Journal of Hazardous Materials 429 (2022) 128321
Contents lists available at ScienceDirect
Journal of Hazardous Materials
journal homepage: www.elsevier.com/locate/jhazmat
Review
Gas sensing based on metal-organic frameworks: Concepts, functions,
and developments
Rui Zhang, Lihui Lu, Yangyang Chang, Meng Liu *
School of Environmental Science and Technology, Key Laboratory of Industrial Ecology and Environmental Engineering (Ministry of Education), Dalian University of
Technology, Dalian 116024, China
H I G H L I G H T S
G R A P H I C A L A B S T R A C T
• The classifications and functions of
MOFs in gas monitoring are provided.
• This review emphasizes the techniques
of MOFs for monitoring gas interactions.
• Roles of MOFs in gas sensors are classi­
fied into three items.
A R T I C L E I N F O
A B S T R A C T
Editor: Zaher Hashisho
Effective detection of pollutant gases is vital for protection of natural environment and human health. There is an
increasing demand for sensing devices that are equipped with high sensitivity, fast response/recovery speed, and
remarkable selectivity. Particularly, attention is given to the designability of sensing materials with porous
structures. Among diverse kinds of porous materials, metal-organic frameworks (MOFs) exhibit high porosity,
high degree of crystallinity and exceptional chemical activity. Their strong host-guest interactions with guest
molecules facilitate the application of MOFs in adsorption, catalysis and sensing systems. In particular, the
tailorable framework/composition and potential for post-synthetic modification of MOFs endow them with
widely promising application in gas sensing devices. In this review, we outlined the fundamental aspects and
applications of MOFs for gas sensors, and discussed various techniques of monitoring gases based on MOFs as
functional materials. Insights and perspectives for further challenges faced by MOFs are discussed in the end.
Keywords:
Gas sensors
Metal-organic frameworks (MOFs)
Monitoring techniques
Adsorption
1. Introduction
There is an increasing need for rapid and efficient detection of gases
(such as toxic gases and cancer biomarkers) (Zhou et al., 2020a, 2020b;
Bag and Lee, 2019), due to the strict limits in the fields of food safety,
emission control, indoor air quality monitoring, public security and
medical diagnosis (Li et al., 2019c). Gas sensors are useful tools for
detecting various gases, and they should cater several requirements,
including high sensitivity/selectivity/speed operation, low drift/power
consumption/limit-of-detection (LOD), and long-term stability. In order
to meet the challenges in the design of gas sensors, researchers devoted
to exploring various sensing materials (Qin et al., 2021; Dai et al., 2020),
such as metal oxide semiconductors (MOSs) (Meng and Zhou, 2020),
carbon-based nanomaterials (Schroeder et al., 2019), solid electrolytes
* Corresponding author.
E-mail address: mliu@dlut.edu.cn (M. Liu).
https://doi.org/10.1016/j.jhazmat.2022.128321
Received 24 November 2021; Received in revised form 16 January 2022; Accepted 19 January 2022
Available online 24 January 2022
0304-3894/© 2022 Elsevier B.V. All rights reserved.
R. Zhang et al.
Journal of Hazardous Materials 429 (2022) 128321
S = ΔX/X0 = (X-X0)/X0 or (X0-X)/X0, S≥0;
(Miura et al., 2014), conductive polymers (Wang et al., 2016), and some
two-dimensional nanostructured materials (Meng et al., 2019). For
organic and carbon-based materials, they usually show insufficient
sensitivity and poor stability. For inorganic materials, especially MOSs,
they often operate at high operating temperatures, leading to baseline
drift and oxidation of analytes. All these issues hinder the developments
of gas sensors (Kaushik et al., 2015).
Derived from their extraordinarily diverse functional sites, tunable
pores and high porosities, metal-organic frameworks (MOFs) exhibit
unique properties in comparison with traditional porous materials, such
as carbon materials and zeolites. The distinct nature of extremely high
porosities and finely tuned pores of MOFs contribute to their wide ap­
plications in the storage and capture of various gases. When MOFs were
used as gas sensitive elements, their physical and/or chemical properties
may change and could be detected once upon adsorption and desorption
of gas molecules (Li et al., 2020d; Chen et al., 2020d; Lin et al., 2018,
2019; Li et al., 2019a, 2019d; Wang and Li, 2019; Xie et al., 2020; Fang
et al., 2018; Wang, 2020c). Herein, we focus on the fundamental func­
tions of MOFs, highlight different types of MOF-based gas sensors, and
further clarify the roles of MOFs in these gas sensors (Fig. 1).
1.1.2. Speed
For a sensor, the response time and recovery time are used to mea­
sure how fast the device responds to the target gas and recovers to the
initial state. Response time is defined as the time taken of 90% variation
of the full response from the baseline. Similarly, recovery time is defined
as the time taken of 90% variation of the full response from the response
maximum. Generally speaking, response/recovery time are expected as
short as possible for an ideal sensor. Apart from morphologies and
composition of sensing materials, the response/recovery time also de­
pends on measurement conditions, including dimensions of measuring
chamber, gas flow and readout electronics.
1.1.3. Selectivity
The selectivity of a sensor is regarded as the primary respond to one
gas species (donated as A) in the presence of interferants (donated as B).
Thus, a good gas sensor should process a high selectivity (usually SA/SB
≥ 3) (Kim et al., 2016).
1.1.4. Stability
Stability is used to measure the resistance ability of the device to
other influencing factors (e.g. temperature and humidity) besides target
gas sensitivity. A good sensor is expected to produce the same output
when the experimental conditions remain the same for an extended
period of time.
1.1. Fundamental characteristics of gas sensor
For better understanding, some key parameters of gas sensors are
discussed as follows:
1.1.1. Response/Signal
The sensor response/signal is given as the relation between the
physical quantity in response (X, X can represent resistance, impedance,
current, frequency, light intensity and so on) and the blank response X0
in the absence of gas stimulus. This parameter reflects the ability of a
sensor to detect target gas molecules and abbreviated by "S". There are
three common forms.
S = X/X0 or X0/X, S≥1;
(1)
S = ΔX = X-X0 or X0-X, S≥0;
(2)
(3)
1.1.5. Repeatability
Repeatability is the ability of a gas sensor to give the maximum
difference between two outputs under identical input conditions. A us­
able sensor should give the same sensing response under the same
operating conditions.
1.1.6. Limit of detection (LOD)
The LOD (= low detection limit LDL) is the minimum gas concen­
tration that the device could recognize. Generally, the ration of the
Fig. 1. Graphic illustration of the advantages of MOFs for developing gas sensing functional applications.
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Journal of Hazardous Materials 429 (2022) 128321
signal to the background noise should be above 3.
1.3. Metal-organic frameworks (MOFs)
1.2. Gas sensing materials
MOFs are a class of crystalline and coordinate materials that are
assembled with inorganic metal nodes (ions or clusters) and organic li­
gands through interactions like van der Waals forces, H-bonding, and pp stacking.
First, the extended infinite networks of MOFs endow them with low
internal densities and high surface areas. A distinctive advantage of
MOFs is that the frameworks could be designed by a modular selfassembly process, that incorporates various metal ions/clusters and
organic linkers with different functions. Additionally, the MOF library
could be more diverse due to the opportunity to perform post-synthetic
modification (PSM). Second, a distinct feature of the pristine MOFs is
high structural tunability, which is considerably used as efficient
membrane layers and studied for gas separation/storage. These selective
gas penetration by MOFs is an efficient way to improve the insufficient
selectivity in chemi-resistive sensors. Third, MOF derivatives could
basically remain the porous and unique structure of MOFs. In the
meanwhile, the derived nanomaterials are diverse due to the high
tunability on structures and compositions of MOF, which is conducive to
the creation of new materials and structures for gas sensing. These
characteristic properties make MOFs ideal candidates to be gas sensing
materials.
The most studied and used sensing materials for gas molecules are
metal oxide semiconductors (MOSs), typically such as SnO2, ZnO, TiO2,
In2O3, Fe2O3 (n-type), Co3O4, NiO (p-type) and their complexes (Su and
Hu, 2019; Zhang et al., 2018b, 2020a). They work on the basis of
reversible redox interactions between pre-adsorbed ambient oxygen
species (O2-, O- and O2-) and target gas analytes on the surface of sensing
layers. When MOSs exposed to air, the electron will flow from MOSs to
oxygen molecules, resulting in formation of adsorbed oxygen ions and
electron depletion regions on the surface of MOSs (take n-type MOS for
example, electron is the charge carrier). When reducing gases intro­
duced, electron will flow from gas molecules to the conduction band of
MOS, resulting in decreasing resistance. The transduced and measurable
electrical signal is useful for the detection of the target gas. This kind of
gas sensor often exhibits a highly sensitive and fast response-recovery
process to target analytes. However, the sensing procedure is often
ensured by extra power, including heating and UV-irradiation. Thus, the
main drawbacks of the sensor are high energy consumption, poor
selectivity, and the associated complicated sensor configuration.
Polymer-based chemo-sensor is another significant class of gas
sensor, typically such as conductive polyaniline (PANI), polypyrrole
(PPy), polyacetylene (PA) and polythiophene (PT) (Ma et al., 2018; Ali
et al., 2021; Kumar et al., 2020). The sensing mechanism of such poly­
mers is different and complex, because they can exhibit electrical con­
ductivity across a range of about fifteen orders of magnitude (Fratoddi
et al., 2016). Compared with MOSs, the polymers are easier to be inte­
grated into flexible devices and manufactured with more transduction
modes, including conductometric, potentiometric, amperometric,
colorimetric and gravimetric mode. Importantly, the fabricated sensor
could operate at room temperature and reduce the energy consumption.
However, polymers-based sensor often exhibits low sensitivity/se­
lectivity and sluggish sensing process.
Carbon-based materials (such as carbon nanotube, graphene, gra­
phene oxides, and Ti3C2Tx), often offer a high specific surface area,
contributing to adsorbing plenty of gas molecules on them (Yin et al.,
2021; Zhang et al., 2017; Zhou et al., 2021). Except direct sensing,
carbon-based materials also fabricated into other sensing materials, such
as MOSs, to modulate the electric properties. After assembly and func­
tionalization, the carbon-based materials exhibit more diverse mor­
phologies and properties, which contributes to improve the gas sensing
performance. Additionally, the production of high-quality and
large-area carbon materials is expected to be realized with the devel­
opment of effective preparation methods, such as chemical vapor
deposition (CVD), epitaxial growth, and oxidation-reduction. Common
carbon-based gas sensors include resistive, optical, and
micro-gravimetric sensors (Huang et al., 2021; Wang et al., 2017c). And
part of carbon materials (graphene) are regarded as arguably safety and
non-toxicity, which shows a great potential in wearable devices. The
sensors often operate at room temperature. However, the poor sensiti­
vity/selectivity/stability and sluggish sensing process are the main
drawbacks.
In recent years, some novel materials have emerged for gas sensing,
like ionic liquids, oxygen-free semiconductors (GaN, SiC), twodimensional materials (MoS2, WS2), DNA and some bio-materials
(Zhou et al., 2021; Reddeppaa et al., 2019; Poonam and Deo, 2008;
Kim et al., 2020; Wang et al., 2019d, 2017d). These materials usually
show a large surface-area-to-volume ratio and adsorptive capacity. And
some of them exhibit fascinating properties that differ from traditional
materials, such as biocompatible and biodegradable, which shows a
great flexibility for various application areas, like health diagnosis and
food monitoring (Jin et al., 2021; Wang et al., 2020b). However, the
relatively expensive and complicated synthesis on a commercial scale
have impeded their growth to some extent.
2. Fundamental properties and functions of MOFs
Among various gas sensing materials, MOFs are unique due to their
intriguingly physicochemical and structural properties. Therefore, there
is a close relationship between MOFs’ properties and their practical
applications. In this section, we summarized the basic properties and
functions of MOFs.
