Self-assembled “bridge” substance for organochlorine pesticides detection in solution based on Surface Enhanced Raman Scattering

Journal Pre-proof Self-assembled “bridge” substance for organochlorine pesticides detection in solution based on Surface Enhanced Raman Scattering De Zhang, Pei Liang, Zhi Yu, Jing Xia, Dejiang Ni, Dan Wang, Yongfeng Zhou, Yu Cao, Jie Chen, Jinlei Chen, Shangzhong Jin

PII:

S0304-3894(19)30977-X

DOI:

https://doi.org/10.1016/j.jhazmat.2019.121023

Article Number:

121023

Reference:

HAZMAT 121023

To appear in:

Journal of Hazardous Materials

Received Date:

30 April 2019

Revised Date:

13 August 2019

Accepted Date:

14 August 2019

Please cite this article as: Zhang D, Liang P, Yu Z, Xia J, Ni D, Wang D, Zhou Y, Cao Y, Chen J, Chen J, Jin S, Self-assembled “bridge” substance for organochlorine pesticides detection in solution based on Surface Enhanced Raman Scattering, Journal of Hazardous Materials (2019), doi: https://doi.org/10.1016/j.jhazmat.2019.121023

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Self-assembled “bridge” substance for organochlorine pesticides detection in solution based on Surface Enhanced Raman Scattering De Zhang, a Pei Liang, b† Zhi Yu, a† Jing Xia, a Dejiang Ni, a Dan Wang, b Yongfeng Zhou, b Yu Cao, b Jie Chen, a Jinlei Chen, a Shangzhong Jin b a. Key Laboratory of Horticultural Plant Biology, Ministry of Education, College of Horticulture & Forestry Sciences, Huazhong Agricultural University, 430070,

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Wuhan, China; College of Optical and Electronic Technology, China Jiliang University, 310018 Hangzhou, China. †Corresponding author: [email protected] (Pei Liang), Tel/Fax number: +86571-86875622; [email protected](Zhi Yu).

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Graphic Abstract

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Manufacturing process of sample detection pool (left) and SERS detection of organochlorine pesticides in liquid solution (right).

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Highlights 

OBM model and a droplet concentration method were proposed.

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Selectivity & stability of “bridge” interact with pesticide was interpreted.

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Mechanism of chloride ions for SERS detection in solution was discussed.

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ABSTRACT: Pesticide residues pose a great threat to human health, and it is an urgent matter to realize fast and accurate detection of pesticide. SERS (Surface Enhanced

Raman Scattering), as a nondestructive detection technology, performs a prominent role

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in fast detection field due to the strong surface plasmon resonance from short range

effect between analyte and nanoparticle. Therefore, in order to solve the incompatibility

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between organochlorine pesticides molecules and noble metal nanoparticles, this paper

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proposed a concept of “bridge” substances acting as an interconnect function role to achieve a binding model (object-binder-metal (OBM)) and developed a droplet

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concentration method to enhance Raman signals. Both combination mode of pesticide molecules to bridge molecules and energy transfer of SERS experiment may relate to

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the compound ring according to the changes of peaks based on surface plasmon

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resonance. The selectivity and stability of different bridge substances interacting with pesticides molecules were illumined via binding energy of these two substances obtained by DFT calculations. A droplet can capture nanoparticles and analytes, which is conducive to SERS performance. Chloride ions in the solution contribute to rearrangement of nanoparticles and can validly promote surface activation of Ag 2

nanoparticles to improve energy transfer efficiency of plasma resonance, resulting in superior SERS effect.

KEYWORDS: SERS; organochlorine pesticides; droplet; OBM; chloride ions

1. Introduction

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Surface Enhanced Raman Scattering (SERS) is a technology that enhances Raman scattering from analyte molecules absorbed on the rough and noble metal surface based

on electromagnetic enhancement (EM) and chemical enhancement (CE) [1, 2]. Strong

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surface plasmon resonance is generally generated by the circumstances that analyte

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must be close enough to the nanoparticles or even adsorbing on the surface of the nanoparticles. The farther the object to be measured is from the nanoparticles, the

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smaller the surface plasmon resonance is [3, 4]. However, SERS phenomenon fails to appear when encountering some detection objects that have weak interaction with noble

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metal nanoparticles or no interaction at a long distance. Particularly, the analyte

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molecules will be in a free state in the solution, contributing to the inability to be aggregated and detected. Forasmuch, the research of chemical binding ability and

