Heliyon 9 (2023) e20610
Contents lists available at ScienceDirect
Heliyon
journal homepage: www.cell.com/heliyon
Electrical and dielectric characteristics of molybdenum dioxide
nanoparticles for high-performance electrocatalysis
Ibrahim Soliman a, b, Bijaya Basnet b, Sulata K. Sahu a, Dhruba Panthi c, Yanhai Du a, *
a
b
c
College of Aeronautics and Engineering, Kent State University, Kent, OH 44242, USA
Advanced Materials and Liquid Crystal Institute, Kent State University, Kent, OH, 44242, USA
Department of Engineering Technology, Kent State University at Tuscarawas, New Philadelphia, OH, 44663, USA
A R T I C L E I N F O
A B S T R A C T
Keywords:
AC conductivity
Dielectric constant
Barrier height
Dynamic response
Electrocatalysis
As an attempt to improve the catalytic processes in different electrochemical systems, molyb
denum dioxide nanoparticles were prepared using the hydrothermal method, and their electrical
and dielectric properties were investigated. The nanoparticles were polycrystalline with an
orthorhombic structure. AC electrical transport properties of the pressed disc were conducted
over a temperature range of 303–423 K and a frequency range of 42–5 × 106 Hz. The AC con
ductivity follows Jonscher’s universal dynamic law, and it has been determined that correlated
barrier hopping (CBH) is the primary conduction mechanism. The maximum barrier height (WM )
was found to be 0.92 eV. The low activation energy showed that hopping conduction is the
dominant mechanism of transporting current. The dielectric parameters were analyzed using both
complex permittivity and complex electric modulus, with a focus on how they vary with tem
perature and frequency. At relatively high temperatures and low frequencies, the dielectric pa
rameters showed a high-frequency dependence. The dielectric modulus showed that relaxation
peaks move towards lower frequency when temperature increases. The dielectric relaxation
activation energy, Δ Eω was determined to be 0.31 eV.
1. Introduction
Molybdenum dioxide (MoO2) nanoparticles have gained significant attention as efficient catalysts in various electrocatalytic
processes due to their unique electrical and dielectric properties [1,2]. These properties play a crucial role in determining the catalytic
performance of MoO2 nanoparticles and can be tailored to enhance their activity and stability. In electrochemical reactions, MoO2
nanoparticles can be used as catalysts to enhance energy conversions and storage technologies such as fuel cells [3,4], water elec
trolyzers [5], and photoelectrochemical cells [6]. These electrochemical reactions are influenced significantly by the electrical pa
rameters of MoO2 nanoparticles, such as conductivity and charge transport characteristics. The high conductivity of MoO2
nanoparticles enhances the electrocatalytic performance at the catalyst-electrolyte interface, facilitating charge transfer and the redox
reaction involved in various electrocatalytic processes [7]. Furthermore, dielectric properties such as dielectric constant and dispersion
loss, can provide insight into the behavior of MoO2 nanoparticles in electrocatalysis. At the catalyst-electrolyte interface, the dielectric
constant influences polarization effects, affecting the kinetics of reactants adsorption and desorption [8]. Additionally, dielectric
spectroscopy sheds light on reaction mechanisms and kinetics by providing a comprehensive understanding of charge storge and
* Corresponding author.
E-mail address: ydu5@kent.edu (Y. Du).
https://doi.org/10.1016/j.heliyon.2023.e20610
Received 23 February 2023; Received in revised form 18 September 2023; Accepted 2 October 2023
Available online 6 October 2023
2405-8440/Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Heliyon 9 (2023) e20610
I. Soliman et al.
relaxation process [9].
There have been extensive studies on the catalytic efficiency of MoO2 nanoparticles in different electrocatalytic processes. In the
oxygen reduction reaction (ORR), MoO2 nanoparticles have displayed a remarkable catalytic activity comparable to traditional
platinum-based catalysts, which makes them an attractive candidate and efficient alternative [10]. Furthermore, MoO2 nanoparticles
have demonstrated promising performance in hydrogen evolution reactions (HERs) and oxygen evolution reactions (OERs) [11],
which are critical in renewable energy and water electrolysis. Optimizing the electrocatalytic performance of MoO2 nanoparticles
requires comprehensive understanding of their electrical and dielectric parameters. By utilizing these parameters, a research endeavor
can be undertaken to uncover the underlying mechanisms that dictate catalytic activities, improve overall performance, and advance
the development of superior electrocatalysts based on MoO2. In this study, we aim to provide valuable insights into the electrical
properties and dielectric spectroscopy of MoO2 nanoparticles under a wide range of temperatures. With the comprehensive charac
terization of these parameters, we are able to establish a deeper understanding of the conduction mechanisms controlling electrical
conduction and gain insights into the sources of dielectric losses and defects within MoO2 nanoparticles. This research contributes to a
broader knowledge base for the application of MoO2 as electrocatalysts.