2.1. Modulated conductivity
MOFs exhibit the nature of insulation, thus limiting their applica­
tions in electronic devices. To solve this problem, electronically
conductive metal-organic frameworks (EC-MOFs) have emerged in
recent years (Clough et al., 2017; Koo et al., 2019; Dong et al., 2018; Yao
et al., 2020). Besides owing the properties of MOFs, EC-MOFs have some
major advantages, including designable charge transport pathway and
the tunable band gap (Dong et al., 2018a, 2018b; Ko et al., 2018). After
modulating, the EC-MOFs showed huge potential in photocatalysis,
supercapacitors, electrocatalysis, lithium-sulfur battery, field effect
transistors (FETs) and chem-resistive gas sensors (Feng et al., 2018; Xu
et al., 2019a, 2019b; Wu et al., 2020; Jiang et al., 2018; Su et al., 2020;
Mu et al., 2020). First of all, the key to unlocking the full potential of
MOFs is understanding and tailoring their electronic properties. In 2017,
Shustova et al. studied three distinct classes of bimetallic systems
(Mx− yM’y-MOFs, MxM’yMOFs, and Mx(ligand-M’y)-MOFs, M, M’=Cu,
Co, Zn or Zr) and analyzed the fundamental properties responsible for
their electronic behaviors (Dolgopolova et al., 2017).
There are two main pathways to modulate the conductivity of MOFs
to form EC-MOFs. One is designing intrinsically conductive frameworks
(through-bond and through-space approaches). It was demonstrated
that the framework topology and unsaturated metal sites had a potential
effect on the density of electronic states near the Fermi level. In 2020,
Martĺ-Gastaldo et al. concluded that the through-bond and throughspace strategies were two efficient ways to produce EC-MOFs (Rubio-­
Giménez et al., 2020). For the through-bond approach, the charge
transport happens through linkers and metal nodes. This requires metal
ions and conjugated organic ligands bond with each other in a certain
degree of covalency. Sun et al. constructed a (-Fe-S-) chains-based
MOF-74 analogue (Fe2(DSBDC), 2,5-disulfhydrylbenzene-1,4-dicarbox­
ylic acid) (Sun et al., 2015). The loosely bound Fe2+ spin electron and
the low electronegativity of S atoms contributed to its increasing
conductivity.
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Journal of Hazardous Materials 429 (2022) 128321
For the through-space approach, the conduction paths are resulted
from π-π stacking interactions between electroactive moieties in MOFs.
Tetrathiafulvalene (TTF) derivatives, as ligands, were the most wide­
spread option to fabricate EC-MOFs (Park et al., 2015; Wang et al.,
2017a; Narayan et al., 2012). Other than TTF, another case was
contributed by Hupp and co-workers (Goswami et al., 2019). They
devoted to turning electrical conductivity in insulating MOFs via elec­
trochemical oxidation of tetraphenyl pyrene linkers and analyzed two
kinds of crystal orientations (parallel and perpendicular to the pore
channels) in the redox hopping charge transport. Results confirmed a
highly anisotropic conduction in NU-1000 (Zr6-cluster-TPPy(COO-)4
linker) (Fig. 2(a-b)).
The other efficient way to modulate the conductivity of MOFs is
introducing guests (including conductive and non-conductive) into
insulating networks (Rubio-Giménez et al., 2020). Carbon-based mate­
rials were often selected as conductive guests to be incorporated into
MOFs (Goswami et al., 2018; Souto et al., 2019). Hupp et al. prepared
electronically conductive zirconium-node-containing MOF by physically
encapsulating C60 within the diamond-shaped cavities of NU-901
(Zr6(μ3-O)4(μ3-OH)4(H2O)4(OH)4-1,3,6,8-(p-benzoate)pyrene
(TBAPy4-)) (Goswami et al., 2018). The bulk electrical conductivity was
increased to 10-3 S⋅cm-1, which was originated from electron
donor-acceptor interaction. The density functional theory (DFT) calcu­
lations and electronic absorption spectrum supported the experimental
results (Fig. 2(c-d)). Except for conductive ligands, non-conductive
I2-doping strategy (I2@CuTCA (I2@Cu3(C21H12NO6)2), FeII-tetra(4-pyr­
idyl)tetrathiafulvalene (TTF(py)4)@I2) has also been successfully
confirmed to turn MOFs from insulating to semi-electrical conductivity
(Pan et al., 2018; Wang et al., 2017b). Three reasons could support this
phenomenon: the oxidation of network, conduction through polyiodide
ions, or donor-acceptor interactions between ligand π electrons and I2.
Additionally, redox-active and conjugated guest molecules could also
tune electrical conductivity of MOFs. Allendorf et al. infiltrated the
nanopores of HKUST-1 (also known as Cu3(BTC)2; BTC, benzene-1,3,
5-tricarboxylic acid) with TCNQ (7,7,8,8-tetracyanoquinododi­
methane) (Fig. 2(e-f)) (Talin et al., 2014). The electrical conductivity
value of HKUST-1 increased to 7 × 10-2 S⋅cm-1, which was improved
over six orders of magnitude. The modulated conductivity was
Fig. 2. Modulated conductivity in MOFs. (a) Schematic illustration of NU-1000 structure and directional charge transport within NU-1000. (b) Schematic repre­
sentations of micro crystallites oriented with a hexagonal face contacting the electrode. (c) Immobilization of C60 within diamond shaped channels of NU-901. d)
Current (I) vs. voltage (V) plot for pressed pelletsof NU-901 and NU-901-C60. (e) Infiltration with a redox-active, conjugated guest molecule (TCNQ). (f) Possible
configuration unit cell of HKUST-1 to provide a conductive channel.
(a and b) Adapted with permission (Goswami et al., 2019). Copyright 2019, American Chemical Society. (c and d) Adapted with permission (Goswami et al., 2018)
Copyright 2018, The Royal Society of Chemistry. (e and f) Reproduced from ref. Talin et al. (2014) with permission from the American Association for the
Advancement of Science, copyright 2014.
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Journal of Hazardous Materials 429 (2022) 128321
attributed to electronic coupling between the dimeric Cu subunits, that
were induced by the redox-active and conjugated guest TCNQ.
Meanwhile, the kinetic or thermodynamic equilibrium also affects the
adsorption selectivity in a given equilibrium time. In these situations,
the surface properties of the pores and adsorbate properties (e.g. po­
larity, H-bonding, and quadruple moment) have a combined effect in the
selectivity of MOFs. For example, there are plenty of uncoordinated N
active sites on the cage surface of Ni/Co(II)-MOFs (YZ-5,
{[Co2(tmdb)2(4,4’-bpy)(H2O)]⋅solvents}n and YZ-6, {[Ni2(tmdb)2(4,4’bpy)(H2O)]⋅solvents}n), which could act as basic adsorption sites (Fig. 3
(c)) (Zhang et al., 2019d). As a result, they exhibited excellent selective
sorption behaviors towards acidic CO2 over CH4 and N2, which was
confirmed by grand canonical Monte Carlo (GCMC) simulation results.
Actually, no MOF exhibits perfectly adsorptive selectivity to one
specific gas. However, it is able to tune the pore size/shape and surface
properties of MOFs through selective modification of metal (clusters), as
well as the functionalization and ligand design, thus resulting in desired
selectivity (Jiang et al., 2017).
2.2. High selectivity
The adsorption selectivity of MOFs is often affected by the prefer­
ential gas adsorption and/or molecular sieving due to the different in­
teractions between adsorbent and adsorbate (Fig. 3(a)) (Li et al., 2009;
Samsonenko et al., 2007). First of all, sieving effect, that is the shape and
size of pores in a MOF must be considered. For example, manganese
formate (Mn(HCOO)2) has rich 1D channels (Fig. 3(b)) (Dybtsev et al.,
2004). These channels are connected to each other via small windows,
resulting in larger cages. At 78 K, Mn(HCOO)2 selectively adsorbed H2
over Ar and N2. At 195 K, it selectively adsorbed CO2 over CH4. In both
cases, Mn(HCOO)2 tended to adsorb the gas molecules that had the
similar size with the narrow channels. Allendorf et al. found that pore
size and open metal site in MOFs affected the adsorption of noble gases
(Perry et al., 2014). On one hand, the amount of gas uptake and Henry’s
constant (kH) of NOTT-100 (also known as MOF-505, Cu
dimetal-tetracarboxylate square-paddlewheel SBU-nbo topology)
increased with the decreasing pore size, especially polarizable gases of
Kr and Xe. On the other hand, the inter-connected and tortuous diffusion
channels of nbo-series MOFs contributed to the increased interaction
between MOFs and gas molecules.
Besides sieving effect, the nature of the interaction between guest
and surface significantly affects the molecular selectivity of MOFs.
2.3. High storage ability
For porous materials, the gas storage capacity is generally enhanced
with their increasing surface areas. MOFs often show high gas storage
ability for a long period of time due to their intrinsic natures of un­
precedented high surface area and ultrahigh porosity [74]. Several gas
storage issues need to be addressed: (i) Some flammable gases, such as
ethylene (C2H2) and methane (CH4), show a high risk of explosion and
leakage, which are usually sealed in high-pressure cylinders during
Fig. 3. High selectivity in MOFs. (a) Schematic illustration of selective gas adsorption in rigid MOFs (top: the molecular sieving effect, bottom: preferential
adsorption). (b) X-ray crystal structure and BET gas sorption isotherms at 78 K and 195 K of Mn(HCOO)2. (c) 3D porous framework for YZ-6 with 1D hexagonal
channels and the IAST adsorption selectivities of CO2/CH4 and CO2/N2 at 273 and 298 K, respectively.
(a) Adapted with permission (Li et al., 2009). Copyright 2009, The Royal Society of Chemistry. (b) Reproduced with permission from ref (Samsonenko et al., 2007).
(c) Reprinted with permission from (Zhang et al., 2019d). Copyright 2019 American Chemical Society.
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Journal of Hazardous Materials 429 (2022) 128321
transportation and storage, leading to the potential security risk. (ii)
Some noble gases are vital in medical, photoelectric and food processing
fields. However, the usage is limited in the world due to its extreme
shortage and high price. (iii) CO2 is a main culprit of the greenhouse
effect. The efficient storage of CO2 is one of the most important tech­
nologies for addressing global climate change in the short term. Using
MOFs as functional materials provides a new approach for gas storage
and controlled release.
Zhang et al. successfully synthesized two MOFs (α-CD-MOF-Na and
α-CD-MOF-K) for C2H2 adsorption and storage (Fig. 4(a)) (Li et al.,
2020a). Using these MOFs, the C2H2 encapsulation capacities both
reached to about 50% (w/w). Furthermore, C2H2 could be encapsulated
into inclusion complexes (ICs) for as long as nearly one month under a
stable condition at 25 ◦ C. Similar to the free release of C2H2, 5 mg of
α-CD-MOF ICs could ripen bananas within 4 days (Fig. 4(b)). Upon
molecular simulation, two MOFs exhibited spindle-shaped and ‘8’-sha­
ped cavity, which could effectively adsorb and store C2H2. Similarly,
Zhai et al. focus on C2H2 uptake and separation in aid of Ga-MOF
(SNNU-63, Ga3(μ3-O)(PTC)2(CH3COO)(H2O)) (Li et al., 2020e). At
273 K and 1 atm, SNNU-63 showed outstanding gas uptake perfor­
mance to C2H2 with an adsorption data of 179 cm3⋅g-1. The C2H2 storage
capacity was achieved by the synergistic effects of hydrophobic pore
environment and open metal sites, which was provided by deformed
inorganic secondary building unit [Ga3O] SBUs derived SNNU-63
(Fig. 4(c)). Inspired by Cu-BTC, Marek and co-workers designed a series
of BTC-based analogues by state-of-the-art atomistic simulations for
recovering xenon from exhaled anesthetic gas. This study indicated that
Ni-BTC could provide improved adsorption-based separation with a
good selectivity of xenon relative to CO2, which was reflected in a higher
API value (API, adsorbent performance indicator) (Fig. 4(d)) (Zar­
abadi-Poor and Marek, 2018). For CO2, tuning functions of MOFs have
been regarded as a powerful tool for addressing the world’s environ­
mental and energy problems. The related works have been summarized
by some reviews (Trickett et al., 2017; Furukawa et al., 2013; Sumida
et al., 2012).