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attempt to narrow the distance between analyte molecules and noble metal are conducive to improve chemical enhancement as well as achieving higher electromagnetic enhancement. SERS has been developed into detecting pesticides in many studies over the last few decades [5, 6]. Many scholars attempted to aggregate free pesticide molecules on 3

nanoparticles in order to generate strong plasma resonance. However, much research, focusing on substances with the certain functional groups, has been developed to be very universal. Catching sight of sulfhydryl group being closely combined with metal nanoparticles, Zhu [7] adopted SERS technique to investigate for trace detection of thiram based on multi-branched gold nanostars with fractal structure and achieved a detection limit as low as 10-10 M in solution and 0.24 ng/cm2 in apple peels. Similarly,

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Mandrile [8] utilized the advantage of interaction between amine and metal

nanoparticles to successfully quantify pyrimethanil residues on pome fruits, which is a

widely used fungicide in horticultural species. Chen [9] synthesized quaternized

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chitosan/silver nanoparticles composite as SERS substrate for detecting Sudan due to

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the existence of hydroxyl group. These possible interactions between nanostructures and pesticide molecules can generate on account of the certain functional groups, such

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as thiol, amine, hydroxyl, carboxyl and so on, which can strongly bind to noble metal

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nanoparticles. One primary problem with above narrate is that a quick and easy SERS detection method to detect organochlorine pesticides without these functional groups is

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scarce. Some research reported materials used as affinity agents to create SERS sensors, which include antibody [10, 11], aptamer [12, 13], small molecule [14, 15], and

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polymer [16, 17]. They can facilitate the intrinsic detection of targets [18]. In order to overcome the inherent problem of the low affinity of organochlorine pesticides with metal

nanoparticles,

Kubackova

[19] developed a strategy consisting of

functionalization of the metal surface with alkyl dithiols to achieve this goal. However, this method always suffers from a series of complicated experimental conditions. 4

Although some research [20] employed viologen dictation in the functionalization of metal surface as host to detect some organochlorine pesticides, they did not explain the selectivity and specificity between the binding molecules and the organochlorine molecules, nor did they make further optimization application. In this paper, “bridge substances” were employed for the detection of

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organochlorine pesticides. Meanwhile, concentration and capture of nanoparticles with analytes based on droplet methods also play a crucial role. The OBM (object-bindermetal) model can effectively induce the plasma resonance of pesticides molecules.

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Compound rings probably play an important role in energy transfer according to the

changes of Raman peaks. The mechanism of bridge substances preference for

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organophosphorus pesticides molecules is explained based on double verification by

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experiment results and DFT (density functional theory) calculation. Chloride ions in the solution can make nanoparticles rearrange and improve energy transfer efficiency

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of plasma resonance by promoting ionization of water molecules to obtain favorable SERS effect. All these studies will provide systematic thinking and solutions for the

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SERS quantitative detection of organochlorine pesticides.

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2. Material and methods 2.1. Preparation of nanoparticles and SERS detection Diquat (DQ, 100 μg/mL), lucigenin (LG, 100 μg/mL) were bought from

Shanghai Macklin Biochemical Technology Co., Ltd. Use specifications of other chemicals and fabrication method of flower like silver nanoparticles are the same 5

as our previous paper [21]. Briefly, 2 mL of polyvinylpyrrolidone (PVP, K30, 1 M) and 0.2 mL of AgNO3 (1 M) were successively put into 10 mL of deionized water under the thermostat magnetic stirrer at room temperature. Subsequently, the color of solution changed into gray-black sharply after adding 1 mL of ascorbic acid (ASA, 0.1 M) into the beaker. Ten minutes later, the solution tended to be stable and its colour remained gray-black. Then, centrifugation with

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deionized water was performed four times in order to remove the impurities on the surface of silver nanoparticles. As can be seen in the Fig S2, the SERS spectra of the impurities of silver nanoparticles were too weak to display any peaks,

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which has no influence on spectra of research targets. Finally, silver colloid

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particles dispersed in 10 mL ultrapure water were obtained.

