Two-dimensional [email protected] nanodot array for sensing dual-fungicides in fruit juices with surface-enhanced Raman spectroscopy technique

Journal Pre-proofs Two-dimensional Au@Ag Nanodot Array for Sensing Dual-Fungicides in Fruit Juices with Surface-Enhanced Raman Spectroscopy Technique Kaiqiang Wang, Da-Wen Sun, Hongbin Pu, Qingyi Wei PII: DOI: Reference:

S0308-8146(19)32061-8 https://doi.org/10.1016/j.foodchem.2019.125923 FOCH 125923

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Food Chemistry

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20 February 2019 15 October 2019 17 November 2019

Please cite this article as: Wang, K., Sun, D-W., Pu, H., Wei, Q., Two-dimensional Au@Ag Nanodot Array for Sensing Dual-Fungicides in Fruit Juices with Surface-Enhanced Raman Spectroscopy Technique, Food Chemistry (2019), doi: https://doi.org/10.1016/j.foodchem.2019.125923

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Two-dimensional Au@Ag Nanodot Array for Sensing Dual-Fungicides in Fruit Juices with Surface-Enhanced Raman Spectroscopy Technique

Kaiqiang Wang1,2,3, Da-Wen Sun1,2,3,4, Hongbin Pu1,2,3, Qingyi Wei1,2,3

1

School of Food Science and Engineering, South China University of Technology, Guangzhou 510641, China

2

Academy of Contemporary Food Engineering, South China University of Technology, Guangzhou Higher Education Mega Center, Guangzhou 510006, China

3

Engineering and Technological Research Centre of Guangdong Province on Intelligent Sensing and Process Control of Cold Chain Foods, Guangzhou Higher Education Mega Center, Guangzhou 510006, China 4

Food Refrigeration and Computerized Food Technology (FRCFT), Agriculture and Food Science Centre, University College Dublin, National University of Ireland, Belfield, Dublin 4, Ireland

Abstract: The design of a novel and reliable plasmonic platform for detecting multiple chemical contaminants in the complex matrix is an exciting topic in the food industry. Herein, a highperformance surface-enhanced Raman scattering (SERS) two-dimensional (2D) nanodot array was designed through liquid-liquid interfacial self-assembly of the core-shell nanoparticles (Au@Ag NPs) and exploited for assessment of dual-fungicides in pear, apple, and orange juices. The 2D Au@Ag nanodot array delivered good uniformity and reproducibility with the substrate-to-substrate relative standard deviation values of 10.51%. This substrate could be used for detecting thiram and thiabendazole in aqueous solutions with the limit of detection of 0.0011 and 0.051 ppm, respectively.



Corresponding author. School of Food Science and Engineering, South China University of Technology, Guangzhou 510641, China. Email: [email protected], URLs: http://www.ucd.ie/refrig; http://www.ucd.ie/sun 1

Furthermore, satisfactory recoveries ranging from 76% − 134% for the juices were obtained, demonstrating that the high-throughput 2D Au@Ag nanodot arrays are promising for their applications as sensitive SERS platforms for monitoring chemical contaminants in food products, especially in the beverage industry. Keywords: SERS, liquid-liquid interface, 2D nanodot array, pesticides, fruit juice

1. Introduction Pesticides are a kind of agrochemicals, widely applied in agriculture to enhance crop production, by protecting different crops diseases or pest attacks. Among such chemicals, fungicides are extensively used to control black spots, gray mold, brown spots, powdery mildew or other fungal diseases in crops. However, in addition to plant protection, such chemical residues can also be part of human food during processing, equipment handling, air, negligence or through any other natural means. Such accidental admixing of health hazardous chemicals in food items is an alarming health concern throughout the world, as such contaminations would induce severe irreversible damage to the human organs (Elbaz et al., 2009). Recently, numerous studies have been reported about pesticide contamination in different food products such as fruit, vegetable, honey, water, and other items. Fruit juices, a great source of phytonutrients and other essential constituents for consumers, are also prone to pesticide contamination. Therefore, it not only needs to strictly regulate the use of pesticides by stipulating the maximum residue limit (MRL) but also requires to develop effective detection methods for assuring food safety. The widely available methods for monitoring pesticides in fruit including chromatography and mass spectroscopy-based techniques, exhibit excellent sensitivity for quantitative detection of pesticides at ultra-low levels (Niessen et al., 2006; Rial-Otero et al., 2007). However, these methods have some drawbacks such as cost-ineffective, labor-intensive, time-consuming, and requiring tedious and complex sample pretreatment steps (Alsammarraie & Lin, 2017). Therefore, highly sensitive, fast and reliable methods are required to be explored for ensuring the safety of each product in the market. 2