2.4. High reaction activity
A significant interest has sparked in the use of MOFs as catalysts due
to the combined advantages of heterogeneous and homogeneous catal­
ysis. The feasibility of controlling tunable species, intrinsic open
frameworks, pore structures, adsorption properties, and the fully
exposed active/co-active sites of MOFs enable themselves with high
reaction activity (Xu et al., 2019a, 2019b; Li et al., 2018).
Henschel et al. synthesized Cr-MIL-101 (Cr3X(H2O)2O(bdc)3;
X = OH, F; bdc = benzene-1,4-dicarboxylate) that showed a high cata­
lytic product yield of 98.5% towards benzaldehyde (Henschel et al.,
2008). The unsaturated pseudo-octahedral coordination architectures
facilitate Cr to be potential reactants. Moreover, iridium-based MOF [Ir
(bipy)-Cl3(THF)], Au-functionalized UiO-67 (Zr-4,4-diphthalic acid),
1⋅ETH-BF4 (ETH, bis(ethylene)) also showed great potential in gas cat­
alytic activity (An et al., 2017; Feng et al., 2019; Levchenko et al., 2020;
Peralta et al., 2020).
2.5. Soft protection
Recently, it has been proved that construction of MOF-biological
macromolecules composites is an effective strategy for protecting
them, including nucleic acids and proteins (Poddar et al., 2019). Espe­
cially, enzymes are the efficient catalysts that always show high selec­
tivity. However, the low reusability and poor chemical/thermal stability
of enzymes hinder their commercial implementations. Fortunately,
physical adsorption could occur between MOFs and enzyme molecules
through numerous weak interactions (e.g. hydrogen bonding, van der
Waals forces, and electrostatic interactions) (Drout et al., 2019). Such
interactions have a negligible effect on enzyme’s native tertiary
Fig. 4. High storage ability in MOFs. (a) Schematic illustration of the ethylene storage process of α-CD-MOF. (b) Color changes of bananas during ripening treatment.
(c) Structure of the deformed [M3O(COO)6(CH3COO)] clusters and its adsorption isotherms for CO2, C2H2, C2H4, and CH4 at three temperatures. (d) Different storage
ability towards xenon of a series of BTC-based MOFs.
(a and b) Reproduced from Li et al. (2020a) with permission from the American Chemical Society, copyright 2020. (c) Reproduced from Li et al. (2020e) with
permission from the American Chemical Society, copyright 2020. (d) Reproduced from Zarabadi-Poor and Marek (2018) with permission from the American
Chemical Society, copyright 2018.
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Journal of Hazardous Materials 429 (2022) 128321
structure and improve enzyme stability simultaneously, which ensure
the preservation of catalytic active sites. And the topological and
chemical structure of MOFs are well defined. The channels, pores and
cages of MOFs are uniformly distributed. These structural features of
MOFs are often connected by microporous windows, facilitating the
diffusion of reagents and products. This application will help researches
to explore and analyze the interactions between guests-decorated MOFs
(e.g. noble nanoparticles) and gas molecules.
broadens the application scope of MOFs.
3. Techniques of MOFs for monitoring gas interactions
Gas sensors are sensitive to the gas atmosphere and can provide realtime and on-line warn signal (Li et al., 2019f). The sensing signal could
be monitored by the following ways, (i) mechanical changes, in the aid
of a quartz crystal microbalance (QCM), microcantilever or micro
resonator (Ma et al., 2020); (ii) optical changes, using luminescence
index or refractive spectroscopic instruments (Wang et al., 2018b); (iii)
electric changes, through observation of resistance, capacitance,
impedance properties or work function (Chidambaram and Stylianou,
2018; Small et al., 2019); (iv) visible color changes (Zhang et al., 2018);
(v) computational simulations (Gustafson and Wilmer, 2018). These
techniques are briefly illustrated in Fig. 5.
2.6. Ideal templates/precursors for MOF derivatives
Besides direct applications, MOFs are also the excellent sacrificial
templates to synthesize diverse porous nanomaterials through modu­
lating thermal and/or chemical treatments (Salunkhe et al., 2017). For
example, metal oxides (MOs) could be obtained by directly heating
MOFs in air (Salunkhe et al., 2015). The derived MOs roughly preserve
the original morphologies of the parent MOFs, and process high surface
areas at the same time. Subtly controllable variations of annealing
temperature and gradient could affect the composition, pore size dis­
tribution and surface area of MOs (Xia et al., 2015; Wei et al., 2020a). In
addition, direct heat treatments of bimetallic MOFs could derive MOSs
composites (Chen et al., 2020a).
Porous carbons with ultrahigh specific surface areas, could also be
achieved from MOFs, along with heat treatment in an inert atmosphere
and chemical etching to remove intrinsic metal ions. The resulted carbon
usually processes ultra-high surface areas, pore volumes, and control­
lable porous architectures. More importantly, porous carbons could be
performed directly without further carbonization. Till now, many MOFs
derived carbons have been synthesized (Jia et al., 2017; Yilmaz et al.,
2017; Zhang et al., 2020a, 2020b; Chen et al., 2020). To further enhance
their functional properties, MOFs-derived carbons could be doped with
impurity atom by a calcination and hydrothermal sulfur­
ization/phosphorization/nitridation strategy (Cheng et al., 2020; Ao
et al., 2020; Du et al., 2019; Liu et al., 2019).
3.1. Mechanical and resonant sensing
QCM could measure vibration frequency to detect mass changes on
the order of nanograms when an alternating electrical current is applied
onto the piezoelectric quartz crystal. A thin piezoelectric quartz crystal
is the core component of a QCM transducer. After being electroplated,
the thin slice oscillates when applied an alternating current (AC). The
mass increases upon adsorption of analyzed gas molecules, and the
resonant frequency decreases. Thus, there is a negative correlation be­
tween QCM frequency and mass change of adsorbed analytes. The
working principle of a piezoelectric microcantilever-based transducer is
similar. The cantilever paddle vibrates at its resonance frequency when
an AC potential difference is applied on it. The difference of frequency
variation could also be attributed to the mass change of adsorbed
analytes.
To enhance the adsorption of gas molecules, it is necessary to coat
the substrate with a recognition film. MOFs could discriminately adsorb
or concentrate gas molecules due to the distinct nature of various pore
structures and large internal surface areas. Thus, the total mass variation
in MOFs could sensitively reflect the gas composition theoretically. The
vibrational frequency could be evaluated by the Sauerbrey equation
(Sturluson et al., 2020). However, it is unlikely adequate for gas
detection in practical applications due to cross-sensitivity. When the
device exposed to a gas mixture with complicated components, all
constituents could be absorbed. Utilizing QCM sensor arrays based on
different MOFs to detect the same gas mixture is an effective way to
address cross-sensitivity (Albert et al., 2000). Such a cross-sensitive
sensor is coined as an electronic nose (e-nose) (Persaud and Dodd,
1982), which mimics human olfaction.
MOFs-based QCM gas sensor arrays have several advantages. First, as
typical porous materials, thousands of MOFs exhibit strong adsorption
capacity, which could lead to drawing diverse components for a QCM
sensor array. Second, the gas species are detected at a wide range of via
MOFs-based QCM sensor due to the sensing mechanism of physical
adsorption. Third, the mass of adsorbed gas molecules is an intrinsic
material property once the gas condition (composition, pressure, and
temperature included) is given. It could also be reliably predicted by
molecular modeling and simulation aforehand (Sturluson et al., 2019).
In aid of QCM, the gases with chemical inertness and nonpolar
characteristics can be detected more easily, such as BTEX (benzene,
toluene, ethylbenzene, xylene), especially benzene (C6H6). Xu. and
collaborators chose four kinds of MOFs (MOF-14, Cu(BTB), BTB: 1,3,5benzenetribenzoate; MOF-74, Mg(DOBDC); MOF-177, Zn(BTB), BTB:
1,3,5-benzenetribenzoate and HKUST-1, Cu(BTC)) to detect C6H6 vapor
(Ma et al., 2020). The QCM sensor modified by microporous MOF-14
stood out. Compared with H3BTC of HKUST-1, more benzene rings in
H3BTB of MOF-14 offer stronger interactions (π-π stacking) and larger
pores for benzene gas. Compared with Zn2+ of MOF-177, the Cu2+ of
MOF-14 is the softer Lewis acid, implying better adsorption to benzene.
Among four MOFs, MOF-74 showed the worst sensing performance,
2.7. Improvable stability
For practical applications for gas sensing, the stability of MOFs
should also be concerned. The concern of various MOFs on stability
mainly includes chemical, mechanical and thermal stability (Ding et al.,
2019). The chemical stability of MOFs correlates with their resistance to
the exposed chemicals, e.g. solvents, moisture, acids, bases, and coor­
dinating anions-contained solution. The mechanical and thermal sta­
bility of MOFs refer to the ability of MOFs to remain their initial
structures when exposed to pressure, vacuum and heat environment.
The degradation of MOFs is widely considered as two aspects, the
breaking of metal-ligand bond, and the formation of more stable MOFs
compared with pristine MOFs (Kirchon et al., 2018). Thus, the intrinsic
structures of MOFs (internal factors) strongly influence the stability of
MOFs, such as charge density of metal ions, hydrophobicity of ligands
and connection numbers of metal ions/clusters (Low et al., 2009). Based
on the HSAB principle (Pearson’s hard soft acid base theory),
high-valent metal ions (such as Fe3+, Al3+, Zr4+, Cr3+ etc.) and
low-valent metal ions (including Zn2+, Ni2+, Fe2+, Co2+, and Ag+ etc.)
can be considered as hard acids and soft acids, respectively. They tend to
coordinate with O donor ligands (hard bases, e.g. carboxylic acid
linkers) and N-containing linkers (soft bases, e.g. azole linkers) to form
MOFs with strong coordination bonding, respectively (Lee et al., 2021;
Yuan et al., 2018). However, the MOF crystals comprised low valent
transition metal ions and carboxylates usually exhibit lack of robust
stability. Employing mix metals or both linkers is an efficient route to
reconcile the above contradiction. Additionally, introduction of hydro­
phobic ligand into MOFs could reduce their affinity to moisture or water.
Conversely, the instability of MOF in some chemical reagent could be
used to realize the gas sensing, such as NH3 H2S, SO2 and H2O (Henkelis
et al., 2021; Chen et al., 2020c). From this view, the instability of MOFs
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Journal of Hazardous Materials 429 (2022) 128321
Fig. 5. Summary of the monitoring techniques of MOF-based gas sensor. In general, the sensing detection are reflected by mechanical changes, optical changes,
electric changes, color changes and computational simulations.
Image ‘Mechanical sensing’ from ref. Ma et al. (2020). Copyright 2020, Elsevier. Image ‘Spectroscopic sensing’ from ref. Wang et al. (2018b) Copyright 2018,
American Chemical Society. Image ‘Color change’ from ref. Zhang et al. (2018). Copyright 2018, American Chemical Society. Image ‘Computational simulations’
from ref. Gustafson and Wilmer (2018). Copyright 2018, Elsevier. Image ‘Electronic sensing’ from ref. Chidambaram and Stylianou (2018). Copyright 2018, Royal
Society of Chemistry and ref. Small et al. (2019). Copyright 2019, American Chemical Society.
which could be attributed to the few benzene rings in the ligand and the
hard Lewis acid nature of central ions Mg2+. In this work, it is implied
that the ligand of MOFs and steric hindrance played vital roles in gas
adsorption.
resulting in a phase change (ΔΦ). The ΔΦ of the interference pattern
generated a variation of the light output intensity distribution, leading
to generation of increasing current (Iup) and decreasing current (Idown),
respectively (Fig. 6(a-b)). The sensor response could be quantified and
the normalized signal (S) was evaluated as Eq. (4):
3.2. Spectroscopic sensing
S=
Transmission or reflection are two main modes to detect gas analytes
by Infrared (IR) spectroscopy. Under transmission mode, the adsorption
of an analyte is quantified by periodically collecting transmitted in­
tensity vs. frequency spectrum of the sensing material. In reflection
mode, the substrate is consisted of a higher relative refractive index (RI)
material (e.g. a silicon wafer), and the sensing material deposited on it.