All the organochlorine pesticide standard solution (100 μg/mL), including α-

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endosulfan, β - endosulfan ， OP’-DDT (Dichlorodiphenyltrichoroethane), α-

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hexachlorocyclohexane, tetradifon, aldrin, β-Hexachlorocyclohexane, pp’-DDE (isomer of DDT) and heptachlor, were purchased from Environmental Protection

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Research and Inspection Institute of Ministry of Agriculture of China (Shanghai, China). “Bridge” substance integrating with nanoparticles was formed by mixing the 1

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mL of silver colloid with 50 μL of bridge substance (10-5 M) under the thermostat magnetic stirrer for 10 minutes. As another substance at the bridge head, 50 μL of single organochlorine pesticide solution (one of α-endosulfan, tetradifon, aldrin, ect.), then was pipetted into the solution, followed by stirring the solution persistently for 5 minutes. Thereafter, 30 μL of the prepared solution was drawn 6

with a pipette into the customized liquid testing chamber (Diameter: 0.5 cm; depth: 3 mm). The SERS spectra were acquired under a He-Ne laser (532 nm) with a laser power of 50 mW with 3 s exposure time and two times accumulation. 2.2. Theoretical modelling The bridge substance and the pesticides molecules were explored by using DFT with the hybrid B3LYP functional based on the Gaussian 09 computational

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package. All calculations adopted the 6-31G(d, p) basis set. Geometries were

reoptimized to explain the interaction of pesticides molecules with the bridge molecules. Both the bridge molecules and the pesticide molecules calculated with

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the Gamma k-point are aperiodic structure [22].

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In the calculation, the binding energy is defined by the following formula: 𝐸𝑏 = 𝐸𝑡𝑜𝑡𝑎𝑙 − 𝐸𝑏𝑖𝑛𝑑 − 𝐸𝑝𝑒𝑠𝑡

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where 𝐸𝑏 is the binding energy, 𝐸𝑡𝑜𝑡𝑎𝑙 is the energy of the bound binding molecule and pesticide molecule, 𝐸𝑏𝑖𝑛𝑑 is the energy of the binding molecule

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and 𝐸𝑝𝑒𝑠𝑡 is the energy of the pesticide molecule.

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2.3. Vibrational spectrum calculations Theoretical Raman spectra of the binding molecule, the pesticide molecule

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and bridge molecule were provided (Support information). The vibration analysis of the ground state of the binding molecules (DQ and LG), the pesticide molecules (α-endosulfan, op’-DDT, α-hexachlorocyclohexane, tetradifon, aldrin, β-Hexachlorocyclohexane, pp’-DDE, heptachlor) and the two combines were completed. Above calculations were based on the DFT/B3LYP functional and 67

31G(d,p) basis set via Gaussian 09, which was the same to geometry optimized of ground state. The IR peak half-width at half height was set at 4 cm-1. Employing the frequency/intensity data from the B3LYP vibrational analysis as a sum of Lorentzian line shapes of 4 cm−1 half-width, the Raman spectrum was acquired and the vibrational spectrum (frequencies) was corrected by a constant actor of 0.97 to align the Raman features with experimental results.

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3. Results and discussions

3.1. SERS detection of organochlorine pesticides by using bridge substances

“Bridge” substance absorbed on the metal nanoparticles plays an important role of

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bridge which unites analyte and shows distinguishable Raman spectra. In order to

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obtain better confirmation on the changes before and after addition of analyte, Raman spectroscopic investigation was conducted. As can be seen in the Fig 1A(a), SERS

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spectra of DQ (10-5 M) based on flower-like silver nanoparticles can be clearly identified. The peaks at 675 cm-1 and 840 cm-1 are both assigned to ring breathing, while

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the two peaks at 1053 cm-1 and 1188 cm-1 can be unambiguously connected with δring

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or deformation of C-H and stretching of H2C–N or bending of C-H [23-25]. In addition to those attribution, the peaks at 1296 cm-1 、 1527 cm-1 and 1642 cm-1 are also

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observed; These peaks are due to the presence of the stretching of C-C and ring or inplane-bending of C-H [23, 26, 27]. Evidently, compared with the SERS spectra of “bridge” substance, the peaks centered at 881 cm-1 and 1222 cm-1 of the mixture SERS spectra of diquat (10-5 M) and α-endosulfan (10-5 M) (Fig 1A(b)) were new rising and can be attributable to C-H stretching and the stretching of SO3, which are important 8

functional groups of α-endosulfan [28, 29]. The above inference is also consistent with our results calculated by DFT (Fig 1B(a) and (b)) and other pervious literature [30], revealing that diquat can be considered as a kind of “bridge” substance that can bind

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both metal nanoparticles and analytes.

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Fig. 1. A: (a): SERS spectra of diquat (10-5 M) based on flower-like silver nanoparticles; (b): SERS spectra of the mixture of diquat (10 -5 M) and α-endosulfan (10-5 M); B: Raman spectra of (a) diquat and (b) α-endosulfan calculated by DFT.

