Nanosensing of Pesticides by Zinc Oxide Quantum ... - ACS Publications

Article pubs.acs.org/JAFC

Cite This: J. Agric. Food Chem. 2018, 66, 414−423

Nanosensing of Pesticides by Zinc Oxide Quantum Dot: An Optical and Electrochemical Approach for the Detection of Pesticides in Water Dibakar Sahoo,*,† Abhishek Mandal,‡ Tapas Mitra,† Kaushik Chakraborty,§ Munmun Bardhan,∥ and Anjan Kumar Dasgupta*,† †

Department of Biochemistry, University of Calcutta, Kolkata 700019, India ICAR-Indian Agricultural Research Institute, New Delhi 110012, India § Center for Research in NanoScience and NanoTechnology, University of Calcutta, Kolkata 700098, India ∥ Chemical Sciences Division, Saha Institute of Nuclear Physics, Kolkata 700064, India ‡

S Supporting Information *

ABSTRACT: Present study reveals the low concentrations (∼4 ppm) of pesticide sensing vis-à-vis degradation of pesticides with the help of nontoxic zinc oxide quantum dots (QD). In our study, we have taken four different pesticides viz., aldrin, tetradifon, glyphosate, and atrazine, which are widely used in agriculture and have structural dissimilarities/diversity. By using optical sensing techniques such as steady state and time-resolved fluorescence, we have analyzed the detailed exciton dynamics of QD in the presence of different pesticides. It has been found that the pesticide containing good leaving groups (−Cl) can interact with QD promptly and has high binding affinity (∼107 M−1). The different binding signatures of QD with different pesticides enable us to differentiate between the pesticides. Time resolved fluorescence spectroscopy provides significant variance (∼150−300 ns) for different pesticides. Furthermore, a large variation (105 Ω to 7 × 104 Ω) in the resistance of QD in the presence of different pesticides was revealed by electrochemical sensing technique. Moreover, during the interaction with pesticides, QD can also act as a photocatalyst to degrade pesticides. Present investigation explored the fact that the rate of degradation is positively affected by the binding affinity, i.e., the greater the binding, the greater is the degradation. What is more, both optical and electrochemical measurements of QD, in tandem, as described in our study could be utilized as the pattern recognition sensor for detection of several pesticides. KEYWORDS: quantum dots, sensor, fluorescence quenching, binding constants, pesticides, degradation, photocatalyst

1. INTRODUCTION Over the last 6 decades the pesticides have been used to control insects, bacteria, weeds, nematodes, rodents, pests, etc. Consistent usage of pesticides has contaminated the food chain through air, water, and soil posing serious damage to the human and animal health.1,2 Therefore, it becomes imperative for environmental scientists to detect these toxic elements in our ecosystem and it is also necessary to invent novel methods to biodegrade or catalyze hazardous as well as toxic pesticidal waste into harmless, nonhazardous metabolites/compounds so that the former may no longer linger as a threat to the environment. Many techniques like high-performance liquid chromatography (HPLC),3 gas chromatography-mass spectroscopy (GC-MS), liquid chromatography-mass spectroscopy (LC-MS), enzyme-linked immunosorbent assays (ELISAs),4 and also tandem techniques like LC-MS/MS, GC-MS/MS have been used for effective detection of pesticides in food, water, etc. in past years. These methods are costly, rely upon sophisticated instruments and skilled manpower, which is why there is a need for newer strategies and de novo techniques, which are fast, reliable, practically economical, analytical and highly sensitive, as well as selective for their detection. Recently sensor based optical and electrochemical techniques are emerging as a promising alternative on this regard due to their rapidity, specificity, and ease for mass fabrication and field applicability.1,5 © 2017 American Chemical Society

Nowadays, the luminescence of semiconductor quantum dots (QDs) has attracted considerable attention of the researchers due to their unique optical properties that are different from their bulk structure components.5a,6,7 QDs are widely used as sensor for medical,8 biological,9 and environmental applications.10 In our study we have extended the use of QDs for the detection of pesticides as well as degradation of pesticides. In our study we have used ZnO QDs for their unique electrical and optical properties.11−13 Among all the techniques for preparing ZnO QD the sol−gel technique at room temperature is the best choice to obtain ZnO QD with highly visible emission because the resulting samples are small enough and contain lots of defects.14 In our investigation in order to prevent ZnO QD from undergoing spontaneous growth and aggregation, we have employed shells like coating with 3-amminopropyltrimethoxysilane (APTES) containing SiO2. As the siloxane has the ability to form the covalent bond with metal oxide surface these molecules are found to create the shielding barrier11b15 that protect the QD at core and stabilize ZnO QD from decomposition in water. Received: Revised: Accepted: Published: 414

September 8, 2017 November 28, 2017 December 14, 2017 December 14, 2017 DOI: 10.1021/acs.jafc.7b04188 J. Agric. Food Chem. 2018, 66, 414−423

Article

Journal of Agricultural and Food Chemistry Scheme 1. Structure of Different Pesticides We Have Used for Study

1710 X-ray diffractometer, equipped with copper Kα radiation (generator voltage, 40 kV; tube current, 20 mA) as the X-ray source in the 2θ range of 3−70°. FTIR Methodology. Infrared absorbance spectra of ZnO quantum dots were recorded on Bruker ALPHA, FTIR system (typically 24 scans; resolution, 4 cm−1) at wave numbers from 400 to 4000 cm−1. Samples were mixed with KBr and ground to a fine power to prepare a KBr pellet containing 0.1% of ZnO QDs. 2.4. Particle Size and Stability Measurement. The diameter of the APTES capped QDs has been determined by TEM (JEOL JEM 2100 HR with EELS TEM (JEOL, Japan) operated at 200 kV) and dynamic light scattering method and the zeta potential of the same materials has been determined by electrophoretic light scattering using a DLS instrument (Malvern Nano-ZS, ZEN 3600). For particle size and zeta potential measurement, sample volumes taken were 40 μL and 1 mL, respectively. 2.5. Steady State Measurement. For measuring absorption and fluorescence spectra, deionized water (Millipore) was used. The absorption spectra at 300 K were recorded with a Shimadzu spectrophotometer (model UV-2104 PC), and emission spectra were obtained with a Hitachi F-7000 fluorescence spectrophotometer. All the experiments were done in aqueous solution. During the experiment, the concentration of QD (5 × 10−5 M) kept constant for all time. The concentration of pesticides for all the experiments are given in the figure caption. After addition of pesticides with QDs, we constantly vortex shake it for 1 min followed by the steady state measurements. The equilibration time of 1 min is enough for the system to attain equilibrium because emission spectra remain unchanged after 1 min, validated by several times discrete scanning of each system. Measurement of Quantum Yield. The following equation was employed to measure the quantum yield of QD and the QD−pesticide complex using Rodamine 6G (ΦR = 0.95 in water)19 as the reference.