A beam of infrared light interacts with the interface between the sample
and silicon substrate. At each reflection, an evanescent wave may extend
into the sample. The absorbed quantity of energy is revealed through
monitoring the evanescent wave or the transmitted light at each fre­
quency. In these cases, the concentration and nature of analyte influ­
enced on the obtained IR spectrum properties, including shape/intensity
of bands and wavenumber of absorption bands. Actually, spectroscopic
sensing performance was not limited to using IR spectroscopy. However,
the working principles were similar.
Interferometric waveguide devices are one of the most sensitive
sensors that have been widely used in environmental monitoring, food
safety analysis, and medical diagnostics (Chocarro-Ruiz et al., 2017).
The devices can detect extremely small RI changes that occur on the
sensor surface (Estevez et al., 2012). An optical CO2 sensor was reported
via self-assembly of ZIF-8 nanoparticles (Zinc 2-methylimidazolate)
onto transparent bimodal optical waveguides (BiMWs) (Chocarro-Ruiz
et al., 2018). When CO2 introduced, the molecules interact with ZIF-8
sensing film, and the RI in the vicinity of the sensor surface changed,
Iup − Idown
α cos ΔΦ(t)
Iup + Idown
(4)
In order to fabricate MOF-based sensors with a large scale and
integration, Lu and collaborators combined UiO-66 crystals
(Zr6O4(OH)4(BDC)6, BDC = terephthalic acid) with the well-controlled
Fabry-P é rot thin-film sensors (Zhang et al., 2019a). The
missing-linker defects and controllable sizes of UiO-66 enable the sensor
with steady and tunable optical properties (Fig. 6(c-d)). Another
attractive proposal was demonstrated by Faustini and co-workers in
2015 (Dalstein et al., 2016). They introduced a new sensing strategy that
focused on the optical-performance variation of ZIF-8 patterns when the
volatile organic compounds (VOCs) were selectively adsorbed on it.
They used a versatile approach to fabricating ZIF-8/TiO2 photonic het­
erostructures via soft nanoimprinting lithography. The resulting systems
exhibited fascinating properties of iridescence characteristic of 2D
diffraction gratings (DGs). The RI of MOF varied after introducing target
analytes. The adsorption-induced color-luminance change could be
evaluated by a CCD camera and be also integrated into a simple
smart-phones. Consequently, VOCs were determined with the help of
ZIF-8 sensible framework combined with 2D DGs successfully (Fig. 6
(e-g)).
Detection of fluorescence or phosphorescence emission spectrum of
luminescence-based sensor systems are also an efficient way to study gas
sensing process. Ma et al. employed aromatic-tag-functionalized MOFs
to detect aniline vapors (Zhao et al., 2016). The results revealed that the
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Journal of Hazardous Materials 429 (2022) 128321
Fig. 6. Spectroscopic sensing of MOFs for monitoring gas interactions. (a) Photo, schematic and field emission scanning electron microscopy (FE-SEM) image of the
nano ZIF-8-based BiMW sensor. Scale bar: 5 mm. (b) Real-time response signal to the change from pure N2 flow to pure CO2 flow. (c) Schematic illustration of the
fabrication of an MOF-crystal optical sensor for vapor sensing. (d) Reflection spectra of CS468/0.26 recorded on exposure to the control (nitrogen) and the saturated
vapors of methanol, ethanol, acetone, n-hexane, and cyclohexane. (e) Illustration of the experimental set-up for the detection by a simple camera. (f) Illustration of
the phenomena taking place during adsorption. (g) Photographs of the ZIF-8/TiO2 heterostructure at 0% and 100% P/P0 of isopropyl alcohol, taken by a smartphone
at an angle of 28◦ .(h) Luminescence response photographs of MOF-5-NH2 luminescent test paper after exposure to various gas species under a 365 nm UV lamp.
(a and b) Adapted from ref. Chocarro-Ruiz et al. (2018) with permission from the Royal Society of Chemistry, copyright 2018. (c and d) Reproduced from ref. Zhang
et al. (2019a) with permission from the American Chemical Society, copyright 2019. (e, f and g) Reproduced from ref. Dalstein et al. (2016) with permission from
Wiley, copyright 2016. (h) Reproduced from ref. Wang et al. (2018b) with permission from the American Chemical Society, copyright 2018.
sensor showed a high selectivity and rapid response, which was attrib­
uted to the size effect of the guest molecule. Cao and co-workers syn­
thesized an amino-functionalized MOF-5 (Zn4O(BDC)3) and investigated
sensing performance for sulfur dioxide (SO2) systematically (Wang
et al., 2018b). The luminescence turn-on phenomenon could be
observed by naked eyes, as shown in Fig. 6(h). This could be explained
by the charge transfer interaction between SO2 molecules and the amino
of MOF. Moreover, luminescence stability, anti-interference ability, and
reusability test confirmed excellent comprehensive performance of
MOF-5-NH2.
3.3. Electronic sensing
Electronic gas sensing devices perform functions based on variation
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Journal of Hazardous Materials 429 (2022) 128321
in the electronic performance of MOFs, which are induced by the spe­
cific interactions with target gas molecules. The detection signals could
be mainly divided into resistance, capacitance, impedance, and work
function.
homogeneously distributed Metallophthalocyanines (MPc) units could
be synthesized by isoreticular process, the donated excellent conduc­
tivities of which were suitable for chem-resistive sensing at a low-power
level. Second, the chem-resistive devices showed excellent sensitivity of
700% to NO and 100% to H2S, respectively) as shown in Fig. 7(d). Third,
the performance of sensor was largely affected by the composition/­
structure of MOFs. This meant that tunable structure-function could be
achieved by the MOF analogs, which was the prominent advantage for
realizing engineered function using the modular chemistry of MOFs
(Rubio-Giménez et al., 2020; Dolgopolova et al., 2017).
3.3.1. Resistance
The impact of gas analytes on the resistance variation of the sensing
layer is relatively complex. The working principle of chem-resistive gas
sensors is based on the electronic or ionic resistive change of the sensing
layer when exposed to or interaction with the target gas analytes. The
MOSs-based resistive gas sensor was developed as early as 1962. As a
most common type of gas sensor, it exhibited extraordinary natures,
such as simple/robust function and low-cost for manufacturing. Due to
the dearth of high conductive MOFs, earlier MOFs-based resistive gas
sensors displayed some irreparable weakness, i.e., relatively sluggish or/
and energy-intensive response-recovery process (Chen et al., 2014a,
2014b). Recently, more and more MOFs with modification have
exhibited the nature of enhanced conductivity, thus promoting the uti­
lization of MOFs as sensing materials.
As introduced in Section 2.1, Cu3(HHTP)(THQ) exhibited the semiconductive behavior (Fig. 7(a)) (Yao et al., 2020). The Cu3(HHTP)
(THQ)-based sensor exhibited good response-recovery performance to
NH3, which could be attributed to the strong gas-framework interaction
between NH3 and Cu+/Cu2+. The good linear plots of response vs.
concentration were consistent with typical chem-resistive behavior
(Fig. 7(b)). Another example of chem-resistive gas sensor was about
isoreticular nickel phthalocyanine-(NiPc) and nickel naphthalocyanine
(NiNPc)-based 2D conductive MOFs (Meng et al., 2019). In this study,
three characteristics of MOF multifunctional application were high­
lighted for gas detection (Fig. 7(c)). First, low-dimensional materials of
3.3.2. Capacitance
The capacitance is the storage quantity of electrical charge under a
given potential and a capacitor is the device that stores charge. A chemcapacitive sensor can be fabricated through incorporation of a dielectric
material (Li et al., 2019f). When gas analytes adsorb on the MOFs, the
relative permittivity changes with the species and quantities of gas
molecules adsorbed on MOFs, resulting in transduced signals. Typically,
interdigitated electrode configuration (IDE) and parallel plate configu­
ration are most widely used. In particular, IDEs offer an outlook for the
low-power sensing platforms, such as lab-on-open chip applications. The
signals of MOFs-based chem-capacitive sensors are influenced by many
factors: (i) The polarity of target molecules, that has a great impact on
the permittivity of the MOFs. (ii) The adsorbed amount of gas/vapor
molecules on the sensing layer. (iii) Some other natures of target ana­
lytes for the purpose of size exclusion-based selectivity, such as molar
mass, chain length and kinetic diameter. (iv) The external environments:
temperature and relative humidity (RH) of the experimental condition
and frequency of measuring circuit.
Zhao et al. synthesized a Mg-MOF-74 film with open metal sites by
Fig. 7. Resistive sensing of MOFs for monitoring gas interactions. (a) Space-filling model of the crystal structure of Cu3(HHTP)(THQ) and (b) room-temperature gassensing performance of Cu3(HHTP)(THQ) nanowires-based sensor. (c) Synthetic scheme for isoreticular phthalocyanine and naphthalocyanine-based MOFs NiPc-M
and NiNPc-M. (d) PCA for arrays of NiPc-Ni (circle), NiPc-Cu (square), NiNPc-Ni (rhombus) and NiNPc-Cu (triangle) sensors, showing capability for differentiating
NH3, NO, and H2S.(For interpretation of the references to. Copyright 2019 American Chemical Society.
(a and b) Reproduced with permission from ref. Yao et al. (2020). Copyright 2019 John Wiley and Sons. (c and d) Reproduced with Reproduced with permissionfrom
ref. Meng et al. (2019). Copyright 2019 American Chemical Society.
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Journal of Hazardous Materials 429 (2022) 128321
in-situ growth on IDE (Yuan et al., 2019). Its selectivity to C6H6 and
carbon dioxide (CO2) vapors could be further enhanced through
adjusting aperture size and functionalization of channels with ethyl­
enediamine (Fig. 8(a-d)). It was also reported that MFM-300-based
capacitive sensor was studied to detect sulfur dioxide (SO2) (Cherni­
kova et al., 2018). MFM-300 (In) MOF, a 3-periodic open framework,
comprises infinite cis InO4(OH)2 octahedral chains that are bridged by
tetradentate
ligands
(biphenyl-3,30,5,50-tetracarboxylic
acid).
Structural analysis of MFM-300 revealed that the free -OH groups along
the metal chains along with four neighbouring C-H groups from benzene
rings supply adsorption sites for SO2, resulting in selectively sensing to
SO2 with a LOD of 75 ppb (part per billion) (Fig. 8(e)). Fum-fcu-­
MOFs-based (fumarate-based MOFs with fcu topology) sensor was
created for H2S detection (Yassine et al., 2016). This as-synthesized
sensor showed a highly selective detection to H2S and a LOD of 5 ppb.
Additionally, the fum-fcu-MOF also showed distinctive stability exposed
Fig. 8. Capacitive sensing of MOFs for monitoring gas interactions. (a) Digital photographs of the sensor after MOF film growth. (b) Magnified optical image of the
IDEs in the center of the chip. (c) SEM images of the as-grown Mg-MOF-74 film on IDEs. (d) The related sensing performance of a Mg-MOF-74-based capacitive gas
sensor. (e) Schematic representation of the optimized solvothermal preparation approach of MFM-300 (In) MOF thin film on the IDEs. (f) Schematic representation of
the optimized solvothermal preparation approach of naphthalene-based fcu-MOF (NDC-Y-fcu-MOF) thin film on IDE substrate. (g) Top view SEM image of the NDCY-fcu-MOF thin film grown on the IDE substrate. (h) Detection of NH3 with different concentrations: from (1–100 ppm). Insets: Linear response for the NDC-Y-fcuMOF.
(a, b, c and d) Reprinted with permission from ref. Yuan et al. (2019) Copyright 2019 John Wiley and Sons. (e) Reproduced from ref. Chernikova et al. (2018).
Copyright 2018 The Royal Society of Chemistry. (f-h) Reproduced from ref. Assen et al. (2017) with permission from the American Chemical Society, copyright 2017.