In order to further verify this conjecture, some other frequently used

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organochlorine pesticides were also detected by this “bridge” technology based on SERS. As is shown in the Figure 2A(b), β-endosulfan can be easily identified by the

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peaks at 878 cm-1 and 1045 cm-1, which can be attributed to stretching of C-H [28, 31, 32]. The peak at 1453 cm-1 is assigned to in-plain deformation of CH2 [28]. The peaks,

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at 1259 cm-1 and 1473 cm-1 due to C-H or ring stretching, can be used to identify αhexachlorocyclohexane

[27,

33].

Similarly,

O,P'-DDT

(Dichlorodiphenyltrichoroethane) can also be distinguished without any efforts on the grounds that the peaks at 1087 cm-1 and 1264 cm-1 are related to ring breathing and inplane C-H deformation [34, 35], respectively. Furthermore, the vibration attribution of 9

all above peaks can be obtained and confirmed from DFT calculation model and spectra (Fig 2 (abc)) and other literature [36]. Visualization of peaks vibration can be observed by visualization for electronic and structural analysis software (VESTA). It also implies

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the powerful application of the “bridge” substance.

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Fig. 2. Raman spectra of various substance in different conditions. A: (a): SERS spectra of diquat (10-5 M) based on flower-like silver nanoparticles; (b): SERS spectra of the mixture of diquat (10-5 M) and β-endosulfan (10-5 M); (c): SERS spectra of the mixture of diquat (105 M) and α-hexachlorocyclohexane (10 -5 M); (d): SERS spectra of the mixture of diquat (10 5 M) and O,P'-DDT (10-5 M); B: Raman spectra of (a) α-hexachlorocyclohexane, (b) βendosulfan and (c) O,P'-DDT calculated by DFT.

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3.2. Detection model of organochlorine pesticides

In fact, this “bridge” substance is capable of absorbing on the surface of silver

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nanoparticles due to the formation of a complex with the absorbed anion, leading to a partial transition from sp2 to sp3 hybridization of the N atoms [37]. Apparently, the

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contact form is stronger than that of other molecules without any affinity group.

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Afterwards, the organochlorine pesticides molecules landed on the surface of “bridge” and intertwined it to form a kind of combination, which can transfer energy and contribute to a certain proportion of Raman effect. As can be seen in Fig 3, Raman laser could directly radiate in the solution and focus on the nanoparticles, resulting in distinguishable SERS spectra. The solution about 30 μL in the cylindrical quartz glass 10

groove was irradiated after the solution became a stable state. The amount of solution is as small as a droplet, which would generate a three-dimensional (3D) “trapping well” that not only could hold hot spots between each of the adjacent flower like nanoparticles but also trap pesticide molecules in the miniature cylindrical device [38]. Solution environment is the most important condition for molecular detection of organochlorine pesticides. Normally SERS signal of organochlorine pesticides cannot be obtained

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based on dried substrate because analyte cannot be efficiently captured, and interfering signals from the substrate would dominate the spectra [4]. Thus, the solvent acting as an initiator and porter could activate the pesticides molecules and transport them to

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nearby region of the bridges substances, leading to effective laser focus. Meanwhile, as

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the liquid droplet evaporated due to laser radiation, the concentration of solution would increase. The droplet would gradually condense into a smaller droplet, capillary,

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funicular, pendular, finally ending with dried state. SERS intensity of mixture solution

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performed erratic on account of evolution of the plasmonic properties of environment and particles’ state. It is worth believing that there exists an optimal surface plasmon

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resonance that can resonate sharply with OBM model, contributing to enormous signal enhancement. Therefore, the irradiation time was optimized to be as short as 3 seconds

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one time in order to prevent solution evaporation. Once the solution evaporates too much, it will directly lead to the increase of concentration and eventually affect the stability of organochlorine pesticides. Consequently, skillful mastery of test conditions is essential for SERS detection of organochlorine pesticides.

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In addition, a particularly interesting phenomenon from the emergence and disappearance of peaks as well as the peaks attribution of pesticides obtained by DFT and experimental results caught our attention (Table S2, S3, S4). C-H, C-C, and SO3 on ring of organochlorine pesticide compounds were susceptible to impact in this experiment, including bending, stretching, twisting and deformation, implying that both combination mode of pesticide molecules to bridge molecules and energy transfer of

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SERS experiment may relate to the ring of pesticides molecules. Besides, not all of

SERS peaks of mixture obtained by this model (object-binder-metal (OBM)) belong to pesticides, while some peaks marked by dotted lines are part of bridges substance in

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Fig 1 and Fig 2. Energy transfer based on EM and electron transport according to CE

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can both perform in the section of bridge substance adsorption on metal once Raman laser starts to excite resonance. However, depending on Van der Waals force, the OB