2. Experimental techniques
The synthesis of MoO2 nanoparticles was performed using a hydrothermal method, following the procedure established by Ellefson
et al. [12]. Molybdenum trioxide (MoO3) dry powder, purchased from Sigma-Aldrich, served as the starting material. To initiate the
synthesis, 0.3 g of MoO3 powder was combined with 10 ml of ethylene glycol. Subsequently, 30 ml of distilled water was added to the
mixture in a stainless steel-lined autoclave. To ensure a controlled reaction environment, the autoclave was tightly sealed, eliminating
any external contaminants. The sealed autoclave was then subjected to a constant temperature of 180 ◦ C for a duration of 12 h,
allowing for the hydrothermal reaction to take place. During the hydrothermal process, the elevated temperature and pressure within
the autoclave provided favorable conditions for the reduction of MoO3 and the subsequent formation of MoO2 nanoparticles. The
interaction between MoO3, ethylene glycol, and water molecules under these conditions facilitated the transformation of the precursor
into the desired MoO2 nanoparticles. After the completion of the hydrothermal reaction, the autoclave was allowed to cool down to
room temperature. The resulting product, MoO2 nanoparticles, was then collected and air-dried at 50 ◦ C. X-ray diffraction spectros
copy (XRD, Rigaku MiniFlex 600) was used to study the nanostructure of the materials in the 2θ range of 5–90◦ . The diffraction
patterns were collected automatically at a scanning speed 2◦ min− 1 within the 2θ range. Scanning electron micrographs of MoO2 were
obtained with a field emission scanning electron microscope model-Quanta 250 FEG (FEI). A uniaxial press with a steel holder and 2 ×
108 Nm− 2 of pressure was used to press the nanopowder into a disc shape. The uniaxial press maintains the output disc homogeneity
and inhibits the growth of cracks or voids. The produced disc has an approximate thickness of 1.1 mm and an average diameter of 7
mm. The study utilized two layers of silver as ohmic contacts for alternating current Ac measurements on an AlPcCl disc. The mea
surements were conducted using a Hioki 3532 programmable RLC bridge and included the determination of phase angle, impedance,
resistance, and capacitance within a frequency range of 42–5 × 106 Hz. Additionally, a technique for calculating the total conductivity
σt of a substance was employed, utilizing a thermocouple within a temperature range of 303–423 K. The equation used to determine
conductivity was σt (ω,T) = d/AZ, where A represents the sample’s cross-sectional area, d represents the thickness of the disc, and Z is a
constant.
Fig. 1. XRD of MoO2 in powder form.
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3. Results and discussion
3.1. Structural characterization
The X-ray diffraction pattern of the MoO2 powder is shown in Fig. 1. The diffraction patterns indicate that the powder material is
polycrystalline. The peaks that were observed were matched to JCPDS standards and it was determined that all of the reflections
observed can be aligned with an orthorhombic structure (JCPDS No.03-065-5787). The Scherrer formula Eq. 1 was utilized to calculate
the full width at half maximum (FWHM) for determining the particle size [13]:
D=
0.94λ
β cos(θ)
(1)
The mean crystallite size (D) was determined by analyzing X-ray diffraction data using the Debye-Scherrer equation. The equation
utilizes the wavelength of the copper target (λ), the full width at half maximum (FWHM) of the diffraction peak (β), and the diffraction
angle (θ). The average grain size as determined by this XRD analysis was approximately 11.44 nm, which is consistent with the size
measurements obtained through scanning electron microscopy, as illustrated in Fig. 2. On the scanning micrograph, nanocrystalline
spherical particles of 15–35 nm are distributed almost uniformly across the surface of the sample.