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R. Zhang et al.
Journal of Hazardous Materials 429 (2022) 128321
to H2S due to the special structure that hexanuclear clusters are bridged
by rigid and short linkers, prohibiting the formation of metal sulfide.
For detection of another reducing gas, ammonia (NH3), Eddaoudi
et al. employed bulk and short bridging organic ligands to construct
isoreticular NDC-Y-fcu-MOFs (naphthalene based rare earth-fcu-MOF)
(Assen et al., 2017). The photograph of IDE and the related sensing curve
were shown in Fig. 8(f-h). The strong interaction between MOF and NH3
was attributed to two reasons, one is the pore-aperture of MOF hinder
the permission of interference gases with larger sizes (C7H8 and C3H8);
the other one is the lone pairs of NH3 are favorable to interact with the
unsaturated metal sites exposed on the MOF pore system (-OH).
materials. Impedance spectroscopy (IS) is a powerful strategy for
studying the charge motion in a complex material system. The influence
factors on sensing properties were similar with (ii), (iii) and (iv) of
capacitive sensor (Chidambaram and Stylianou, 2018).
NH3 is a critical nitrogen source and it plays vital roles in the global
biogeochemical nitrogen cycle, environmental monitoring and disease
diagnosis (Yao et al., 2017; Wang et al., 2018a). Li and co-workers
fabricated a kind of water-stable proton-conductive MOF, donated as
Ba(o-CbPhH2IDC)(H2O)4]n (Guo et al., 2018). The sensing results
revealed that the amplitude of the proton conductivity was strongly
affected by NH3 concentration. The sensor showed a good selectivity
towards NH3 even at a high RH (>85%) environment (Fig. 9(a)), which
could be used to diagnose kidney disease from exhaled air. Li’s group
successfully synthesized {Na[Cd(MIDC)]}n with three-dimensional ionic
conductivity for NH3 and amine detection (Liu et al., 2019c). They
investigated the relationship between proton conductivity and the hu­
midity of testing environment. They concluded that the un-coordination
carboxylate sites may facilitate proton transfer and NH3/amine recog­
nition (Fig. 9(b)).
3.3.3. Impedance
Detection of electrical impedance of the sensing materials is another
method to perceive the existence of gas analytes (Mohammadi et al.,
2020). ‘Impedance’ is regarded as the ratio of complex voltage to
complex current in a specific circuit. The electrical impedance changes
as a function of the frequency of an applied sinusoidal voltage, which
can effectively avoid the requirement of high conductivity of sensitive
Fig. 9. Impedance and work function-based sensing of MOFs for monitoring gas interactions. (a) 3D solid-state packing of MOF supported by H-bonds and columnar
chart about responses for the MOF toward dissimilar gases. Inset was gas response of the sensor toward different concentration of NH3 at different RHs and 30 ◦ C. (b)
3D framework of MOF 1 showing the 1D channels and the related sensing performance to NH3. (c) Photograph of IDEs uncoated (top), coated with ZIF-8 (middle),
and coated with ZIF-8 and exposed to I2 at 70 ◦ C, as well as impedance response and equivalent circuit fits of IDEs uncoated, coated with ZIF-8, and coated with ZIF-8
and exposed to I2 at 70 ◦ C. (d) Chemical-sensitive field-effect transistor (CS-FET) and its operation.
(a) Adapted with permission Guo et al. (2018). American Chemical Society. (b) Adapted with permission Liu et al. (2019c) Copyright 2019, American Chemical
Society. (c) Reproduced from ref. Small and Nenoff (2017) with permission from the American Chemical Society, copyright 2017. (d) Reprinted with permission from
ref. Gardner et al. (2019). Copyright 2019 John Wiley and Sons.
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Journal of Hazardous Materials 429 (2022) 128321
Iodine (I2) detection is vital for nuclear waste clean-up (Kai et al.,
2015). In 2017, Nenoff and co-workers used ZIF-8 to detect the
adsorption of I2 with the aid of IS (Fig. 9(c)) (Small and Nenoff, 2017).
Two years later, they further fabricated several prototype sensors
through drop-casting MFM-300(X) (X = Al, Fe, In, Sc; biphenyl-3,3’,5,
5’-tetracarboxylate linker) materials onto IDEs (Small et al., 2019), and
investigated the influence of different metal centers on electrical
response to I2. The variation of electrical response is affected by the
diverse MOFs’ structures and the degree of reversibility of I2 adsorption.
To develop large signal-generating and highly reversible MOF-based
materials for I2 sensing, the intrinsic (adsorption capacity and re­
sistivity) and extrinsic (particle morphology and surface area) properties
were both needed to be tuned.
electrode adsorbed and concentrated the gas/vapor molecules, resulting
in amplifying the response signal. The majority of the insightful and
systematic work have been performed by Davydovskaya and co-workers
from Germany. These works have been summarized in a previous review
detailly (Chidambaram and Stylianou, 2018).
Additionally, the work function of sensing materials could be indi­
rectly measured by a bulk silicon-based chemical sensitive field effect
transistor (CS-FET). When CS-FETs exposed to gas/vapors, electrical
signals varied because of work function modulations (Fig. 9(d)) (Gard­
ner et al., 2019). Javey et al. gave several examples to study the sensing
mechanism, including HKUST-1 to H2O, ZIF-8 to H2O/NO2 and
MFM-300(In) to NO2. The sensing results revealed that the mode had the
potential to be calibrated quantitative sensors. No matter Kelvin probe
or CS-FET, the aim is to visualize how the surface electronic structure
responds to the reactive environments (Fahad et al., 2017).
3.3.4. Work function
Kelvin probe is the technique to monitor work function changes. It is
conducive to screen various sensing layers on a lab scale. The changes in
the work function are reflected as signal variation in the response of
contact potential difference (CPD, Δφ) in the Kelvin probe transducer.
And the CPD response was affected by Fermi level and surface chemical
potential of the electrodes simultaneously. The surface modified
3.4. Colorimetric sensing
Naked-eye colorimetric detection is desirable and efficient for the
sensing process. In working mode, a color change could be observed
through transducing signals due to the shift of optical absorption bands
Fig. 10. Observation of visible color change and computational simulations of MOFs for monitoring gas interactions. (a) Representation of 2D sheets and 3D
framework of TMU-34. (b) Sensing cycle for TMU-34. (c) Dynamic conversion of H2DPT into DPT and transformation of a dihydrotetrazine to a tetrazine moiety
inside the TMU-34 framework after exposure to chloroform. (d) Devices made from arrays of multiple surface acoustic waves (SAW) sensors on which five MOFs are
layered. (e) Flow diagram of analysis described in the methodology section. (f) Unit cells of all MOFs used in this study.
(a, b and c) Reproduced with permission from ref. Razavi et al. (2017). Copyright 2017 John Wiley and Sons. (d) Reprinted with permission from ref. Gustafson and
Wilmer (2017). Copyright 2017 American Chemical Society. (f) Reproduced from ref. Chidambaram and Stylianou (2018) with permission from the Elsevier,
copyright 2018.
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Journal of Hazardous Materials 429 (2022) 128321
(Sheng et al., 2019). EC-MOFs could interact with specific analytes with
a good selectivity, resulting in change of electronic structures and
functionalities. A MOF-based colorimetric sensor has the characteristics
of fast, facile, selective detection with high reusability, stability, and
regenerability.
The structures and properties of stimuli-responsive EC-MOFs could
change with an external signal, including chemical agent, temperature,
and electric field (Gui et al., 2015). TMU-34 ([Zn(OBA)(H2DPT)0.5]⋅
DMF) is a kind of chemo-switchable MOFs that is functionalized by
dihydrotetrazine (Razavi et al., 2017). When the device exposed to
chloroform, the dihydrotetrazine groups conversed into tetrazine
groups, accompanied with TMU-34 converting into O-TMU-34 (oxida­
tion state). The color of TMU-34 changed from yellow to pink. Study of
the recovery process revealed that DMF was a good regenerator for
O-TMU-34 reduction within 60 s (Fig. 10(a-c)). Xiang et al. reported a
novel 3D FJU-56 (Co(II/III)-[tris-(4-tetrazolyl-phenyl)-amine, H3L]) for
NH3 sensing with naked-eye color response (Zhang et al., 2018). The
samples changed from red to brown when the device exposed to NH3,
which was caused by the change of coordination situation of Co ions.
could also be utilized as templates or precursors to design novel struc­
tures of final sensing materials, especially MOSs (composites). In this
case, the gas sensing mechanism varies and depends on the types of final
sensing products.
4.1. MOFs as sensitive materials directly
Many single MOF-based sensors for detecting gases are reviewed
above. This section would mainly focus on the MOF composites or their
rare applications (e.g. on textiles) in tracing gases.
4.1.1. MOF-organics
Inspired by the host-guest concept, Strauss et al. evaluated organic
semi-conductive tetrathiafulvalene (TTF)-infiltrated Co-MOF-74 (CoDHBDC) composite in resistive gas sensing (Strauss et al., 2019). In
comparison to Co-MOF-74, Co-MOF-74-TTF exhibited a decreased
resistance. The sensor showed a selectivity to CO2 among CO2, CH4, and
N2, which was attributed to the strong interaction between Co-centers
and CO2 (Fig. 11(a)). Xu and co-workers employed HITP doped
Cu-HHTP-10 C nanofilm (2,3,6,7,10,11-hexahydrotriphenylene (HHTP,
-OH) and 2,3,6,7,10,11-hexaiminotriphenylene (HITP, -NH2)) as gas
sensitive material (Wu et al., 2021). They found that the sensing prop­
erties (including sensitivity and selectivity) to NH3 and C6H6 could be
well controlled by modulating HITP loading contents. The selectivity
was improved over 220% for C6H6 vs. NH3 because of the introduction
of rich defects of HITP doping (Fig. 11(b)).
Polymer is another common type assembled with MOFs as sensing
materials (Sabetghadam et al., 2016; Seidi et al., 2020; Shin et al., 2020;
Pei et al., 2020). Salama and colleagues equipped a novel receptor layer
on an organic field-effect transistors (OFETs) (Yuvaraja et al., 2020). The
receptor was encompassed by a porous 3D MOF-A ([Ni(TPyP)-(TiF6)]n)
film. The film acted as a NO2 specific preconcentrator, and it
hetero-contacted an ultrathin and stable PDVT-10 layer (DPP copolymer
with thiophene donor blocks) on an OFET platform (Fig. 11(c)). The
sensitivity of the device towards NO2 was increased by 700%, in the
meanwhile, there was a negligible effect of humidity on the sensing
properties. This could be attributed to the synergistic combination of
PDVT-10 and MOF-A. Moreover, the device exhibited a shelf life of
around half a year accompanied by insignificant changes in the baseline.
Polymer decorated MOFs could combine the characteristics of both
components to obtain superior sensing properties. For instance, a com­
posite film comprised with Matrimid 5218 and NH2-MIL-53(Al) (ami­
no-terephthalic acid linker) was reported by Sachdeva et al. (2017). In
aid of plana capacitive transducer devices, authors detailly studied the
effect of mixing ratios on their sensing properties towards ethanol/water
vapors (Fig. 11(d)). With the increasing concentration of MOF, the
sensor response increased and response time decreased, respectively.
Meanwhile, higher MOF loadings (>50 wt%) leaded in brittle coatings.
The performance of all composite-based sensors was found to be
in-between those of 100% Matrimid and 100% MOF-coated devices. In
order to miniaturize the device while reducing the kinds of sensing
materials, Gascón and co-workers deposited porous MIL-96(Al) nano­
particles onto interdigitated electrode (IDE) chips (Andrés et al., 2020b).
The MOF films showed good selectivity and rapid response/recovery
speed to water and methanol molecules. Furthermore, in aid of chemical
vapor deposition (CVD), a porous polymeric film of Parylene C was
deposited onto the MOF film to improve selectivity of the sensor to water
(Fig. 11(e)).