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(object-binder) part is arduous to transfer electrons. Accordingly, the resonance energy

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of bridge substance (diquat) would be transferred and shared to promote the resonance of binding model (object-binder-metal (OBM)), thus generating SERS spectra of the

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model. After laser wavelength being set, this plasma resonance will gradually weaken or even disappear with the increasing of the distance among OBM model, revealing that

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structure model determines performance. 3.3. The selectivity and stability of detection model DQ, as a kind of “bridge” substance, has exerted strong applicability in SERS detection of organochlorine pesticides in above-mentioned experiment. In fact, it is not the only substance with bridge effect. There is another candidate 12

substance as well, such as LG. These bridge substances have different attraction and energy transfer efficiency, eventually bringing about diverse SERS effect. Therefore, it involves a problem of selectivity and stability for detection. Fig 4(A) clearly shows the fundamental diversity of binding energy calculated by DFT, which reveals the preferential tropism of organochlorine pesticides molecules for bridge substance. The binding energy of DQ with most of

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commonly used organochlorine pesticides are lower than that of LG with

pesticides. It also indicates that DQ tends to interact with organochlorine pesticides molecule and forms more stable SERS detection state. Whereas LG

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can be employed to combine individual organochlorine molecules, for instance

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op’-DDT and aldrin, which precisely illustrates the specificity of bridge substances for different pesticides molecules. Consequently, all above discussion

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indicates that bridge substances are valid for use in organochlorine pesticides

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SERS detection and have a certain degree of selectivity.

Fig. 3. Manufacturing process of sample detection pool (left) and SERS detection of organochlorine pesticides in liquid solution (right).

3.4. The effect of chloride ions on detection model 13

In the above description, we only discuss the effect of the determined system itself on SERS performance. In fact, some environmental changes in the solution will have a profound impact on the detection results, such as pH, solvent type and some ions. The first two factors have been discussed in detail in our previous article [21]. Then the ions effect, especially the chloride ions, were investigated in the Fig 4(B). The intensity of peaks at 881 cm-1 and 1222 cm-1 of α-endosulfan

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(10-5 M) in the presence of diquat (10-5 M) rises first and then decreases with the increasing of chloride ions concentration in Fig 4(D). This significant

phenomenon indicates that some changes occurred between silver nanoparticles

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and bridge substance. After adding a certain amount of chloride ions, silver

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nanoparticles could rearrange and aggregate by charge action, contributing to reduction of specific surface area and more concentrated number of effective

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enhancements of regional molecules. Aggregation effect of nanoparticles

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narrowed the gap between adjacent nanoparticles and more hot spots were obtained [39]. Meanwhile, chloride ions can promote surface activation of Ag

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nanoparticles [40]. The nanoparticles with charges offer positive electron to chloride ions, leading to ionization of water molecules for the sake of maintaining

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the charge balance (Fig 4(B)). As a result, the number of protons increased and participated in plasma resonance and electron transfer, which can promote OBM resonance and SERS performance to some extent, especially in the chloride ions concentration of about 10-3 M (Fig 4(D)). Meanwhile, we could not ignore the dynamic process of droplet evaporation, which also drove nanoparticles and 14

analytes to aggregate. In the initial stage, charge transfer and neutralization effects were much faster than the interaction between chloride ions and the OBM structure. When chloride ions concentration continued to increase, the rate of chloride ions addition was much faster than the rate of water molecules ionization. The charge sites on the surface of nanoparticles were ultimately limited. Excessive chloride ions began to participate in competitive adsorption

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with pesticides molecules, compelling SERS effect to weaken. Not only that,

redundant chloride ions caused redispersion of metal nanoparticles due to charge

repulsion, thus decreasing SERS intensity (Fig 4(C)). Therefore, the existence of

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chloride ions in solution plays a vital role in SERS detection system.

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Organochlorine pesticides can be effectively detected by the method we proposed, which provides a powerful reference for qualitative and quantitative testing of organochlorine pesticide in the future. However, in this process, there are some points that we need to focus on. More bridge substances need to be excavated and discovered in order to be applied to the wider detection of organochlorine pesticide molecules. The SERS intensity of organochlorine pesticides is not the strongest at present by this method. With the dynamic evaporation process of droplets irradiated by Raman laser, there is an optimal detection period that we are trying to study. The promotion of chloride ions for detection is also not negligible. On the basis of qualitative detection of organochlorine pesticides, strict gradient test and appropriate data model design may be an effective way for quantitative detection. In addition, the OBM model combined with droplet microfluidic technology under optimized conditions will have great application value [41].