Surface-enhanced Raman scattering (SERS) is an intriguing and powerful analytical method in biochemical assays due to its advantages in ultrasensitive detection and incomparable superiority in multiple molecular label-free identifications (Schlucker, 2014). Therefore, the SERS-based analytical methods have increasingly attracted attention in various aspects, including quantitative detection of chemical contaminants such as illegal drugs, pesticides and mycotoxins at ultra-low levels (He et al., 2014; Luo et al., 2016; Pan et al., 2018; Yaseen et al., 2018; Mandrile et al., 2018; Jiang et al., 2019; Pu et al., 2019), as well as analysis of complex systems, such as lipids, proteins, DNA, microorganisms and cells (Liu et al., 2017; Pallaoro et al., 2015; Matthews et al., 2015; Wang et al., 2018). In recent years, the SERS method has been integrated with various plasmonic nanostructures to investigate pesticides in different fruit juices. For instance, Luo et al. (2018) and Zhao et al. (2019) developed the gold nanoparticles (Au NPs) based SERS chemosensors to detect paraquat and atrazine in apple juice, which could achieve the limit of detection (LOD) of 100 and 1.2 μg/L, respectively. Likewise, Feng et al. (2017) synthesized silver nanoparticles (Ag NPs) as a SERS and colorimetric dual sensor to determine chlorpyrifos in apple juice. The lowest detectable concentration was 10 μg/L. Subsequently, Feng et al. (2018) also reported an innovative molecularly imprinted solid-phase extraction-SERS chemosensor with silver colloid as a substrate to detect thiabendazole in orange juice with the LOD of 4 ppm Generally, the detection performance of a SERS sensor is closely related to the type, size, shape, and the gap between metallic nanoparticles. In particular, it has been reported that the electromagnetic enhancement is considered as the dominant contributor towards the overall SERS effect (Stiles et al., 2008; Zong et al., 2018), and strong localized surface plasmon resonance (LSPR) can be generated between adjacent nanoparticles with sub-10 nm gaps, leading to tremendous amplification of the Raman signal of molecules located in the nanogap (Wang et al., 2005). Therefore, the self-assembly ordered nanoparticle arrays have become emerging ideal SERS substrates due to their potential to generate intense “hot spots” at the junction of neighboring nanoparticles (Alsammarraie & Lin, 2017; 3