The pesticides that were used for detection in the study are (1) aldrin, (2) glyphosate, (3) tetradifon, and (4) atrazine (Scheme 1).16 Here in our study we have used four pesticides which are widely/popularly used and structurally dissimilar to each other except for aldrin, which is an organochlorine insecticide that was widely used until 1999, when it was banned in most countries. Before the ban, it was heavily used as a pesticide to treat seed and soil. To date there are several reports available for the detection of different pesticides using different materials.17 However, only a few reports were found to discuss using metal oxide quantum dots as a sensor for pesticides. Here for the first-time interaction dynamics of QDs with pesticides has been carefully analyzed by steady state, time-resolved fluorescence spectroscopy as well as electrochemical methods via resistance. We have elucidated the effect of exciton quenching of QD in the presence of different pesticides. Beyond sensing, unique surface area and the surface activity of our ZnO QD make them desirable candidates in the catalytic reactions which further degraded pesticides into harmless and useful components. In addition, understanding the fundamental mechanism of excited state processes of QD in the presence of pesticides will also have direct applications in agriculture and the environment.

2. MATERIALS AND METHODS 2.1. Chemicals. Analytical grade tetradifon [purity, 98%; octanol− water partition coefficient (Pow), 4.61; water solubility, (10 °C) 0.05%, (20 °C) 0.08%, (50 °C) 0.34% at pH 7; GUS potential, 4.10; DT50, 0.33 years]; atrazine [purity, 98.9%; Pow, 2.82; water solubility, 33 mg L−1 at pH 7; GUS potential, 3.75; DT50, 14−109 days]; aldrin [purity, 98%; octanol−water partition coefficient (Pow), 6.50; water solubility, 0.027 mg L−1 (20−25 °C); GUS potential, −0.35; DT50, 5−10 years]; and glyphosate [purity, 98.9%; octanol−water partition coefficient (Pow), 3.2; water solubility, 157 000 mg L−1 (20−25 °C, pH 7); GUS potential, −0.69; DT50, 12−91 days] were purchased from the SigmaAldrich, India. Solvents used were purchased locally and were of HPLC grade. 2.2. Preparation of QDs. Preparation of APTES capped ZnO QDs is a two-step procedure as of previously reported literature.18 First 0.1 M zinc acetate solution of methanol and 1 M KOH solution in methanol were prepared separately. At room temperature KOH solution was added to zinc acetate solution dropwise with constant stirring. The resulting solution was homogenized by stirring continuously for 1 h with a magnetic stirrer. The solution thus obtained was found to show yellow luminescence under UV excitation, thereby indicating formation of ZnO particles. At this stage, 0.25 mL of 3-aminopropyl triethoxysilane (APTES) solution was added into the ZnO solution to control particle growth. Immediately after this, 0.5 mL of distilled water was injected to the colloidal solution for mild sol−gel reaction of silica on particle surfaces. The as-prepared colloid was separated by centrifuging and washed several times by methanol followed by distilled water to remove unreacted molecules. Finally, the as-obtained colloid was dispersed in water medium. The schematic representation of ZnO QD synthesis is given in Scheme S1. The aqueous dispersions of colloids thus obtained were characterized for their structural, microscopic, and optical properties. 2.3. Methodology to Characterize QDs. XRD Methodology. X-ray diffraction (XRD) analyses were carried out using a Philips PW

Φ = ΦR

I ODR n2 IR OD nR 2

(1)

where Φ is fluorescence quantum yield, I is the integrated fluorescence intensity, n is the refractive index of solvent, and OD is optical density (absorption). The subscript R refers to reference fluorophore of known quantum yield. 2.6. Time-Resolved Measurements. For time-resolved fluorescence measurements, the samples were excited at 336 nm using a picosecond diode (IBH Nanoled- 07). The emission was collected at a magic angle polarization using a Hamamatsu MCP photomultiplier (2809U). The time correlated single-photon counting (TCSPC) set up consists of an ortec 9327 CFD and a Tennelec TC 863 TAC. The data are collected with a PCA3 card (Oxford) as a multichannel analyzer. The typical fwhm of the system response is about 25 ps. The channel width is 12 ps per channel. The fluorescence decays were deconvoluted using IBH DAS6 software. The concentration of pesticides during TCSPC measurements kept same as the steady state measurements, and for pesticides we take the highest concentrations only which were used in steady state measurements. 2.7. Electrochemical Measurement. We measure the resistance of different pesticides with our instrument using ARM based open hardware board and DropSens Platinum Inter Digitated Electrode (IDE). We have used a cell containing 2 mL sample in a cuvette and IDE is used as an electrode of the cell. According to the Scheme S2, we assume that the resistance of cell is R1. In the system, we have used a known resister with resistance R Ω. To measure the voltage V1 across R1, we have used open hardware device. 415

DOI: 10.1021/acs.jafc.7b04188 J. Agric. Food Chem. 2018, 66, 414−423

Article

Journal of Agricultural and Food Chemistry We have measured the resistance of the cell using the following expression: V1 = V

R1 (R + R1)