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4. Conclusions

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Fig. 4. Comparison of binding energies between different “bridge” substance and diverse organochlorine pesticides (A); Mechanism of chloride ion effect on nanoparticles state and SERS performance in solution (B); SERS spectra of α-endosulfan under different concentration of chloride ion (C); strength variation tendency of α- endosulfan (10-5 M) in the presence of diquat (10-5 M) under different concentration of chloride ion (D); (DQ: diquat; LG: lucigenin; O1: op’-DDT; O2: α-hexachlorocyclohexane; O3: tetradifon; O4: aldrin; O5: β-hexachlorocyclohexane; O6: pp’-DDE; O7: heptachlor).

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In conclusion, “bridge” substances with bidirectional affinity were selected as valid linkers to detect organochlorine pesticides in solution based on SERS

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technology. In this study, droplet-based methods of concentration and capture of

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nanoparticles with analytes also play an important role. OBM model can effectively achieve energy transfer and molecular resonance by laser excitation, obtaining identifiable SERS spectra. Organic rings of pesticides may act on the OBM model. The experimental results and DFT calculation model are used to explore their selectivity and stability. DQ was found to be a suitable bridge 16

substance for most commonly used organochlorine pesticides, while LG for a small part due to diversity of their binding energy. In addition, the solution environment containing a certain amount of chloride ions have a very good effect on SERS detection because of assistance of aggregation effect and surface activation of Ag nanoparticles. All these studies provide a systematic description and interpretation for organochlorine pesticides SERS detection. It is irresistible

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that quantitative detection will also be realized with the maturity of conditions and technologies in future.

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Conflicts of interest The authors declare no competing financial interest.

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Acknowledgements

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The Project was financially Supported by the Fundamental Research Funds for the Central Universities（Program No.2662017JC035）, and the National Science

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Foundation for Young Scholars of China (Grant No.31000316), the Application Research Program of Commonweal Technology of Zhejiang Province (No.

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2014C37042), the Zhejiang province university students in scientific and

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technological innovation activities (No. 2016R409011), and the Science and technology project of Zhejiang Province (No. 2016C33026) and National Key Research and Development Program project (No. 2017YFD040800).

References [1] S. Shanmukh, L. Jones, J. Driskell, Y. Zhao, R. Dluhy, R.A. Tripp, Rapid and sensitive detection of respiratory virus molecular signatures using a silver nanorod array SERS substrate, Nano Letters, 6 (2006) 2630-2636. 17

[2] S. Abalde-Cela, C. Abell, R.A. Alvarez-Puebla, L.M. Liz-Marzan, Real Time Dual-Channel Multiplex SERS Ultradetection, J Phys Chem Lett, 5 (2014) 73-79. [3] E. Hutter, J.H. Fendler, Exploitation of Localized Surface Plasmon Resonance, Advanced Materials, 16 (2004) 1685-1706. [4] M.L. Xu, Y. Gao, X.X. Han, B. Zhao, Detection of Pesticide Residues in Food Using Surface-Enhanced Raman Spectroscopy: A Review, J Agric Food Chem, 65 (2017) 6719-6726. [5] Q. Zhao, G. Liu, H. Zhang, F. Zhou, Y. Li, W. Cai, SERS-based ultrasensitive detection of organophosphorus nerve agents via substrate's surface modification, J Hazard Mater, 324 (2017) 194-202. [6] L. Zhang, Self-assembly Ag nanoparticle monolayer film as SERS Substrate for pesticide detection, Applied Surface Science, 270 (2013) 292-294. [7] J. Zhu, M.-J. Liu, J.-J. Li, X. Li, J.-W. Zhao, Multi-branched gold nanostars with fractal structure for SERS detection of the pesticide thiram, Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 189 (2018) 586-593.

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[8] L. Mandrile, A.M. Giovannozzi, F. Durbiano, G. Martra, A.M. Rossi, Rapid and sensitive detection of pyrimethanil residues on pome fruits by Surface Enhanced Raman Scattering, Food Chem, 244 (2018) 1624.

[9] K. Chen, Z. Shen, J. Luo, X. Wang, R. Sun, Quaternized chitosan/silver nanoparticles composite as a SERS substrate for detecting tricyclazole and Sudan I, Applied Surface Science, 351 (2015) 466-473. Immunobiology - NCBI Bookshelf, Garland Science, (2001).