3.5. Computational simulations
The diverse compositions and structures of MOFs enable them to be
high-performance functional materials in gas sensors. A gas-sensing
array, as an electronic nose, is the core component of imitation biolog­
ical nose. In recent years, more and more electronic noses based on
MOFs exhibited excellent sensing performance (Fig. 10(d)) (Gustafson
and Wilmer, 2019, 2017). MOFs are crystalline materials, lending
themselves to computational modeling accurately and conveniently.
Simulation prediction in advance effectively avoids the potential in­
efficiency of selecting sensing units for an integrated through experi­
mental trial-and-error. From this perspective, theory could help select
sensor arrays with the best performance intelligently.
A recent report was focused on computationally designing gas
sensing arrays based on MOFs for detecting SO2 and CO2 (Sturluson
et al., 2020). In order to obtain the best signal for each gas/MOF from
designing arrays with maximal complementarity, authors calculated the
Henry’s coefficients and predicted the condition of gas adsorption under
dilute conditions. In Gustafson’s work (Gustafson and Wilmer, 2018),
nine different MOFs were selected to compose multiple arrays of sensors.
Their sensing performance to methane were evaluated via molecular
simulations. The results showed that the arrays were able to precisely
quantify methane concentrations superior to nitrogen and oxygen
(Fig. 10(e-f)).
Strictly speaking, such computational simulations should be classi­
fied as prediction technology rather than detection technique. However,
with the aid of computational simulations, selecting the right combi­
nations of MOFs intelligently enables predicting the concentrations of all
components in the mixture accurately (Mancuso et al., 2020; Day and
Wilmer, 2020).
Combining with newly emerging synthetic, predicted and moni­
toring technologies will push the development of increasing functional
building blocks for multifarious applications.
4. Roles of MOFs in gas sensors
Up to now, many researchers have paid attention to the MOFs films
as gas sensing materials directly or the barrier/preconcentration layer
outside the sensing elements. For the former approach, MOFs are usually
directly integrated with electrodes, which allows variations in signals to
reflect the gas type and/or concentration. For the latter one, the effect of
MOFs film largely depends on the conventional working principle of
MOSs or noble metals-based gas sensors. In this situation, the optional
aperture size and highly porous structure of MOFs facilitate pre­
concentrating or sieving gas molecules, resulting in gas detection with
high sensitivity and selectivity (Yuan et al., 2019). In addition, MOFs
4.1.2. MOF-MOF
Recently, some researchers have focused on MOFs-based hetero­
structures. They have the potential to exhibit unexpected functions that
could not be observed by the single component. In 2019, Yao et al.
overcame the lattice-matching limits and successfully synthesized
highly oriented MOF-on-MOF thin film (Fig. 12(a)) (Yao et al., 2019).
The Cu-TCPP-on-Cu-HHTP-based sensor exhibited a good selectivity to
14
R. Zhang et al.
Journal of Hazardous Materials 429 (2022) 128321
Fig. 11. MOF composites as sensitive materials. (a) Measurement home-build electrodes and I− V-curves of Co-MOF-74-TTF-based sensor. (b) Schematic illustration
and response-recovery curves toward benzene with different concentrations of HITP ligand doped Cu-HHTP-10 C thin film gas sensors. (c) Structural accessibility of
MOF-A and schematic illustration of gas molecules’ interaction process in a PDVT-10/MOF-A OFET transistor device. (d) Schematic illustration and comparison of
the response of these sensor devices toward 1000 ppm (0.1%) of methanol. (e) Illustration of the structure of the used IDEs showing the MOF LB film characterization
by SEM and the related selectivity/moisture study diagram.
(a) Adapted with permission Strauss et al. (2019) Copyright 2019, The American Chemical Society. (b) Reprinted with permission from ref. Wu et al. (2021).
Copyright 2020 Springer. (c) Reprinted with permission from ref. Li et al. (2019a). Copyright 2020 American Chemical Society. (d) Reproduced with permission from
ref. Sachdeva et al. (2017). Copyright 2017, American Chemical Society. (e) Reproduced with permission from ref. Andrés et al. (2020b). Copyright 2020, American
Chemical Society.
15
R. Zhang et al.
Journal of Hazardous Materials 429 (2022) 128321
Fig. 12. MOF composites as sensitive materials. (a) Illustration of the preparation of MOF-on-MOF thin films and application of the films as highly selective benzenesensing materials. (b) Macroscopic through molecular level, from a photograph of cotton SOFT sensor postreaction. (c) Custom Teflon enclosure used to determine
membrane breakthrough for SOFT-devices. (d) Representative breakthrough sensing traces for SOFT-devices. The first device exposed to analyte is represented by a
solid line, the second device by a dashed line.
(a) Reprinted with permission from ref. Yao et al. (2019). Copyright 2019 John Wiley and Sons. (b, c and d) Reprinted with permission from ref. Smith and Mirica
(2017). Copyright 2017 American Chemical Society.
C6H6 with a sensitivity of 250% at room temperature. Moreover, the
LOD for C6H6 was calculated as low as 0.12 ppm (part per million). This
work not only introduces a new strategy to fabricate MOF composites,
but also highlighted the synergistic effect of heterostructure MOFs on
advanced device applications.
H2S and NO were as low as sub-ppm level at room temperature (Fig. 12
(b-d)).
In summary, directly using MOFs as sensing elements displays a
higher response with considerable sensitivity, selectivity and repro­
ducibility at the room working temperature. However, the selectivity of
pure MOFs-based chemi-resistors should be further studied and
extended to more analytes.
4.1.3. MOF-inorganics
Among various hazardous gases, hydrogen sulfide (H2S) is known as
a highly flammable, toxic, and chemical asphyxiation gas. In order to
develop a highly sensitive H2S sensor that could work at room temper­
ature, Suryawe et al. synthesized Ag2O nanoparticles-decorated UiO-66
sensing material (Zr-BDC) (Surya et al., 2019). On one hand, the opti­
mized composite exhibited experimental LOD of 1 ppm at room tem­
perature in aid of MOF introduction and capacitive transduction. One
the other hand, transformation of Ag2O to Ag2S contributed to selective
detection
of
H2S.
Apart
from
above,
the
wearable
electronics-self-organized frameworks on textiles (SOFT) were also re­
ported for H2S detection. Mirica and collaborators integrated 2D
EC-MOFs into fabrics for fabricating multifunctional e-textiles (Smith
and Mirica, 2017). The device could differentiate H2S, NO, and H2O at
ppm levels and showed ignorable humidity influence on their
chem-resistive function (5000 ppm, 18% RH). Moreover, the LODs for
4.2. MOFs as barrier/filter layers
Currently, the reported integrated coatings of sensing devices mainly
include metal nanocrystals, carbon materials, inorganic compounds,
polymers, biomaterials, and MOF crystals. These materials could be used
to realize multifunctional and practical applications, such as drug de­
livery, batteries, photocatalysis, electrocatalysis, hydrogenation, gas
adsorption/storage/separation and sensors (Chen and Xu, 2019; Zhang
et al., 2019b; Yoo et al., 2020; Woo et al., 2020; Wang et al., 2020a; Chen
et al., 2019; Meng et al., 2020).
In order to enhance the selectivity and sensitivity of a sensor to a
specific target gas, a MOF-based barrier/filter layer can be integrated on
the sensing region. On one hand, such barrier layer can prevent unex­
pected gas molecules reaching the sensing materials. On the other hand,
16
R. Zhang et al.
Journal of Hazardous Materials 429 (2022) 128321
the MOF filter layer can be used for pre-concentration when the target
gas concentration is low (Rieger et al., 2018). The accumulated gas
molecules are released followed by the adsorbent is cleaned after a given
time, resulting in the signal enhancement. However, this process of
sensor response is always sluggish because of the accumulation period,
accompanying with long response/recovery time.
ZnO is one of the first used materials for gas sensing due to its sen­
sitive nature and low price. However, it has the common fault of metal
oxides, that is insufficient selectivity. In order to enhance the selectivity
and sensitivity of ZnO, Xu et al. groundbreakingly proposed to
combining high selectivity and catalytic activity of MOF with ZnO (Yao
et al., 2016). In this work, ZnO nanorods were used as sacrificial tem­
plate and supplied Zn2+ for constructing the MOF shell, leading to the
formation of ZnO@ZIF-CoZn. Compared with the ZnO-based one, the
composite-based sensor showed significantly higher sensitivity, lower
LOD, and selective sensing to acetone (Fig. 13(a)). Additionally, Zeng
et al. used ZIF-71 as filter (Zn-hexamethylenetetramine (HMTA)) to coat
ZnO nanorods (Fig. 13(b)) (Zhou et al., 2019). Apart from enhanced
response and shorter response-recovery time to ethanol and acetone, the
ZnO@ZIF-71-based sensor also showed humidity neglectable effect
because of the hydrophobic nature of ZIF-71. Later, Ma and collabora­
tors reported that ZnO@ZIF-8 core-shell nanorods-based sensor showed
obviously selective sensing to formaldehyde (HCHO) due to the limited
channels of ZIF-8 shell (Tian et al., 2016). Moreover, the ZIF-8 shell was
also confirmed to show an enrichment and selective effect to hydrogen
(H2) in Kim’s and Penner’s works (Drobek et al., 2016; Weber et al.,
2018; DMello et al., 2018). (Fig. 13(c)).
SnO2 was another gas sensing material that was often studied by
researchers. Kalidindi et al. found that the SnO2 @ZIF-67-based sensor
(Co 2-methylimidazolate) showed a much higher response
(16.5 ± 2.1%) to CO2 compared with that of SnO2-based one. Apart
from filtration and enrichment effect, the electronic structure changes of
SnO2 caused by introduction of ZIF-67 was also influential in this
sensing process (Fig. 14(a-b)) (Koo et al., 2017b). Additionally, in order
to minimize the moisture interference and improve the gas selectivity of
SnO2-based gas sensor, Park et al. used MIL-160/PDMS and Cu
(BTC)/PDMS as filters to adsorb H2O and CO molecules, respectively
(Hwang et al., 2020). As a result, a significant selectivity to H2 against
CO and negligible moisture effect were observed (Fig. 14(c-d)).
The sensing properties of previously reported MOFs coating for gas
sensors are tabulated in Table 3. The proposed MOFs-barriers/filters can
be utilized in various sensing applications that require stability and
selectivity in a complex environment, including medical diagnosis,
environmental monitoring, and hydrogen energy systems.
In the case of MOF barrier/filter layers, facile and simple deposition
techniques is vital for sensing performance. The deposited films should
provide a uniform and homogeneous coverage of diverse matrix, and in
the meanwhile, the minimal active sites are maintained. Furthermore,
the sensing mechanism among surfaces, interfaces, surfaces, reaction
kinetics, and thermodynamics is also required to establish.
4.3.1. MOFs-derived single MOSs
In order to increase the sensitivity of ZnO, Wu and co-workers
designed and synthesized hollow ZnO nanocages that were derived
from MOF-5. The ZnO products present hollow interiors combined with
meso/macro-porous channels, thereby facilitating the diffusion of gas
molecules. Compared with that of ZnO NPs, the sensing performance of
ZnO nanocages-based sensor was significantly improved for detecting
acetone and C6H6. This was ascribed to the unique hierarchical structure
of ZnO, which was equipped with abundant exposed active sites and
surface-adsorbed oxygen (Li et al., 2016). Ji et al. proposed a strategy for
synthesizing α-Fe2O3 and γ-Fe2O3 through controlling calcining condi­
tion of Fe-MOF (FeFe(CN)6) cubes. They found that Fe2O3 crystal phase
affected the sensing properties, especially to n-butanol. For α-Fe2O3, the
concentration changes of surface free carriers mainly affected the
sensitivity of the sensor. For γ-Fe2O3, the resistance change relied on the
transformation between γ-Fe2O3 and Fe3O4 during the gas sensing pro­
cedure (Wang et al., 2019a).
Besides n-type MOSs of ZnO and Fe2O3, p-type Co3O4 was another
typical MOS that was easily prepared using MOF as sacrifice template.