⇒R1 = R

V1 (V − V1)

spectra and the UV-absorption spectra of ZnO QD was shown in Figure 1b. The maximum absorption peak is at 337 nm. In order to investigate the size, shape, and stability of QD, we used DLS, zeta potential, and TEM. The DLS study shows that the hydrodynamic radius of capped QD is −40 nm and zeta potential is −16 mV, which is good for stability (Supporting Information Figure S2). The TEM images shows that the average size of the QD is 5 nm (Supporting Information Figure S2). Also the histogram plot of TEM image indicates that there is no aggregation at all. The good Gaussian fit and peak at 5 nm suggests uniformity of the particle size. Also the fluorescence of this particles proves it as QDs. 3.2. Fluorescence Quenching Spectroscopy. In our study we have excited the QD solution at 340 nm and got a broad emission spectrum having peak maximum at 525 nm Figure 1b. The broad emission peak of QDs, which is intrinsic is nature, is dominated by the excitonic transition at the surface of QD and defect-mediated origin of green fluorescence.21 Van Dijiken et al. claimed that the visible emission is due to recombination of electron from conduction band with deep trap electron center of V0+2. On the other hand Van heusden et al. proposed that the recombination of isolated V0+ centers with the photoexcited holes are responsible for green emission. So the broad emission peak can be decomposed in two components. One is centered at 555 nm (2.2 eV) while is another is at 500 nm (2.5 eV). It is already reported that the emission around 555 nm occurs from the defects states near the surface layer whereas the shorter wavelength at 500 nm originates from defects near bulk of QD.21b The intrinsic fluorescence of QD (peak at 525 nm) is very much sensitive to different pesticides environments, namely, aldrin, tetradifon, glyphosate, and atrazine. After gradual introduction of different pesticides, the fluorescence of QD got quenched gradually without having any shift (Figure 2). Interestingly this quenching phenomena is different for different pesticides. Therefore, the measurement of intrinsic fluorescence of QD in the presence of pesticides can add valuable information regarding the sensing property of QD for pesticides. Quenching of fluorescence are of two types: dynamic and static quenching. Static quenching is involved in ground state complex formation between fluorophore and quencher, and this complex isnonfluorescent. The dynamic quenching is resulted from collisional encounters between the excited-state fluorophore and the quencher.22 Here to clarify the quenching mechanism between QD and pesticides, we have used the Stern−Volmer (S−V) equation (eq 5).23

(2)

(3)

To get the conductivity, we have used the relationship

G = 1/R1 where G is the measured conductance of cell. In this experiment, we have logged the conductance data using Arduino due to open hardware platform. Data has been collected in one sample/second over 90 s, with 16 bit precession resolution ADC. We have used a 29.1 KΩ resister as R and 3.3 V Source as V. The whole set up for measuring the conductance is shown in Scheme S2d.

3. RESULTS AND DISCUSSION 3.1. Characterization of Synthesized ZnO QD. The ZnO QDs crystallinity was confirmed by XRD analysis (Supporting Information Figure S1a). In the XRD spectrum of dry ZnO QDs, broad peaks are observed at 31.8 (001), 34.48 (002), 36.4 (101), 47.65 (102), 56.66 (110), 62.85 (103), and 67.86 (112), respectively. The XRD pattern fits well with a wurtzite structure. The average crystal (diameter), evaluated by the Scherrer equation:20 d=

kλ β cos θ

(4)

where k is a structural constant, λ is the wavelength of the X-ray, d is the size of the QD, β is full width at half-maximum, and θ is the Bragg angle. For the calculation of the size of QDs, we used the signal of the (102) where there is no overlap of the consequent spectrum with 2θ = 47.65° and the diameter was found to be equal to 6 nm. For the detection of the capping state of APTES molecules on ZnO QDs, FT-IR spectra have been carried out (Supporting Information Figure S1b). N−H stretching vibration of primary amines on the outer surface of the QDs corresponds to the signals at 3431 and 1599.5 cm−1. The peak at 2930 cm−1 is due to the asymmetric stretching vibration of C−H bond and the presence of Si−O−Si groups (polymerization of APTES 10 molecules) was confirmed by the peak at 1110 cm−1. The peak at1380 cm−1 is attributed to C−H bonds vibration while the peak at 1010 cm−1 is due to the presence of C−N bonds. The peak at 669 cm−1 is to in plane bending of C−C−C groups, and the signal at ∼400 cm−1 is due the Zn−O bond.20 The synthesized APTES capped ZnO QD solution exhibited a yellowish color under UV radiation, which was known as the signature of ZnO QD Figure 1a. The fluorescence emission

F0/F = 1 + KSV[Q] = τ0/τ

(5)

KSV = kqτ0

(6)

where F0 denotes the steady-state fluorescence intensity of QD, F is the steady state fluorescence intensity of QD in the presence of different concentration of pesticides; KSV is the Stern−Volmer quenching constant for QD; [Q] is the concentration of pesticides; kq is the quenching rate constant of QD; τ0 is the average fluorescence lifetime QD without pesticides; and τ is the average lifetime of QD in the presence of pesticides. Depending on the nature of the S−V plot we can determine the nature of quenching. If the S−V plot is linear, then only one kind of quenching mechanism is involved, i.e., only dynamic or only static. However, if the plot shows an upward or downward curvature, then both types of quenching processes are involved. Here the S−V plots are found linear in nature for all pesticides with good fitting linearity R > 0.99

Figure 1. (a) Luminescence of ZnO QD under UV radiation and (b) absorption of ZNO QD (inset) and emission of QD excite @ 340. 416


Article

Journal of Agricultural and Food Chemistry

Figure 2. Emission spectra (λex = 340 nm) of ZnO QD (5 × 10−5 M) in the presence of different pesticides (a) glyphosate, (b) atrazine, (c) aldrin, and (d) tetradifon.