Jiang et al., 2012). Recently a self-assembled standing gold nanorod array on silicon slide was reported, which could be used as a highly sensitive technique for detecting a variety of pesticides in fruit juices (Zhang et al., 2015; Alsammarraie & Lin, 2017). However, the procedure for fabrication of the standing gold nanorod array was tedious and time-consuming, which required at least five days. In comparison, the self-assembled nanoparticle array at the liquid-liquid interface (LLI) showed the advantage of low-cost fabrication, no need for complex engineering, and easy renewability (Edel et al., 2016). In recent years, several kinds of LLI self-assembly nanoparticle arrays have been successfully developed, such as gold nanospheres arrays, gold trisoctahedron arrays, and gold nanorods arrays, and demonstrated that these substrates could be used as prospective material platforms in many fields including SERS sensing, catalysts, and nanophotonics (Dong et al., 2018; Ma et al., 2016; Liu et al., 2018). Regarding the SERS performance of these plasmonic arrays, although the gold nanostructures with uniform morphologies were conducive to create highly ordered arrays, the Raman enhancement of gold nanostructures was much weaker than silver nanostructures. In contrast, the shape of the silver nanostructures is more difficult to control. Alternatively, the bimetallic core-shell nanostructures have received increasing attention recently, as they synergistically combined the excellent stability of gold nanoparticles and fascinating optical characteristics of silver nanoparticles (Li et al., 2017; Wang et al., 2019b). However, few studies have focused on the fabrication of LLI self-assembly bimetallic nanoparticle arrays for pesticide detection. The objective of the current study was to develop a SERS method coupled with the LLI self-assembly Ag-coated Au nanoparticles (Au@Ag NPs) two-dimensional (2D) nanodot array for the rapid detection of dual-fungicides (thiram and thiabendazole) in fruit juices including pear, apple, and orange juices (Figure 1). Firstly, Au NPs with a diameter of around 30 nm were synthesized, and the Ag shell was then deposited over the Au core with a seed-growth method for fabrication of Au@Ag NPs. Subsequently, the prepared Au@Ag NPs were self-assembled at the cyclohexane/water biphasic interface, forming a densely packed nanoparticle 2D array by the rapid injection of inducer. After the 4

spontaneous evaporation of the organic phase, the created 2D array was transferred onto a silicon wafer as a SERS-active substrate for fungicides detection. To the best of our knowledge, this was the first study to combine the LLI 2D Au@Ag nanodot array with the SERS technique for the detection of fungicides in fruit juices. It is also anticipated that the developed 2D Au@Ag nanodot array could provide an ideal SERS platform candidate for sensing multiple chemical contaminants in foods in the future.

2. Materials and Methods 2.1. Chemicals Trisodium citrate, ascorbic acid, silver nitrate (AgNO3), Rhodamine 6G (R6G), thiram (THR), thiabendazole (TBZ), primary secondary amine (PSA) sorbent, and C18 sorbent were obtained from Aladdin Reagent Co., Ltd. (Shanghai, China). Chloroauric acid (HAuCl4·4H2O), cyclohexane, hexane, n-pentane, isoamyl acetate, ethanol, methanol, islpropanol, acetone, and acetonitrile were purchased from Sinopharm Chemical Reagent Co., Ltd. (Beijing, China). Silicon wafer (p-type, 1 cm × 1 cm) was purchased from Topvendor Technology Co., Ltd. (Beijing, China). Before the preparation of Au NPs and core-shell Au@Ag NPs, all of the magnetic stirring bars and glassware were cleaned with aqua regia (HCl:HNO3 = 3:1, v/v) for over 24 h. Ultrapure water prepared by a Milli-Q system (Millipore Corp., Bedford, USA) was used to prepare all the required solutions.

2.2. Preparation of Au NPs and core-shell Au@Ag NPs Firstly, Au NPs with a diameter of around 30 nm were synthesized by the reduction of HAuCl4·4H2O using trisodium citrate, as reported in our previous study (Wang et al., 2019a). The prepared Au NPs colloid was injected into Eppendorf tubes (Eppendorf, Hamburg, Germany), and then centrifuged at 3663 g for 15 min. Afterward, the supernatant was removed, and the resultant precipitates were redispersed in 3 mL of ultrapure water containing 0.02% trisodium citrate. 5

Au@Ag NPs were synthesized through a seed-mediated growth process. In a typical run, an aliquot of 3 mL of as-prepared Au NPs was injected into a 10 mL Eppendorf tube. Afterward, 125 μL of 10 mM ascorbic acid was injected into the solution under vigorous shaking by an IKA MS 3 digital shaker (IKA Inc., Staufen im Breisgau, Germany), and then 125 μL of 10 mM AgNO3 solution was dropwise added to the mixture at a rate of one drop per 40 s. The resultant solution was reacted in the dark for 30 min at 25 °C to fabricate the Au@Ag NPs.