-p

[10] C.A.J. Jr, P. Travers, M. Walport, M.J. Shlomchik, The structure of a typical antibody molecule [11] D.R. Davies, G.H. Cohen, Interactions of protein antigens with antibodies, Proceedings of the National

re

Academy of Sciences of the United States of America, 93 (1996) 7-12.

[12] M. Maumita, R.R. Breaker, Gene regulation by riboswitches, Nature Reviews Molecular Cell Biology, 5 (2004) 451-463.

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[13] A.V. Lakhin, V.Z. Tarantul, L.V. Gening, Aptamers: problems, solutions and prospects, Acta Naturae, 5 (2013) 34-43.

[14] K. Carron, L. Peitersen, M. Lewis, Octadecylthiol-modified surface-enhanced Raman spectroscopy substrates: A new method for the detection of aromatic compounds, Environmental Science &

na

Technology, 26 (1992) 1950-1954.

[15] L.G. Crane, D.X. Wang, L.M. Sears, B. Heyns, K. Carron, SERS Surfaces Modified with a 4-(2Pyridylazo)resorcinol Disulfide Derivative: Detection of Copper, Lead, and Cadmium, Analytical Chemistry,

ur

67 (1995) 360-364.

[16] A. Pal, D.L. Stokes, J.P. Alarie, T. Vo-Dinh, Selective surface-enhanced Raman spectroscopy using a polymer-coated substrate, Analytical Chemistry, 67 (1995) 3154-3159.

Jo

[17] T. Vo-Dinh, D.L. Stokes, Surface‐enhanced Raman detection of chemical vapors with the use of personal dosimeters, Field Analytical Chemistry & Technology, 3 (2015) 346-356. [18] V.M. Szlag, R.R. Sarahi, H.E. Jiayi, N.V. Hudson-Smith, K. Hyunho, L. Ngoc, T.M. Reineke, C.L. Haynes, Molecular Affinity Agents for Intrinsic Surface-enhanced Raman Scattering (SERS) Sensors, ACS Applied Materials & Interfaces. [19] J. Kubackova, G. Fabriciova, P. Miskovsky, D. Jancura, S. Sanchez-Cortes, Sensitive surface-enhanced Raman spectroscopy (SERS) detection of organochlorine pesticides by alkyl dithiol-functionalized metal nanoparticles-induced plasmonic hot spots, Anal Chem, 87 (2015) 663-669. 18

[20] L. Guerrini, J.V. Garciaramos, C. Domingo, S. Sanchezcortes, Nanosensors Based on Viologen Functionalized Silver Nanoparticles: Few Molecules Surface-Enhanced Raman Spectroscopy Detection of Polycyclic Aromatic Hydrocarbons in Interparticle Hot Spots, Analytical Chemistry, 81 (2009) 1418-1425. [21] D. Zhang, P. Liang, Z. Yu, J. Huang, D. Ni, H. Shu, Q.-m. Dong, The effect of solvent environment toward optimization of SERS sensors for pesticides detection from chemical enhancement aspects, Sensors and Actuators B: Chemical, 256 (2018) 721-728. [22] G. Stefan, Semiempirical GGA-type density functional constructed with a long-range dispersion correction, Journal of Computational Chemistry, 27 (2010) 1787-1799. [23] M.R. Lopez-Ramirez, L. Guerrini, J.V. Garcia-Ramos, S. Sanchez-Cortes, Vibrational analysis of herbicide diquat: A normal Raman and SERS study on Ag nanoparticles, Vibrational Spectroscopy, 48 (2008) 58-64. [24] P. Liu, X. Han, B. Zhao, X.U. Weiqing, X. Wang, Surface-enhanced Raman Scattering-based Diquat Detection, Chemical Journal of Chinese Universities, (2015) 1517-1520.

ro of

[25] S. Tang, Y. Li, H. Huang, P. Li, Z. Guo, Q. Luo, Z. Wang, P.K. Chu, J. Li, X.F. Yu, Efficient Enrichment and Self-Assembly of Hybrid Nanoparticles into Removable and Magnetic SERS Substrates for Sensitive Detection of Environmental Pollutants, Acs Applied Materials & Interfaces, 9 (2017) 7472.

[26] Preparation of Au Nanoparticles and the Study of Their Property as the Surface Enhanced Raman Scattering Substrates, Journal of Light Scattering, 25 (2013).

