another adsorbed ethanol, which is reduced to
alkoxide.
This process may form a complex in a transition state
that requires participation of the surface oxygen: where
an adsorbed acetaldehyde molecule with the participa-
tion of a surface oxygen anion transfers a hydride to an-
other adsorbed ethanol molecule that in Figure 7
showed ballstick model for it. In this figure is seen
ethanol and acetaldehyde near by Sn4+, so their O atom
interacted with Sn4+ surface. All stapes of this interaction
is showed in Figure 6 by nine steps.
The retention of oxygen associated with the C (5th step
in Figure 6) intermediate believed to be caused by the
strong bonding of the alkyl oxygen in the di-oxygenated
CH3CH2OCH3CO-intermediate anion to the ethyl acetate
which theirs results showed in Table 2. The electric re-
sistance (Ω) for this interaction calculated by Eq.4 that
is showed in Figure 8. The ethanol and acetaldehyde are
neared to nano-surface and converted to ethyl acetate,
their electrons are transferred to SnO2, and so the electric
resistance is decreased.
It is well accepted that upon adsorption, the O–H bond
of alcohol and C = O of acetaldehyde dissociates hydro-
lytically to yield an ethoxide and alkoxide, which inter-
mediate molecules are presented on nano-surface and
increased the electric energy (V) in Table 2.
It is clear from the table that for all steps the electrical
conductivity increased with an increase in the nuclear
energy (11355.11MJ/mol) of interaction, indicating the
semiconductor enhanced for it in Figure 8.
At the same time, the SnO2 nano-crystal based sensors
always showed higher sensitivity to acetaldehyde and
ethanol mixture than to ethanol, the adsorption energy is
–1269.60 MJ/mol for time 4(h). The hydrogen formation
was monitored during steady state ethanol oxidation and
SnO2 were found to be the most active catalysts. These
results show that Sn sites also increase rates of C–H
bond activation in acetaldehyde and O-H in ethanol. In
Figure 6. The mechanism converted ethanol to ethyl acetate on SnO2 (110) by nine steps.

L. Mahdavian / Natural Science 3 (2011) 471-477 476
Figure 7. the adsorption ethanol and formation of surface
(SnO2 (110)) ethoxides so converted ethyl acetate.
Figure 8. Electrical resistance (Ω) of from ethanol and acetal-
dehyde to ethyl acetate with SnO2 (110).
Table.2. The properties thermodynamic of interaction ethanol
and acetaldehyde with SnO2 (110).
Ethanol and acetaldehyde on SnO2 (110) - based sensor to ethyl
acetate
Time(h) E ads
(MJ/mol)
RMS
kcal/mol·Å
Eelec
(V)
E bin
(MJ/mol)
1 –303.03 1484 –1496.14 1622.64
4 –1269.60 1503 –1791.39 1649.98
6 –532.05 1510 –1657.00 1372.81
8 –141.10 1561 –1647.19 1460.70
10 –222.57 1669 –1618.53 1542.18
11 –580.38 1685 –1546.74 1377.64
Time(h) H
(MJ /mol)
Gele
(MJ /mol)
E nuc
(MJ/mol)
1 1643.48 –10185.68 10488.71
4 1670.82 –12195.73 10926.11
6 1393.65 –11280.83 11334.04
8 1481.54 –11214.02 11355.11
10 1563.02 –11018.90 11241.48
11 1398.49 –10530.17 10588.20
Table 2 is showed, this interaction is exothermic, when
they are converted to ethyl acetate; their heat of forma-
tion is increased so decreased for this conversion be-
cause electrons are translated between surface and so
between ethoxide and alkoxide molecules in transient
state. The heat of formation has lease amount the inter-
mediates (1393.65 MJ/mol) in time 6 (h) then it is re-
duced to product (1398.46 MJ/mol). The changes of
binding energy and nuclear energy are to likes the heat
of formation that can see in Table 2.
4. CONCLUSIONS
The tin oxide (SnO2) is a well-known n-type semi
conducting oxide that has been widely used for reducing
gases in an operating temperature range of 273–443 K.
This oxide material has high reactivity towards reducing
gases at relatively low operating temperature, easy ad-
sorption of oxygen on its surface because of its natural
non-stoichiometry, stable phase and many more desir-
able attributes such as cheapness and simplicity. For
monolayer coverage the C–O bond cleavage process was
favored. This appears to be in contradiction to the ex-
perimental results discussed above where ethoxide and
acetaldehyde production was observed.
At the gas sensor surface, associative adsorption of
the ethanol molecules was preferred similar to the DFT
calculations. Accurate DFT calculations as well as com-
putationally less expensive interatomic potential based
simulations have been employed to study the structures
and stabilities of SnO2 surface and their affinity for
ethanol. We investigated the adsorption of ethanol mo-
lecules at the under-coordinated (110) surface in SnO2.
Upon full electronic and geometry optimization, the
ethanol molecule associated, with the formation of acet-
aldehyde on the surface (Figures 6, 7), indicating that
there is significant energy barrier to the association of an
ethanol molecule. The surface energy of a surface is a
measurement of its thermodynamic stability, where a
low and positive value indicates a stable surface, which
showing the interplay between electronic structure cal-
culations and potential-based techniques, is a clear ex-
ample of the benefits derived in employing complemen-
tary methods to identify and investigate important sur-
face features and reactivates.
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