Kuang and co-workers successfully synthesized Co3O4 concave cubic
particles with high porosity using ZIF-67 as template. The Co3O4
exhibited a large specific surface area of 120.9 m2⋅g-1 and high porosity.
The unique structure ensured remarkable capabilities of surfaceadsorbed oxygen, leading to a low LOD (10 ppm), fast responserecovery speed (<10 s), and good selectivity to ethanol (Lu¨ et al.,
2014). Zhang et al., Lee et al. and Ji et al. synthesized a series of Co3O4
structures derived from ZIF-67 and systematically studied their sensing
performances to VOCs, respectively [184–186. It was concluded that
Co3O4 could be well-controlled through changing the thermal condition
of ZIF-67 rhombic dodecahedra precursor. More importantly, the fine
nanostructures of the Co3O4, including shell thickness, particle size and
mesopores, played vital parts in determining the observed sensing
properties. Similarly, Li and collaborators synthesized a kind of Co3O4
with hierarchical nanostructure via calcining Co5-based MOF micro­
crystals. Its extraordinarily efficient HCHO sensing properties (LOD =
10 ppm) could be induced by the hierarchically unique pore structures
and large surface area (Zhou et al., 2017).
MOFs-templating method facilitates the construction of novel and
unique architectures, such as hollow and porous structures with multishells, which can be explained by Oswald or Kirkendall effects. Mean­
while MOFs-derived single-phase MOSs often exhibit large specific
surface area with high porosity. The hierarchical structure reduces the
potential barrier to ensure efficient mass diffusion.
4.3.2. MOFs-derived MOSs composites
To further enhance the sensing properties, more and more re­
searchers focused on the construction of MOFs-derived MOSs compos­
ites. Compared with single component, composite templates are more
diverse by mixing and doping procedures.
MOF-5, ZIF-8 and HPU-15 {[Zn5(L)2(H2O)5]⋅7(DMA)⋅10(H2O)}n
were the desired template to obtain ZnO-based composites. Zhang and
co-workers proposed a strategy for preparation of ZnO/In2O3 samples
using MOF-5/MIL-68(In) as templates (Zhang et al., 2019c). Compared
with In2O3-based one, the sensor based on ZnO/In2O3 composite showed
enhanced ozone sensing performance. The heterointerfaces originated
from In2O3 and ZnO crystal particles played an important role in the
sensing process. Yang et al. prepared ZnO/ZnCo2O4 hollow core-shell
nanocages (HCSNCs) using ZIF-8/Co-Zn hydroxide as template (Qu
et al., 2016). The ZnO/ZnCo2O4 HCSNCs-based sensor exhibited better
performances to xylene than those of ZnCo2O4 shells and ZnO nanoc­
ages. The enhanced properties were ascribed to their unique structure
and the synergistic effect between ZnO and ZnCo2O4. In Zhao’s work,
they first synthesized diamond-shape ZnO derived from HPU-15 (Li
et al., 2020b). The ZnO-based sensor showed selectively sensing signals
to TEA. Then, they synthesized CuO/ZnO composite using Cu
(II)-infiltrated HPU-15. Surprisingly, this composite showed a good
4.3. MOFs as templates
In spite of significant advantages, there are some intrinsic drawbacks
of MOFs, such as low electrical conductivity and poor stability. When
MOFs are constructed into hierarchical morphologies, like hollow and
core-shell micro/nano-spheres, the problems become more serious.
They strongly restrict their wide applications in gas sensing. Trans­
forming MOFs into their derivatives (metal hydroxides, metal oxides,
metal phosphides, metal sulfides, carbon matrixes and their composites)
is a suitable approach to break these imprisonments (Liu et al., 2019d).
The resulting porous materials, especially MOSs, typically retain the
porosity and shape of the parent MOFs, and usually exhibit high surface
area and relatively good conductivity/semi-conductivity (Wang et al.,
2021). According to this, we broadly divide the final products into two
categories: single MOSs and MOSs composites (Fig. 15).
17
R. Zhang et al.
Journal of Hazardous Materials 429 (2022) 128321
Fig. 13. MOF as porous barrier (filter) layers for gas sensor. (a) Schematic preparation process and response-recovery curves in different environments and
temperature-dependent responses of ZnO@ 5 nm ZIF-CoZn to acetone. (b) Schematic illustration of the enhanced gas sensing performance of ZnO@ZIF-71 NRAs gas
sensor. (c) Schematic illustration of the accelerated hydrogen sensing properties of Pd NWs@ZIF-8.
(a) Reproduced with permission from ref. Yao et al. (2016). Copyright 2016 John Wiley and Sons. (b) Reproduced with permission from ref. Zhou et al. (2019).
Copyright 2019 American Chemical Society. (c) Reprinted with permission from ref. DMello et al. (2018). Copyright 2017 American Chemical Society.
18
R. Zhang et al.
Journal of Hazardous Materials 429 (2022) 128321
Fig. 14. MOF as porous barrier (filter) layers for gas sensor. (a) Schematic illustration of SnO2 @ZIF-67 architecture formation used for chem-resistive CO2 sensing.
(b) Compared sensing performance between sensors for 500–5000 ppm CO2. (c) Schematic image of a filtering system based on a microporous elastomer filter coated
with MOFs of metal oxide gas sensor. (d) H2 sensor response and selectivity to the mixture of 20 ppm H2 gas, RH 40% air, and 20/40/60 ppm CO gas with/without
microporous Cu(BTC)/PDMS and MIL-160/PDMS filters.
(a and b) Reprinted with permission from ref. Koo et al. (2017b). Copyright 2018 John Wiley and Sons. (c and d) Reprinted with permission from ref. Hwang et al.
(2020). Copyright 2020 American Chemical Society.
Table 1
Gas sensors employing different materials.
Material
Sensitivity
Speed
Selectivity
Metal oxide semiconductors
Conductive polymers
Carbon-based materials
Metal-organic frameworks
√
×
×
×
√
×
×
×
×
×
×
√
Selectivity
√
×
×
√×
selectivity towards CH3OH due to the adsorption energy changes of the
sensing materials. Also to detect this harmful and toxic gas TEA, Wang
and co-workers prepared Fe2O3/ZnFe2O4 spindles using MIL-88(Fe) and
ZIF-8 as templates by a solvothermal method (Wei et al., 2020b). The
sensor based on this composite could detect TEA even at a low con­
centration of 200 ppb with a distinct response of 2.44.
MIL-68 and CPP-3 were the universal template to obtain In2O3-based
composites. Qu et al. successfully synthesized p-n Co3O4-In2O3 hollow
microcubes derived from CoII-impregnated MIL-68(In) (Shi et al.,
2018). The excellent TEA sensing behaviors were attributed to the
electronic structure variation and the increased active oxygen contents.
Additionally, the bamboo-like CuO/In2O3 heterostructures were syn­
thesized by Zhu’s group, which were derived from Cu2+-impregnated
CPP-3(In) (Li et al., 2020). The CuO/In2O3-based sensor exhibited
excellent sensing properties with a high response of 229.3 (5 ppm), a
LOD of 200 ppb, a low working temperature of 70︒C and good selec­
tivity to H2S.
HKUST-1 and ZIF-67 were often used to construct Cu and Co-based
MOSs. In Kuang’s work, three morphologies of Cu2O/CuO cages were
successfully synthesized through fine controlling the thermal decom­
position condition of Cu-MOFs (HKUST-1) as self-sacrificial template.
Ethanol-sensing tests revealed that the octahedral Cu2O/CuO cages-
Simplicity
Low cost
√
√
√
√
√
×
√
×
Low working temperature
×
√
√
√
based sensor stand out, which could be attributed to the large specific
surface area (150.3 m2⋅g-1) and high capacity of surface-adsorbed oxy­
gen (Wang et al., 2015). ZIF-67 was the most used template to obtain
Co3O4. Wang et al. synthesized novel mesoporous Co3O4/N-doped RGO
nanocomposite using ZIF-67/RGO as template (Lin et al., 2020). The
fabricated sensor owned higher sensitivity (24.5) to ethanol (100 ppm),
which was 4.9 times more than pristine Co3O4-based one. Additionally,
Liu et al. synthesized unique double-shelled Co3O4/NiCo2O4 nanocages
for H2S detection (Tan et al., 2020). The preparation process was in aid
of ZIF-67 as template. The gas sensing performance of previous reported
MOFs-derived MOSs are listed in Table 4.
We noticed that Kim’s group had synthesized a series of MOFsderived MOSs sensing materials. In 2017, they first loaded Pd NPs
onto the cavity of Co-based ZIF-67 (Fig. 16(a)) (Koo et al., 2017b). Then,
PdO NPs functionalized Co3O4 hollow nanocages (HNCs) were obtained
via the calcination process. Results revealed that the hybrid HNCs-based
sensor exhibited a response of 2.51 to acetone (5 ppm) and a good
selectivity to acetone. Furthermore, Co3O4-PdO loaded n-SnO2 HNCs
were synthesized. The galvanic replacement reaction process induced in
p-n transition of Co3O4 HNCs, leading to a high response of 22.8–5 ppm
acetone (Jang et al., 2017). For acetone sensing, they also reported Pd
NPs encapsuled ZnO-ZnCo2O4 hybrid hollow spheres (Koo et al., 2017c).
19
R. Zhang et al.
Journal of Hazardous Materials 429 (2022) 128321
Table 2
A summary of functional sensing materials based on pure MOFs for gas detection.
MOF
Metal
nodes
Ligands
Device
Gas
Temp.
(◦ C)
Res
Tres (s)
LOD (ppm)
Reference
MOF-14
Cu2+
BTB
QCM
Benzene
25
0.15
Ma et al. (2020)
MOF-74
Mg
DOBDC
QCM
Benzene
25
–
–
Ma et al., 2020
MOF-177
Zn2+
BTB
QCM
Benzene
25
–
–
Ma et al. (2020)
HKUST-1
Cu2+
BTC
QCM
Benzene
25
–
–
Ma et al. (2020)
Imidazole
Waveguide
CO2
RT
1200 Hz
(80 ppm)
200 Hz
(80 ppm)
743 Hz
(80 ppm)
480 Hz
(80 ppm)
15 π rad (100%)
10
2+
~1
3130
24.6 (saturated
vapor)
–
~15 (100 ppm)
2
33
Chocarro-Ruiz et al.
(2018)
Clough et al. (2017)
15
99
0.05
0.02
Wang et al. (2018b)
Yao et al. (2020)
138/
78
~200
0.019–0.032
Meng et al. (2019)
–
Yuan et al. (2019)
Chernikova et al.
(2018)
Yassine et al. (2016)
Assen et al. (2017)
Guo et al. (2018)
Kai et al. (2015)
2+
ZIF-8
Zn
UiO-66
Zr4+
BDC
Optical sensor
Ethanol
RT
MOF-5-NH2
Cu3(HHTP)
(THQ)
NiPc-M
Zn2+
Cu2+
BDC-NH2
HHTP, THQ
Test paper
Thick-film sensor
SO2
NH3
RT
RT
NiPc
Thick-film sensor
H2S
RT
MOF-74
Ni2+/
Cu2+
Mg2+
DOBDC
Benzene
RT
MFM-300
In3+
Biphenyl-3,3’,5,5’tetracarboxylic
Fluorobenzoic acid
Naphthalene
o-CbPhH4IDC
MIDC
Chemiresistive
sensor
IDE
64–98%
(80 ppm)
5.7 (100 ppm)
SO2
RT
17 (1 ppm)
~800
0.075
IDE
IDE
Poton-conductive
Poton-conductive
H2S
NH3
NH3
NH3
RT
RT
30
25
~1000
~500
–
–
0.1
0.1
1
1
IS
I2
RT
13 (10 ppm)
7 (25 ppm)
243% (25 ppm)
1379%
(30 ppm)
106 variation
–
–
Fum-fcu-MOF
RE-fcu-MOF
Ba-MOF
Na[Cd
(MIDC)]
MFM-300
TMU-34
FJU-56
3+
Y
Y3+
Ba2+
Al3+
Al3+
2+
Zn
Co2+/3+
Biphenyl-3,3’,5,5’tetracarboxylate
Dihydrotetrazine
H3L
–
–
Chloroform
NH3
RT
RT
10
–
Small et al. (2019)
-5
2.5 * 10 M
1.38
Razavi et al. (2017)
Zhang et al. (2018)
Temp.: Temperature; RT: Room temperature; Res.: Response; Tres: Response time; LOD: Limit of detection.