-p

[27] K. Jana, F. Gabriela, M. Pavol, J. Daniel, S.C. Santiago, Sensitive surface-enhanced Raman spectroscopy

(SERS) detection of organochlorine pesticides by alkyl dithiol-functionalized metal nanoparticles-induced plasmonic hot spots, Analytical Chemistry, 87 (2015) 663-669.

re

[28] L. Guerrini, A.E. Aliaga, J. Cárcamo, J.S. Gómez-Jeria, S. Sanchez-Cortes, M.M. Campos-Vallette, J.V. García-Ramos, Functionalization of Ag nanoparticles with the bis-acridinium lucigenin as a chemical assembler in the detection of persistent organic pollutants by surface-enhanced Raman scattering,

lP

Analytica Chimica Acta, 624 (2008) 286-293.

[29] M.I. Hernándezcastillo, O. Zacamorán, P. Zacamorán, A. Orduñadiaz, R. Delgadomacuil, M. Rojaslópez, Surface-enhanced Raman scattering of the adsorption of pesticide endosulfan on gold nanoparticles, (2015) 584-589.

na

Journal of Environmental Science & Health.part.b Pesticides Food Contaminants & Agricultural Wastes, 50 [30] M.I. Hernández-Castillo, O. Zaca-Morán, P. Zaca-Morán, A. Orduña-Diaz, R. Delgado-Macuil, M. RojasLópez, Surface-enhanced Raman scattering of the adsorption of pesticide endosulfan on gold

ur

nanoparticles, Journal of Environmental Science and Health, Part B. [31] E.G. Brutan, G.T. Voronina, N.I. Dvorovenko, A.A. Kolesnikova, A.V. Sechkarev, Effects of temperature and phase state on the C-H frequencies in the Raman spectra of organic compounds, Soviet Physics

Jo

Journal, 10 (1967) 80-80.

[32] M.I. Hernández-Castillo, O. Zaca-Morán, P. Zaca-Morán, A. Ordu?a-Diaz, R. Delgado-Macuil, M. RojasLópez, Surface-enhanced Raman scattering of the adsorption of pesticide endosulfan on gold nanoparticles, Journal of Environmental Science & Health.part.b Pesticides Food Contaminants & Agricultural Wastes, 50 (2015) 584-589. [33] X. Zhou, G. Liu, H. Zhang, Y. Li, W. Cai, Porous zeolite imidazole framework-wrapped urchin-like AuAg nanocrystals for SERS detection of trace hexachlorocyclohexane pesticides via efficient enrichment, J Hazard Mater, 368 (2019) 429-435.

19

[34] M.L. Nicholas, D.L. Powell, T.R. Williams, R.H. Bromund, Reference Raman spectra of DDT and five structurally related pesticides and of five pesticides containing the norbornen group, J Assoc Off Anal Chem, 59 (1976) 197-208. [35] A.P. Paula, F. Erwan, R.A. Alvarez-Puebla, L.M. Liz-Marzán, B. Mathias, Recyclable molecular trapping and SERS detection in silver-loaded agarose gels with dynamic hot spots, Analytical Chemistry, 81 (2009) 9233-9238. [36] B.F. Rud'Ko, N.A. Krinitsyna, V.G. Moskalenko, Raman spectral analysis for determination of the γisomer concentration in hexachlorocyclohexane, Journal of Applied Spectroscopy, 6 (1967) 529-532. [37] L. Guerrini, J.V. García-Ramos, S. Sánchez-Cortés, C. Domingo, Building Highly Selective Hot Spots in Ag Nanoparticles Using Bifunctional Viologens: Application to the SERS Detection of PAHs, J.phys.chem.c, 112 (2008) 7527-7530. [38] L. Yang, P. Li, H. Liu, X. Tang, J. Liu, A dynamic surface enhanced Raman spectroscopy method for ultrasensitive detection: from the wet state to the dry state, Chem Soc Rev, 44 (2015) 2837-2848.

ro of

[39] X. Dong, H. Gu, J. Kang, X. Yuan, J. Wu, Comparative study of surface-enhanced Raman scattering activities of three kinds of silver colloids when adding anions as aggregating agents, Colloids & Surfaces A Physicochemical & Engineering Aspects, 368 (2010) 142-147.

[40] S. Kruszewski, M. Cyrankiewicz, Activation of Silver Colloids for Enhancement of Raman Scattering, Acta Physica Polonica A, 119 (2011) 1018-1022.

-p

[41] E. Brouzes, M. Medkova, N. Savenelli, D. Marran, M. Twardowski, J.B. Hutchison, J.M. Rothberg, D.R.

Link, N. Perrimon, M.L. Samuels, Droplet microfluidic technology for single-cell high-throughput screening, Proceedings of the National Academy of Sciences of the United States of America, 106 (2009) 14195-

Jo

ur

na

lP

re

14200.

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