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The potential utility of metal-organic framework (MOF)-based platform for sensing pesticides K Vikrant, Daniel CW Tsang, Nadeem Raza, Giri Balendu Shekher, Deepak Kukkar, and Ki-Hyun Kim ACS Appl. Mater. Interfaces, Just Accepted Manuscript • DOI: 10.1021/acsami.8b00664 • Publication Date (Web): 21 Feb 2018 Downloaded from http://pubs.acs.org on February 22, 2018

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ACS Applied Materials & Interfaces

The potential utility of metal-organic framework (MOF)-based platform for sensing pesticides

Kumar Vikrant1a, Daniel C.W. Tsang2a, Nadeem Raza3,4a, Balendu Shekher Giri1, Deepak Kukkar5,6*, Ki-Hyun Kim6* 1

Department of Chemical Engineering and Technology, Centre of Advanced Study, Indian Institute of Technology, Banaras Hindu University, Varanasi 221005, India.

2

Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, China 3

Government Emerson College affiliated with Bahauddin Zakariya University, Multan 60800, Pakistan.

4

Department of Materials Science and Metallurgy, University of Cambridge, CB3 0FS, United Kingdom.

5

Department of Nanotechnology, Sri Guru Granth Sahib World University, Fatehgarh Sahib 140406, Punjab, India.

6

Department of Civil and Environmental Engineering, Hanyang University, 222 Wangsimni-Ro, Seoul 04763, Republic of Korea.

*Corresponding Author: [email protected] (K.H. Kim), [email protected] (DK) a

These authors are considered as co-first authors because they contributed equally to this work.

Keywords: Analytical performance, water quality assessment, health issues, environmental monitoring, pesticides

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Abstract The progress in modern agricultural practices could not have been realized without the large-scale contribution of assorted pesticides (e.g., organophosphates [OPs] and non-organophosphates [non-OPs]). Precise tracking of these chemicals has become a crucial component for safeguarding the environment and food resources owing to their very high toxicity. Hence, the development of sensitive and convenient sensors for the on-site detection of pesticides is imperative to overcome practical limitations encountered in conventional methodologies which require skilled manpower at the expense of high cost and low portability. In this regard, the role of novel advanced functional materials such as metal-organic frameworks (MOFs) has drawn great interest as an alternative for conventional sensory systems due to their numerous advantages over other nanomaterials. This review was organized to address the recent advances in applications of MOFs for sensing various pesticides due to their tailorable optical and electrical characteristics. It also provides indpeth comparison of the performance of MOFs with other nanomaterial sensing platforms. Further, we discuss the present challenges (e.g., potential bias due to instability under certain conditions, variations in diffusion rate of the pesticide, chemical interferences, and the precise measurement of luminesce quenching) for developing robust and sensitive sensors using tailored porosity, functionalities, and better framework stability.


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Content 1. Introduction 2. Exposure and toxicity of pesticides 2.1 Pesticide exposure and health effects 2.2. Mechanism of pesticide induced toxicity 3. MOF-based pesticide sensing methodologies 3.1 Electrochemical sensing mechanisms 3.2 Luminescence sensing mechanisms 3.3 Biosensing and miscellaneous approaches 4. Use of MOF-based sensors for pesticides 4.1 Sensing of OPs 4.1.1. Electrochemical sensing of OPs 4.1.2. Luminescence sensing of OPs 4.1.3. Biosensing and miscellaneous sensing approaches for detection of OPs 4.2 Sensing of non-OPs 4.2.1. Electrochemical sensing of non-OPs 4.2.2. Luminescence sensing of non-OPs 4.2.3. Biosensing and miscellaneous sensing approaches for detection of non-OPs 5. Performance comparison of MOFs and other sensors 5.1. Electrochemical sensing approaches 5.2. Luminescence sensing approaches 5.3. Biosensing and miscellaneous approaches 6. Challenges in MOF technology for pesticide sensing 6.1 Stability of MOFs 6.2 Diffusion of pesticides 7. Conclusions and future research Acknowledgements References



List of abbreviations Acronym Expanded form AChE

acetylcholinesterase

2-ABA

2-aminobenzyl amine

ATC

amino terephthalic acid

AM

azinphos-methyl

BTC

benzene-1,3,5-tricarboxylic acid

H2L

benzo-(1,2;4,5)-bis(thiophene-2'-carboxylic acid

bpdc

biphenyl-4,4’-dicarboxylic acid

bptc

2,2’,4,4’-biphenyltetracarboxylic acid

L

bis-(3,5-dicarboxy-phenyl)terephthalamide

bimb

4,4’-bis(1-imidazolyl)biphenyl

BChE

butyryl cholinesterase

CNTs

carbon nanotubes

CT

charge transfer

ChOx

choline oxidase

DCN

2,6-dichloro-4-nitroaniline

DNB

dinitrobenzene

DNT

dinitrotoluene

BPyTPE (E)-1,2-diphenyl-1,2-bis(4-(pyridin-4-yl)phenyl)ethene EIS

electrochemical impedance spectroscopy

GC

gas chromatography

GCE

glassy carbon electrode

GP

glyphosate

GF

glufosinate

GO

graphene oxide

HPLC

high-performance liquid chromatography


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ITO

indium tin oxide

LB

leucomethylene blue

LMCT

ligand-to-metal charge transfer

LOD

limit of detection

LSPR

localized surface plasmon resonance

LMOFs

luminescent metal organic frameworks

MIL

Materials Institut Lavosier

MIPs

molecularly imprinted polymers

MOF

metal organic frameworks

MLCT

metal-to-ligand charge transfer

MP

methyl parathion

MB

methylene blue

NT

nitrotoluene

OMS

open metal sites

OPs

organophosphate pesticides

OPAA

organophosphorus acid anhydrolase

OPH

organophosphorus hydrolase

HDMA

protonated dimethylamine cation

PATP

p-aminothiophenol

PDA

1,4-phenylenediacetate

PBS

phosphate buffer saline

PEC

photoelectrochemical

PET

photoinduced electron transfer

PL

photoluminescence

PAH

poly (allylamine hydrochloride)

PANI

polyaniline

PSM

post synthetic modification



pbdc

5-(4-pyridyl)-isophthalic acid

QDs

quantum dots

QCMs

quartz crystal microbalances

SPE

solid phase extraction

Ksv

Stern-Volmer constant

SV

stripping voltammetry

SAWs

surface acoustic wave sensors

SERS

surface enhanced Raman spectroscopy

TPOM

tetrakis(4-pyridyloxy-methylene) methane

TMDs

transition metal dichalcogenides

TPs

transition products

tz

1,2,4-triazolate

UiO

University of Oslo


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1. Introduction In recent years, a noticeable growth in agricultural productivity has been realized with the optimization of water management strategies, the development of hybrid and genetically superior seeds, advances in cultivation science, and efficient utilization of potent pesticides 1-2. The extensive utilization of various pesticides (OPs and non-OPs) (Table 1) for pest control has resulted in the rise of grave concerns in agricultural and many other sectors throughout the world, including animal husbandry (to protect animals from pests), public health (to control the spread of vector-borne diseases like malaria), and public aesthetics (e.g., parks and walkways, and in storage facilities), 3. Pesticides play a pivotal role in agriculture because approximately one-third of the global agricultural production is dependent on such chemicals. However, accurate assessment of their pollution status in the ecosystem is necessary for proper management and control because of shortterm health issues (e.g., eye and skin irritation, nausea, headache, and dizziness) and chronic diseases (e.g., cancer, asthma, diabetes, and neurological disorders) associated with pesticide use 3-5. Swift and dependable quantification of pesticides in different environmental matrices (e.g., wastewater and surface waters) is critical to ensure public safety and security. The detection of pesticides has long been achieved using conventional methods such as gas chromatography (GC) 6, high-performance liquid chromatography (HPLC) 6, capillary electrophoresis 7-8, potentiometry 9-10, and flow injection spectrophotometry 11. However, use of these methods has often been limited by a number of disadvantages, including high analytical costs, time-consuming procedures (in sample preparation and pretreatment), and sophisticated instrumentation 12. In light of the limitations associated with the conventional methods, there has been a growing demand for quick and reliable methods for detection of various pesticides in environmental



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samples. This demand has been partially met using chromogenic and luminescent chemosensors 15

13-

. Likewise, immunosensing and enzymatic biosensing approaches have also been recognized as

effective sensing platforms for organophosphate pesticides (OPs)

16-17

. The feasibility of these

sensing techniques has been demonstrated with the recent development of new and advanced functional materials (e.g., carbon nanotubes [CNTs], quantum dots [QDs], and molecularly imprinted polymers [MIPs]). Such progress has provided opportunities for the development of efficient pesticide sensors with very short response times

18-19

and diverse uses in both solid and

liquid phases 6, 12. However, such advanced sensors also suffer from a number of drawbacks, e.g., a complicated procedure for synthesis, substandard photostability, deficiencies in molecular organization, and regular interference by the other analytes. To date, OPs are the most widely used pesticides in the world. According to an estimate, OPs constitute more than 50% of the destructive agents in most commercially used pesticides 20. As such, OPs are the most common cause of poisoning throughout the world 6, 21. Due to their predominance, most of the literature addressing the sensing of pesticides deals with the identification of OPs

22-26

.

The transformation products (TPs) of OPs result from the interaction of pesticide molecules with different microbes and other physicochemical processes such as hydrolysis and photolysis. Interestingly, many studies have shown that the TPs of OPs have a lower toxicity than the parent OPs

6, 19

. However, this trend is not necessarily universal, as some TPs can exhibit enhanced

toxicity and mobility. As such, there is a growing demand for the development of novel sensors for both important pesticides and their derivative TPs. Our discussion will thus focus primarily on OPs while encompassing other types of pesticides (e.g., non-OPs like lindane, clithodim, and flusilazole) along with their precursors (e.g., hydrazine) or less common TPs (Table 1).


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Nanotechnology has led to the invention of different types of sophisticated materials for specific applications. Among these various types, metal organic frameworks (MOFs) have emerged as an advanced material for analyte sensing. This review highlights the recent advancements in MOFbased sensing techniques for pesticides (with the main emphasis being on OPs) in light of the many advantageous properties associated with MOFs (e.g., stable structure, high selectivity, tunable porosity, luminescent nature, and presence of chemical functional groups). MOF-based sensors have immense capacities for post-synthetic modification (PSM), possible activation of pendant groups, suitable signal transduction, and possible biofunctionalization

17

. Moreover, practical

exploitation of the available functional groups in the framework coupled with the luminescent behavior result in a very attractive field of research 19. In this review, the sensing principles of MOFs are described along with areas of practical applications in pesticide detection. Subsequently, the performance of these MOF-based sensing approaches is evaluated in terms of quality assurance, such as the detection limit relative to other sensing methods. Finally, this review provides ample insight into the present challenges hindering the development of MOF-based sensors for pesticides. Our discussion has been extended to the prospects and future directions for this attractive and rewarding field of research.

2. Exposure and toxicity of pesticides A large section of society is exposed unintentionally to pesticides due to their recent use in combatting vector-borne diseases such as malaria and dengue (insecticides) and to kill unwanted grass and weeds (herbicides) in public parks, gardens and decorative landscapes. The adverse effects of pesticides on human health are recognized worldwide despite their potent role in



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maintaining the substantial increase in agricultural productivity. Pesticides are known to accumulate and persist in the environment for a very long time due to their non-biodegradable nature. Recent studies have revealed that leaks in pipes and underground storage tanks, waste heaps, spills, and runoff into surface water are the primary culprits for the accumulation of pesticides in the food chain and harm to human health 27-28. 2.1. Pesticide exposure and health effects As mentioned earlier, pesticides are tailor-made to kill living cells, be it weeds, different kinds of insects, rodents, or fungi. Note that chemical formulations of the pesticides may be different depending on the targeted pests. In light of the predominance of OPs in pest products, all pesticides can generally be grouped under two broad categories, namely OPs and non-OPs (Table 1). Pesticides are often not specific enough to differentiate between target and non-target populations. This indiscriminate nature of pesticides has caused irreparable damage to flora and fauna in the form of numerous health-related issues. In spite of the direct application of pesticides in plants and soils, recent studies have shown that merely 1% of the sprayed pesticides actually reach the targeted species. The remaining 99% of the applied pesticides bioaccumulate in the food chain via accumulation in farmland soils and carry over to surface bodies of water (e.g., lakes and rivers) via surface runoff 3, 17. Also, the application of pesticides to control the proliferation of various bacteria, fungi, insects, pests, and algae in different household and industrial settings (such as electrical equipment, carpet, wall paint, cupboards) and in various packaging materials has increased the risk of contact and exposure to pesticides. The primary exposure routes and health impacts of pesticides are summarized in Figure 1. The most common ways pesticides enter the human body are diverse and include dermal, oral,


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respiratory, and eye exposure 3, 27. Recent studies have shown that most critical pesticide poisoning ensues via oral exposure, which may occur intentionally or accidentally 14, 29. Accidental exposures have been reported to occur during the transfer of pesticides from one container to another or via beverage bottles or water bottles contaminated with pesticides 27-28. Also, workers actively involved in pesticide handling might also be accidentally exposed due to improper sanitation habits or smoking without washing their hands 3. It should be noted that the degree of contamination via pesticides is related to various factors associated with exposure (Figure 1 (a)), such as the concentration of the pesticide, dosage amount, and toxicity level of the specific chemical. Figure 1 (b) describes the major health issues associated with acute and/or chronic pesticide exposure. The threat of health problems resulting from such exposure depends both on the chemical makeup and potency of the pesticide and on the type of human receptors. For example, children, pregnant women, and senior citizens are more susceptible to such risks due to their physiology, conduct, and metabolism 3.

2.2. Mechanism of pesticide induced toxicity Over the last decade, the mechanism of pesticide poisoning has been studied in depth, with a main emphasis on OPs. In principle, OP molecules target the acetylcholinesterase (AChE) enzyme in the human body that is present at cholinergic brain synapses and neuromuscular junctions. The toxic effect of OPs irreversibly inhibits AChE which, in turn, results in inactivation of the neurotransmitter “acetylcholine”. Consequently, the normal transmission of stimulations between the nerves in the human body are hindered 3, 6.



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OP poisoning disrupts the functions of vital organs and muscular responses. As a result, the human body becomes susceptible to various neurological disorders and other diseases such as cancer and reproductive disorders 6. Higher levels of OP poisoning have been documented to cause severe heart attacks, fluctuations in blood pressure and strokes, which can eventually lead to death 34, 6

.

3. MOF-based pesticide sensing methodologies The detection of pesticides and their residues in the environment has traditionally been carried out via conventional analytical approaches such as GC and HPLC, which involve proper pretreatment and sample extraction procedures 6. However, as mentioned earlier, their use can be limited by the previously mentioned drawbacks

12

. To overcome such constraints, a feasible

pesticide sensor is necessary that can: (1) widen the parameters associated with proper detection, i.e., sensitivity, specificity, temperature range, pH range, and the type of pesticide, (2) provide rapid response, (3) be used under practical conditions, (4) provide quantitative as well as qualitative analysis, (5) be economically viable, and (6) be capable of miniaturization. Among a myriad of available nanomaterial systems, MOFs have emerged as a possible solution for selective and sensitive detection of OPs based on biosensing, chemosensing, and electrochemical sensing techniques as robust and novel sensors

30-32

. Figure 2 shows a schematic diagram of MOF-based

sensing approaches used for the detection of pesticides, which will be discussed in detail in the following subsections.

3.1 Electrochemical sensing mechanisms


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Recent years have witnessed a great rise in the development and utilization of electrochemical sensing methodologies for the successful detection of various amounts of environmental pollutants including pesticides

1-2, 14

. The high sensitivity and specificity of electrochemical sensors make

them prospective candidates for the efficient sensing of pesticides. However, the detection limits of electrochemical sensors are largely dependent on the electrochemical properties of the transducer MOFs or NMs

33-34

. Interestingly, the properties related to the conductivity of the NMs govern the

sensitivity of electrochemical sensors. As a result, a great deal of effort has been dedicated towards improving the conductive properties of MOFs to facilitate the fabrication of better and more sensitive MOF-based electrochemical sensors 19, 35. The research on MOF-based sensing and electrical conductivity is in its infancy. In principle, as the organic linkers are redox-inactive and are bound to hard metallic clusters via hard oxygen or nitrogen containing groups, their insulating characteristics make pristine MOFs poor electrical conductors (conductivity: < 10-10 S cm-1)

36-38

. To overcome such limitations, many modification

strategies have been introduced to increase the electrical conductivity, such as doping pristine MOFs with specific materials (e.g., nanotubes, nanoparticles, and selected ionic species)

1, 39

. In

addition, certain organic linkers (e.g., tetracyanoquinodimethane and tetrathiafulvalene) have also been utilized to prepare conductive MOFs

38, 40

. Such modifications can be used to improve the

conducting properties of the MOFs to develop potential electrochemical sensor technology based upon MOFs

41

. Conductive MOF-based sensors can thus be synthesized by modifying their

conductive behavior and their good sorption properties 41. In principle, both hopping transport (jumping of charge carriers localized at discrete sites with specific energy levels between potential neighboring sites) and band transport (delocalization of charge carriers with an effective mass, m*, via the band curvature) are required for the preparation



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of conducting MOFs 42-43. In this respect, ‘through-bond’ and ‘through-space’ approaches have been postulated as the prime candidates for inducing lower energy pathways (through both hopping and band transport) for transportation of charges within the framework of MOFs

38, 41, 43

. Metallic and

ligand orbitals involved in covalent interactions are utilized by the ‘through-bond’ approach to intensify the movement of charges by complimentary energetic and spatial overlapping

44

. On the

other hand, the ‘through-space’ methodology focuses on quantification of intramolecular charge transfer (CT) in hybrid compounds. The theory states that CT occurs via π-π stacking and other non-covalent interactions between molecular pieces possessing easily accessible organic/inorganic redox couples 45-46. Also, doping of the porous structure of the MOF by guest molecules that can play the role of charge carriers themselves (e.g., ionically conductive MOFs) has proven to be an innovative approach to inducing conductivity

38

. Alternately, doping via redox-active guest molecules can

induce free-charge carriers within the MOF-structural framework through charge transfer interactions taking place between the guest molecule and the MOF skeleton

37

. Notably, a list of

modification techniques (e.g., proton doping, hetero-bimetallic structures, metallic clusters from second or third-row transition metals, and redox-active linkers) have been suggested to endow MOFs with electrical conductivity 36. Recent advancements in the promotion of electron transfer reactions and lowering of the work over potential have greatly helped in the development of MOF-based electrochemical sensors

47

.