2.3. Protocol for interfacial self-assembly of 2D Au@Ag nanodot array The beaker glassware and silicon wafer for preparing and for transferring the interfacial self-assembly 2D Au@Ag nanodot arrays were cleaned by immersing in a piranha solution (H2SO4:H2O2 = 7:3, v/v) for 2 h, followed by rinsing with ultrapure water and drying with nitrogen gas. The self-assembly 2D Au@Ag nanodot array was fabricated at the organic/aqueous interfacial system. In details, 3 mL of the Au@Ag NPs colloid was poured into the above-treated beaker glassware, and 1 mL of the organic phase (including cyclohexane, hexane, n-pentane, or isoamyl acetate) was slowly added to the solution to form organic/aqueous interface. After that, 1.5 mL of the inducer (including ethanol, methanol, islpropanol, acetone, or acetonitrile) was then rapidly injected into the solution to entrap Au@Ag NPs at the organic/aqueous interface. After the organic phase solution was evaporated spontaneously, the entrapped Au@Ag NPs were self-assembled to a densely packed array at the organic/aqueous interface. The silicon wafer was used to transfer the 2D nanodot array according to a previously reported method (Li et al., 2006), and then air-dried at room temperature for further use.

2.4. Characterization The UV-Vis spectra of nanoparticle colloids were acquired using a spectrophotometer (UV-1800, Shimadzu Co., Kyoto, Japan). The transmission electron microscopy (TEM), high angle annular dark field-scanning transmission electron microscopy (HAADF-STEM) and scanning transmission electron 6

microscopy-energy dispersive X-ray spectroscopy (STEM-EDS) elemental mapping images were taken from a high-resolution transmission electron microscope (JEM-2100F Plus, JEOL Ltd., Tokyo, Japan) at an acceleration voltage of 200 kV. The scanning electron microscopy (SEM) images of the interfacial self-assembly 2D Au@Ag nanodot arrays were acquired using a field emission scanning electron microscope (Zeiss Merlin FE-EM, Carl Zeiss NTS GmbH, Oberkochen, Germany) with an acceleration voltage of 10 kV.

2.5. SERS detection of fungicides in standard solutions A 100 ppm stock solution of THR and TBZ fungicides was first prepared in methanol and then diluted to a series of concentrations using ultrapure water. Raman spectra were acquired by a laser confocal Raman microscope system (LabRAM HR, Horiba France SAS, Villeneuve d'Ascq, France), which was equipped with a cooled charge-coupled device detector and a 633 nm He-Ne laser (laser power: 4.25 mW). Before SERS measurements, the 2D Au@Ag nanodot array substrates were immersed into the fungicides solution for 1 h at room temperature under slowly shaking by an IKA MS 3 digital shaker (IKA Inc., Staufen im Breisgau, Germany). The SERS spectrum was obtained under a 50× objective lens (numerical aperture NA = 0.5). The integration time for each spectrum was 15 s with 2 accumulations.

2.6. Detection of fungicides in fruit juices Firstly fresh pear, apple, and orange juices were prepared by denucleation, homogenization, and filtration steps used in our previous study (Pan et al., 2017). Then juices were spiked with THR (0.05 – 2.5 ppm) or TBZ (0.5 – 10 ppm) followed by centrifugation at 2935 g for 5 min. In order to suppress interference from non-targeted SERS constituents such as pectin, sugar and organic acid, a portion of 5 mL supernate was cleaned up by mixing with 1 g PSA sorbent and 1 g C18 sorbent, and then centrifuged at 2935 g for 5 min. For SERS detection, the as-prepared 2D nanodot array substrate was 7

immersed into the supernatant with slowly shaking for 1 h, and finally air-dried at room temperature. The SERS spectrum was obtained using a 633 nm laser (power: 4.25 mW) under a 50× objective lens (NA = 0.5) with an integration time of 15 s.