3.2. AC conductivity
The total electrical conductivity σt (ω, T) of a material is a measure of its ability to conduct electrical current. It is a function of both
frequency (ω) and temperature (T) and can vary greatly depending on the material and the specific conditions under which it is being
measured. In the literature, Eq. (2) is an empirical relation that describes the total electrical conductivity over a wide range of fre
quencies and temperatures [14,15]:
(2)
σt (ω, T) = σdc (T) + σac (ω, T)
The total electrical conductivity σt (ω, T) of the material can be separated into two components: a frequency-independent DC
conductivity σdc (ω, T), and a frequency-dependent conductivity σac (ω, T). The frequency-independent conductivity σdc (ω, T), can be
calculated by extrapolating experimental data at low frequency down to zero value, using Eq. (2). The frequency dependence of σac (ω,
T) at different temperatures is illustrated in Fig. 3, and can be described mathematically using Eq. (3) [16]:
(3)
σac (ω) = Aωs
where ω is the angular frequency, A is a constant that is dependent on temperature, and S is the frequency exponent factor. The
frequency exponent S is plotted as a function of temperature, and different theoretical models for AC conductivity can be used to
explain the temperature dependence of s and the conduction mechanism. This can provide insight into the electronic properties of the
material. As per the electron tunneling model, the frequency exponent s is not depending on the temperature but on frequency. For
some forms of tunneling, such as large polaron tunneling, s is seen to decrease to a certain temperature range and then increase. This is
observed in Fig. 4 where the value of s reduces as temperature increases. This pattern is explained by the correlated barrier hopping
theory, where the charge carriers move between sites by jumping over potential barriers between them. This mechanism states that the
frequency exponent s decreases as temperature increases. Eq. (4) represents the AC conductivity in this model is represented as follows
[17]:
Fig. 2. SEM micrographs of MoO2 surface.
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Fig. 3. Frequency dependence of σac for MoO2 at different temperatures.
Fig. 4. Temperature dependence of power exponent (s).
Fig. 5. Temperature dependence of σ ac at different frequencies.
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σac (ω) =
π 2 [N(EF )]2 ε
24
(
8e2
εWM
)6
ωs
τ1−0 s
(4)
The model includes several parameters, including the density of localized states N (EF ), dielectric constant (ε), electronic charge (e),
maximum barrier height for electron hopping WM , and effective relaxation time τo . Additionally, the frequency exponent (s) is also
provided [17]:
s=1−
6KB T
[WM + KB Tln(ωτo )]
(5)
The initial approximation results in a simple formula for the s value, which is given by Eq. (6) [18]:
(
/
)
s = 1 – 6K (B) T WM
(6)
The value of WM was determined to be 0.92 eV when the temperature is set to 303 K and using the Boltzmann constant KB. Fig. 5
shows how σac changes with temperature. The temperature causes the ln (σac ) to increase linearly at different frequencies, meaning that
the ac conductivity is affected by temperature through different localized states of the gap [19]. It has been determined that the
dependence of σac on temperature determined by the following Eq. (7) [16].
(7)
σac = σ0 exp(− ΔEac / KB T)
Where σo is the pre-exponential constant and ΔEac is the activation energy of Ac conduction. The slopes of the lines in Fig. 5 are used to
calculate the activation energy of AC conduction at different frequencies. Fig. 6 shows the relationship between frequency and ΔEac. As
the frequency increases, ΔEac tends to decrease. The current transport is mainly driven by hopping conduction, which is characterized
by low activation energy. Thus, when the frequency increases, the electronic jumps between the localized states also increase [20].
3.3. Dielectric studies
The complex dielectric permittivity of a material, ε* (ω) = ε1 (ω) + ε2 (ω), is composed of two parts: the dielectric constant (ε1 )
which is the real component, and the dielectric loss (ε2 ) which is the imaginary component [19–21]. The ratio between these two parts
is called the loss tangent (tan δ = ε2 / ε1 ) [21]. Studying the frequency dependence of the dielectric constant is shown in Fig. 7. The
results show that at a constant temperature, the dielectric constant decreases as the frequency increases. This means that the material’s
ability to store electrical energy in an electric field decreases as the frequency increases. The decrease in dielectric constant with
increasing frequency is caused by the dipoles’ inability to rotate quickly and follow the applied field at high frequencies [21]. Fig. 8
illustrates the relationship between the dielectric constant represented by ε1 , and temperature at constant frequencies. The figure
shows that as the temperature increases, the dielectric constant also increases. This implies that the material’s ability to store electrical
energy in an electric field increases as the temperature increases. This behavior can be attributed to the increase in kinetic energy of the
material’s electrons as the temperature rises, which allows them to move more freely and align better with the electric field. Addi
tionally, at higher temperatures, the material’s ions vibrate more, leading to increased polarizability of the material, and further
contributing to the increase in dielectric constant [22]. Figs. 9 and 10 show how the dielectric loss, ε2 , changes with frequency and
temperature respectively. The data in the figures reveal that the values of ε2 follow a similar pattern as ε1 . The main source of dielectric
loss is dipole loss which occurs due to the rotational movement of the dipoles in the material [22]. Additionally, as the temperature
increases, the movement of the dipoles and free charge carriers in the material increases, leading to an increase in the losses due to
Fig. 6. Frequency dependence of the AC activation energy for MoO2.