Moreover, the availability of various methodologies to alter electrodes coupled with the introduction of MOFs with enhanced conductivity have greatly stimulated research activity in the field of MOF-based electrochemical sensors for monitoring diverse pesticide species.


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3.2 Luminescence sensing mechanisms In recent years, MOFs have emerged as one of the most promising advanced functional materials for the sensing of small molecules

48-49

, gases

50-51

, solvents

52-53

, and explosives

54-55

. MOF-based

sensing approaches for pesticides can be mainly categorized based on luminescent and electrochemical principles (Figure 2). Given that the detection capability of luminescent MOFs (LMOFs) can be tuned by host-guest interactions, they have been proposed as excellent candidates for pesticide sensing applications

56-58

. The prospective sensing applications of LMOFs have been

explored in the past few years 59-61. The sensing method employed for signal transduction governs the sensitivity of MOF-based detection of pesticides

62

. The sensitive nature of LMOFs is thus related to the high loading

capacities of MOFs and the facile transport of the analyte within their structural framework

19

.

Moreover, the limits of detection (LODs) for LMOFs are also affected by the active incorporation of the analyte into the MOF framework

19

. Researchers have concluded that the primary

mechanisms involved in the LMOF-based sensing approach are based upon: (1) variation in the intermolecular distances between the metallic centers and the organic linkers, (2) chemical interactions between the target analyte and the metallic clusters in the MOF framework, and (3) host-guest interactions between the organic ligands and the guest analyte 19, 58, 62. These mechanisms are observed through variations in luminescence-related phenomena such as ligand-localized emissions, ligand-to-metal charge transfer (LMCT), metal-to-ligand charge transfer (MLCT), plasma-induced gate oxide damage (antenna effects), sensitization, and metal/excimer/exciplex emissions 62-63.



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Interestingly, LMOFs have small organic ligands as one of the structural components. These ligand molecules are observed to repetitively undergo self-quenching, resulting in a meager electro/photoluminescence quantum yield

64

. The MOF structure of some LMOFs containing

stabilizing organic ligands has shown a tuned HOMO-LUMO (the highest occupied molecular orbital-the

lowest

unoccupied

molecular

orbital)

photoluminescence quantum yield toward a value of one

energy 63

gap,

which

improved

the

. Moreover, the use of organic linkers

that tend to absorb UV/visible light in MOFs can lead to the generation of fluorescence

63, 65

.

Interestingly, metal-cluster-based luminescence has been observed in cases when the metal ions with unpaired electrons in f-orbitals can function as nodes (e.g., lanthanide ion-based MOFs as paramagnetic in nature)

65

. A characteristic progressive filling of the 4f orbitals in the general

electronic configuration [Xe]4fn (n=0-14) has been observed for lanthanide ions (Ln3+) 66 (Figure 3). These electronic configurations gave rise to a variety of complex optical properties

67-69

. The

shielding effect of the 5s2 5p6 filled subshells resulted in the low sensitivity of 4f orbitals towards chemical environments in the vicinity of lanthanide ions characteristic and limited 4f-4f transitions

67, 69

67

. As a result, lanthanide ions showed

. All lanthanide ions (Ln3+), with the exception of

La3+ and Lu3+, have produced luminescent f-f emissions ranging from ultraviolet (UV) to visible, including the near-infrared (NIR) range 67-69. In the case of LMOFs, quenching of the optical intensity (i.e., turn off fluorescence) is the most commonly used method for signal transduction

65

. An overlap between the electron acceptor and

donor is believed to be the reason for this quenching behavior

63

. However, changes in the redox

potential of the in-built moieties have also been known to account for quenching in certain cases 19. Interestingly, the luminescence intensity of the LMOFs, although not common, also increases (i.e., turn on fluorescence) upon their interaction with the guest analyte. Such behavior may be useful to


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quantify the analyte concentration at a single wavelength with increasing luminescence intensity 19, 63, 65

.

The interaction of a MOF with an analyte is accompanied by some variations in the physicochemical properties such as optical/electrical conductivity. Likewise, LMOF-based optical detection can produce detection signals that can be perceived even by the naked eye

65

. Also, the

extremely high molecular specificity coupled with significant sorptive tendencies make LMOFs prime candidates for MOF-based sensing applications (for more information, readers may refer to Table 2 and Section 3). Moreover, LMOFs can be used directly in powdered form without any treatment

63

. Overall, monitoring of changes in optical characteristics allows highly sensitive

detection of targets (i.e., low LODs), and this option has indeed been pursued for pesticide detection 6, 19, 70

. Nonetheless, LMOF-based sensing of pesticides warrants further research and development

due to some identified drawbacks (e.g., variations in the quenching rate and pathways along with medium stabilization and detrimental porosity) 19, 63, 65.

3.3 Biosensing and miscellaneous approaches Modern biotechnological tools have made biosensors an economical and rapid technique for the detection of pesticides

71

. A biosensor is a self-sufficient, coherent device that contains all

subsystems needed for electronic quantification and transmission of results acquire a usable signal via integrating bio and electrochemical interactions

73

72

. These sensors

. Such signals are

obtained by utilizing a biological recognition element that is exposed to an electrochemical transducer 76

74-75

. However, the bio-recognition element often decreases the selectivity of the sensor

. Pesticide molecules can inhibit the activity of specific enzymes used to quantify the target



analyte

71, 76

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. Thus, the biosensing approach for pesticide detection usually employs various

biomolecules such as enzymes (e.g., AChE, BChE, tyrosine, ChOx, OPH, and OPAA) antibodies

79-80

and nucleic acids

77

77-78

,

. In addition to the enzymes mentioned above, many authors

have reported the incorporation of other enzymes such as cholinesterase, ascorbate oxidase, acid phosphate, urease, acetolactate synthase, and aldehyde dehydrogenase for the biosensing of different pesticides

71, 81-82

. OPH-based hydrolysis has also been used for the sensitive detection of

OPs 6. The hydrolysis of OPs is catalyzed by OPH, which results in a release of protons

83

. The

quantity of hydrolyzed substrate is directly proportional to the concentration of the released protons 84

. Interestingly, OPAA can be used to specifically detect fluorine-based OPs such as sarin GB and

soman GD because the detection is based on the hydrolysis of P-F bonds 78. The substrate molecules bind to an active site present in the enzyme, resulting in the formation of an enzyme-substrate complex

85

. Upon successful interaction with the enzyme, the substrate

converts into different products, which are then liberated from the part of the enzyme where the bonding of the substrate took place; this frees the active sites to accept other substrates throughout the catalysis operation

85-86

. The substrate and enzymes have distinct complementary geometrical

shapes that exactly fit with one another 86. In the presence of multiple substrates, molecules bond to the active sites in a fixed order governed by the relative ease and preference of the product being formed

86-87

. As a result of this selectivity of the enzymes towards substrates, it is possible to

engineer specific enzyme-substrate complexes to meet specific needs. Immobilization of the enzyme on the biosensor transducer is the principal step for the successful detection of pesticides

76

. Biosensing has been the primary methodology for the detection of

pesticides via NMs (Table 3). In contrast, biosensing of pesticides via MOFs is still in its infancy (Table 2) and requires more rigorous research. Immunosensing has provided new avenues that can


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be explored for MOF-based biosensors 23. Here, antibodies serve as identification receptors, which are organic compounds that govern the peripheral physicochemical properties and control the grafting procedure to improve the sensitivity and selectivity of the biosensing approach 88-89. As explained in Section 2.2, OPs irreversibly inhibit AChE. This fact has been exploited to develop immunosensors capable of developing measurable signals 90. Oxidation of thiocholine takes place under an applied voltage 91, and the anodic oxidation current is inversely proportional to the concentration of OPs present in the sample and the exposure time

90-91

. This large change in the

voltammetric signal of the AChE complex is used in sensing the pesticide 92. The sensitivity of such sensors is dependent upon the enzyme-based bio recognition layer that catalyzes the reaction 90. A comprehensive analysis of the reported literature suggests that the majority of the electrochemical-based MOF sensors for pesticides have been developed for biosensing. Electrochemical biosensors detect pesticides by utilizing specific enzymes in biorecognition films, which produce electroactive substances

93

. Chemical sensing proceeds via the recognition of

comparable compositions (between the substrate and the pesticide molecule) or by inhibiting the activity of the enzyme in the substrate due to the presence of the analyte

93-94

. Static detection

(sensing via enzyme inhibition) and dynamic detection (pesticide hydrolysis) are the two main electrochemical biosensing methodologies 71. Although the dynamic approach provides a rapid rate of catalysis and short response time, the static detection technique has been predominantly used due to its simplistic operation and broad array of available enzymes

71

. In electrochemical biosensors, the chemical data from the enzymes

are converted proportionally into electrical parameters such as resistance, current, or voltage

93-94

.

The efficiency of such sensors is governed by the amount of immobilized bioactive species on the



exterior of the sensor

95

Page 20 of 71

. The sensor surface can be tailored to immobilize bioanalytes by definite

receptor identification interactions and minimizing the non-specific sorption of the analyte

93, 96

.

Although electrochemical biosensors are robust, sensitive, and compact, their efficiency and portability needs to be increased significantly by modifying and redesigning the immobilization substrates used for the enzymes 71. Other than biosensing approaches, MOF-based pesticide detection has also been employed using some non-conventional approaches such as surface enhanced Raman spectroscopy (SERS) and adsorption-based approaches (e.g., solid phase microextraction [SPME]). The SERS approach requires MOFs to be complexed with noble metal NPs such as Au or Ag to function as SERS probes

97

, whereas the SPME approach relies on affinity-based selective adsorption platforms for

pesticides using MOF matrices 98.

4. Use of MOF-based sensors for pesticides The sensing applications of MOFs explicitly depend upon their structural attributes. Insight into the precursor components and synthesis approaches reveals that MOFs possess a mesoporous nature, high specific surface area, open metal sites (OMS), low framework density, tailorable luminescent properties, and facile conjugation with the guest species. These properties in turn account for a diverse range of functional characteristics including luminescent, conducting, chromogenic, and optical characteristics. In light of this structure property-functional capability relationship, the design of MOF architecture can result in the construction of new MOFs that are highly efficient for specific applications. Accordingly, performance-based pesticide sensing of various MOFs is presented in Table 2. As discussed in the previous sections, the two most extensively reported


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strategies for pesticide detection are luminescent and electrochemical approaches. Many researchers have also relied on other principles (such as immunosensing, colorimetric, and SERS approaches) for such applications. Note that the OPs represent one of the most extensively utilized classes of pesticides. The majority of the pesticide sensing applications of MOFs have thus centered on the screening of these pollutants. Herein, we discuss some of the recently reported case studies for pesticide sensing applications of MOFs in light of both the sensing methodologies and the types of pesticides.

4.1 Sensing of OPs Among various OPs, parathion and methyl parathion (MP) have become important for screening the capabilities of MOFs in pesticide detection (Table 2). Both of these pesticides are characterized by the presence of electron withdrawing –NO2 groups, which make them electron deficient

99-100

.

On the other hand, MOFs possess electron-rich centers in the form of OMS or organic ligand molecules 101. The Lewis base nature of OMS allows for facile diffusion of the guest OPs molecules in MOF pores

102

. These Lewis acid base interactions form the core of pesticide sensing

mechanisms in all the detection and concentration methods including electrochemical, luminescence, colorimetric, and solid phase microextraction (SPM) approaches.

4.1.1. Electrochemical sensing of OPs Electrochemical sensing relies on the ability of MOFs to conduct electric charge under the influence of an applied voltage

103-104

. As stated earlier, the poor electrical conductivity of MOFs



Page 22 of 71

means that they must be fabricated using a conducting organic linker or be post-synthetically modified, which makes them suitable for electrochemical sensing applications

105-106

. The potential

of the electrochemical sensing approach was explored for the detection of glyphosate (GP) These

authors

prepared

molecularly

imprinted

polymer

(MIP)-MOF

thin

films

107

.

by

electropolymerization of p-aminothiophenol (PATP) and PATP-functionalized Au NPs using GP as a template molecule. The embedded GP molecules were passively extracted by incubation in the phosphate buffer saline (PBS; pH = 7.2) solution, leading to the formation of cavities

107

. These

cavities showed specific recognition and the ability to bind to GP through hydrogen bonds between GP molecules and aniline moieties of the PATP

108-109

. The GP sensing potential of the MIP-MOF

sensor was investigated further using a linear sweep voltammetry approach in the presence of a [Fe(CN)6]3-/4- redox probe

110

. The prepared MIP-MOF sensor exhibited selective sensing of GP

with a quantification limit of 0.8 pg/L. Furthermore, these authors tested the practical applicability of the developed sensor by spiking GP standards into two tap water samples, and the results showed excellent recovery (e.g., 102.6 and 98.7%) 107. Stripping voltammetry (SV) analysis requires pre-concentration of the analytes on an electrode surface

26

. In this context, the application of MOF as a sorbent matrix for solid phase extraction

(SPE) of analytes led to an improvement in the SV approach using glassy carbon electrodes (GCEs) modified with MOF thin films 35, 111. The conjugated MOFs can synergistically attract nitroaromatic compounds through hydrogen bonding and π - π stacking interactions

26

. The authors performed

trace level sensing of MPs based on a sorptive reaction using Cd(2,2’,4,4’-bptcH2)]n MOFs (bptc = 2,2’,4,4’-biphenyltetracarboxylic acid) prepared from the precursors of Cd(NO3)2·6H2O and bptc 22,2’,4,4’-biphenyltetracarboxylic acid

112

. The MOF/GCE immersed in an MP solution with a

predetermined concentration exhibited a continuous increase in the peak current with immersion


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time (e.g., until adsorption saturation of the pesticide, ~12 min). The stripping peak voltage was 0.08 V, which corresponds to the maximum current condition (Figure 4). The as-prepared sensor showed highly reproducible and sensitive adsorption behavior towards MP, resulting in LOD values of 0.006 µg.mL-1 and a relative standard deviation of 5.2% (at 0.1 µg.mL-1 MP)

26

. The synthesis

and pesticide sensing potential of luminescent [Zn(pbdc)(bimb).(H2O)]n MOFs (pbdc = 5-(4pyridyl)-isophthalic acid; bimb = 4,40-bis(1-imidazolyl)biphenyl) were reported for the first time by

113

, who showed a selective luminescent quenching response to MP in the presence of other

pesticides (including acetamiprid, isocarbophos, methomyl, and phenamiphos) in a DMF solution. Almost complete quenching of the MOFs was observed at 1 mM of MP with a LOD of 2.5 µM (Figure 5).

4.1.2. Luminescence sensing of OPs The basic concept of luminescence sensing of pesticides originates from the interactions between electron withdrawing –NO2 groups of OPs and electron excess OMS, as mentioned in Section 4.1. The luminescence sensing behavior of nitroaromatic compounds with other organic compounds (e.g., alcohols, ethers, ketones, benzene, toluene, and styrene) using Cd(L).(HDMA)2(DMF)(H2O)3 and Zn(L).(HDMA)2(DMF)(H2O)6 (L = bis-(3,5-dicarboxy-phenyl)terephthalamide; HDMA = protonated dimethylamine cation) was pioneered by

114

. The authors showed that all the

nitroaromatic compounds caused a significant turn off effect in the luminescence intensity of both MOFs. However, MOFs treated with other organic compounds did not show significant quenching behavior. It was suggested that the electron withdrawing capabilities of the guest nitroaromatic compounds caused the transfer of photoexcited electrons from the MOF-based sensor to the analyte,



Page 24 of 71

instead of radiative relaxation to the ground state. This redox quenching mechanism accounted for the turn off luminescent intensity of both MOF sensors under consideration. When treated with three analytes (including nitrotoluene [NT], 1,4-dinitrobenzene [1,4-DNB], and 2,4-dinitrotoluene [2,4-DNT]), both MOFs exhibited higher quenching efficiencies (e.g., ~85%) than those treated with nitrobenzene (NB) and 1,3-dinitrobenzene (1,3-DNB)

114

. This confirmed that quenching of

the luminescent MOFs may be ascribed to the presence of –NO2 groups in the target analyte. Inspired by this work, 80 investigated the chemosensing potential of [Cd(atc)(H2O)2]n (NMOF-1) for highly sensitive detection of OPs (including parathion, MP, paraoxon, and fenitrothion). Accordingly, a substantial turn off fluorescence was observed for the interaction of NMOF-1 (at an emission maxima of λem = 436 nm) with OPs. The NMOF-1 showed a very low LOD value of 1 ppb for all the above mentioned OPs when simultaneously exposed to a list of potential interfering molecules (e.g., dichlorvos, malathion, and monocrotophos in a mixture). These authors further extended the chemosensing of the previously mentioned OPs by exploring the luminescent MOF-5 material

115

. The OPs were analyzed in the concentration range of 5-60 ppb with a LOD value of 5

ppb. In another case study, bioconjugation of NMOF-1 with antiparathion antibodies was probed for sensitive and selective sensing of parathion

23

. The use of this immunosensing approach

demonstrated a highly selective response to parathion with a LOD value of 1 ppb. In addition, the prepared bioconjugate did not show any fluorescent response to the other OPs used during the course of the study. As such, the selective sensing behavior of the MOF nanoprobes can be improved significantly if aided by biological molecules 23, 116. The attenuation of luminescence for NMOF-1 and MOF-5 is primarily due to the generation of holes (hVB+) and electrons (eCB-) in the valence and conduction bands, respectively

63, 80

. Redox

processes take place either on the surface or inside the MOF framework between pesticide


Page 25 of 71 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


molecules and the trapped (etr-) or photo generated (htr+) carriers 65, 80. Quenching then occurs due to equilibrium between the complexed or uncomplexed MOF particles and the pesticide molecules 80. Studies have shown that, under most circumstances, it can be assumed that PL quenching occurs only in the integrated MOF and OP complex 80. The association constant (Ka) is given by Equation 1: Io / (Io - I) = Io / (Io – I`) + Io / [Ka x (Io – I`) x [OP]].