Figure 3. Stern−Volmer (SV) plot from steady-state fluorescence emission intensity measurements of ZnO QD in the presence of different pesticides at 300 K. 417


Article


of aldrin are accessible by QDs, whereas for the other pesticides, 2 sites of each can be reacted by QDs. The variation in quenching constants, binding constants, and stoichiometry ratio for different pesticides can be explained by taking into account the structural variation of pesticides. The structures of the pesticides are shown in Scheme 1. Among all the target pesticides, aldrin and tetradifon have a number of good leaving groups (−Cl). The APTES capped ZnO QDs contain a number of free primary amine groups which take part in the interaction between QD and pesticides. The Cl¯ ions of aldrin are replaced by the primary amine group of QDs through a nucleophilic substitution reaction (Scheme 2). In aldrin, there are 6 Cl¯ ions which act as leaving groups for the above said substitution reaction. Existence of many leaving group compels aldrin to bind stronger with APTES capped QD, and this also reflects from our experimental data showing strong binding constant for aldrin in Table 1. The obtained lower value of binding constant of tetradifon than aldrin is due to the presence of a lesser number of leaving groups. The above-mentioned reaction helps the pesticides to bind covalently with the QD. For atrazine as well, there happens to be one Cl¯ ion but as there is also a possibility of steric hindrance due to presence of alkyl amine group in atrazine, QD cannot easily interact with the former. Because of this steric hindrance, the binding affinity is also low which is revealed in our result by the lowest binding constant among all the pesticides. As for glyphosate, the −COOH group is the reaction center for the interaction with QD. Here the −COOH group of glyphosate converts to COO¯, whereas the free primary amine group of QD converts to NH3+ and ionically interact with each other (Scheme 2). There is also possibility for the formation of hydrogen bonding interaction between −COOH groups of glyphosate and the −NH2 group of APTES capped ZnO QD. Therefore, both the ionic and hydrogen bonding interaction shows a higher binding constant of glyphosate compared to atrazine. So the structural differences of pesticides create different binding affinities with QDs, which in other words QDs have the ability to detect different pesticides. 3.4. Time-Resolved Fluorescence Decay. The fluorescence decay kinetics was measured for different pesticides maintaining the same concentration of QD (Figure 5). From the Supporting Information, Table T2, it is noticed that the QD gives three exponential fittings of the fluorescence decay profile from which we obtained three lifetimes of QD. Upon addition of different pesticides, the lifetime of QD having the longer value changes significantly. Interestingly the lifetime of QD is changed as a function of concentration of all pesticides (Supporting Information, Table T3). In our previous discussion we have stated that if the quenching of QD in the presence of pesticides is dominated by collision phenomena then there should be a change of the lifetime by varying the concentration of pesticides. Here our result infers that there is a certain change in lifetime as a function of pesticide concentration which implies the quenching phenomena is completely dominated by dynamic quenching. The multiexponential fitting of fluorescent decay curve for QD indicates that there are multiple trapping levels which significantly contribute to the radiative transitions (Supporting Information, Table T2). In general, the II−VI semiconductor QDs commonly have the defects. These defects create different band gaps having an extra lifetime along with the normal lifetime. For bulk semiconductors, these trapping levels are inactive for its forbidden optical transition. Here for ZnO QDs, the photoexcited

(Figure 3). The linearity of the plots indicates the presence of only one type of quenching in each interaction. Table 1 displays different value of KSV for different pesticides. Now to address which particular type of quenching is responsible Table 1. Stern−Volmer Quenching and Binding Parameters for QD−Pesticides Interactions samples aldrin tetradifon glyphosate atrazine

KSV (103L mol−1)

Kb (M−1)

n

8.49 7.01 4.83 0.987

2.51 × 10 1.2 × 1010 1.12 × 109 6.65 × 107

2.9 2.1 2 1.8

13

for each interaction we measure the same quenching effect in different temperatures. The dynamic quenching depends upon diffusion by rule. With the increasing temperature, the diffusion coefficient increased and the bimolecular quenching constants also increased. However, for static quenching the reverse effect would be observed. For static quenching, the KSV values decreased with an increase in temperature. In the present study, the KSV values increase with increasing temperature (Supporting Information, Table T1). This reveals that the type of quenching should be primarily dynamic in nature. To further confirm the mode of quenching, we also measured fluorescence lifetime of QDs in the time-resolved decay section in the support. From Table 1 it may be inferred that the quenching constant is different for different pesticides. The quenching constant is found to be highest for aldrin and lowest for atrazine due to structural differences of the target pesticides. The different quenching constants of QDs for different pesticides help us to detect pesticides easily. These differences in the quenching constants suggest different binding interactions of each pesticide with QD. In order to investigate the binding affinities, we have studied the binding interaction of QDs which is described in the next section. 3.3. Analysis of the Binding Constants and the Stoichiometry of Binding. The value of binding constant (Kb) that describes the binding ability of pesticides to QDs is helpful to understand the interaction state of the pesticides with QDs. This degree of binding affinity of the QD−pesticides complex could also be used to distinguish between the different pesticides. In order to analyze thoroughly the equilibrium between free and bound molecules and rationalize our experimental data on QDs−pesticides systems, the following equation has been employed.23 log[(F0 − F )/F ] = log Kb + n log[Q ] (7) F where F0 and F are fluorescence intensity of the QD in the absence and presence of different concentrations of pesticides, respectively. Kb is the binding constant and n is the stoichiometry of binding. According to eq 6, the Kb and n values can be obtained by the plot of log[(F0 − F)/F] versus log [Q] (Figure 4). The values of n and Kb at 300 K for the pesticides are listed in Table 1. For all pesticides, the Kb values are equal or more than 107 M−1 order, which indicates the higher affinity of pesticides to QDs. From Table 1 it may also be noticed that the binding constant is highest for aldrin (∼1013 M−1) and lowest for atrazine (107 M−1). From these hugely different values we can easily distinguished different pesticides of our concern. The stoichiometry of binding (n) with QDs is also different for different pesticides. For aldrin, the “n” value is found to be 3 but for other pesticides the value is 2. This indicates that 3 sites 418


Article


Figure 4. Plot of log [(F0 − F)/F] vs log [Q] for the interaction of different pesticides with QDs.