3. Results and Discussion 3.1. Characterization of 2D Au@Ag nanodot array The successful synthesis of core-shell Au@Ag NPs and the corresponding 2D nanodot array were demonstrated using the UV-Vis spectroscopy, TEM, and SEM methods. As shown in Figure 2A, the UV-Vis spectra of Au NPs showed that the maximum absorbance was centered at 525 nm, due to the surface plasmon resonance (SPR). With the deposit of Ag shell over the Au core, the purple color of the colloid turned into orange-yellow, and the UV-Vis spectra showed two SPR peaks. The band centered at 488 nm resulting from the SPR of Au core and the other one at 395 nm was responded by the Ag shell. After the process of interfacial self-assembly, there was a highly packed metal film formed between the interface of organic and aqueous phases. Consequently, the color of the residual Au@Ag NPs colloid turned into pale yellow color, and the SPR of the residual colloid was remarkably reduced due to the entrapment of the Au@Ag NPs to the organic/aqueous interface. After the evaporation of the organic phase, the array was transferred onto a glass slide for measuring the UVVis absorption spectrum. A new band centered at 766 nm was observed, which might be due to strong plasmonic coupling between tightly adjacent Au@Ag NPs of the 2D nanodot array (Zhong et al., 2014). Furthermore, the morphologies of the prepared Au NPs and the 2D Au@Ag nanodot array are displayed in Figure 3. As evidenced in Figure 3A, the average diameter of the synthesized Au NPs was around 30 nm. In the case of core-shell Au@Ag NPs, the average size of nanoparticles was around 40 nm, indicating that the Ag shell thickness over Au@Ag NPs was approximately 5 nm (Figure 3B). Moreover, due to the significant difference in the atomic number between Ag atom and Au atom, a structure of bright core and the gray shell was validated from the HAADF-STEM image (Figure 3C). 8

Meanwhile, Au core in red color and Ag shell in green color architecture could be observed from the superimposed STEM-EDS image of elemental Au and Ag, evidencing the successful fabrication of Au@Ag NPs (Figure 3D-F). The sensitivity and reproducibility of the self-assembled plasmonic array are primarily determined by the size and shape of metal nanoparticles (Dong et al., 2018; Liu et al., 2018). In our previous studies, it was demonstrated that the Au NPs of 30 nm and Au@Ag NPs with an Ag shell of 5 nm showed uniform morphologies and stable SERS signals (Wang et al., 2019b; Wang et al., 2019c). Therefore, nanoparticles with similar sizes were used to prepare the self-assembled nanodot array substrate in the current experiment. As shown in Figure 3G, a representative 2D Au@Ag nanodot array SERS platform was prepared with cyclohexane as the organic phase and ethanol as the inducer. It indicated that the Au@Ag NPs were closely self-assembled, forming a monolayer of 2D nanodot array with a large area, which was mainly attributed to van der Waals attractive forces between core-shell nanoparticles (Shin et al., 2015; Xu et al., 2016). The key to compress the interfacial nanoparticles was associated with the interfacial tension at the organic/aqueous interface, providing the surface pressure in the formation of the monolayer 2D nanoparticle array (Li et al., 2006). Higher magnification SEM images were analyzed using J software (Version Java 1.6.0_20 64-bit; National Institutes of Health (NIH), Bethesda, Md, USA), revealing that the gap between adjacent nanoparticles was approximately 3 nm. According to previous reports, the field coupling from closely adjacent nanoparticles with sub10 nm gaps responded to the intense “hot spots” for high-sensitive SERS detection (Wang et al., 2015). In addition, although a few voids existed in some regions, the Au@Ag NPs of the self-assembly 2D array were uniformly distributed on the silicon wafer in a large area, guaranteeing the repeatability of Raman signals when using this platform for SERS measurements. More noteworthy, the fabrication of the high-throughput, low-cost SERS-active 2D nanodot array substrate was easy to handle and no expensive or sophisticated equipment was involved, thus suitable for sensing chemical contaminants in complex food matrices. 9