(1)

Here, Io and I are the intensity of emission for NMOF1 particles before and after the addition of OP (concentration = [OP]). I` is defined as the intensity of emission for the analyte OP. Recently, a Cd-based luminescent MOF [Cd2.5(PDA)(tz)3] (PDA= 1,4-Phenylenediacetate and tz= 1,2,4-triazolate) has been explored for the detection of azinphos-methyl (AM) in an aqueous phase 12. The MOF was characterized by an intense emission peak in the UV region (λem = 290 nm). The reaction between AM and MOF resulted in a significant turn off (92.7% at 40 µM concentration) luminescent effect. The LOD and Stern Volmer constant (Ksv) for AM were estimated to be 16 ppb and 16.58 x 104 M-1, respectively. In addition, there were no interfering effects (i.e., no quenching behavior was observed) for these MOFs against other pesticides (such as chlorpyrifos, diazinon, dichlorvos endosulfan, malathion, and parathion).

4.1.3. Biosensing and miscellaneous approaches for detection of OPs As explained in Section 3.3, the biosensing method involves the use of bio recognition elements to increase the selectivity of the MOFs for target specific applications

112, 117

. Although biosensing

approaches do not offer the trace level analysis observed with GC/HPLC analysis, they enable in



Page 26 of 71

situ analysis, which gives them a distinct advantage over other techniques

117-118

. As our

understanding of bioconjugation approaches has increased, numerous biosensing techniques employing various types of nanomaterials such as metal NPs, carbon-based nanomaterials, and semiconductor NPs (e.g. quantum dots) have been extensively reported for pesticide detection 121

119-

.

The majority of the reported cases of electrochemical biosensing approaches for MOF-based pesticide detection have been realized by covalent conjugation with anti-pesticide antibodies

79-80

.

These bioconjugates are consumed during the subsequent electrochemical or optical methods for analysis of the target pesticides

112

. Despite all these advantages, biosensing is still in its infancy

with regard to MOF-based pesticide sensors 117, 119. Studies involving biomolecules for MOFs-based colorimetric, fluorescent or other detection methods for OP sensing have rarely been reported in the literature. In this section, we describe three case studies on MOF-mediated pesticide detection through immunosensing, adsorption, and SPME techniques. Impedimetric sensing of parathion was reported using thin films of [Cd(atc)(H2O)2]n MOFs synthesized on 2-aminobenzyl amine (2-ABA) modified indium tin oxide (ITO) substrates by exploiting the available –COOH pendent functional groups on the fabricated film 79. The thin film deposited MOFs were bioconjugated with anti-parathion antibodies using a standard carbodiimide covalent linking approach. This electrode surface was covered with an antibody layer that was insulating in nature 35, 122. The electrode was capable of catalyzing the redox probe in the measuring solution. Interactions between the antibody and the antigen resulted in an increase in the charge transfer resistance due to hindered faradaic reactions mimicked a capacitor and stored electric charge

125

123-124

. In principle, the immunosensor

. The sensor was subsequently treated with

various concentrations of parathion (0.1-20 ng/ml). Electrochemical impedance spectroscopy (EIS)


Page 27 of 71 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


analysis showed that an increase in the charge transfer resistance was accompanied by a decrease in the capacitance (e.g., due to the immune complex formation between the antibody and parathion analyte)

117, 126

. The immune complex was capable of the specific detection of parathion at a LOD

value of 0.1 ng/ml

79

. [Cd(atc)(H2O)2]n has a unique hierarchical structure that provides an

organized geometry to obtain stable sensing results (a mere ± 3% observed variation in the charge transfer resistance (Rct) over a 10 day period and a variation of ± 5% in the Rct after 25 days of storage) compared to other arbitrary platforms such as electrodes fabricated from Nafion

79, 127

.

These results are an exemplary form of the chemosensing approach based on host-guest interactions with high specificity and selectivity. The sensing capabilities of MOFs can also be improved considerably by the formation of composites with metals and metal oxides 104, 128. For instance, a composite mixture of MIL-101 (Fe) (MIL= Materials of institute Lavosier) MOFs (Fe3O4/MIL-101) was prepared with a low quantity (50 mg) of magnetite (Fe3O4) NPs through a novel in situ solvothermal method

98

. The hybrid

magnetic MOFs were tested by using a magnetic SPME against six OPs including dichlorvos, dimethoat, malathion, MP, methamidophos, and parathion in a range of samples from human hair and urine. The analysis process was optimized for operating parameters, including desorption of solvent (acetone, dichloromethane, ethyl acetate, and methanol), extraction time (10-50 min), desorption time (5-20 min), and solution ionic strength (0-25% (m/v) NaCl)

98

. The LOD values

were a minimum of 0.21 ng/ml (for parathion) and a maximum of 2.28 ng/ml (for methamidophos). In addition, the precision of this approach was moderate with ranges of 1.8–8.7% (within a day) and 2.9–9.4% (for inter-day) with acceptable recoveries (76.8–94.5% for hair samples and 74.9–92.1% for urine samples). The study thereby supported the feasibility of Fe3O4/MIL-101 as magnetic SPE sorbents for trace level analysis of OPs from biological samples 98, 111.



Page 28 of 71

The majority of MOF sensing approaches have been directed toward a few important pesticides (e.g., malathion and parathion) 6, 19, 129. However, some studies have also focused on other OPs 12, 75, 130

. Most other OPs also share a similar organothiophosphate ester bond in their backbone as in the

malathion and parathion molecules for various substituents

131

131-132

. However, the structure of the aromatic ring is different

. Studies on MOF sensing on these other OPs are rarely found in

literature. However, the concentration of these pollutants is increasing at an alarming rate in the environment, especially in developing countries

133

. Herein, we discuss some of the recently

reported case studies of MOF sensing for sensitive detection of non-parathion/malathion OPs through an adsorption and SPM approach. The pore size and pore volume play an important role in determining the absorption capacity of the MOFs

134-135

. Among the different MOFs, UiO (UiO = University of Oslo) MOFs are

characterized by a very large pore size and high pore volume with high stability 135. Therefore, they have been extensively investigated for adsorption and removal of various target analytes

135-136

. In

one particular study, a UiO-67 MOF was subjected to the selective removal of two OPs including glyphosate (GP) and glufosinate (GF)

137

. The high concentration of −OH groups in the MOF

architecture resulted in a high affinity towards phosphoric groups of OPs and increased adsorption of these compounds 137-138. The adsorption process of this MOF was examined in relation to diverse variables (e.g., reaction time, concentration of the OPs, adsorbent dose, pH, and ionic strength). The adsorption of GP took place more rapidly than that of GF, with the adsorption kinetics following a Langmuir model and pseudo-second-order rate equation 137. The calculated adsorption capacities of GP and GF by UiO-67 were measured to be 3.18 mmol (537 mg) g-1 for GP and 1.98 mmol (360 mg) g-1, respectively. These authors further claimed that these adsorption values were the highest of all the previously reported adsorption values

137

. The performance of MOF-mediated adsorption


Page 29 of 71 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


approaches has also been explored for the removal of organophosphate pesticides 130. These authors investigated hybrid MOF-graphene oxide (GO) nanocomposites (UiO-67/GO) for the adsorption of GP pesticides 130, 139. Accordingly, the adsorption process of UiO-67/GO followed a pseudo-secondorder kinetic model and a Langmuir adsorption isotherm with the maximum GP adsorption capacity of 2.855 mmol (482.69 mg) g-1 130.

4.2 Sensing of non-OPs The health risks associated with exposure to non-OPs are relatively more intense than the OPs 140-142

. This is because the former class of pesticides is more biopersistent and biomagnified than the

latter

140

. Non-OPs are diverse and include neonicotinoid pesticides, carbamates, organochlorines,

pyrethroids, sulfonylurea, and bipesticides

141-142

. Commercial use of these pesticides (e.g.,

organochlorines such as dichlorodiphenyl trichloroethane) has been banned in many countries across the globe

140

. In light of their life-threatening health effects (e.g., neurotoxicity and cancer)

and adverse environmental impacts, it is necessary to develop sensing technologies that can provide real-time monitoring of non-OPs with high sensitivity and selectivity

141

. Here we discuss recent

advances in MOF technology for selective and sensitive sensing of non-OPs.

4.2.1. Electrochemical sensing of non-OPs A nanocomposite material made of Au-SH-SiO2 NPs immobilized Cu-MOFs (Au-SH-SiO2@CuMOF) was employed for electrocatalytic oxidation of hydrazine on GCE

143

. The composite

electrode (Au-SH-SiO2@Cu-MOF/GCE) showed a well-defined anodic peak at 0.53 V with a



Page 30 of 71

substantial increase in peak current as a function of hydrazine concentration. Further chronoamperometric studies of the sensor showed satisfactory electrocatalytic oxidation of hydrazine, as evident from its broad linear detection range (0.04–500 µM), low LOD (0.01 µM), high sensitivity (0.1 µA. µM-1), and appreciable stability/reproducibility

143

. This study

demonstrated the successful adaptation of an electrocatalysis approach for sensing of pesticides in an aqueous medium. Photoactive semiconductor materials such as TiO2 can separate the source (light) and detector (electric current) signals, thereby increasing the signal-to-noise ratio in the electrical conductivity measurements and ultimately improving the sensitivity of the probe compounds

144

. However, they

also suffer from certain limitations such as rapid recombination of electron-hole pairs and narrow optical absorption windows

27

. Considering both the advantages and disadvantages of TiO2,

22

prepared an amino-MIL125 (Ti)/TiO2 composite for photoelectrochemical (PEC) sensing of the cyclohexanone herbicide clethodim through a combination of TiO2 NPs with amino-MIL-125 (Ti) MOFs. Following a PEC sensing mechanism, this composite produced excited electrons under visible light illumination that transferred to the underlying GCE

145

. As such, positively charged

holes (h+) left on the composite surface reacted with H2O to generate hydroxy radicals (•OH). The charge separation efficiency improves considerably as these •OH radicals are rapidly captured by clethodim (herbicide) 27, 145. This process accounts for the enhanced photocurrent that was observed with increasing concentration of clethodim. The PEC method showed considerably enhanced sensitivity to clethodim with a detection limit (3 S/N) of 10 nmol L-1 over a linear concentration range of 0.2-25 µmol L-1. The PEC assay applied for clethodim in soil samples showed great compatibility with those determined by HPLC in parallel experiments. These observations suggest that the PEC approach is feasible for pesticide detection 22.


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As discussed earlier, an immunosensing approach combined with electrochemical measurements may considerably enhance both the sensitivity and selectivity of the MOF probes

116, 119

. In light of

these remarks, thin films of SiO2-modified Cu3(BTC)2 MOFs (Cu3(BTC)2@SiO2; BTC = benzene1,3,5-tricarboxylic acid) on a conducting polymer polyaniline (PANI) (doped with atc) were investigated for immunosensing of atrazine 116. The as-prepared Cu3(BTC)2@SiO2/BDC-PANI thin films showed enhanced electrical conductivity in the range of 35 µS in comparison to the Cu3(BTC)2 (76.2 nS) and Cu3(BTC)2@SiO2 (34.9 nS) thin films. Subsequently, these thin films were conjugated with antiatrazine antibodies using a standard carbodiimide covalent coupling reaction to produce an immunosensor

122

. The prepared immunosensor showed enhanced and

selective conductometric response towards atrazine with a low LOD value of 0.01 nM in the presence of potential interfering pesticides (e.g., endosulfan, malathion, monochrotophos, parathion, and paraoxon) 116.

4.2.2. Luminescence sensing of non-OPs An entangled luminescent MOF [Zn2(bpdc)2(BPyTPE)] (H2bpdc = biphenyl-4,4’-dicarboxylic acid; BPyTPE = (E)-1,2-diphenyl-1,2-bis(4-(pyridin-4-yl)phenyl)ethene) with a pillared-layered structure has been recently investigated for quantitative detection of 2,6-dichloro-4-nitroaniline (DCN)

25

. These authors first investigated the anti-interference effect of many volatile aromatic

compounds (VOCs, e.g., aniline, m-xylene, mesitylene, p-nitroaniline, nitrobenzene, and toluene) on the solid state luminescence spectra of the MOFs

51, 146

. Among the tested VOCs, those

containing -NO2 groups (e.g., nitrobenzene and p-nitroaniline) exhibited a significant turn off effect at the emission peak of the MOFs (λem = 490 nm)

25

. These authors observed an enhanced



Page 32 of 71

sensitivity of p-nitroaniline (LOD ~4.9 x 10-2 ppm), probably due to the hydrogen bonding interactions (N – H---O) between its amino group and the oxygen of bpdc2-

122

. They further

developed a luminescent assay for DCN. The solid state luminescent spectrum of MOFs underwent oppressive quenching upon reaction with trace levels of DCN, resulting in high reproducibility and a low LOD value of 0.13 ppm 25. Recently, methylene blue (MB) encapsulated UiO-66-NH2 (MB- UiO-66-NH2) MOFs were tested as chromogenic and fluorescent sensors for hydrazine hydrate 147. Hydrazine is a precursor to several pesticides consisting of heterocyclic rings such as pyrazoles and pyridazines

148

. These

pesticides (e.g., oxadiazoles, pyrazoles, pyridazines, thiadiazoles, and triazines) are used primarily as fungicides, herbicides, and plant growth regulators 148. However, due to their neurotoxicity (e.g., low acceptable environmental limit of 0.1 ppm), chronic exposure to these compounds may cause damage to the lungs, liver, or kidneys 143. The MB-UiO-66-NH2 MOFs are characterized by strong optical absorption peaks (at 357 nm) and a broad peak (around 613 nm) due to the electronic transitions in the MOFs and the MB dye, respectively

149

. In the presence of hydrazine, the characteristic peak of MB dye showed a gradual

reduction in the optical absorbance, which was accompanied by a change in the solution color from blue to colorless 149. This phenomenon can be attributed to a hydrazine induced reduction of MB to leucomethylene blue (LB), which is referred to as the blue bottle reaction

150

. These observations

were linear in the photoluminescence studies, where the characteristic emission peak of MB was observed upon excitation of the MB-UiO-66-NH2 complex (at 613 nm) 149. However, the UiO peak (λem = 449 nm) showed a significant enhancement and blue shift in the emission intensity with increasing volume of hydrazine. This enhanced emission of the UiO-66-NH2 MOFs can be


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attributed to a photoinduced electron transfer (PET) phenomena from MB to the MOFs 151-152. This photophysical response of the MB-UiO-66-NH2 MOFs was selective to hydrazine only despite the presence of other potential interfering analytes (e.g., hydroxylamine, aniline, NH3, urea, ethylene diamine) and metal ions (e.g., Ag+, Hg2+, Cd2+, Fe2+, Zn2+, Ni2+, K+, and Pb2+)

147

. This dye-MOF

complex exhibited enhanced sensitivity for hydrazine in an aqueous medium (e.g., LOD value of 0.012 ppm).

4.2.3. Biosensing and miscellaneous approaches for detection of non-OPs Similar to OPs, the majority of MOFs-based sensing studies for non-OPs have been made through electrochemical and luminescence detection approaches

116, 143, 147

. However, some authors

have also employed biosensing, adsorptive removal, or SERS approaches. Three representative case studies are described here to illustrate these approaches. In one recently reported study, a novel PEC biosensor based upon a GOx/CS/NH2-MIL125(Ti)/TiO2 (GOx = glucose oxidase; CS = chitosan) bionanocomposite was investigated for sensitive detection of the herbicide acetochlor in a glucose solution

153

. The as-prepared biosensor

showed a photoactive response in the presence of visible light by producing a stable photocurrent in a glucose solution

36, 49

. The magnitude of the photocurrent produced was highly dependent on the

amount of pesticide acetochlor added to the glucose solution. The PEC biosensor showed a linear response towards acetochlor in the concentration ranges from 0.02-1.0 nM and 10 to 200 nM. The LOD value was 0.003 nM, and the system showed stable photocurrent production over 10 days of study 153. These authors further utilized the PEC biosensor on vegetable and fruit samples to check the selectivity of the biosensor towards acetochlor detection 153. No interfering effect was observed



Page 34 of 71

in the presence of 1000-fold concentrations of potential interferences (e.g., citric acid, glycine, sucrose, Ca2+, Na+, and K+, ions). In addition, the biosensor performance remained unaffected by the addition of other pesticides including clethodim, cycloxydim, prometryn, and sethoxydim 22, 153. The study, therefore, demonstrated the exclusive response of the PEC biosensor to acetochlor in real world samples. The pesticide 2,4-dichlorophenol is a reactive intermediate formed during the synthesis of the herbicide 2,4-dichlorophenoxy acetic acid. Recently, the adsorptive removal performance of luminescent MOF [Cd(L)(TPOM)0.75]•xS (H2L = benzo-(1,2;4,5)-bis(thiophene-2'-carboxylic acid, TPOM = tetrakis(4-pyridyloxy-methylene) methane, S = uncoordinated solvent molecules) was tested to specifically remove 2,4-dichlorophenol 144. The removal efficiencies of this MOF against a list of pesticides (e.g., bisphenol A, 2,4-dichlorophenol, triclosan, carbofuran, carbaryl, and pirimicarb) were estimated to be 41.5, 77.5, 65.2, 7.3, 26.7, and 11.7%, respectively. Overall, the MOFs demonstrated outstanding absorptive removal of 2,4-dichlorophenol due to their sizeexclusion effect on the smaller 2,4-dichlorophenol 144. The use of the SERS method can offer highly sensitive and label free detection of target analytes with enhanced reproducibility

154-155

. Successful demonstration of the SERS approach depends on

the interaction and the distance between the NPs and target analytes

155

. The use of MOF

technology for SERS detection of an odorless neonicotinoid compound called acetamiprid was recently reported by 97. Herein, the impregnation of Au NPs was separately carried out with each of the three types of MOFs (e.g., MOF-199 (1), UiO-66 (2), and UiO-67 (3)) for preparing three SERS probes. Excellent SERS activity was demonstrated from these as-prepared composites (i.e., Au NPs/MOF-199, Au NPs/ Uio-66, and Au NPs/Uio-67) due to the localized surface plasmon


Page 35 of 71 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


resonance (LSPR) characteristics of Au NPs embedded in the MOF matrix. The sensing potential of Au NP/MOFs (as SERS probes) tested against acetamiprid was optimized in relation to several experimental variables (including the effects of the reducing concentrations of sodium citrate)

97

.