Scheme 2. Schematic Representation of Interaction of QD with (a) Aldrin and (b) Glyphosate

QDs can return to the ground state via three different processes: (1) exciton emission, (2) trap emission, and (3) nonradiative recombination. The first two processes contribute to the radiative emission and also to fluorescence lifetime, which was reflected in our result. Because of this trapping state, a broad emission band is observed in our study which is already reported.24 The increase of long lifetime with the addition of pesticides is due to alternation of transition route of energy transfer due to presence of pesticides. The long-lifetime is the dominating factor as it has the larger amplitude. Also the value of this long lifetime

is greater for aldrin as it binds strongly with QD and smaller for atrazine as it binds weakly than other pesticides. The rest two components having small amplitude and having lifetimes of the order of 10−8 S and 10−10 S correspond to amino silane induced decays, which fails to integrate with the major component. To avoid the complexity, we calculate the average lifetime, radiative, and nonradiative rate constants with the help of following equations. τf = a1τ1 + a 2τ2 419

(8) DOI: 10.1021/acs.jafc.7b04188 J. Agric. Food Chem. 2018, 66, 414−423

Article


responsible for emission by recombination with the hole. This e− must be used to bind the pesticides. So the fluorescence lifetime measurement conclude that the average lifetimes increases in the following way, atrazine < glyphosate < tetradifon < aldrin. These values also reflect the different binding abilities of pesticides with QDs, which corroborates with our steady state results. Thus, from the steady state and timeresolved results, different pesticides could easily be detected by QDs. 3.5. Electrochemical Sensing of Pesticides with QD. To further support our previous finding, we have introduced for the very first time another method called the electrochemical method. We measure the resistance of QD in the presence of different pesticides with our own customized instrument (Scheme S2). The results are shown in Table 3.

Figure 5. Time-resolved fluorescence decays of QDs (5 × 10−5 M), in aqueous solution and with different pesticides solutions. The concentration of pesticides is the highest one as in steady state measurements.

Φf = K rτf

Table 3. Values of Resistance and Conductivity of Different Pesticides

(9)

1/τf = K r +

∑ K nr

(10)

τf is average lifetime component of QD and Kr, Knr, Φf are the radiative constant, nonradiative constant, and fluorescence quantum yield of QD, respectively. The average lifetime is also increased in the presence of pesticides. This increment of the average lifetime of QD follows the opposite trends to that observed in the steady state profile for which we observed a decrease in quantum yields in the presence of pesticides. This can be explained by taking account of modulation of the radiative and nonradiative decay pathways (eqs 9 and 10). To rule out the complexity, we take the average lifetime to estimate Kr and Knr values. The enhanced average lifetime and the reduced quantum yield values of QD in the presence of pesticides suggests that the decrease in radiative rate constant Kr is significantly higher than the decrease in the nonradiative rate constant after interaction of pesticides with QD, which is reflected in our results (Table 2).

samples

φ

average τf (ns)

Kr

Knr

0.44 ± 0.1 0.186 ± 0.02 0.19 ± 0.01 0.298 ± 0.03 0.379 ± 0.03

104 312 288 275 150

0.00426 0.000596 0.000666 0.00108 0.00252

0.00535 0.0026 0.0028 0.00183 0.00414

resistance (Ω)

conductivity (mho)

123685 69239 77347 103599 85174

8.1616 × 10−6 1.4508 × 10−5 1.3015 × 10−5 9.7684 × 10−6 1.18188 × 10−5

It is noticed that the resistance of QD is the highest, but after the addition of pesticides the resistance gets decreased leading to the different resistances for different pesticides. Hence these different values of resistance in turn help in identifying the pesticides under our study. The difference in resistance depends upon the molecular structure of the analytes and the extent of interaction between the pesticides and the ZnO QDs. The resistance depends upon the amount of electrolyte present in the solution, which for QDs is very low than other samples due to the lesser amount of electrolyte present, thereby showing higher resistance. Among all the pesticides in our investigation, the resistance was highest for glyphosate and lowest for aldrin. As a matter of fact, this is in line with our previous spectroscopic results findings where upon interaction with QDs, the molecular structure of aldrin facilities the leaving of Cl¯ ions. These Cl¯ ions, consequently, may act as an electrolyte in the solution resulting high conductivity of aldrin, vis-à-vis, lesser resistance. In contrast tetradifon contains a lesser amount of Cl¯ ions (4 in number) as compared to aldrin leading to the greater resistance than aldrin while interacting with QDs. In the case of atrazine there is lesser availability of Cl¯ ions, which creates lesser possibility for generation of free Cl¯ ions owing to lesser interaction with QDs. Here only Cl¯ ion (per atrazine molecule) generates very mild electrolytic strength, making the resistance of atrazine higher than tetradifon. On the other hand, glyphosate not only interacts with QDs through ionic interaction between the COOH− group of glyphosate and the amine group of QD vis-à-vis it also interacts with the surface modified ZnO QDs by H-bonding interactions between the −COOH¯ (carboxylic) group of glyphosate and the hydrogen pertaining amine group of the QD. As a result, there is no possibility of getting electrolyte through interaction with QD resulting in the highest resistance for glyphosate than other pesticides. So, by simply measuring the resistances, different pesticides can be easily distinguished (Figure S4). Thus, our electrochemical sensing method can be used to detect structurally different pesticides as it has successfully differentiated the pesticides in our present study, aldrin, tetradifon, glyphosate,

Table 2. Quantum Yield and Radiative and Nonradiative Parameters of QDs Alone and in the Presence of Different Pesticides ZnO aldrin tetradifon glyphosate atrazine

samples ZnO aldrin tetradifon glyphosate atrazine

The radiative rate constant is also a signature of the binding affinity of QD with different pesticides. Here the fluorescence is going to decrease with the interaction of pesticides. So the radiative rate constant has a significant contribution in binding of QD with pesticides. The plot of the radiative rate constant vs the binding constant is shown in Figure S3. Here it was noticed that the strong binding of pesticides with QDs highly facilitates the decrease of the radiative rate constant. From Table 2 it could be apparent that in the presence of different pesticides, the nonradiative decay constant of QD also decreases. This reduction rate of nonradiative decay may be attributed to the restriction of production of e−, which is 420