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Fig. 7. Frequency dependence of dielectric constant, ε1 , at different temperatures.
Fig. 8. Temperature dependence of dielectric constant, ε1 , at different frequencies.
Fig. 9. Frequency dependence of dielectric constant, ε2 , at different temperatures.
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Fig. 10. Temperature dependence of dielectric constant, ε2 , at different frequencies.
dipole movement and conduction [22]. Dielectric modulus, also known as electric modulus, M*, can be used as an alternative way to
describe the electrical properties of materials. M* gives an insight into how a material responds to an applied electric field and the
relationship between electric displacement and field strength and helps to distinguish between the material’s general electrical
conductivity and localized dielectric properties, like dipole reorientation. The real and imaginary dielectric moduli, represented by M′
and M″, respectively, were calculated using the standard formulas as shown in Eqs. (8)–(10) [23]:
(8)
M* (ω) = 1 / ε* (ω) = M′ + iM″
M′(ω) = ε1
M″(ω) = ε2
/[
]
(ε1 )2 + (ε2 )2
(9)
/[
]
(ε1 )2 + (ε2 )2
(10)
The values of M (ω) as depicted is shown in Fig. 11. In the low-frequency range, values tend to zero. The presence of a lowfrequency tail may be a result of the high capacitance associated with the electrodes [24]. A well-defined peak becomes more pro
nounced as the temperature increases. This is accompanied by a systematic shift of the maximum peak position towards higher fre
quencies, implying that the relaxation rate of the process increases with increasing temperature [21]. The area below the peak
maximum in frequency is significant in figuring out the range where the charge carriers are capable of moving over long distances. The
characteristic relaxation times can be calculated by measuring the inverse frequency of maximum positions, with the equation τm =
ω−m1 [25]. By utilizing the Arrhenius relationship using Eq. (11), the temperature dependence of the characteristic relaxation time can
be identified, as depicted in Fig. 12.
″
Fig. 11. Frequency dependence of electric modulus, M″, at different temperatures.
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Fig. 12. Variation of ln ωmax vs. 1000/T.
(11)
ωm = ωo exp(− ΔEω / KB T)
where ωo is the pre-exponent factor, Δ Eω is the activation energy for dielectric relaxation. the value of ΔEω was determined to be
approximately 0.31 eV. The graph in Fig. 13 depicts the plots between M″/ M″max vs. ln (ω /ωm ) at different temperatures, where M″max is
the maximum value of the imaginary component of the electric modulus. The fact that the curves for all temperatures overlap shows
that all the dynamic processes are relatively independent of temperature [26].
4. Conclusion
A simple hydrothermal synthesis method was used to synthesize MoO2 nanoparticles. Microstructural, morphological, electrical,
and dielectric properties of the catalyst material were conducted. The XRD and SEM results confirmed the polycrystalline nature of the
prepared samples. The frequency dependence of σac at different temperatures was studied to determine the conduction mechanism.
Correlated barrier hopping was found to be the dominant conduction mechanism where carriers hop between conduction sites over a
potential barrier separating them. The temperature dependence of σac at different frequencies was investigated to determine the
activation energy ΔEac, which was found to be decreased with increasing frequency. The dielectric properties were studied as a
function of frequency and temperature. The dielectric properties were decreasing with increasing frequency, but at relatively high
temperatures and low frequencies, the dielectric constant exhibited high-frequency dependence. As a result, the polarizability factor of
ϵ1 and ϵ2 is a result of relaxation polarization (interfacial and orientational) and deformational polarization (ionic and electronic). The
electric modulus M* was studied to determine dielectric relaxation, which was found to be 0.31 eV. Besides, it explained how dynamic
processes depend on temperature.
Fig. 13. Normalized plots of M″/ M″max vs. ln (ω /ωmax ) at different temperatures.
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Author contribution statement
Ibrahim Soliman: Conceived and designed the experiments; Performed the experiments; Analyzed and interpreted the data; Wrote
the paper.