The LODs for the nanocomposites Au NPs/MOF-199, Au NPs/UiO-66, and Au NPs/UiO-67 at the characteristic peak of 632 cm-1 were 0.02, 0.009, and 0.02 mM, respectively. Each of these composites was an efficient SERS approach and provided enhanced, specific, and reproducible responses for pesticide sensing 97.

5. Performance comparison of MOFs and other sensors As discussed in the previous sections, the performance of MOFs as simple, sensitive, and quick sensors for the detection of different types of pesticides has been demonstrated (Table 2). MOFs can discriminately interact with pesticide molecules to generate detectable signals due to their acceptordonor electron transfer ability 6. However, some crucial factors (such as the integrity of the structural framework, high degree of porosity, large internal surface area, chemical and thermal stability, high selectivity, and toxicity) of the MOFs are detrimental for the practical application of MOFs for sensing purposes 19, 23, 58, 62, 156. In addition to MOFs, other advanced (either functionalized or non-functionalized) materials (e.g., CNTs, QDs, and MIPs) have also offered realistic and straightforward solutions for the sensing of a wide array of pesticides (Table 3)

30-31

. Along with other nanomaterials, MOFs can be used to

develop highly miniaturized sensors capable of different sensing approaches based on biological, optical, and electrochemical principles

26, 157

. The sensitivity of MOFs towards pesticides depends

highly on their structural features and the type of pesticide, while the conditions prevalent during



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sensing can also influence their performance. As a result, some other nanomaterials outperformed MOFs in this regard (Tables 2 and 3) 152, 158. For instance, CdTe QDs were able to detect parathion down to 0.0013 ppb, while the LOD of NMOF1 approached 1 ppb (Tables 2 and 3). These cases showed better performance than other NMs for the detection of pesticides (as compared to MOFs), which might be a consequence of different experimental conditions. Most NM-based pesticide sensors are heavily based on biosensing (Table 3) as opposed to MOF-based sensors, which are primarily based on luminescence quenching (Table 2). The complex interactions between the pesticide molecules and different sensor frameworks dictate the sensing capability, and hence biosensing-based approaches (such as immunosensing) might be a better choice under specific sensing conditions for a particular pesticide.

5.1. Electrochemical sensing approaches Electrochemical sensors have received widespread attention in recent years for various pollutants (Readers can refer to Section 3.1). High specificity and sensitivity are the primary attributes of these sensors that have attracted widespread attention. As explained earlier, most of the electrochemical sensing techniques for MOFs utilize the principles of biosensing to generate measurable signals. MOF-based electrochemical sensors have displayed superior performance for the detection of pesticides as compared to NM-based approaches (Tables 2 and 3). In terms of sensitivity (e.g., LODs), many MOFs (e.g., biphenyltetracarboxylic acid derived MOF 143

, amino-MIL-125(Ti)/TiO2

22

, [Cd(atc)(H2O)2]n

79

, NMOF-1

23

26

, Au-SH-SiO2@Cu-MOF

, and Cu3(BTC)2@SiO2

116

)

outperformed other nanomaterial-based sensors for the detection of different pesticides (OPs as well as non-OPs) in one respect or another. Among them, Cu3(BTC)2@SiO2 was the best performer for


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the sensing of atrazine, while [Cd(atc)(H2O)2]n was best suited for the sensing of parathion

79, 116

.

The apparent superiority of MOFs can be seen in terms of practical utility and sensing characteristics.

5.2. Luminescence sensing approaches Most MOF-based pesticide sensing approaches are based on the luminescent nature of the MOFs as explained in Section 2.3.1. As discussed earlier, MOFs undergo a change in their luminescence upon interacting with the pesticide molecules. This quenching of the luminescence can be easily exploited to detect pesticides. Tables 2 and 3 show that luminescence-based sensing is the primary pesticide detection mechanism for MOFs. On the contrary, this approach has rarely been applied for other NMs. Interestingly, the dominant mechanism for photoluminescence (PL) quenching is known to be governed by the interactions between the ligand molecules present in the structural framework of the MOFs and the guest pesticides 65. The nature of the ligands can thus result in vital differences in the sensing capabilities of the MOFs. For instance, MOF-5 was able to detect methyl parathion up to only 5 ppb, whereas NMOF-1 displayed a much improved LOD value of 1 ppb (Figure 6) 80, 115. The exact mechanism involved in the luminescence attenuation for both the MOFs are identical, i.e., the intra-ligand transfer of electrons was due to the intra-ligand emission excitation (photoinduced electron transfer), while the only difference is the nature of the ligand 65, 159. Among all the different MOFs employed for luminescence sensing, NMOF-1 displayed the lowest LOD value (1 ppb) for parathion, methyl parathion, paraoxon, and fenitrothion (Table 2). Both parathion and methyl parathion are –NO2-based aromatic compounds and are capable of high



Page 38 of 71

acceptor-donor electron transfer. As a result, the high electron-withdrawing ability of nitroaromatic OPs resulted in an on-off response for the MOF-based sensors 160. The obtained average quenching rate constants (Kqav) for NMOF-1 were either higher than or comparable to the typical diffusion controlled value of 1010 M-1 s-1 in the bulk solution 161. This peculiar observation indicates the high diffusion of the OP molecules towards the surface and deep into the structural framework of NMOF-1, resulting in its superior performance for sensing methyl parathion, parathion and the other previously mentioned pesticides 79-80, 161. In a recent case study, ratiometric fluorescent QDs outperformed MOFs with a detection limit of 0.018 ppb for methyl parathion 162. The lower LOD value of this QD may be explained by better PL quenching, which was observed to be a result of the hydrolysis of protamine by trypsin. The fluorescence can be coherently turned on by utilizing the electrostatic attraction between gold nanoparticles used in the sensor and protamine

162

. Also, methyl parathion inhibits the activity of

trypsin, resulting in the recovery of fluorescence, further adding to the efficiency of this sensor 162. However, more NM-based case studies focusing on luminescence sensing are required for a comparison with MOF-based pesticide sensors. The non-discriminating and direct chemosensing capacity of MOFs (e.g., NMOF-1 and MOF-5) towards OPs adds to their usefulness. In contrast, such target pesticide-specific reactions are not achievable using other NMs such as QDs

80, 162-163

.

This targeted specificity of MOFs is because their functional groups are tailorable and because of the host-guest interactions in the MOF skeleton, as explained in the previous sections.

5.3. Biosensing and miscellaneous approaches


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Recent advancements in biotechnology and microelectronics have encouraged the use of electrochemical biosensors for diverse applications such as the detection of bacteria, pesticides, ions, and gases

77, 164

(for more information, readers can refer to Section 3.3). Enzyme-based

electrochemical biosensing approaches have become prominent in the last decade due to their promising advantages such as easy handling and portability 77. As shown in Tables 2 and 3, biosensing has been the predominant mechanism for the detection of pesticides via NMs. In contrast, direct biosensing of pesticides via MOFs has rarely been investigated (Table 2). AChE inhibition has been commonly used to detect pesticides via CNTs, QDs, and MIPs

27, 162-163, 165

. A literature survey suggests that single walled carbon nanotubes self-

assembled and wrapped by thiol terminated single strand oligonucleotides on gold outperformed all other NMs for the biosensing of methyl parathion (Table 3) 166. An AChE-acetylcholine enzymatic reaction was the key step for this biosensor. The inhibition of enzyme reaction was exploited to detect methyl parathion

166

. Other CNTs and QDs also performed reasonably well for different

pesticides (Table 3). Interestingly, transition metal dichalcogenides (TMDs) provided a new opportunity for the development in the field of NM-based biosensors for pesticides 167-168. Because of enhanced surface area and electronic properties, exfoliated single (or multi-layered) TMDs can be efficiently exploited for biosensing applications

169-170

. Recently, a WS2-based TMD system exfoliated with

AChE and t-BuLi was used for the sensing of fenitrothion through the immobilization on glassy carbon electrode 29. The promising potential of TMD as biosensor for fenitrothion has been reported with a good linearity at LOD of 0.79 ppb 29. In pesticide biosensing (either for monitoring of food safety or for environmental protection), ZnO nanoparticles are also recognized as the promising option owing to their excellent enzyme mimicking and charge transfer capabilities


39, 171

. A


Page 40 of 71

Pt/ZnO/AChE/Chitosan bioelectrode showed good sensing capability for carbosulfan (LOD of 0.092 ppb) with great biocompatibility and conductivity for such application

39

. Also, a laccase-

immobilized liquid phase (i.e., Pt nanoparticles, montmorillonite, and an ionic liquid (1-butyl-3methylimidazolium tetrafluoroborate)) showcased efficient biosensing capabilities for methomyl in food samples

34

. An electrochemical displacement immunoassay in concert with oligonucleotide

sensing, when applied for coumaphos in food samples, was observed to record an exceptionally enhanced sensitivity (LOD of 0.18 ppt)

33

. These authors investigated guanine-rich single-strand

DNA label to enhance the binding efficiency of the antigen-antibody pair which in fact highlights great improvement in the area of food safety monitoring 33. Research and development of MOF-based biosensors for pesticides is imperative. Further research should draw inspiration from the advantages of these biosensors and develop advanced MOF-based biosensors with increased sensitivity and portability. Many nanomaterial-based pesticide sensing approaches adopt the electrochemical approach in combination with biosensing principles to involve enzymes, nucleic acids, or antibodies as the recognition elements 172-175 (Table 3). These elements can interact with the pesticide molecules to create measurable signals that can be quantified using electrical or optical sensing approaches 25, 60, 77, 162.

6. Challenges in MOF technology for pesticide sensing The sensing potential of MOFs for pesticide detection has been well recognized due to their superior physical and chemical properties. However, this technology must overcome certain challenges that limit their extensive practical use. To this end, the major critical issues include the stability of MOFs (as a function of water, temperature, moisture, and light), variations in diffusion


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rates of target molecules (e.g., from surface to bottom) in the structural framework, low PL quenching rate, a lack of proper understanding for mechanisms of sensing, nature, redox potential, and levels of targets, and chemical interference from matrices

65, 80, 151

. In this section, we will

highlight the major challenges associated with the scale-up of MOF-based pesticide sensing technology from laboratory scale to useful commercial devices. We will also discuss the possible strategies to overcome these challenges.

6.1 Stability of MOFs The detection capability of an MOF-based sensor for a target chemical is influenced by numerous physical and chemical parameters (e.g. temperature, pressure, pH, and moisture level) 176177

. The most notable limiting factor among these is the chemical instability of MOFs in aqueous

solutions. MOFs are most susceptible to hydrolysis at their nodes or metal ligand bonds, and hydrolysis results in protonated linkers and hydroxide metal nodes

176

. The chemical stability of

MOFs can be enhanced by using organic linkers with water repelling groups in their pores. These primarily include nitrogen-containing linkers such as 2-methyl imidazole (2-MI). Zeolitic imidazole frameworks (ZIFs) constructed using 2-MI as the linker component have outstanding stability in aqueous systems

178

. The other approaches to enhance the aqueous stability of MOFs include the

use of water shielding linkers, framework catenation, and incorporation of higher valency center metal ions

176

. The water shielding linkers exhibit highly non-polar characteristics and include

carboxylates (e.g., benzene dicarboxylate and its derivatives, BPDC and closely associated linkers) 179-180

and phosphonates 181.



Page 42 of 71

Thermal instability is another major limiting factor for producing MOFs that target specific applications. High temperatures may result in disruption of the nodes or metal-linker bonds 182, loss of the crystal structure of MOFs, dehydration of metal nodes

183

, or dehydrogenation of the linker

molecules 184. All these phenomena result in thermal degradation of the MOFs. Use of high valency metals (such as Zr(IV), Al(III))

183

, carboxylate or nitrogen containing linkers (178-179, framework

catenation, and different linker pendant groups may enhance the thermal stability of the MOFs. In contrast, high moisture content may catalyze hydrolytic reactions and may collapse MOF clusters 185

. MOF films must be mechanically stable during repetitive cycling of anions and cations in

electrochemical sensing applications. Thus, the use of stable radicals is highly desirable because of their conductive nature within MOF film structures 186. The sensitivities of MOFs are correlated to the types of metal ions and other functionalities. For example, peptide-based colorless crystals of [Zn(Gly-Thr)2]CH3OH via the reaction of zinc nitrate and Gly-Thr in a methanolic solution confirmed the selective adsorption of CO2 in preference to CH4

187

. Hence, the introduction of

suitable functionalities in MOF clusters may substantially improve these characteristics. Photo instability is another area of concern for producing stable LMOFs for sensitive PL detection of pesticides. A direct relationship between LOD values (for a specified MOF-based chemosensor) and PL quenching shows a strong interdependence between these two variables. Measurement of quenching of the optical intensity is a successful method employed for signal transduction for LMOFs

163, 188

. Hence, accurate measurements of PL quenching may significantly

enhance the precision of the analysis. Note that the PL quenching primarily depends on the migration of holes from the photoexcited MOF cluster to the targets. Hence, the extent of quenching is mainly governed by the redox potential of the targets. Considering the redox potentials of the


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targets, the adjustment of PL quenching rates may provide promising results in terms of achieving low LODs or higher sensitivities 19, 151.

6.2 Diffusion of pesticides Another big challenge in the sensing of pesticides through MOFs is the variation in diffusion rates of pesticides. As the sensing of target pesticides is directly related to their diffusion through the MOF structures, any factors that affect such diffusion can indirectly alter the rate of sensing. The variation in such diffusion can be minimized by adopting several approaches (e.g., systematic passivation of structural defects within MOF structures along with engineering optimum porosities, topologies, functionalities and internal surface area). Furthermore, using hypothesis-driven computational assessments (such as density functional theory and grand canonical Monte Carlo) of ideal and defect-containing versions of both known and non-synthesized MOF clusters may provide a deeper understanding of the mechanism of diffusion. These computational approaches help reduce the variations in the pesticide diffusion rate via tailoring the MOF framework 189.

7. Conclusions and future research This review outlines various MOF-based sensing approaches used to efficiently sense pesticides. Due to their advantageous structural and framework features (e.g., large specific area, tunable porosity and functional sites, customizable luminescent characteristics, and complex interactions with the guest species), MOFs are an ideal platform for the practical sensing of pesticides. The sensing properties of many different MOFs (such as NMOF-1, MOF-5, MIL-101, [Cd(atc)(H2O)2]n,



Page 44 of 71

and others) have been analyzed in terms of their luminescent, conductive, chromogenic, and optical behaviors. MOF-based sensing of pesticides is primarily dependent upon the intricate host-guest interactions. The type of sensing method adopted for signal transduction dictates the sensitivity of the MOF-based sensor. Extensive research on the framework and functional capability of MOFs has identified the principles required for the pre-processing of a MOF architectural framework; these include selecting suitable organic linkers and metallic centers to tailor the framework chemistry to provide appropriate host-guest interactions as explained in Section 2. Also, the selection of an appropriate synthesis route is necessary to provide a favorable porosity

146

and construct superior

MOFs with highly selective and efficient sensing abilities for a vast array of pesticides. Electrochemical sensing of pesticides via MOFs is a promising field with different chemical functionalities, and metallic ions play a dominant role in determining the sensitivity and selectivity of the sensor. This review also highlights a comparison between MOF-based sensors and other nanomaterial platforms such as CNTs, QDs, and MIPs for the effective sensing of pesticides. The majority of studies reveal that MOFs are efficient pesticide sensors, despite some specific cases showing the opposite conclusion, which may be due to differences in experimental conditions and specific interactions with surface functional groups. Considering all the observations, the crucial challenges associated with MOF-based pesticide sensing approaches include: the instability of MOFs (aqueous, thermal, moisture, light, and mechanical), diffusion rates of analyte molecules within the framework, rate of PL quenching, and various chemical interferences. These limitations can be diminished or eliminated by utilizing different advanced solutions such as the incorporation of framework catenation, anionic linkers, addition of higher valency metal sites, increasing the


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framework stability, improving conductivity within the MOF structure, and tailoring the porosity and functionalities of the MOFs. An active collaboration between different scientific disciplines may overcome the technical hurdles and improve the present understanding of the MOF-based pesticide sensors in terms of their characteristics, functionalities, and sensitivity. An integrated approach will provide rational and practical designs of MOF-based sensors that are field-deployable, cost effective, portable, robust, sensitive, and swift in nature. Such developments will aid in the advancement of MOF-based technologies in the field of environmental pollution control and allied areas of interest such as the sensing of other potentially hazardous materials such as explosives, heavy metals, and solvents.

Acknowledgements This study was supported by a grant from the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (No. 2016R1E1A1A01940995). This work was also carried out with the support of the "Cooperative Research Program for Agriculture Science and Technology Development (Project No. PJ012521032017)" Rural Development Administration, Republic of Korea. Deepak Kukkar acknowledges the support of Science and Engineering Research Board (SERB), Government of India, for providing financial assistance under the early carrier research program (No. YSS/2015/000212).