Article


reactive. The molecular structure of aldrin and tetradifon contain electron-withdrawing groups (−SO2 and −Cl), but the presence of QDs help to promote photolytic ozone reactions on certain preferential sites. (Scheme S2) Aldrin and tetradifon degradation followed a polynomial curve with a significant R2 value (0.989 and 0.992). Thus, the highest degradation was recorded for pesticides with the highest association/binding affinities with QD. Thus, ZnO QDs are not only sensing toxic pesticidal residues but also increasing the rate of degradation of the pesticides drastically.

and atrazine. Nonetheless, this electrochemical sensing method could be exploited further to distinguished normal water and pesticides contaminated water. A step ahead, this electrochemical sensing may find its potential usage in the field of agricultural sciences, wherein using sensor network and IoT (Internet of Things), an infrastructure can be built which may not only simply detect the pesticide contamination but further be able to quantify the degree of contamination by the same. 3.6. Degradation of Pesticides. Apart from accessing the ability of surface modified ZnO QDs in sensing and distinguishing toxic pesticides in order to further investigate the potentiality of our ZnO QDs toward degradation of pesticides, the fluorescence intensity was measured as a function of time. The concentration of QDs is 5 × 10−5, and the concentration of pesticides is the highest one as in steady state measurements. From Figure 6, it was observed that the fluorescence intensity

4. CONCLUSIONS Ultralow sensing of different pesticides was carried out by ZnO QDs. All the interactions of pesticides with QDs happened in the excited state of QDs. In our investigation, the capping of QD by APTES played an important role for the interaction with pesticides. From steady state measurements, it has been revealed that pesticides aldrin and tetradifon can bind more strongly with QD than glyphosate and atrazine. Excited state dynamics of QDs showed the dynamic quenching of QDs in the presence of different pesticides of our concern. The presence of several number of good leaving group (−Cl) in aldrin and tetradifon was the probable reason behind their covalent binding with QDs which can be substituted by primary amine group of QDs. On the other hand, in glyphosate, the ionic interaction was playing the key role in binding with QDs which resulted in less binding affinity. Here in our study we have described the electrochemical measurement as another sensing method of pesticides. We obtained lesser resistance due to the availability of more electrolytes for aldrin and tetradifon in comparison to the other pesticides. Besides sensing of pesticides our ZnO QD also degrade the pesticides with which it binds strongly. The stronger binding of the QDs with aldrin and tetradifon led to the degradation of these pesticides. We believe that the present study opens a new avenue for the development of a simple hand-held method for the identification of different pesticides, which may hold great potential application in environmental protection and food safety. In our future work, we will further improve the discrimination ability of the quantum dots based sensor array to extend its application for recognition of other pesticides.

Figure 6. Degradation of pesticides as a function of time. The concentration of QDs is 5 × 10−5 and the concertation of pesticides is the highest one as in steady state measurements.

of QDs starts to change after 3 min and drastic changes were observed in the presence of some pesticide whereas some have shown meagre changes with time. It should be noted that the equilibrium of a solution of the QD−pesticide complex was reached within 1 min of the equilibration and the detection of pesticides was done within 2 min after the QD−pesticides complex formation. In the degradation study, the degradation starts after 3 min. As during the detection process there is no degradation phenomena involved at all, we could safely identify the different pesticides as previously described. Thus, we can infer that detection and degradation did not interfere with each other Within the time-window of 20 min, the intensity of QD falls drastically due to the addition of aldrin and tetradifon. From the previous discussions, it could be seen that the binding affinities of these two pesticides (aldrin, tetradifon) with QD are stronger than others. This stronger binding affinity further helps them to degrade more efficiently than the other two pesticides in target, viz., atrazine and glyphosate. These results also support our previous assumption about the lower binding affinity of aforementioned pesticides with QD. On the basis of the observed experimental results, the probable mechanism for the photocatalyzed degradation of aldrin and tetradifon onto QDs in the presence of UV light is proposed as following. In photocatalyzed degradation, the photoinduced holes and electrons in semiconductor particles may produce highly oxidizing agents/molecular species, which play a key role in degradation of pesticides.25 Zinc oxide (ZnO) has been found to be a very useful photocatalyst semiconductor.26 The fundamental properties of the zinc oxide catalyst are chemical stability and the presence of active surface sites, which are responsible for catalyzed reactions.27 In particular, aromatic compounds substituted with electron withdrawing groups (−SO2, −Cl) are weakly photolytically

■

ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.jafc.7b04188. Size and stability measurement of QDs, temperature dependent KSV values, and lifetime data for different pesticides as a function of concentration (PDF)

■

AUTHOR INFORMATION

Corresponding Authors

*E-mail: [email protected]. *E-mail: [email protected]. ORCID

Dibakar Sahoo: 0000-0002-0201-1411 Funding

D.S. thanks UGC, New Delhi, India, for providing the financial assistance in the form of a D.S. Kothari Fellowship. A.M. acknowledges ICAR-IARI and ICAR-NAARM for the Scientific Attachment Programme of 103rd FOCARS. T. M. acknowledges DST, 421


Article

Journal of Agricultural and Food Chemistry New Delhi, for financial assistance provided in the form of a SERB-National Post-Doctoral Fellowship (SERB-NPDF). M.B. would like to express her sincere gratitude to the DST-SERB Project (Grant YSS/2015/000589), DST, Govt. of India.