3.2. Assembly efficiency of different inducers and organic phases The method of preparation and application of interfacial self-assembly 2D Au@Ag nanodot arrays for SERS sensing fungicides is illustrated in Figure 1. It was reported that the entrapment of charged nanoparticles to the interface of the organic/aqueous phase must be driven by the minimization of the interfacial energy (Reincke et al., 2004). The total energy for the formation of an interfacial monolayer nanoparticles array is ultimately decided by three forces, that is, the interfacial surface tension, Coulombic repulsion and van der Waals attraction between the nanoparticles. An overriding strategy for promoting the interfacial monolayer is the reduction of the charge density on nanoparticles by adding low-dielectric solvents as inducers (Park & Park, 2008). As a result, the van der Waals attraction combined with the reduction in the Coulombic repulsion gives rise to the tendency of nanoparticles to assemble at the organic/aqueous interface with the formation of a three-phase boundary (Edel et al., 2016; Xu et al., 2016). In order to investigate the superiority of different inducers including ethanol, methanol, islpropanol, acetone, and acetonitrile, the assembly efficiencies of entrapping Au@Ag NPs from aqueous phase onto the interface of organic/aqueous were compared. The UV-Vis absorbance spectra of the residual Au@Ag NPs colloid after assembling equilibrium under different inducers are shown in Figure 2B. In this study, the assembly system was 3 mL Au@Ag NPs colloid solution and 1 mL cyclohexane solvent. It was indicated that the intensity of the Au@Ag NPs absorption peak at 395 nm due to Ag shell plasmon resonance was 0.75. After the rapid addition of 1.5 mL inducers, all of the intensity of UV-Vis spectra were reduced significantly. The inset histogram illustrated the assembly efficiency (E), which is described as:

(

𝐴𝑅

)

𝐸 = 1 ― 𝐴𝑜 × 100%

(1)

where AO is the absorbance of the UV-Vis spectrum at 395 nm of Au@Ag NPs colloid, and AR is the corresponding absorbance of residual Au@Ag NPs after assembly equilibrium. As indicated in Figure 10

2B, ethanol, methanol, and islpropanol could induce a high assembly efficiency of 64%, 62%, and 60%, respectively. Therefore, we selected ethanol as the inducer to prepare the 2D Au@Ag NP array. In addition, it was also reported that the polarity of the organic solvent could affect the assembly process at the oil/water interface. Generally, the polarity of organic solvent closer to that of water would have more interaction with water, which could favor the assembly process due to the synergistic effect of the interfacial energy and polarity of different solvents (Liu et al., 2012). Therefore, the assembly efficiency was further investigated as affected by using different solvents including cyclohexane, hexane, n-pentane, and isoamyl acetate as the organic phase (Figure 2C). The polarity of the solvents was water > isoamyl acetate > cyclohexane > hexane > n-pentane. As indicated in Figure 2C, higher E was found at the isoamyl acetate/water and cyclohexane/water interface. The results were in accordance with previous reports (Liu et al., 2012). In comparison, the volatilization of cyclohexane above the water phase was much faster than that of isoamyl acetate. Therefore, ethanol and cyclohexane were selected as the inducer and organic phase to prepare the 2D array for SERS sensing in the following experiments.

3.3. Sensitivity of 2D Au@Ag nanodot array SERS platform The ultra-sensitive detections of SERS methods totally depend on the sensitivity of employed SERS active substrates. For this reason, numerous studies have been conducted to control the coupling of plasmonic fields, by adjusting the interspace between the adjacent metal nanoparticles (Ma et al., 2016; Liu et al., 2018). The sensitivity of the currently designed 2D Au@Ag nanodot array was investigated by a probe molecule R6G. The enhancement factor (EF) of the substrate is displayed in Figure S1. Several characteristic peaks appeared when R6G adsorbed with 2D Au@Ag nanodot array. A peak at 612 cm−1 was corresponding to C-C-C bond stretching vibration, while the Raman band at 1183 cm−1 was due to C-H in-plane bending. Likewise, the peaks observed at 1313, 1363, and 1511 cm−1 were ascribed to carbon skeleton stretching modes. Herein, the EF was calculated by targeting the peak at 11