Page 46 of 71

References

(1) Chen, J.; Huang, Y.; Kannan, P.; Zhang, L.; Lin, Z.; Zhang, J.; Chen, T.; Guo, L. Flexible and Adhesive Surface Enhance Raman Scattering Active Tape for Rapid Detection of Pesticide Residues in Fruits and Vegetables. Analytical Chemistry 2016, 88 (4), 2149-2155, DOI: 10.1021/acs.analchem.5b03735. (2) Kesik, M.; Ekiz Kanik, F.; Turan, J.; Kolb, M.; Timur, S.; Bahadir, M.; Toppare, L. An acetylcholinesterase biosensor based on a conducting polymer using multiwalled carbon nanotubes for amperometric detection of organophosphorous pesticides. Sensors and Actuators B: Chemical 2014, 205, 39-49, DOI: https://doi.org/10.1016/j.snb.2014.08.058. (3) Kim, K.-H.; Kabir, E.; Jahan, S. A. Exposure to pesticides and the associated human health effects. Science of The Total Environment 2017, 575 (Supplement C), 525-535, DOI: https://doi.org/10.1016/j.scitotenv.2016.09.009. (4) Dinabandhu, B. Pesticides and Health Risks. Economic and Political Weekly 2000, 35 (38), 3381-3383. (5) Evenset, A.; Hallanger, I. G.; Tessmann, M.; Warner, N.; Ruus, A.; Borgå, K.; Gabrielsen, G. W.; Christensen, G.; Renaud, P. E. Seasonal variation in accumulation of persistent organic pollutants in an Arctic marine benthic food web. Science of The Total Environment 2016, 542 (Part A), 108-120, DOI: https://doi.org/10.1016/j.scitotenv.2015.10.092. (6) Kumar, P.; Kim, K.-H.; Deep, A. Recent advancements in sensing techniques based on functional materials for organophosphate pesticides. Biosensors and Bioelectronics 2015, 70 (Supplement C), 469-481, DOI: https://doi.org/10.1016/j.bios.2015.03.066. (7) Chang, P.-L.; Hsieh, M.-M.; Chiu, T.-C. Recent Advances in the Determination of Pesticides in Environmental Samples by Capillary Electrophoresis. International Journal of Environmental Research and Public Health 2016, 13 (4), 409. (8) El Rassi, Z. Capillary electrophoresis of pesticides. ELECTROPHORESIS 1997, 18 (12-13), 2465-2481, DOI: 10.1002/elps.1150181236. (9) Fernando, J. C.; Rogers, K. R.; Anis, N. A.; Valdes, J. J.; Thompson, R. G.; Eldefrawi, A. T.; Eldefrawi, M. E. Rapid detection of anticholinesterase insecticides by a reusable light addressable potentiometric biosensor. Journal of Agricultural and Food Chemistry 1993, 41 (3), 511-516, DOI: 10.1021/jf00027a031. (10) Ristori, C.; Del Carlo, C.; Martini, M.; Barbaro, A.; Ancarani, A. Potentiometric detection of pesticides in water samples. Analytica Chimica Acta 1996, 325 (3), 151-160, DOI: https://doi.org/10.1016/00032670(96)00023-2. (11) Zheng, Y.-H.; Hua, T.-C.; Sun, D.-W.; Xiao, J.-J.; Xu, F.; Wang, F.-F. Detection of dichlorvos residue by flow injection calorimetric biosensor based on immobilized chicken liver esterase. Journal of Food Engineering 2006, 74 (1), 24-29, DOI: https://doi.org/10.1016/j.jfoodeng.2005.02.009. (12) Singha, D. K.; Majee, P.; Mondal, S. K.; Mahata, P. Highly Selective Aqueous Phase Detection of Azinphos-Methyl Pesticide in ppb Level Using a Cage-Connected 3D MOF. ChemistrySelect 2017, 2 (20), 5760-5768, DOI: 10.1002/slct.201700963. (13) Hu, S.; Ouyang, W.; Guo, L.; Lin, Z.; Jiang, X.; Qiu, B.; Chen, G. Facile synthesis of Fe3O4/g-C3N4/HKUST1 composites as a novel biosensor platform for ochratoxin A. Biosensors & bioelectronics 2017, 92, 718723, DOI: 10.1016/j.bios.2016.10.006. (14) Kanda, S.; Yamashita, K.; Ohkawa, K. A Proton Conductive Coordination Polymer. I. [N,N′-Bis(2hydroxyethyl)dithiooxamido]copper(II). Bulletin of the Chemical Society of Japan 1979, 52 (11), 3296-3301, DOI: 10.1246/bcsj.52.3296.


Page 47 of 71 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


(15) Li, Q.; Xu, P.; Gao, W.; Ma, S.; Zhang, G.; Cao, R.; Cho, J.; Wang, H.-L.; Wu, G. Graphene/Graphene-Tube Nanocomposites Templated from Cage-Containing Metal-Organic Frameworks for Oxygen Reduction in Li– O2 Batteries. Advanced Materials 2014, 26 (9), 1378-1386, DOI: 10.1002/adma.201304218. (16) Wei, X.; Lin, W.; Ma, N.; Luo, F.; Lin, Z.; Guo, L.; Qiu, B.; Chen, G. Sensitive fluorescence biosensor for folate receptor based on terminal protection of small-molecule-linked DNA. Chemical communications (Cambridge, England) 2012, 48 (49), 6184-6, DOI: 10.1039/c2cc31979a. (17) Zhu, X.; Zheng, H.; Wei, X.; Lin, Z.; Guo, L.; Qiu, B.; Chen, G. Metal-organic framework (MOF): a novel sensing platform for biomolecules. Chemical Communications 2013, 49 (13), 1276-1278, DOI: 10.1039/C2CC36661D. (18) Jung, S.; Kim, Y.; Kim, S.-J.; Kwon, T.-H.; Huh, S.; Park, S. Bio-functionalization of metal-organic frameworks by covalent protein conjugation. Chemical Communications 2011, 47 (10), 2904-2906, DOI: 10.1039/C0CC03288C. (19) Kumar, P.; Deep, A.; Kim, K.-H. Metal organic frameworks for sensing applications. TrAC Trends in Analytical Chemistry 2015, 73 (Supplement C), 39-53, DOI: https://doi.org/10.1016/j.trac.2015.04.009. (20) Dyro, F. M. Organophosphates. http://emedicine.medscape.com/article/1175139-overview#a4%3E/ (accessed 10/01). (21) Eddleston, M.; Buckley, N. A.; Eyer, P.; Dawson, A. H. Management of acute organophosphorus pesticide poisoning. Lancet (London, England) 2008, 371 (9612), 597-607, DOI: 10.1016/s01406736(07)61202-1. (22) Jin, D.; Xu, Q.; Yu, L.; Hu, X. Photoelectrochemical detection of the herbicide clethodim by using the modified metal-organic framework amino-MIL-125(Ti)/TiO2. Microchimica Acta 2015, 182 (11), 1885-1892, DOI: 10.1007/s00604-015-1505-9. (23) Kumar, P.; Kim, K.-H.; Bansal, V.; Paul, A. K.; Deep, A. Practical utilization of nanocrystal metal organic framework biosensor for parathion specific recognition. Microchemical Journal 2016, 128 (Supplement C), 102-107, DOI: https://doi.org/10.1016/j.microc.2016.04.008. (24) Ma, J.; Yao, Z.; Hou, L.; Lu, W.; Yang, Q.; Li, J.; Chen, L. Metal organic frameworks (MOFs) for magnetic solid-phase extraction of pyrazole/pyrrole pesticides in environmental water samples followed by HPLCDAD determination. Talanta 2016, 161 (Supplement C), 686-692, DOI: https://doi.org/10.1016/j.talanta.2016.09.035. (25) Tao, C.-L.; Chen, B.; Liu, X.-G.; Zhou, L.-J.; Zhu, X.-L.; Cao, J.; Gu, Z.-G.; Zhao, Z.; Shen, L.; Tang, B. Z. A highly luminescent entangled metal-organic framework based on pyridine-substituted tetraphenylethene for efficient pesticide detection. Chemical Communications 2017, 53 (72), 9975-9978, DOI: 10.1039/C7CC05031C. (26) Wen, L.-L.; Wang, F.; Leng, X.-K.; Wang, C.-G.; Wang, L.-Y.; Gong, J.-M.; Li, D.-F. Efficient Detection of Organophosphate Pesticide Based on a Metal−Organic Framework Derived from Biphenyltetracarboxylic Acid. Crystal Growth & Design 2010, 10 (7), 2835-2838, DOI: 10.1021/cg1004352. (27) Aragay, G.; Pino, F.; Merkoçi, A. Nanomaterials for Sensing and Destroying Pesticides. Chemical reviews 2012, 112 (10), 5317-5338, DOI: 10.1021/cr300020c. (28) Blazkova, M.; Mickova-Holubova, B.; Rauch, P.; Fukal, L. Immunochromatographic colloidal carbonbased assay for detection of methiocarb in surface water. Biosensors & bioelectronics 2009, 25 (4), 753-8, DOI: 10.1016/j.bios.2009.08.023. (29) Nasir, M. Z. M.; Mayorga-Martinez, C. C.; Sofer, Z.; Pumera, M. Two-Dimensional 1T-Phase Transition Metal Dichalcogenides as Nanocarriers To Enhance and Stabilize Enzyme Activity for Electrochemical Pesticide Detection. ACS nano 2017, 11 (6), 5774-5784, DOI: 10.1021/acsnano.7b01364. (30) Ge, X.; Asiri, A. M.; Du, D.; Wen, W.; Wang, S.; Lin, Y. Nanomaterial-enhanced paper-based biosensors. TrAC Trends in Analytical Chemistry 2014, 58 (Supplement C), 31-39, DOI: https://doi.org/10.1016/j.trac.2014.03.008.



Page 48 of 71

(31) Wang, X.; Liu, D.; Li, W.; Xu, L.; Dong, Y. Study of laser bending of a preloaded Titanium alloy sheet. Manufacturing Rev. 2014, 1. (32) Xu, M.-L.; Liu, J.-B.; Lu, J. Determination and Control of Pesticide Residues in Beverages: A Review of Extraction Techniques, Chromatography, and Rapid Detection Methods. Applied Spectroscopy Reviews 2014, 49 (2), 97-120, DOI: 10.1080/05704928.2013.803978. (33) Dai, Z.; Liu, H.; Shen, Y.; Su, X.; Xu, Z.; Sun, Y.; Zou, X. Attomolar determination of coumaphos by electrochemical displacement immunoassay coupled with oligonucleotide sensing. Anal Chem 2012, 84 (19), 8157-63, DOI: 10.1021/ac301217s. (34) Zapp, E.; Brondani, D.; Vieira, I. C.; Scheeren, C. W.; Dupont, J.; Barbosa, A. M. J.; Ferreira, V. S. Biomonitoring of methomyl pesticide by laccase inhibition on sensor containing platinum nanoparticles in ionic liquid phase supported in montmorillonite. Sensors and Actuators B: Chemical 2011, 155 (1), 331-339, DOI: https://doi.org/10.1016/j.snb.2011.04.015. (35) Kumar, P.; Kim, K.-H.; Vellingiri, K.; Samaddar, P.; Kumar, P.; Deep, A.; Kumar, N. Hybrid porous thin films: Opportunities and challenges for sensing applications. Biosensors and Bioelectronics 2018, 104, 120137, DOI: https://doi.org/10.1016/j.bios.2018.01.006. (36) Nasalevich, M. A.; van der Veen, M.; Kapteijn, F.; Gascon, J. Metal-organic frameworks as heterogeneous photocatalysts: advantages and challenges. CrystEngComm 2014, 16 (23), 4919-4926, DOI: 10.1039/C4CE00032C. (37) Sun, L.; Campbell, M. G.; Dincă, M. Electrically Conductive Porous Metal–Organic Frameworks. Angewandte Chemie International Edition 2016, 55 (11), 3566-3579, DOI: 10.1002/anie.201506219. (38) Talin, A. A.; Centrone, A.; Ford, A. C.; Foster, M. E.; Stavila, V.; Haney, P.; Kinney, R. A.; Szalai, V.; El Gabaly, F.; Yoon, H. P.; Léonard, F.; Allendorf, M. D. Tunable Electrical Conductivity in Metal-Organic Framework Thin-Film Devices. Science 2014, 343 (6166), 66. (39) Nesakumar, N.; Sethuraman, S.; Krishnan, U. M.; Rayappan, J. B. Electrochemical acetylcholinesterase biosensor based on ZnO nanocuboids modified platinum electrode for the detection of carbosulfan in rice. Biosensors & bioelectronics 2016, 77, 1070-7, DOI: 10.1016/j.bios.2015.11.010. (40) Narayan, T. C.; Miyakai, T.; Seki, S.; Dincă, M. High Charge Mobility in a Tetrathiafulvalene-Based Microporous Metal–Organic Framework. Journal of the American Chemical Society 2012, 134 (31), 1293212935, DOI: 10.1021/ja3059827. (41) Hendon, C. H.; Tiana, D.; Walsh, A. Conductive metal-organic frameworks and networks: fact or fantasy? Physical Chemistry Chemical Physics 2012, 14 (38), 13120-13132, DOI: 10.1039/C2CP41099K. (42) Grosso, G.; Parravicini, G. P. Chapter 5 - Band Theory of Crystals. In Solid State Physics (Second Edition); Academic Press: Amsterdam, 2014; pp 179-241. (43) Stallinga, P. Electronic Transport in Organic Materials: Comparison of Band Theory with Percolation/(Variable Range) Hopping Theory. Advanced Materials 2011, 23 (30), 3356-3362, DOI: 10.1002/adma.201101129. (44) Shen, S.-L.; Ning, J.-Y.; Zhang, X.-F.; Miao, J.-Y.; Zhao, B.-X. Through-bond energy transfer-based ratiometric fluorescent probe for the imaging of HOCl in living cells. Sensors and Actuators B: Chemical 2017, 244 (Supplement C), 907-913, DOI: https://doi.org/10.1016/j.snb.2017.01.073. (45) Ciofini, I.; Le Bahers, T.; Adamo, C.; Odobel, F.; Jacquemin, D. Through-Space Charge Transfer in RodLike Molecules: Lessons from Theory. The Journal of Physical Chemistry C 2012, 116 (22), 11946-11955, DOI: 10.1021/jp3030667. (46) Lacroix, P. G.; Padilla-Martinez, I. I.; Lopez Sandoval, H.; Nakatani, K. Through space charge transfer and quadratic nonlinear optical (NLO) properties in alternated stacks of 2-amino-1,3-benzothiazoleethylcoumarin-3-carboxylate charge transfer complexes: from the molecular to the bulk NLO response. New Journal of Chemistry 2004, 28 (4), 542-547, DOI: 10.1039/B313294C.


Page 49 of 71 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


(47) Gassensmith, J. J.; Kim, J. Y.; Holcroft, J. M.; Farha, O. K.; Stoddart, J. F.; Hupp, J. T.; Jeong, N. C. A Metal–Organic Framework-Based Material for Electrochemical Sensing of Carbon Dioxide. Journal of the American Chemical Society 2014, 136 (23), 8277-8282, DOI: 10.1021/ja5006465. (48) Tomar, K.; Gupta, M.; Gupta, A. K. A novel 2D porous Cd(II) MOF with a (4,4) connected binodal network: Synthesis and photoluminescence sensing of small molecules. Inorganic Chemistry Communications 2016, 64, 16-18, DOI: https://doi.org/10.1016/j.inoche.2015.12.009. (49) Wang, S.; Shan, L.; Fan, Y.; Jia, J.; Xu, J.; Wang, L. Fabrication of Ln-MOFs with color-tunable photoluminescence and sensing for small molecules. Journal of Solid State Chemistry 2017, 245, 132-137, DOI: https://doi.org/10.1016/j.jssc.2016.10.006. (50) Assen, A. H.; Yassine, O.; Shekhah, O.; Eddaoudi, M.; Salama, K. N. MOFs for the Sensitive Detection of Ammonia: Deployment of fcu-MOF Thin Films as Effective Chemical Capacitive Sensors. ACS Sensors 2017, 2 (9), 1294-1301, DOI: 10.1021/acssensors.7b00304. (51) Li, W.; Wu, X.; Han, N.; Chen, J.; Qian, X.; Deng, Y.; Tang, W.; Chen, Y. MOF-derived hierarchical hollow ZnO nanocages with enhanced low-concentration VOCs gas-sensing performance. Sensors and Actuators B: Chemical 2016, 225 (Supplement C), 158-166, DOI: https://doi.org/10.1016/j.snb.2015.11.034. (52) Liu, X.-J.; Zhang, Y.-H.; Chang, Z.; Li, A.-L.; Tian, D.; Yao, Z.-Q.; Jia, Y.-Y.; Bu, X.-H. A Water-Stable Metal– Organic Framework with a Double-Helical Structure for Fluorescent Sensing. Inorganic Chemistry 2016, 55 (15), 7326-7328, DOI: 10.1021/acs.inorgchem.6b00935. (53) Zhao, S.-S.; Yang, J.; Liu, Y.-Y.; Ma, J.-F. Fluorescent Aromatic Tag-Functionalized MOFs for Highly Selective Sensing of Metal Ions and Small Organic Molecules. Inorganic Chemistry 2016, 55 (5), 2261-2273, DOI: 10.1021/acs.inorgchem.5b02666. (54) Wang, K.; Liu, T.; Liu, Y.; Tian, X.; Sun, J.; Zhang, Q. Fluorescent heterometallic MOFs: tunable framework charges and application for explosives detection. CrystEngComm 2016, 18 (42), 8301-8308, DOI: 10.1039/C6CE01818A. (55) Xu, H.; Liu, F.; Cui, Y.; Chen, B.; Qian, G. A luminescent nanoscale metal-organic framework for sensing of nitroaromatic explosives. Chemical Communications 2011, 47 (11), 3153-3155, DOI: 10.1039/C0CC05166G. (56) Kuppler, R. J.; Timmons, D. J.; Fang, Q.-R.; Li, J.-R.; Makal, T. A.; Young, M. D.; Yuan, D.; Zhao, D.; Zhuang, W.; Zhou, H.-C. Potential applications of metal-organic frameworks. Coordination Chemistry Reviews 2009, 253 (23), 3042-3066, DOI: https://doi.org/10.1016/j.ccr.2009.05.019. (57) Lee, J.; Farha, O. K.; Roberts, J.; Scheidt, K. A.; Nguyen, S. T.; Hupp, J. T. Metal-organic framework materials as catalysts. Chemical Society Reviews 2009, 38 (5), 1450-1459, DOI: 10.1039/B807080F. (58) Liu, B. Metal-organic framework-based devices: separation and sensors. Journal of Materials Chemistry 2012, 22 (20), 10094-10101, DOI: 10.1039/C2JM15827B. (59) Czaja, A. U.; Trukhan, N.; Muller, U. Industrial applications of metal-organic frameworks. Chemical Society Reviews 2009, 38 (5), 1284-1293, DOI: 10.1039/B804680H. (60) Hu, Z.; Deibert, B. J.; Li, J. Luminescent metal-organic frameworks for chemical sensing and explosive detection. Chemical Society Reviews 2014, 43 (16), 5815-5840, DOI: 10.1039/C4CS00010B. (61) Li, S.-L.; Xu, Q. Metal-organic frameworks as platforms for clean energy. Energy & Environmental Science 2013, 6 (6), 1656-1683, DOI: 10.1039/C3EE40507A. (62) Lei, J.; Qian, R.; Ling, P.; Cui, L.; Ju, H. Design and sensing applications of metal–organic framework composites. TrAC Trends in Analytical Chemistry 2014, 58 (Supplement C), 71-78, DOI: https://doi.org/10.1016/j.trac.2014.02.012. (63) Allendorf, M. D.; Bauer, C. A.; Bhakta, R. K.; Houk, R. J. T. Luminescent metal-organic frameworks. Chemical Society Reviews 2009, 38 (5), 1330-1352, DOI: 10.1039/B802352M.