transfer of poly (o-phenylenediamine)−Rhodamine B copolymer dots: application in ultrasensitive detection of nitrite in vivo. J. Mater. Chem. A 2015, 3 (14), 7568−7574. (c) Liu, X.; Cheng, L.; Lei, J.; Liu, H.; Ju, H. Formation of Surface Traps on Quantum Dots by Bidentate Chelation and Their Application in Low-Potential Electrochemiluminescent Biosensing. Chem. - Eur. J. 2010, 16 (35), 10764−10770. (10) (a) Thomas, A.; Nair, P. V.; George Thomas, K. InP quantum dots: an environmentally friendly material with resonance energy transfer requisites. J. Phys. Chem. C 2014, 118 (7), 3838−3845. (b) De, B.; Karak, N. Recent progress in carbon dot−metal based nanohybrids for photochemical and electrochemical applications. J. Mater. Chem. A 2017, 5, 1826. (11) (a) Fonoberov, V. A.; Balandin, A. A. ZnO quantum dots: physical properties and optoelectronic applications. J. Nanoelectron. Optoelectron. 2006, 1 (1), 19−38. (b) Gulia, S.; Kakkar, R. ZnO quantum dots for biomedical applications. Adv. Mater. Lett. 2013, 4 (12), 876−887. (c) Liu, D.; Lv, Y.; Zhang, M.; Liu, Y.; Zhu, Y.; Zong, R.; Zhu, Y. Defect-related photoluminescence and photocatalytic properties of porous ZnO nanosheets. J. Mater. Chem. A 2014, 2 (37), 15377−15388. (d) Zhang, C.; Li, K.; Song, S.; Xue, D. Reversible phase transfer of luminescent ZnO quantum dots between polar and nonpolar media. Chem. - Eur. J. 2013, 19 (20), 6329−6333. (12) Zhang, Y.; Nayak, T.; Hong, H.; Cai, W. Biomedical applications of zinc oxide nanomaterials. Curr. Mol. Med. 2013, 13 (10), 1633− 1645. (13) Moussodia, R.-O.; Balan, L.; Schneider, R. Synthesis and characterization of water-soluble ZnO quantum dots prepared through PEG-siloxane coating. New J. Chem. 2008, 32 (8), 1388−1393. (14) Liu, D. P.; Li, G. D.; Su, Y.; Chen, J. S. Highly Luminescent ZnO Nanocrystals Stabilized by Ionic-Liquid Components. Angew. Chem., Int. Ed. 2006, 45 (44), 7370−7373. (15) (a) Selegård, L.; Khranovskyy, V.; Soderlind, F.; Vahlberg, C.; Ahrén, M.; Käll, P.-O.; Yakimova, R.; Uvdal, K. Biotinylation of ZnO nanoparticles and thin films: a two-step surface functionalization study. ACS Appl. Mater. Interfaces 2010, 2 (7), 2128−2135. (b) Materne, T.; de Buyl, F.; Witucki, G. L. Organosilane technology in coating applications: review and perspectives. Dow Corning Corporation, AGP11933, 2012. (16) (a) Barco-Bonilla, N.; Romero-González, R.; Plaza-Bolaños, P.; Vidal, J. L. M.; Frenich, A. G. Systematic study of the contamination of wastewater treatment plant effluents by organic priority compounds in Almeria province (SE Spain). Sci. Total Environ. 2013, 447, 381−389. (b) Moreno-González, R.; Campillo, J. A.; García, V.; León, V. M. Seasonal input of regulated and emerging organic pollutants through surface watercourses to a Mediterranean coastal lagoon. Chemosphere 2013, 92 (3), 247−257. (17) (a) Erbahar, D. D.; Gürol, I.; Gümüs,̧ G.; Musluoğlu, E.; Ö ztürk, Z. Z.; Ahsen, V.; Harbeck, M. Pesticide sensing in water with phthalocyanine based QCM sensors. Sens. Actuators, B 2012, 173, 562−568. (b) Rao, G. S.; Hussain, T.; Islam, M. S.; Sagynbaeva, M.; Gupta, D.; Panigrahi, P.; Ahuja, R. Adsorption mechanism of graphene-like ZnO monolayer towards CO2 molecules: enhanced CO2 capture. Nanotechnology 2016, 27 (1), 015502. (18) Zhao, L.-H.; Zhang, R.; Zhang, J.; Sun, S.-Q. Synthesis and characterization of biocompatible ZnO nanoparticles. CrystEngComm 2012, 14 (3), 945−950. (19) Du, H.; Fuh, R. C. A.; Li, J.; Corkan, L. A.; Lindsey, J. S. PhotochemCAD: A computer-aided design and research tool in photochemistry. Photochem. Photobiol. 1998, 68 (2), 141−142. (20) (a) Wahab, R.; Kim, Y.-S.; Lee, D. S.; Seo, J.-M.; Shin, H.-S. Controlled Synthesis of Zinc Oxide Nanoneedles and Their Transformation to Microflowers. Sci. Adv. Mater. 2010, 2, 35−42. (b) Wang, Z.; Zhang, H.; Zhang, L.; Yuan, J.; Yan, S.; Wang, C. Lowtemperature synthesis of ZnO nanoparticles by solid-state pyrolytic reaction. Nanotechnology 2003, 14, 11−15. (21) (a) Ghosh, M.; Raychaudhuri, A. K. Shape transition in ZnO nanostructures and its effect on blue-green photoluminescence. Nanotechnology 2008, 19 (44), 445704. (b) Ye, J. D.; Gu, S. L.; Qin, F.; Zhu, S. M.; Liu, S. M.; Zhou, X.; Liu, W.; Hu, L. Q.; Zhang, R.; Shi,

Notes

The authors declare no competing financial interest.

■

ACKNOWLEDGMENTS We wish to express our heartiest thanks to Prof. Nikhil Guchhait of Chemistry Department, University of Calcutta, Kolkata, for helping in the measurements of fluorescence lifetime by the timecorrelated single-photon counting technique.