Bijaya Basnet: Conceived and designed the experiments; Performed the experiments; Analyzed and interpreted the data;
Contributed reagents, materials, analysis tools or data.
Sulata K. Sahu, Dhruba Panthi: Contributed reagents, materials, analysis tools or data.
Yanhai Du: Conceived and designed the experiments; Analyzed and interpreted the data; Contributed reagents, materials, analysis
tools or data; Wrote the paper.
Data availability statement
Data will be made available on request.
Declaration of competing interest
We do not have either financial interest or personal relationship which may be considered as potential competing interest.
References
[1]
[2]
[3]
[4]
[5]
[6]
[7]
[8]
[9]
[10]
[11]
[12]
[13]
[14]
[15]
[16]
[17]
[18]
[19]
[20]
[21]
[22]
[23]
[24]
[25]
[26]
Z. Zhuang, J. Huang, Y. Li, L. Zhou, L. Mai, Chemelectrochem 6 (2019) 3570–3589.
I.A. De Castro, R.S. Datta, J.Z. Ou, A. Castellanos-Gomez, S. Sriram, T. Daeneke, K. Kalantar-zadeh, Adv. Mater. 29 (2017), 1701619.
X. Yang, D. Panthi, N. Hedayat, T. He, F. Chen, W. Guan, Y. Du, Electrochem. Commun. 86 (2018) 126–129.
S. Karthick, K. Haribabu, Fuel 275 (2020), 117994.
A.Y. Faid, A.O. Barnett, F. Seland, S. Sunde, ACS Appl. Energy Mater. 4 (2021) 3327–3340.
X. Wu, J. Li, Y. Li, Z. Wen, Chem. Eng. J. 409 (2021), 128161.
X. Chen, H. Sun, P. Liang, X. Zhang, X. Huang, J. Power Sources 324 (2016) 79–85.
D. Saha, P. Kruse, J. Electrochem. Soc. 167 (2020), 126517.
E. Zhou, C. Wang, Q. Zhao, Z. Li, M. Shao, X. Deng, X. Liu, X. Xu, Ceram. Int. 42 (2016) 2198–2203.
L. Yang, J. Yu, Z. Wei, G. Li, L. Cao, W. Zhou, S. Chen, Nano Energy 41 (2017) 772–779.
J. Chen, X. Qi, C. Liu, J. Zeng, T. Liang, ACS Appl. Mater. Interfaces 12 (2020) 51418–51427.
A. V Shishkin, M.Y. Sokol, A.A. Vostrikov, Thermophys. Aeromechanics 20 (2013) 647–650.
M.M. El-Nahass, H.S. Soliman, B.A. Khalifa, I.M. Soliman, Mater. Sci. Semicond. Process. 38 (2015).
A.K. Jonscher, Nature 267 (1977) 673–679.
K. Shimakawa, S.R. Elliott, Phys. Rev. B 38 (1988), 12479.
I.M. Soliman, M.M. El-Nahass, Y. Mansour, Solid State Commun. 225 (2016).
S.R. Elliott, Philos. Mag. A 36 (1977) 1291–1304.
S.A. Mansour, I.S. Yahia, F. Yakuphanoglu, Dye. Pigment. 87 (2010) 144–148.
F. Yakuphanoglu, Y. Aydogdu, U. Schatzschneider, E. Rentschler, Solid State Commun. 128 (2003) 63–67.
H.S. Soliman, M. Ibrahim, M.A.M. El-Mansy, S.M. Atef, Opt. Mater. 72 (2017) 122–129.
M.M. El-Nahass, H.A.M. Ali, Solid State Commun. 152 (2012) 1084–1088.
N.A. Hegab, M.A. Afifi, H.E. Atyia, A.S. Farid, J. Alloys Compd. 477 (2009) 925–930.
J. Wei, L. Zhu, Prog. Polym. Sci. 106 (2020), 101254.
S.B. Aziz, O.G. Abdullah, S.R. Saeed, H.M. Ahmed, Int. J. Electrochem. Sci. 13 (2018) 3812–3826.
M.H. Buraidah, L.P. Teo, S.R. Majid, A.K. Arof, Phys. B Condens. Matter 404 (2009) 1373–1379.
M. Jebli, M.A. Albedah, J. Dhahri, M. Ben Henda, M.L. Bouazizi, H. Belmabrouk, J. Inorg. Organomet. Polym. Mater. (2022) 1–20.
9