Page 50 of 71

(64) Lustig, W. P.; Wang, F.; Teat, S. J.; Hu, Z.; Gong, Q.; Li, J. Chromophore-Based Luminescent Metal– Organic Frameworks as Lighting Phosphors. Inorganic Chemistry 2016, 55 (15), 7250-7256, DOI: 10.1021/acs.inorgchem.6b00897. (65) Cui, Y.; Yue, Y.; Qian, G.; Chen, B. Luminescent functional metal-organic frameworks. Chemical reviews 2012, 112 (2), 1126-62, DOI: 10.1021/cr200101d. (66) Binnemans, K. Lanthanide-Based Luminescent Hybrid Materials. Chemical reviews 2009, 109 (9), 42834374, DOI: 10.1021/cr8003983. (67) Bünzli, J.-C. G. Lanthanide Luminescence for Biomedical Analyses and Imaging. Chemical reviews 2010, 110 (5), 2729-2755, DOI: 10.1021/cr900362e. (68) Eliseeva, S. V.; Bunzli, J. C. Lanthanide luminescence for functional materials and bio-sciences. Chem Soc Rev 2010, 39 (1), 189-227, DOI: 10.1039/b905604c. (69) Moore, E. G.; Samuel, A. P. S.; Raymond, K. N. From Antenna to Assay: Lessons Learned in Lanthanide Luminescence. Accounts of chemical research 2009, 42 (4), 542-552, DOI: 10.1021/ar800211j. (70) Kumar, P.; Deep, A.; Kim, K.-H.; Brown, R. J. C. Coordination polymers: Opportunities and challenges for monitoring volatile organic compounds. Progress in Polymer Science 2015, 45 (Supplement C), 102-118, DOI: https://doi.org/10.1016/j.progpolymsci.2015.01.002. (71) Vargas-Bernal, R.; Rodríguez-Miranda, E.; Herrera-Pérez, G. Evolution and Expectations of Enzymatic Biosensors for Pesticides. In Pesticides - Advances in Chemical and Botanical Pesticides; Soundararajan, R. P., Ed.; InTech: Rijeka, 2012; p Ch. 14. (72) Yang, Y.; Liu, X.; Wu, M.; Wang, X.; Hou, T.; Li, F. Electrochemical biosensing strategy for highly sensitive pesticide assay based on mercury ion-mediated DNA conformational switch coupled with signal amplification by hybridization chain reaction. Sensors and Actuators B: Chemical 2016, 236 (Supplement C), 597-604, DOI: https://doi.org/10.1016/j.snb.2016.06.044. (73) Du, D.; Wang, J.; Wang, L.; Lu, D.; Smith, J. N.; Timchalk, C.; Lin, Y. Magnetic Electrochemical Sensing Platform for Biomonitoring of Exposure to Organophosphorus Pesticides and Nerve Agents Based on Simultaneous Measurement of Total Enzyme Amount and Enzyme Activity. Analytical Chemistry 2011, 83 (10), 3770-3777, DOI: 10.1021/ac200217d. (74) Khadem, M.; Faridbod, F.; Norouzi, P.; Foroushani, A. R.; Ganjali, M. R.; Shahtaheri, S. J. Biomimetic electrochemical sensor based on molecularly imprinted polymer for dicloran pesticide determination in biological and environmental samples. Journal of the Iranian Chemical Society 2016, 13 (11), 2077-2084, DOI: 10.1007/s13738-016-0925-8. (75) Zhu, C.; Yang, G.; Li, H.; Du, D.; Lin, Y. Electrochemical Sensors and Biosensors Based on Nanomaterials and Nanostructures. Analytical Chemistry 2015, 87 (1), 230-249, DOI: 10.1021/ac5039863. (76) Songa, E. A.; Okonkwo, J. O. Recent approaches to improving selectivity and sensitivity of enzymebased biosensors for organophosphorus pesticides: A review. Talanta 2016, 155 (Supplement C), 289-304, DOI: https://doi.org/10.1016/j.talanta.2016.04.046. (77) Sassolas, A.; Prieto-Sim¨®n, B.; Marty, J.-L. Biosensors for Pesticide Detection: New Trends. American Journal of Analytical Chemistry 2012, Vol.03No.03, 23, DOI: 10.4236/ajac.2012.33030. (78) Simonian, A. L.; Grimsley, J. K.; Flounders, A. W.; Schoeniger, J. S.; Cheng, T.-C.; DeFrank, J. J.; Wild, J. R. Enzyme-based biosensor for the direct detection of fluorine-containing organophosphates. Analytica Chimica Acta 2001, 442 (1), 15-23, DOI: https://doi.org/10.1016/S0003-2670(01)01131-X. (79) Deep, A.; Bhardwaj, S. K.; Paul, A. K.; Kim, K.-H.; Kumar, P. Surface assembly of nano-metal organic framework on amine functionalized indium tin oxide substrate for impedimetric sensing of parathion. Biosensors and Bioelectronics 2015, 65 (Supplement C), 226-231, DOI: https://doi.org/10.1016/j.bios.2014.10.045.


Page 51 of 71 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


(80) Kumar, P.; Paul, A. K.; Deep, A. A luminescent nanocrystal metal organic framework for chemosensing of nitro group containing organophosphate pesticides. Analytical Methods 2014, 6 (12), 4095-4101, DOI: 10.1039/C3AY42189A. (81) Warner, J.; Andreescu, S. An acetylcholinesterase (AChE) biosensor with enhanced solvent resistance based on chitosan for the detection of pesticides. Talanta 2016, 146 (Supplement C), 279-284, DOI: https://doi.org/10.1016/j.talanta.2015.08.030. (82) Zhang, W.; Asiri, A. M.; Liu, D.; Du, D.; Lin, Y. Nanomaterial-based biosensors for environmental and biological monitoring of organophosphorus pesticides and nerve agents. TrAC Trends in Analytical Chemistry 2014, 54 (Supplement C), 1-10, DOI: https://doi.org/10.1016/j.trac.2013.10.007. (83) Mulchandani, A.; Chen, W.; Mulchandani, P.; Wang, J.; Rogers, K. R. Biosensors for direct determination of organophosphate pesticides. Biosensors and Bioelectronics 2001, 16 (4), 225-230, DOI: https://doi.org/10.1016/S0956-5663(01)00126-9. (84) Mulchandani, A.; Mulchandani, P.; Kaneva, I.; Chen, W. Biosensor for Direct Determination of Organophosphate Nerve Agents Using Recombinant Escherichia coli with Surface-Expressed Organophosphorus Hydrolase. 1. Potentiometric Microbial Electrode. Analytical Chemistry 1998, 70 (19), 4140-4145, DOI: 10.1021/ac9805201. (85) Agarwal, P. K. Enzymes: An integrated view of structure, dynamics and function. Microbial Cell Factories 2006, 5 (1), 2, DOI: 10.1186/1475-2859-5-2. (86) Niu, B.; Huang, G.; Zheng, L.; Wang, X.; Chen, F.; Zhang, Y.; Huang, T. Prediction of Substrate-EnzymeProduct Interaction Based on Molecular Descriptors and Physicochemical Properties. BioMed Research International 2013, 2013, 7, DOI: 10.1155/2013/674215. (87) Robinson, P. K. Enzymes: principles and biotechnological applications. Essays in Biochemistry 2015, 59, 1-41, DOI: 10.1042/bse0590001. (88) Mehta, J.; Bhardwaj, N.; Bhardwaj, S. K.; Tuteja, S. K.; Vinayak, P.; Paul, A. K.; Kim, K.-H.; Deep, A. Graphene quantum dot modified screen printed immunosensor for the determination of parathion. Analytical Biochemistry 2017, 523 (Supplement C), 1-9, DOI: https://doi.org/10.1016/j.ab.2017.01.026. (89) Verma, N.; Bhardwaj, A. Biosensor Technology for Pesticides—A review. Applied Biochemistry and Biotechnology 2015, 175 (6), 3093-3119, DOI: 10.1007/s12010-015-1489-2. (90) Zhou, L.; Zhang, X.; Ma, L.; Gao, J.; Jiang, Y. Acetylcholinesterase/chitosan-transition metal carbides nanocomposites-based biosensor for the organophosphate pesticides detection. Biochemical Engineering Journal 2017, 128 (Supplement C), 243-249, DOI: https://doi.org/10.1016/j.bej.2017.10.008. (91) Dhull, V.; Gahlaut, A.; Dilbaghi, N.; Hooda, V. Acetylcholinesterase Biosensors for Electrochemical Detection of Organophosphorus Compounds: A Review. Biochemistry Research International 2013, 2013, 18, DOI: 10.1155/2013/731501. (92) Du, D.; Huang, X.; Cai, J.; Zhang, A. Amperometric detection of triazophos pesticide using acetylcholinesterase biosensor based on multiwall carbon nanotube–chitosan matrix. Sensors and Actuators B: Chemical 2007, 127 (2), 531-535, DOI: https://doi.org/10.1016/j.snb.2007.05.006. (93) Hammond, Jules L.; Formisano, N.; Estrela, P.; Carrara, S.; Tkac, J. Electrochemical biosensors and nanobiosensors. Essays in Biochemistry 2016, 60 (1), 69-80, DOI: 10.1042/EBC20150008. (94) Grieshaber, D.; MacKenzie, R.; Vörös, J.; Reimhult, E. Electrochemical Biosensors - Sensor Principles and Architectures. Sensors (Basel, Switzerland) 2008, 8 (3), 1400-1458. (95) Prakash, S.; Chakrabarty, T.; Singh, A. K.; Shahi, V. K. Polymer thin films embedded with metal nanoparticles for electrochemical biosensors applications. Biosensors and Bioelectronics 2013, 41 (Supplement C), 43-53, DOI: https://doi.org/10.1016/j.bios.2012.09.031. (96) Lawal, A. T. Synthesis and utilization of carbon nanotubes for fabrication of electrochemical biosensors. Materials Research Bulletin 2016, 73 (Supplement C), 308-350, DOI: https://doi.org/10.1016/j.materresbull.2015.08.037.



Page 52 of 71

(97) Cao, X.; Hong, S.; Jiang, Z.; She, Y.; Wang, S.; Zhang, C.; Li, H.; Jin, F.; Jin, M.; Wang, J. SERS-active metalorganic frameworks with embedded gold nanoparticles. Analyst 2017, 142 (14), 2640-2647, DOI: 10.1039/C7AN00534B. (98) Zhang, S.; Jiao, Z.; Yao, W. A simple solvothermal process for fabrication of a metal-organic framework with an iron oxide enclosure for the determination of organophosphorus pesticides in biological samples. Journal of Chromatography A 2014, 1371 (Supplement C), 74-81, DOI: https://doi.org/10.1016/j.chroma.2014.10.088. (99) Li, Y.; Liu, J.; Zhang, Y.; Gu, M.; Wang, D.; Dang, Y.-y.; Ye, B.-C.; Li, Y. A robust electrochemical sensing platform using carbon paste electrode modified with molecularly imprinted microsphere and its application on methyl parathion detection. Biosensors and Bioelectronics 2018, 106, 71-77, DOI: https://doi.org/10.1016/j.bios.2018.01.057. (100) Rawtani, D.; Khatri, N.; Tyagi, S.; Pandey, G. Nanotechnology-based recent approaches for sensing and remediation of pesticides. Journal of Environmental Management 2018, 206, 749-762, DOI: https://doi.org/10.1016/j.jenvman.2017.11.037. (101) Rostamnia, S.; Mohsenzad, F. Nanoarchitecturing of open metal site Cr-MOFs for oxodiperoxo molybdenum complexes [MoO(O2)2@En/MIL-100(Cr)] as promising and bifunctional catalyst for selective thioether oxidation. Molecular Catalysis 2018, 445, 12-20, DOI: https://doi.org/10.1016/j.mcat.2017.11.003. (102) Qian, J.; Li, Q.; Liang, L.; Li, T.-T.; Hu, Y.; Huang, S. A microporous MOF with open metal sites and Lewis basic sites for selective CO2 capture. Dalton Transactions 2017, 46 (41), 14102-14106, DOI: 10.1039/C7DT03255B. (103) Asadian, E.; Shahrokhian, S.; Iraji Zad, A. Highly sensitive nonenzymetic glucose sensing platform based on MOF-derived NiCo LDH nanosheets/graphene nanoribbons composite. Journal of Electroanalytical Chemistry 2018, 808, 114-123, DOI: https://doi.org/10.1016/j.jelechem.2017.10.060. (104) Kempahanumakkagari, S.; Vellingiri, K.; Deep, A.; Kwon, E. E.; Bolan, N.; Kim, K.-H. Metal–organic framework composites as electrocatalysts for electrochemical sensing applications. Coordination Chemistry Reviews 2018, 357, 105-129, DOI: https://doi.org/10.1016/j.ccr.2017.11.028. (105) Wei, W.; Dong, S.; Huang, G.; Xie, Q.; Huang, T. MOF-derived Fe2O3 nanoparticle embedded in porous carbon as electrode materials for two enzyme-based biosensors. Sensors and Actuators B: Chemical 2018, 260, 189-197, DOI: https://doi.org/10.1016/j.snb.2017.12.207. (106) Zhang, X.; Luo, J.; Tang, P.; Morante, J. R.; Arbiol, J.; Xu, C.; Li, Q.; Fransaer, J. Ultrasensitive binderfree glucose sensors based on the pyrolysis of in situ grown Cu MOF. Sensors and Actuators B: Chemical 2018, 254, 272-281, DOI: https://doi.org/10.1016/j.snb.2017.07.024. (107) Do, M. H.; Florea, A.; Farre, C.; Bonhomme, A.; Bessueille, F.; Vocanson, F.; Tran-Thi, N.-T.; JaffrezicRenault, N. Molecularly imprinted polymer-based electrochemical sensor for the sensitive detection of glyphosate herbicide. International Journal of Environmental Analytical Chemistry 2015, 95 (15), 14891501, DOI: 10.1080/03067319.2015.1114109. (108) Mazouz, Z.; Rahali, S.; Fourati, N.; Zerrouki, C.; Aloui, N.; Seydou, M.; Yaakoubi, N.; Chehimi, M. M.; Othmane, A.; Kalfat, R. Highly Selective Polypyrrole MIP-Based Gravimetric and Electrochemical Sensors for Picomolar Detection of Glyphosate. Sensors 2017, 17 (11), DOI: 10.3390/s17112586. (109) Zhang, C.; She, Y.; Li, T.; Zhao, F.; Jin, M.; Guo, Y.; Zheng, L.; Wang, S.; Jin, F.; Shao, H.; Liu, H.; Wang, J. A highly selective electrochemical sensor based on molecularly imprinted polypyrrole-modified gold electrode for the determination of glyphosate in cucumber and tap water. Analytical and Bioanalytical Chemistry 2017, 409 (30), 7133-7144, DOI: 10.1007/s00216-017-0671-5. (110) Yan, D.; Bazant, M. Z.; Biesheuvel, P. M.; Pugh, M. C.; Dawson, F. P. Theory of linear sweep voltammetry with diffuse charge: Unsupported electrolytes, thin films, and leaky membranes. Physical Review E 2017, 95 (3), 033303.


Page 53 of 71 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


(111) Hashemi, B.; Zohrabi, P.; Raza, N.; Kim, K.-H. Metal-organic frameworks as advanced sorbents for the extraction and determination of pollutants from environmental, biological, and food media. TrAC Trends in Analytical Chemistry 2017, 97, 65-82, DOI: https://doi.org/10.1016/j.trac.2017.08.015. (112) Kempahanumakkagari, S.; Kumar, V.; Samaddar, P.; Kumar, P.; Ramakrishnappa, T.; Kim, K.-H. Biomolecule-embedded metal-organic frameworks as an innovative sensing platform. Biotechnology Advances 2018, DOI: https://doi.org/10.1016/j.biotechadv.2018.01.014. (113) Zheng, X.; Zhou, L.; Huang, Y.; Wang, C.; Duan, J.; Wen, L.; Tian, Z.; Li, D. A series of metal-organic frameworks based on 5-(4-pyridyl)-isophthalic acid: selective sorption and fluorescence sensing. Journal of Materials Chemistry A 2014, 2 (31), 12413-12422, DOI: 10.1039/C4TA01900H. (114) Wang, G.-Y.; Song, C.; Kong, D.-M.; Ruan, W.-J.; Chang, Z.; Li, Y. Two luminescent metal-organic frameworks for the sensing of nitroaromatic explosives and DNA strands. Journal of Materials Chemistry A 2014, 2 (7), 2213-2220, DOI: 10.1039/C3TA14199C. (115) Kumar, P.; Paul, A. K.; Deep, A. Sensitive chemosensing of nitro group containing organophosphate pesticides with MOF-5. Microporous and Mesoporous Materials 2014, 195 (Supplement C), 60-66, DOI: https://doi.org/10.1016/j.micromeso.2014.04.017. (116) Bhardwaj, S. K.; Bhardwaj, N.; Mohanta, G. C.; Kumar, P.; Sharma, A. L.; Kim, K. H.; Deep, A. Immunosensing of Atrazine with Antibody-Functionalized Cu-MOF Conducting Thin Films. ACS Appl Mater Interfaces 2015, 7 (47), 26124-30, DOI: 10.1021/acsami.5b07692. (117) Wang, H.-S. Metal–organic frameworks for biosensing and bioimaging applications. Coordination Chemistry Reviews 2017, 349, 139-155, DOI: https://doi.org/10.1016/j.ccr.2017.08.015. (118) Tuerhong, M.; Xu, Y.; Yin, X.-B. Review on Carbon Dots and Their Applications. Chinese Journal of Analytical Chemistry 2017, 45 (1), 139-150, DOI: https://doi.org/10.1016/S1872-2040(16)60990-8. (119) Hua, X.; Eremin, S. A.; Liu, F.; Wang, M. Antibody Developments and Immunoassays for Organophosphorus Chemicals: A Review. Current Organic Chemistry 2017, 21 (26), 2640-2652, DOI: 10.2174/1385272821666170428122718. (120) Shahbaaz, M.; Kanchi, S.; Sabela, M.; Bisetty, K. Structural basis of pesticide detection by enzymatic biosensing: a molecular docking and MD simulation study. Journal of Biomolecular Structure and Dynamics 2017, 1-15, DOI: 10.1080/07391102.2017.1323673. (121) Stoytcheva, M.; Zlatev, R.; Montero, G.; Velkova, Z.; Gochev, V. A nanotechnological approach to biosensors sensitivity improvement: application to organophosphorus pesticides determination. Biotechnology & Biotechnological Equipment 2018, 32 (1), 213-220, DOI: 10.1080/13102818.2017.1389618. (122) Sun, J.; Yang, L.; Jiang, M.; shi, Y.; Xu, B.; Ma, H.-l. Stability and activity of immobilized trypsin on carboxymethyl chitosan-functionalized magnetic nanoparticles cross-linked with carbodiimide and glutaraldehyde. Journal of Chromatography B 2017, 1054, 57-63, DOI: https://doi.org/10.1016/j.jchromb.2017.04.016. (123) Lu, C.; Liu, W.-w.; Pan, H.; Kang Tay, B.; Wang, X.; Liang, K.; Wei, X. Mesoporous NiCo2O4 nanoneedles supported by 3D interconnected carbon network on Ni foam for electrochemical energy storage. Applied Surface Science 2018, DOI: https://doi.org/10.1016/j.apsusc.2017.12.212. (124) Tsai, M.-Y.; Creedon, N.; Brightbill, E.; Pavlidis, S.; Brown, B.; Gray, D. W.; Shields, N.; Sayers, R.; Mooney, M. H.; O'Riordan, A.; Vogel, E. M. Direct correlation between potentiometric and impedance biosensing of antibody-antigen interactions using an integrated system. Applied Physics Letters 2017, 111 (7), 073701, DOI: 10.1063/1.4986190. (125) Bandodkar, A. J.; Dhand, C.; Arya, S. K.; Pandey, M. K.; Malhotra, B. D. Nanostructured conducting polymer based reagentless capacitive immunosensor. Biomedical microdevices 2010, 12 (1), 63-70, DOI: 10.1007/s10544-009-9360-2.