■

REFERENCES

(1) Sassolas, A.; Prieto-Simón, B.; Marty, J.-L. Biosensors for pesticide detection: new trends. Am. J. Anal. Chem. 2012, 3 (3), 210. (2) (a) Del Prado-Lu, J. L. Insecticide residues in soil, water, and eggplant fruits and farmers’ health effects due to exposure to pesticides. Environ. Health Prev. Med. 2015, 20 (1), 53−62. (b) Aktar, W.; Sengupta, D.; Chowdhury, A. Impact of pesticides use in agriculture: their benefits and hazards. Interdiscip. Toxicol. 2009, 2 (1), 1−12. (3) Stachniuk, A.; Fornal, E. Liquid Chromatography-Mass Spectrometry in the Analysis of Pesticide Residues in Food. Food Analytical Methods 2016, 9 (6), 1654−1665. (4) (a) Katsoudas, E.; Abdelmesseh, H. H. Enzyme inhibition and enzyme-linked immunosorbent assay methods for carbamate pesticide residue analysis in fresh produce. J. Food Prot. 2000, 63 (12), 1758− 1760. (b) Nunes, G. S.; Toscano, I. A.; Barceló, D. Analysis of pesticides in food and environmental samples by enzyme-linked immunosorbent assays. TrAC, Trends Anal. Chem. 1998, 17 (2), 79− 87. (5) (a) Smith, A. M.; Mohs, A. M.; Nie, S. Tuning the optical and electronic properties of colloidal nanocrystals by lattice strain. Nat. Nanotechnol. 2009, 4 (1), 56−63. (b) Aragay, G.; Pino, F.; Merkoçi, A. Nanomaterials for sensing and destroying pesticides. Chem. Rev. 2012, 112 (10), 5317−5338. (6) (a) Balandin, A. A.; Wang, K. L. Handbook of Semiconductor Nanostructures and Nanodevices. American Scientific Publishers: Los Angeles, CA, 2006; Vol. 1. (b) Smith, A. M.; Nie, S. Semiconductor nanocrystals: structure, properties, and band gap engineering. Acc. Chem. Res. 2010, 43 (2), 190−200. (7) (a) Wang, Y.; Hu, R.; Lin, G.; Roy, I.; Yong, K.-T. Functionalized quantum dots for biosensing and bioimaging and concerns on toxicity. ACS Appl. Mater. Interfaces 2013, 5 (8), 2786−2799. (b) Li, J.; Zhu, J.J. Quantum dots for fluorescent biosensing and bio-imaging applications. Analyst 2013, 138 (9), 2506−2515. (c) Sapsford, K. E.; Pons, T.; Medintz, I. L.; Mattoussi, H. Biosensing with luminescent semiconductor quantum dots. Sensors 2006, 6 (8), 925−953. (d) Park, Y.; Jeong, S.; Kim, S. Medically translatable quantum dots for biosensing and imaging. J. Photochem. Photobiol., C 2017, 30, 51. (e) Tran, H. N.; Nghiem, T. H. L.; Vu, T. T. D.; Chu, V. H.; Le, Q. H.; Hoang, T. M. N.; Nguyen, L. T.; Pham, D. M.; Tong, K. T.; Do, Q. H. Optical nanoparticles: synthesis and biomedical application. Adv. Nat. Sci.: Nanosci. Nanotechnol. 2015, 6 (2), 023002. (8) (a) Medintz, I. L.; Mattoussi, H.; Clapp, A. R. Potential clinical applications of quantum dots. Int. J. Nanomed. 2008, 3 (2), 151. (b) Liu, G.; Wang, J.; Barry, R.; Petersen, C.; Timchalk, C.; Gassman, P. L.; Lin, Y. Nanoparticle-Based Electrochemical Immunosensor for the Detection of Phosphorylated Acetylcholinesterase: An Exposure Biomarker of Organophosphate Pesticides and Nerve Agents. Chem. Eur. J. 2008, 14 (32), 9951−9959. (9) (a) Abbasi, E.; Kafshdooz, T.; Bakhtiary, M.; Nikzamir, N.; Nikzamir, N.; Nikzamir, M.; Mohammadian, M.; Akbarzadeh, A. Biomedical and biological applications of quantum dots. Artif. Cells, Nanomed., Biotechnol. 2016, 44 (3), 885−891. (b) Liao, F.; Song, X.; Yang, S.; Hu, C.; He, L.; Yan, S.; Ding, G. Photoinduced electron 422


Article

Journal of Agricultural and Food Chemistry Y. Correlation between green luminescence and morphology evolution of ZnO films. Appl. Phys. A: Mater. Sci. Process. 2005, 81 (4), 759−762. (22) Tian, F.-F.; Li, J.-H.; Jiang, F.-L.; Han, X.-L.; Xiang, C.; Ge, Y.S.; Li, L.-L.; Liu, Y. The adsorption of an anticancer hydrazone by protein: an unusual static quenching mechanism. RSC Adv. 2012, 2 (2), 501−513. (23) Lakowicz, J. R. Fluorescence anisotropy. In Principles of Fluorescence Spectroscopy; Springer, 1999; pp 291−319. (24) (a) Wuister, S. F.; van Driel, F.; Meijerink, A. Phys. Chem. Chem. Phys. 2003, 5, 1253−1258. (b) Chen, W.; Joly, A. G.; McCready, D. E. J. Chem. Phys. 2005, 122, 224708. (25) Zhang, W.; Zou, L.; Wang, L. Photocatalytic TiO 2/adsorbent nanocomposites prepared via wet chemical impregnation for wastewater treatment: a review. Appl. Catal., A 2009, 371 (1), 1−9. (26) (a) Sehili, T.; Boule, P.; Lemaire, J. Photocatalysed transformation of chloroaromatic derivatives on zinc oxide III: chlorophenols. J. Photochem. Photobiol., A 1989, 50 (1), 117−127. (b) Sehili, T.; Boule, P.; Lemaire, J. Photocatalysed transformation of chloroaromatic derivatives on zinc oxide IV: 2, 4-Dichlorophenol. Chemosphere 1991, 22 (11), 1053−1062. (27) Kasprzyk-Hordern, B.; Ziółek, M.; Nawrocki, J. Catalytic ozonation and methods of enhancing molecular ozone reactions in water treatment. Appl. Catal., B 2003, 46 (4), 639−669.

423