Table 3
A summary of functional sensing materials based on MOF coatings for gas detection.
Sensing material
Morphology
MOF
Target gas
Temp. (◦ C)
Res.
Tres (s)
LOD (ppm)
Reference
ZnO
ZnO
Nanowire
Nanorod array
ZIF-CoZn
ZIF-71
260
150
Nanorod
Nanowire
Nanowire
Nanoparticle
Nanowire
gas sensor
ZIF-8
ZIF-8
ZIF-8
ZIF-67
ZIF-8
MIL-160/Cu
(BTC)
27 (10 ppm)
13.4%(10 ppm)/38.9%
(5 ppm)
13 (100 ppm)
2.62 (50 ppm)
8.5 (50 ppm)
16.5 (5000 ppm)
0.7% (0.1%)
0.7% (160 ppm)
43.2
194/
196
16
~300
–
~20
30
200
0.0019
0.021/
0.003
5.6
–
–
–
600
–
Yao et al. (2016)
Zhou et al. (2019)
ZnO
ZnO
ZnO/Pd
SnO2
Pd
Commercial
Acetone
Ethanol/
Acetone
HCHO
H2
H2
CO2
H2
H2
300
300
200
205
RT
RT
Tian et al. (2016)
Drobek et al. (2016)
Weber et al. (2018)
DMello et al. (2018)
Koo et al. (2017b)
Hwang et al. (2020)
Temp.: Temperature; RT: Room temperature; Res.: Response; Tres: Response time; LOD: Limit of detection.
Another strategy proposed by Kim was incorporating few-layered WS2
nanoplates into ZIF-67-derived Co, N-doped hollow carbon nanocages
(Koo et al., 2018). The sensor based on as-synthesized product showed
exceptionally a high response (48.2% to 5 ppm) and outstanding NO2
selectivity towards NO2.
Kim’s group also focused on fabrication of one-dimensional struc­
tures due to the easy gas accessibility and their high surface area. In
2017, they introduced Pd@ZIF-8-derived PdO@ZnO complex catalyst
onto the thin walls of SnO2 nanotubes (NTs) as effective functionaliza­
tion (Fig. 16(b)) (Koo et al., 2017d). As a result, the sensor based on
PdO@ZnO-SnO2 NTs exhibited a high response of 5.06 (1 ppm), fast
response/recovery speed of 20/64 s and a good cross-selectivity towards
acetone. In 2019, they reported a more complex sensing system.
ZIF-8-derived Pd-loaded ZnO nanocubes (Pd@ZnO NCs) were fixed on
the framework of WO3 nanofibers (NFs) (Fig. 16(c)). The sensor per­
formed an unparalleled sensitivity of 4.37–100 ppb, short response time
of 20 s and a superior cross-selectivity to toluene.
Compared with single MOSs, mixed MOSs derived from MOFs
exhibit new structures and novel composition. Self-templating method
of MOFs precursor offers a potential opportunity to rational design
morphology, composition and conductivity-controlled MOSs by modu­
lating the synthesis parameters. These results demonstrated that MOFsderived MOS-based multi-heterostructures could be created through
diverse methods. And the sensing mechanism varied according to the
final sensing materials.
5. Promising applications of MOFs-based gas sensors
The past decade has witnessed gas sensing progress in a variety of
MOFs-based sensors in public health and environmental safety.
5.1. Environment monitoring
MOFs-based sensors show great potential in environment moni­
toring, which could detect different gas species, including VOCs, and
inorganic hazardous gases and some explosives (Woellner et al., 2018;
Zhou et al., 2020). MOFs have shown great potential for trace gas
sensing, especially for polar analytes, such as NH3, NOx, SO2 etc. In this
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R. Zhang et al.
Journal of Hazardous Materials 429 (2022) 128321
Fig. 15. SEM and transmission electron microscope (TEM) images of MOF-derived MOSs (composites).
(a) MOF-5 derived ZnO from ref. Li et al. (2016). Copyright 2016, Elsevier; (b) FeFe(CN)6 derived Fe2O3 from ref. Wang et al. (2019a). Copyright 2019, Elsevier.
(c-d) ZIF-67 derived Co3O4 from ref. Wang et al. (2019b). Copyright 2019, Elsevier. (e-g) ZIF-67 derived Co3O4 from ref. Zhang et al. (2018a). Copyright 2017,
American Chemical Society. (h) ZIF-67 derived Co3O4 from ref. Jo et al. (2018). Copyright 2017, American Chemical Society. (i) ZIF-8/Co-Zn double hydroxides
derived ZnO-ZnCo2O4 from ref. Qu et al. (2016). Copyright 2016, The Royal Society of Chemistry. (j) ZIF-67/Ni-Co derived Co3O4-NiCo2O4 from ref. Tan et al.
(2020). Copyright 2020, Elsevier. (k) MIL-88/ZIF-8 derived Fe2O3-ZnFe2O4 from ref. Wei et al. (2020b). Copyright 2020, Elsevier. (l) HPU-15 derived CuO-ZnO
from ref. Li et al. (2020b). Copyright 2020, Elsevier.
Table 4
A summary of functional sensing materials based on MOFs as templates for gas detection.
Sensing material
Morphology
MOF
Target gas
Temp. (◦ C)
Res.
Tres (s)
LOD (ppm)
Reference
ZnO
Fe2O3
Co3O4
Co3O4
Co3O4
Co3O4
Co3O4
ZnO/In2O3
ZnO/ZnCo2O4
CuO/ZnO
Fe2O3/ZnFe2O4
In2O3/Co3O4
CuO/In2O3
Cu2O/CuO
Co3O4/NiCo2O4
Nanocage
Cube
Cubic particle
Core-shell particle
Nanocage
Octadecahedron
Sphere
Particle
Nanocage
Diamond shape
Spindle
Microcube
Microrod
Octahedron/cube
Nanocage
MOF-5
FeFe(CN)6
ZIF-67
ZIF-67
ZIF-67
ZIF-67
Co5-MOF
MIL-68/MOF-5
ZIF-8/Co-Zn
Cu-infiltrated HPU-15
MIL-88(Fe)/ZIF-8
Co-impregnated MIL-68(In)
Cu-impregnated CPP-3(In)
HKUST-1
ZIF-67/Ni-Co
Benzene
N-butanol
Ethanol
Acetone
P-xylene
N-butanol
HCHO
O3
hydroxide Xylene
TEA
TEA
TEA
H2S
Ethanol
H2S
400
230
300
190
225
100
170
150
320
220
300
250
70
150
250
0.35 (5 ppm)
~10 (100 ppm)
~3 (100 ppm)
13 (200 ppm)
78.6 (5 ppm)
21 (100 ppm)
14 (200 ppm)
14.08 (1 ppm)
34.26 (100 ppm)
~450 (500 ppm)
69.24 (100 ppm)
786.8 (50 ppm)
229.3 (5 ppm)
6.6 (100 ppm)
~9 (100 ppm)
39
59
10
4
63
127
46
21
–
11
2
47
10
–
153
–
1
10
–
–
–
10
0.025
0.126
0.175
0.2
2
0.2
–
–
Li et al. (2016)
Wang et al. (2019a)
Lu et al. (2014)
Zhang et al. (2018a)
Jo et al. (2018)
Wang et al. (2019b)
Zhou et al. (2017)
Zhang et al. (2019c)
Qu et al. (2016)
Li et al. (2020b)
Wei et al. (2020a)
Shi et al. (2018)
Li et al. (2020)
Wang et al. (2015)
Tan et al. (2020)
Temp.: Temperature; Res.: Response; Tres: Response time; LOD: Limit of detection.
case, MOFs are usually integrated with novel sensing devices and
techniques, including SERS, FET and film preparation technology, so as
to realize fingerprint-level spectral outputs (Yang et al., 2020; Ellis et al.,
2021). Ingle et al. fabricated EC- MOF (Ni3(HHTP)2) with a charge
mobility of 8.5 × 10-2 cm2V-1s-1 for SO2 sensing with a LOD of 625 ppb
(Ingle et al., 2020). The MOFs-based devices for environmental
applications have been summarized in a previous review (Ricco et al.,
2019).
5.2. Health monitoring
Facing the foreseeable aging population and increasing concern on
21
R. Zhang et al.
Journal of Hazardous Materials 429 (2022) 128321
Fig. 16. MOF as templates for the preparation of active components. (a) Synthetic process of PdO-Co3O4 HNCs derived from Pd@ZIF-67 by optimized thermal
treatment. (b) Dynamic resistance transition toward 5 ppm of acetone molecule. (c) Schematic illustration of synthetic process of PdO@ZnO-SnO2 NTs. (d) Dynamic
resistance transition toward 1 ppm of acetone at 400 ◦ C. (e) Schematic illustration of synthetic process for the Pd@ZnO-WO3 NFs. (f) Dynamic resistance transition
characteristics toward 1 ppm of toluene at 350 ◦ C.
(b) Reproduced from ref. Koo et al. (2017b) with permission from the American Chemical Society, copyright 2017. (d) Reproduced from ref. Koo et al. (2017d) with
permission from the American Chemical Society, copyright 2017. (f) Koo et al. (2016) with permission from the American Chemical Society, copyright 2016.
health, it is of great significance to develop wearable health monitoring
devices. Preclinical prognosis and diagnosis of diseases are very
important for later treatments, thus reducing the death rate. Some gases
could be used as disease bio-markers, and the concentration of biomakers reflects the pathogenic processes of diseases (Li et al., 2020c).
For example, above 2 ppm H2S from exhaled breath of a human is
regarded as a biomarker for halitosis. Acetone concentration of exhaled
mixture from a healthy person is under 0.9 ppm but from a diabetic
cancer patient is always above 1.8 ppm (Liu et al., 2019b). Thus, newly
developed sensors should require accurate and sensitive detection of
these markers. Such devices could monitor physiological signals of
patients (disease diagnosis) in an unobtrusive and noninvasive manner.
For detecting chronic kidney disease (CKD) from breath gases,
Wilmer et al. apply computational methods to design mass-based gas
sensor arrays (electronic noses) to recognize NH3 (Day and Wilmer,
2022). The sensor array based on five MOFs (ZIF-8, MOF-5, MOF-399,
CMOF-4b, and XUKYEI) successfully detected NH3 in gas mixtures,
down to 0.1 ppm. Additionally, ZIF-derived Co-doped ZnO particles
demonstrated potentials in detection of diabetes biomarkers (Zhu et al.,
2020). Optimized Zn/Co MOSs-based sensor was sensitive towards
5 ppm acetone by testing healthy exhaled breath and simulated diabetic
breath samples. André et al. reviewed porous materials (including
22
R. Zhang et al.
Journal of Hazardous Materials 429 (2022) 128321
MOFs) biomarker sensing in exhaled breath (André et al., 2020a). The
above applications ensure effectively monitoring of human health con­
dition through breath to realize remote healthcare.
Declaration of Competing Interest
The authors declare that they have no known competing financial
interests or personal relationships that could have appeared to influence
the work reported in this paper.
5.3. Other applications
Acknowledgement
The development of industrial automation largely depends on com­
puter technology. Computer-guided MOF research gradually extends to
materials screening and performance prediction, like electronic nose
and tongue for robotics (Okur et al., 2021; Wu et al., 2020). Moreover,
MOFs-based sensors will further facilitate the development of other
related industries, such as food security (Wang et al., 2019c; Sun et al.,
2021).
This work was supported by the National Natural Science Foundation
of China (NSFC; Grant No. 21922601, 22106015), LiaoNing Revitali­
zation Talents Program (XLYC1807080), the Fundamental Research
Funds for the Central Universities (DUT20YG123).
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MOFs offer tremendous versatility and flexibility in the detection of
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