Page 54 of 71

(126) Hassani, S.; Momtaz, S.; Vakhshiteh, F.; Maghsoudi, A. S.; Ganjali, M. R.; Norouzi, P.; Abdollahi, M. Biosensors and their applications in detection of organophosphorus pesticides in the environment. Archives of Toxicology 2017, 91 (1), 109-130, DOI: 10.1007/s00204-016-1875-8. (127) Wang, X.; Liu, Y.; Xu, C.; Guo, Q.; Hou, H.; Fan, Y. Series of Cd(II) Metal–Organic Frameworks Based on a Flexible Tripodal Ligand and Polycarboxylate Acids: Syntheses, Structures, and Photoluminescent Properties. Crystal Growth & Design 2012, 12 (5), 2435-2444, DOI: 10.1021/cg3000729. (128) Qian Tang, X.; Dan Zhang, Y.; Wei Jiang, Z.; Mei Wang, D.; Zhi Huang, C.; Fang Li, Y. Fe3O4 and metal– organic framework MIL-101(Fe) composites catalyze luminol chemiluminescence for sensitively sensing hydrogen peroxide and glucose. Talanta 2018, 179, 43-50, DOI: https://doi.org/10.1016/j.talanta.2017.10.049. (129) Karmakar, A.; Samanta, P.; Desai, A. V.; Ghosh, S. K. Guest-Responsive Metal-Organic Frameworks as Scaffolds for Separation and Sensing Applications. Acc Chem Res 2017, 50 (10), 2457-2469, DOI: 10.1021/acs.accounts.7b00151. (130) Yang, Q.; Wang, J.; Zhang, W.; Liu, F.; Yue, X.; Liu, Y.; Yang, M.; Li, Z.; Wang, J. Interface engineering of metal organic framework on graphene oxide with enhanced adsorption capacity for organophosphorus pesticide. Chemical Engineering Journal 2017, 313 (Supplement C), 19-26, DOI: https://doi.org/10.1016/j.cej.2016.12.041. (131) Chang, C.-H.; Yu, C.-J.; Du, J.-C.; Chiou, H.-C.; Chen, H.-C.; Yang, W.; Chung, M.-Y.; Chen, Y.-S.; Hwang, B.; Mao, I. F.; Chen, M.-L. The interactions among organophosphate pesticide exposure, oxidative stress, and genetic polymorphisms of dopamine receptor D4 increase the risk of attention deficit/hyperactivity disorder in children. Environmental Research 2018, 160, 339-346, DOI: https://doi.org/10.1016/j.envres.2017.10.011. (132) Sahub, C.; Tuntulani, T.; Nhujak, T.; Tomapatanaget, B. Effective biosensor based on graphene quantum dots via enzymatic reaction for directly photoluminescence detection of organophosphate pesticide. Sensors and Actuators B: Chemical 2018, 258, 88-97, DOI: https://doi.org/10.1016/j.snb.2017.11.072. (133) Pan, L.; Sun, J.; Li, Z.; Zhan, Y.; Xu, S.; Zhu, L. Organophosphate pesticide in agricultural soils from the Yangtze River Delta of China: concentration, distribution, and risk assessment. Environmental Science and Pollution Research 2018, 25 (1), 4-11, DOI: 10.1007/s11356-016-7664-3. (134) Towsif Abtab, S. M.; Alezi, D.; Bhatt, P. M.; Shkurenko, A.; Belmabkhout, Y.; Aggarwal, H.; Weseliński, Ł. J.; Alsadun, N.; Samin, U.; Hedhili, M. N.; Eddaoudi, M. Reticular Chemistry in Action: A Hydrolytically Stable MOF Capturing Twice Its Weight in Adsorbed Water. Chem 2018, 4 (1), 94-105, DOI: https://doi.org/10.1016/j.chempr.2017.11.005. (135) Vikrant, K.; Kumar, V.; Kim, K.-H.; Kukkar, D. Metal-organic frameworks (MOFs): potential and challenges for capture and abatement of ammonia. Journal of Materials Chemistry A 2017, 5 (44), 2287722896, DOI: 10.1039/C7TA07847A. (136) Hu, J.; Liu, Y.; Liu, J.; Gu, C.; Wu, D. High CO2 adsorption capacities in UiO type MOFs comprising heterocyclic ligand. Microporous and Mesoporous Materials 2018, 256, 25-31, DOI: https://doi.org/10.1016/j.micromeso.2017.07.051. (137) Zhu, X.; Li, B.; Yang, J.; Li, Y.; Zhao, W.; Shi, J.; Gu, J. Effective adsorption and enhanced removal of organophosphorus pesticides from aqueous solution by Zr-based MOFs of UiO-67. ACS Appl Mater Interfaces 2015, 7 (1), 223-31, DOI: 10.1021/am5059074. (138) Yang, Q.; Wang, Y.; Wang, J.; Liu, F.; Hu, N.; Pei, H.; Yang, W.; Li, Z.; Suo, Y.; Wang, J. High Effective Adsorption/Removal of Illegal Food Dyes from Contaminated Aqueous Solution by Zr-MOFs (UiO-67). Food Chemistry 2018, DOI: https://doi.org/10.1016/j.foodchem.2018.02.011.


Page 55 of 71 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


(139) Ma, J.; Guo, X.; Ying, Y.; Liu, D.; Zhong, C. Composite ultrafiltration membrane tailored by MOF@GO with highly improved water purification performance. Chemical Engineering Journal 2017, 313, 890-898, DOI: https://doi.org/10.1016/j.cej.2016.10.127. (140) Rodrigues, E. T.; Alpendurada, M. F.; Ramos, F.; Pardal, M. Â. Environmental and human health risk indicators for agricultural pesticides in estuaries. Ecotoxicology and Environmental Safety 2018, 150, 224231, DOI: https://doi.org/10.1016/j.ecoenv.2017.12.047. (141) Sun, G.; Li, Z.; Liu, T.; Chen, J.; Wu, T.; Feng, X. Rare earth elements in street dust and associated health risk in a municipal industrial base of central China. Environmental Geochemistry and Health 2017, 39 (6), 1469-1486, DOI: 10.1007/s10653-017-9982-x. (142) Yu, J.; Bian, Z.; Tian, X.; Zhang, J.; Zhang, R.; Zheng, H. Atrazine and its metabolites in surface and well waters in rural area and its human and ecotoxicological risk assessment of Henan province, China. Human and Ecological Risk Assessment: An International Journal 2018, 24 (1), 1-13, DOI: 10.1080/10807039.2017.1311768. (143) Hosseini, H.; Ahmar, H.; Dehghani, A.; Bagheri, A.; Fakhari, A. R.; Amini, M. M. Au-SH-SiO2 nanoparticles supported on metal-organic framework (Au-SH-SiO2@Cu-MOF) as a sensor for electrocatalytic oxidation and determination of hydrazine. Electrochimica Acta 2013, 88 (Supplement C), 301-309, DOI: https://doi.org/10.1016/j.electacta.2012.10.064. (144) Zhao, Y.; Xu, X.; Qiu, L.; Kang, X.; Wen, L.; Zhang, B. Metal-Organic Frameworks Constructed from a New Thiophene-Functionalized Dicarboxylate: Luminescence Sensing and Pesticide Removal. ACS Appl Mater Interfaces 2017, 9 (17), 15164-15175, DOI: 10.1021/acsami.6b11797. (145) Wang, Y.; Ge, S.; Zhang, L.; Yu, J.; Yan, M.; Huang, J. Visible photoelectrochemical sensing platform by in situ generated CdS quantum dots decorated branched-TiO2 nanorods equipped with Prussian blue electrochromic display. Biosensors and Bioelectronics 2017, 89, 859-865, DOI: https://doi.org/10.1016/j.bios.2016.09.106. (146) Vellingiri, K.; Kumar, P.; Kim, K.-H. Coordination polymers: Challenges and future scenarios for capture and degradation of volatile organic compounds. Nano Research 2016, 9 (11), 3181-3208, DOI: 10.1007/s12274-016-1230-7. (147) Helal, A.; Qamaruddin, M.; Aziz, M. A.; Shaikh, M. N.; Yamani, Z. H. MB-UiO-66-NH2 Metal-Organic Framework as Chromogenic and Fluorogenic Sensor for Hydrazine Hydrate in Aqueous Solution. ChemistrySelect 2017, 2 (25), 7630-7636, DOI: 10.1002/slct.201701230. (148) Schirmann, J.-P.; Bourdauducq, P. Hydrazine. In Ullmann's Encyclopedia of Industrial Chemistry; Wiley-VCH Verlag GmbH & Co. KGaA: 2000. (149) Xu, J.; Gao, J.; Liu, Y.; Li, Q.; Wang, L. Fabrication of In2O3/Co3O4-palygorskite composites by the pyrolysis of In/Co-MOFs for efficient degradation of methylene blue and tetracycline. Materials Research Bulletin 2017, 91, 1-8, DOI: https://doi.org/10.1016/j.materresbull.2017.03.018. (150) Engerer, S. C.; Cook, A. G. The Blue Bottle Reaction as a General Chemistry Experiment on Reaction Mechanisms. Journal of Chemical Education 1999, 76 (11), 1519, DOI: 10.1021/ed076p1519. (151) Scott, A. M.; Algar, W. R.; Stewart, M. H.; Trammell, S. A.; Blanco-Canosa, J. B.; Dawson, P. E.; Deschamps, J. R.; Goswami, R.; Oh, E.; Huston, A. L.; Medintz, I. L. Probing the Quenching of Quantum Dot Photoluminescence by Peptide-Labeled Ruthenium(II) Complexes. The Journal of Physical Chemistry C 2014, 118 (17), 9239-9250, DOI: 10.1021/jp501039w. (152) Wang, Y.; Zang, D.; Ge, S.; Ge, L.; Yu, J.; Yan, M. A novel microfluidic origami photoelectrochemical sensor based on CdTe quantum dots modified molecularly imprinted polymer and its highly selective detection of S-fenvalerate. Electrochimica Acta 2013, 107 (Supplement C), 147-154, DOI: https://doi.org/10.1016/j.electacta.2013.05.154.



Page 56 of 71

(153) Jin, D.; Gong, A.; Zhou, H. Visible-light-activated photoelectrochemical biosensor for the detection of the pesticide acetochlor in vegetables and fruit based on its inhibition of glucose oxidase. RSC Advances 2017, 7 (28), 17489-17496, DOI: 10.1039/C7RA00164A. (154) Li, D.; Ma, Y.; Duan, H.; Deng, W.; Li, D. Griess reaction-based paper strip for colorimetric/fluorescent/SERS triple sensing of nitrite. Biosensors and Bioelectronics 2018, 99, 389-398, DOI: https://doi.org/10.1016/j.bios.2017.08.008. (155) Tang, J.; Guo, H.; Zhao, M.; Liu, W.; Chou, X.; Zhang, B.; Xue, C.; Zhang, W.; Liu, J. Ag nanoparticles cladded with parylene for high-stability microfluidic surface-enhanced Raman scattering (SERS) biochemical sensing. Sensors and Actuators B: Chemical 2017, 242, 1171-1176, DOI: https://doi.org/10.1016/j.snb.2016.09.125. (156) Kumar, P.; Bansal, V.; Deep, A.; Kim, K.-H. Synthesis and energy applications of metal organic frameworks. Journal of Porous Materials 2015, 22 (2), 413-424, DOI: 10.1007/s10934-015-9910-3. (157) Barreto, A. S.; da Silva, R. L.; dos Santos Silva, S. C. G.; Rodrigues, M. O.; de Simone, C. A.; de Sá, G. F.; Júnior, S. A.; Navickiene, S.; de Mesquita, M. E. Potential of a metal–organic framework as a new material for solid-phase extraction of pesticides from lettuce (Lactuca sativa), with analysis by gas chromatographymass spectrometry. Journal of Separation Science 2010, 33 (23-24), 3811-3816, DOI: 10.1002/jssc.201000553. (158) Liang, H.; Song, D.; Gong, J. Signal-on electrochemiluminescence of biofunctional CdTe quantum dots for biosensing of organophosphate pesticides. Biosensors and Bioelectronics 2014, 53 (Supplement C), 363369, DOI: https://doi.org/10.1016/j.bios.2013.10.011. (159) Banerjee, D.; Hu, Z.; Li, J. Luminescent metal-organic frameworks as explosive sensors. Dalton Transactions 2014, 43 (28), 10668-10685, DOI: 10.1039/C4DT01196A. (160) Zhang, M.; Zhang, L.; Xiao, Z.; Zhang, Q.; Wang, R.; Dai, F.; Sun, D. Pentiptycene-Based Luminescent Cu (II) MOF Exhibiting Selective Gas Adsorption and Unprecedentedly High-Sensitivity Detection of Nitroaromatic Compounds (NACs). Scientific Reports 2016, 6, 20672, DOI: 10.1038/srep20672. (161) Cho, W.; Lee, H. J.; Oh, M. Growth-Controlled Formation of Porous Coordination Polymer Particles. Journal of the American Chemical Society 2008, 130 (50), 16943-16946, DOI: 10.1021/ja8039794. (162) Yan, X.; Li, H.; Han, X.; Su, X. A ratiometric fluorescent quantum dots based biosensor for organophosphorus pesticides detection by inner-filter effect. Biosensors and Bioelectronics 2015, 74 (Supplement C), 277-283, DOI: https://doi.org/10.1016/j.bios.2015.06.020. (163) Zheng, Z.; Zhou, Y.; Li, X.; Liu, S.; Tang, Z. Highly-sensitive organophosphorous pesticide biosensors based on nanostructured films of acetylcholinesterase and CdTe quantum dots. Biosensors and Bioelectronics 2011, 26 (6), 3081-3085, DOI: https://doi.org/10.1016/j.bios.2010.12.021. (164) Mehrotra, P. Biosensors and their applications – A review. Journal of Oral Biology and Craniofacial Research 2016, 6 (2), 153-159, DOI: 10.1016/j.jobcr.2015.12.002. (165) Marx, S.; Zaltsman, A.; Turyan, I.; Mandler, D. Parathion Sensor Based on Molecularly Imprinted Sol−Gel Films. Analytical Chemistry 2004, 76 (1), 120-126, DOI: 10.1021/ac034531s. (166) Viswanathan, S.; Radecka, H.; Radecki, J. Electrochemical biosensor for pesticides based on acetylcholinesterase immobilized on polyaniline deposited on vertically assembled carbon nanotubes wrapped with ssDNA. Biosensors and Bioelectronics 2009, 24 (9), 2772-2777, DOI: https://doi.org/10.1016/j.bios.2009.01.044. (167) Chhowalla, M.; Shin, H. S.; Eda, G.; Li, L.-J.; Loh, K. P.; Zhang, H. The chemistry of two-dimensional layered transition metal dichalcogenide nanosheets. Nature Chemistry 2013, 5, 263, DOI: 10.1038/nchem.1589. (168) Su, S.; Sun, H.; Cao, W.; Chao, J.; Peng, H.; Zuo, X.; Yuwen, L.; Fan, C.; Wang, L. Dual-Target Electrochemical Biosensing Based on DNA Structural Switching on Gold Nanoparticle-Decorated MoS2 Nanosheets. ACS Appl Mater Interfaces 2016, 8 (11), 6826-33, DOI: 10.1021/acsami.5b12833.


Page 57 of 71 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


(169) Chia, X.; Eng, A. Y.; Ambrosi, A.; Tan, S. M.; Pumera, M. Electrochemistry of Nanostructured Layered Transition-Metal Dichalcogenides. Chemical reviews 2015, 115 (21), 11941-66, DOI: 10.1021/acs.chemrev.5b00287. (170) Pumera, M.; Loo, A. H. Layered transition-metal dichalcogenides (MoS2 and WS2) for sensing and biosensing. TrAC Trends in Analytical Chemistry 2014, 61, 49-53, DOI: https://doi.org/10.1016/j.trac.2014.05.009. (171) Gumpu, M. B.; Nesakumar, N.; Sethuraman, S.; Krishnan, U. M.; Rayappan, J. B. B. Development of electrochemical biosensor with ceria–PANI core–shell nano-interface for the detection of histamine. Sensors and Actuators B: Chemical 2014, 199, 330-338, DOI: https://doi.org/10.1016/j.snb.2014.04.009. (172) Jayanthi, V. S. P. K. Sankara A.; Das, A. B.; Saxena, U. Recent advances in biosensor development for the detection of cancer biomarkers. Biosensors and Bioelectronics 2017, 91 (Supplement C), 15-23, DOI: https://doi.org/10.1016/j.bios.2016.12.014. (173) Liu, K.; Dong, H.; Deng, Y. Recent Advances on Rapid Detection of Pesticides Based on Enzyme Biosensor of Nanomaterials. Journal of Nanoscience and Nanotechnology 2016, 16 (7), 6648-6656, DOI: 10.1166/jnn.2016.11392. (174) Palchetti, I.; Mascini, M. Nucleic acid biosensors for environmental pollution monitoring. Analyst 2008, 133 (7), 846-854, DOI: 10.1039/B802920M. (175) Schlensog, M. D.; Gronewold, T. M. A.; Tewes, M.; Famulok, M.; Quandt, E. A Love-wave biosensor using nucleic acids as ligands. Sensors and Actuators B: Chemical 2004, 101 (3), 308-315, DOI: https://doi.org/10.1016/j.snb.2004.03.015. (176) Howarth, A. J.; Liu, Y.; Li, P.; Li, Z.; Wang, T. C.; Hupp, J. T.; Farha, O. K. Chemical, thermal and mechanical stabilities of metal–organic frameworks. 2016, 1, 15018, DOI: 10.1038/natrevmats.2015.18. (177) Yap, M. H.; Fow, K. L.; Chen, G. Z. Synthesis and applications of MOF-derived porous nanostructures. Green Energy & Environment 2017, 2 (3), 218-245, DOI: https://doi.org/10.1016/j.gee.2017.05.003. (178) Banerjee, R.; Furukawa, H.; Britt, D.; Knobler, C.; O’Keeffe, M.; Yaghi, O. M. Control of Pore Size and Functionality in Isoreticular Zeolitic Imidazolate Frameworks and their Carbon Dioxide Selective Capture Properties. Journal of the American Chemical Society 2009, 131 (11), 3875-3877, DOI: 10.1021/ja809459e. (179) Alezi, D.; Peedikakkal, A. M. P.; Weseliński, Ł. J.; Guillerm, V.; Belmabkhout, Y.; Cairns, A. J.; Chen, Z.; Wojtas, Ł.; Eddaoudi, M. Quest for Highly Connected Metal–Organic Framework Platforms: Rare-Earth Polynuclear Clusters Versatility Meets Net Topology Needs. Journal of the American Chemical Society 2015, 137 (16), 5421-5430, DOI: 10.1021/jacs.5b00450. (180) Liang, Y.-T.; Yang, G.-P.; Liu, B.; Yan, Y.-T.; Xi, Z.-P.; Wang, Y.-Y. Four super water-stable lanthanideorganic frameworks with active uncoordinated carboxylic and pyridyl groups for selective luminescence sensing of Fe3+. Dalton Transactions 2015, 44 (29), 13325-13330, DOI: 10.1039/C5DT01421B. (181) Ramaswamy, P.; Wong, N. E.; Shimizu, G. K. H. MOFs as proton conductors - challenges and opportunities. Chemical Society Reviews 2014, 43 (16), 5913-5932, DOI: 10.1039/C4CS00093E. (182) Bennett, T. D.; Goodwin, A. L.; Dove, M. T.; Keen, D. A.; Tucker, M. G.; Barney, E. R.; Soper, A. K.; Bithell, E. G.; Tan, J. C.; Cheetham, A. K. Structure and properties of an amorphous metal-organic framework. Physical review letters 2010, 104 (11), 115503, DOI: 10.1103/PhysRevLett.104.115503. (183) Valenzano, L.; Civalleri, B.; Chavan, S.; Bordiga, S.; Nilsen, M. H.; Jakobsen, S.; Lillerud, K. P.; Lamberti, C. Disclosing the Complex Structure of UiO-66 Metal Organic Framework: A Synergic Combination of Experiment and Theory. Chemistry of Materials 2011, 23 (7), 1700-1718, DOI: 10.1021/cm1022882. (184) Fujiwara, Y.-i.; Horike, S.; Kongpatpanich, K.; Sugiyama, T.; Tobori, N.; Nishihara, H.; Kitagawa, S. Control of pore distribution of porous carbons derived from Mg2+ porous coordination polymers. Inorganic Chemistry Frontiers 2015, 2 (5), 473-476, DOI: 10.1039/C5QI00019J.



Page 58 of 71

(185) Fernandez, C. A.; Nune, S. K.; Annapureddy, H. V.; Dang, L. X.; McGrail, B. P.; Zheng, F.; Polikarpov, E.; King, D. L.; Freeman, C.; Brooks, K. P. Hydrophobic and moisture-stable metal–organic frameworks. Dalton Transactions 2015, 44 (30), 13490-13497. (186) D'Alessandro, D. Exploiting redox activity in metal–organic frameworks: concepts, trends and perspectives. Chemical Communications 2016, 52 (58), 8957-8971. (187) Martí-Gastaldo, C.; Warren, J. E.; Stylianou, K. C.; Flack, N. L.; Rosseinsky, M. J. Enhanced Stability in Rigid Peptide-Based Porous Materials. Angewandte Chemie International Edition 2012, 51 (44), 1104411048. (188) Cui, Y.; Yue, Y.; Qian, G.; Chen, B. Luminescent functional metal–organic frameworks. Chemical reviews 2011, 112 (2), 1126-1162. (189) Coudert, F.-X.; Fuchs, A. H. Computational characterization and prediction of metal–organic framework properties. Coordination Chemistry Reviews 2016, 307, 211-236. (190) Kumar, P.; Kumar, P.; Deep, A.; Bharadwaj, L. Doped Zinc-Organic Framework for Sensing of Pesticide, 2012; Vol. 488-489. (191) Ghosh, P.; Saha, S. K.; Roychowdhury, A.; Banerjee, P. Recognition of an Explosive and Mutagenic Water Pollutant, 2,4,6-Trinitrophenol, by Cost-Effective Luminescent MOFs. European Journal of Inorganic Chemistry 2015, 2015 (17), 2851-2857, DOI: 10.1002/ejic.201500233. (192) Anirudhan, T. S.; Alexander, S. Design and fabrication of molecularly imprinted polymer-based potentiometric sensor from the surface modified multiwalled carbon nanotube for the determination of lindane (γ-hexachlorocyclohexane), an organochlorine pesticide. Biosensors and Bioelectronics 2015, 64 (Supplement C), 586-593, DOI: https://doi.org/10.1016/j.bios.2014.09.074. (193) Pardieu, E.; Cheap, H.; Vedrine, C.; Lazerges, M.; Lattach, Y.; Garnier, F.; Remita, S.; Pernelle, C. Molecularly imprinted conducting polymer based electrochemical sensor for detection of atrazine. Analytica Chimica Acta 2009, 649 (2), 236-245, DOI: https://doi.org/10.1016/j.aca.2009.07.029. (194) Prasad, K.; Prathish, K. P.; Gladis, J. M.; Naidu, G. R. K.; Rao, T. P. Molecularly imprinted polymer (biomimetic) based potentiometric sensor for atrazine. Sensors and Actuators B: Chemical 2007, 123 (1), 65-70, DOI: https://doi.org/10.1016/j.snb.2006.07.022. (195) Chen, Y.; Ren, H. L.; Liu, N.; Sai, N.; Liu, X.; Liu, Z.; Gao, Z.; Ning, B. A fluoroimmunoassay based on quantum dot-streptavidin conjugate for the detection of chlorpyrifos. J Agric Food Chem 2010, 58 (16), 8895-903, DOI: 10.1021/jf101778t. (196) Cummins, C. M.; Koivunen, M. E.; Stephanian, A.; Gee, S. J.; Hammock, B. D.; Kennedy, I. M. Application of europium(III) chelate-dyed nanoparticle labels in a competitive atrazine fluoroimmunoassay on an ITO waveguide. Biosensors & bioelectronics 2006, 21 (7), 1077-85, DOI: 10.1016/j.bios.2005.04.003. (197) Du, D.; Wang, M.; Cai, J.; Zhang, A. Sensitive acetylcholinesterase biosensor based on assembly of βcyclodextrins onto multiwall carbon nanotubes for detection of organophosphates pesticide. Sensors and Actuators B: Chemical 2010, 146 (1), 337-341, DOI: https://doi.org/10.1016/j.snb.2010.02.053. (198) Meng, X.; Wei, J.; Ren, X.; Ren, J.; Tang, F. A simple and sensitive fluorescence biosensor for detection of organophosphorus pesticides using H2O2-sensitive quantum dots/bi-enzyme. Biosensors and Bioelectronics 2013, 47 (Supplement C), 402-407, DOI: https://doi.org/10.1016/j.bios.2013.03.053. (199) Qu, Y.; Sun, Q.; Xiao, F.; Shi, G.; Jin, L. Layer-by-Layer self-assembled acetylcholinesterase/PAMAM-Au on CNTs modified electrode for sensing pesticides. Bioelectrochemistry 2010, 77 (2), 139-144, DOI: https://doi.org/10.1016/j.bioelechem.2009.08.001.


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Figures and Tables

Figure 1: (a) Prominent routes of pesticide exposure. (b) Health effects of pesticide exposure.


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Figure 2: Schematic diagram of various MOF-based approaches used for pesticide sensing.



Figure 3: A description of the electronic excited-state energy levels for lanthanide ions (Ln3+); reproduced with permission from 69.


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Figure 4: Stripping voltammograms with increasing MP concentrations (from bottom to top: 0, 0.01, 0.05, 0.1, 0.2, and 0.5 µg 3mL-1, respectively). The inset shows the calibration curve. SWV conditions: scanning potential range of -0.25 to 0.25 V, frequency of 25 Hz, potential increase of 4 mV, square-wave amplitude of 20 mV. The electrolyte was 0.1 M PBS, pH 5.7; reproduced with permission from 26.



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Figure 5: The PL intensity of [Zn(pbdc)(bimb).(H2O)]n MOFs as a function of parathion–methyl concentration in DMF. The inset shows the emission quenching linearity relationship of 4 below 5 x 10-5 M excited at 290 nm; reproduced with permission from 113.


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Figure 6: Effect of the addition of different concentrations of parathion on the PL intensity. (a) NMOF1; reproduced with permission from 80. (b) MOF-5; reproduced with permission from 115.


ACS Applied Materials & Interfaces 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47

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Table 1. Different types of commonly used pesticides. Order

Name

Chemical formula

CAS No.

MW (g/mole)

Type

[A] OPs 1

Azinphos-methyl

C10H12N3O3PS2

86-50-0

317.32

Organophosphate insecticide

2

Chlorpyrifos

C9H11Cl3NO3PS

2921-88-2

350.57


3

Diazinon

C12H21N2O3PS

333-41-5

304.34


4

Dichlorvos

C4H7Cl2O4P

62-73-7

220.98


5

Dimethoate

C5H12NO3PS2

60-51-5

229.26


6

Fenitrothion

C9H12NO5PS

122-14-5

277.23


7

Malathion

C10H19O6PS2

121-75-5

330.35


8

Methyl parathion

(CH3O)2P(S)OC6H4NO2

298-00-0

263.2


9

Paraoxon

C10H14NO6P

311-45-5

275.195

Insecticide

10

Parathion

C10H14NO5PS

56-38-2

291.26


11

Phosmet

C11H12NO4PS2

732-11-6

317.32


12

Triazofos

C12H16N3O3PS

24017-47-8

313.31


1


Cl2C6H2(NO2)NH2

99-30-9

207.01

Broad-spectrum pesticide

2

Atrazine

C8H14CIN5

1912-24-9

215.69

Herbicide

3

Carbofuran

C12H15NO3

1563-66-2

221.26

Carbamate pesticide

4

Chlorfenapyr

C15H11BrClF3N2O

122453-73-0

407.62

Pro-insecticide

5

Clethodim

C17H26ClNO3S

99129-21-2

359.909

Herbicide

6

Fenpyroximate

C24H27N3O4

134098-61-6

421.497

Pesticide

7

Fenvalerate

C25H22CINO3

51630-58-1

419.91

Insecticide

8

Fipronil

C12H4Cl2F6N4OS

120068-37-3

437.14

Insecticide

[B] Other pesticides

9

Flusilazole

C16H15F2N3Si

85509-19-9

315.399

Organosilicon fungicide

10

Hydrazine

N2H4

302-01-2

32.0452

Pesticide precursor

11

Lindane

C6H6Cl6

58-89-9

290.83

Organochlorine pesticide


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Table 2. Sensing applications of MOFs for pesticides. Order

Exact method/Principle

Target Pesticide

MOF

Name

Detection limit

Reference

Raw information

in ppb

[A] Electrochemical sensing 1

Electrochemical sensing

Methyl parathion

Biphenyltetracarboxylic acid derived MOF

0.006 µg/ml

6

26

2


Methyl parathion

Inorganic–Organic Hybrid SWNTs

2.3 ng ml-1

2.3

127

3


Hydrazine

Au-SH-SiO2@Cu-MOF

0.01 µM

0.32

143

4

PEC sensing

Clethodim

amino-MIL-125(Ti)/TiO2

10 nmol/L

3.6

22

5

Conductometric sensing

Parathion

ZIF-8

NA

NA

190

[B] Luminescence sensing 1

Chemosensing

Parathion

NMOF-1

1 ppb

1

80

2

Chemosensing

Parathion

MOF-5

5 ppb

5

115

3

Chemosensing

Methyl parathion

NMOF-1

1 ppb

1

80



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4

Chemosensing

Methyl parathion

MOF-5

5 ppb

5

115

5

Chemosensing

Paraoxon

NMOF-1

1 ppb

1

80

6

Chemosensing

Paraoxon

MOF-5

5 ppb

5

115

7

Chemosensing

Fenitrothion

NMOF-1

1 ppb

1

80

8

Chemosensing

Fenitrothion

MOF-5

5 ppb

5

115

9

Chemogenic/fluorogenic sensing

Hydrazine

MB-UiO-66-NH2

0.012 ppm

12

147

10

Luminescent sensing

Azinphos-methyl

[Cd2.5(PDA)(tz)3]

16 ppb

16

12

11

Luminescent sensing


[Zn2(bpdc)2(BPyTPE)]

0.13 ppm

130

25

12

Luminescent sensing

2,4,6-Trinitrophenol

Cd-NDC

4 x 10–6 M

916.4

191

13

Luminescent sensing

Methyl parathion

[Zn(pbdc)(bimb).(H2O)]n

2.5 x 10-6 M

658

113

1

Impedimetric immunosensing

Parathion

[Cd(atc)(H2O)2]n

0.1 ppb

0.1

79

2

Immunosensing

Parathion

NMOF-1

1 ppb

1

23

3

Immunosensing

Atrazine

Cu3(BTC)2@SiO2

0.01 nM

2.15 x 10-3

116

4

PEC-based biosensing

Acetochlor

GOx/CS/NH2-MIL-125(Ti)/TiO2 bionanocomposite

0.003 nM

81 x 10-3

153

[C] Biosensing

[D] Use of MOF as pretreatment media for conventional detection methods 1

Liquid phase extraction

Parathion

N[(La0.9Eu0.1)2(DPA)3(H2O)3]

0.02 - 0.05 mg/kg

20 - 50

157

2

HPLC-DAD

Fipronil

MIL-101

1.4 µg/L

1.4

24

3

HPLC-DAD

Chlorfenapyr

MIL-101

0.3 µg/L

0.3

24

4

HPLC-DAD

Flusilazole

MIL-101

1.5 µg/L

1.5

24

5

HPLC-DAD

Fenpyroximate

MIL-101

0.3 µg/L

0.3

24

6

ICP-AES

Glyphosate

UiO-67

537 mg g−1

537 x 106

137

7

ICP-AES

Glufosinate

UiO-67

360 mg g−1

36 x 107

137

8

UV-visible spectroscopy

Glyphosate

UiO-67/GO

482.69 mg g-1

48.3 x 107

153


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Table 3. Sensing applications of some nanomaterials for pesticides. Order

Exact method/Principle

Target Pesticide

Nanomaterial

Name

Detection limit Raw information

in ppb

[A] Electrochemical sensing

1


Parathion

MIP

0.005 µg/mL

5

2

Photoelectrochemical sensing

Fenvalerate

QD

3.2 x 10-9 mol/L

1.34

MIP

-10

3

Potentiometric sensing

Lindane

10

M

0.029

-7

4


Atrazine

MIP

10 M

21.56

5

Potentiometric sensing

Atrazine

MIP

0.1 ppm

100

1

Fluorescent sensing

Methyl parathion

QD

0.018 ng/mL

0.018

2

Fluorescent sensing

Chlorpyriphos

QD

11 nM

3.856

3

Fluorescent sensing

Atrazine

Polystyrene-Eu (III) chelate NP

0.4 nM

0.086

4

Fluorescent sensing

Methiocarb

Carbon NPs

0.6 nM

0.135

1

Amperometric biosensing

Triazofos

CNT

0.01 µM

3.13

2


Dimethoate

CNT

2 nM

0.45

CNT

-12

M

263.2 x 10-6

-12

M

350.6 x 10-6

[B] Luminescence sensing

[C] Biosensing

3

Electrochemical biosensing

Methyl parathion

10

4


Chlorpyrifos

CNT

10

5


Methyl parathion

QD

1 ng/mL


1


Page 70 of 71

6

Biosensing

Parathion

QD

4.47 x 10-12 M

1301.93 x 10-6

7

Biosensing

Paraoxon

QD

1.05 x 10-11 M

2889.54 x 10-6

8

Biosensing

Dichlorvos

QD

4.49 nM

0.99

9

Biosensing

Methyl parathion

QD

0.06 ng/mL

0.06

10


Carbofuran

CNT

4 x 10-9 M

0.88


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Graphic Abstract


(MOF)-based platform for sensing pesticides - ACS Publications

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