612 cm−1 under the 633 nm laser, and EF is defined as follows: EF =

𝐼𝑆𝐸𝑅𝑆 𝐼𝑁𝑅

𝑁𝑁𝑅

× 𝑁𝑆𝐸𝑅𝑆

(2)

where ISERS and INR are the SERS intensity and normal Raman intensity of R6G at 612 cm−1, respectively; NSERS and NNR are the corresponding concentration of R6G for SERS and normal Raman measurements, respectively. The EF value was calculated as 1.2 × 106 for the 2D Au@Ag nanodot array (calculation details are available in the Supporting Information). In comparison, Au@Ag NPs colloid was also used to detect R6G (10−7 M), and the results are displayed in Figure S1. SERS intensity at 612 cm−1 from 2D Au@Ag nanodot array was about threefold higher Au@Ag NPs colloid. This was probably because the assembled Au@Ag NPs exhibited smaller interspace between the adjacent nanoparticles, hence resulting in denser LSPR “hot spots” and higher enhancement effect.

3.4. Uniformity and reproducibility of 2D Au@Ag nanodot array SERS platform In addition to high sensitivity, uniformity and reproducibility are also compulsory requirements for a novel proposed SERS platform for practical applications. The development of plasmonic array at LLI still has some challenges. As the self-assembly performance is closely related to the shape and size distribution of metal nanoparticles, and one of the great challenges is to create the self-assembled array with uniform morphology (Park & Park, 2008). As can be seen from Figure 3G, the dense 2D domains coexist with some voids, and in some areas, the nanoparticles were stacked together, which may affect the uniformity of SERS signals in different regions of the substrate. To evidence the uniformity of the fabricated 2D nanodot array, the point-to-point stability was investigated with a total of 196 SERS spectra within an area of 40 × 40 μm2 in the array (Figure 4A). It was observed that the trend of the collected SERS spectra of R6G in this area was similar, and the SERS intensity did not show a significant difference. Furthermore, the Raman mapping of the vibration modes at 612, 1183, and 1363 cm−1 of R6G molecules absorbed on 2D Au@Ag nanodot array are shown in Figure 4B. Changes in different colors from bright to dark represent the SERS intensity distributions. In the case of these 12

three peaks, the color distributions of these Raman images were uniform and no obvious SERS intensity fluctuation occurred. The relative standard deviation (RSD) of SERS intensities at 612, 1183, and 1363 cm−1 were calculated as 8.51%, 9.21%, and 9.68%, respectively, demonstrating that the homogeneity of SERS signals on the 2D Au@Ag nanodot array was acceptable. Moreover, the reproducibility of the substrate-to-substrate is another concern for the practical use of the SERS substrate. Therefore, the reproducibility of the 2D Au@Ag nanodot array SERS platform was estimated by investigating the SERS intensity variation from different batches. Fifty SERS spectra of R6G molecules at 10−7 M from six batches of the 2D Au@Ag nanodot arrays platforms were randomly collected, and the corresponding SERS intensities at 612 cm−1 is plotted in Figure 4C, indicating that the Raman intensity at 612 cm−1 fluctuated among 8108 – 11964 with the RSD value of 10.51%. Many researchers have accepted that the RSD value from point-to-point and substrate-tosubstrate of a novel SERS sensing platform should be less than 20% (Natan, 2006; Luo et al., 2009; Cara et al., 2018). Therefore, the uniformity and reproducibility of the currently developed 2D Au@Ag nanodot array can act as a desirable SERS platform for quantitative analysis in the future.

3.5. Detection of fungicides using 2D Au@Ag nanodot array The weak background interference of the SERS-active substrate is a crucial concern for practical quantitative analysis. It can be seen that the SERS spectrum of the 2D Au@Ag nanodot array substrate only had one sharp band at 520 cm−1, while it did not show any other obvious Raman peaks with THR concentration at 0 ppm (Figure 5A1). Because the nanodot array was transferred to a silicon wafer, the band at 520 cm−1 was ascribed to monocrystalline silicon. The result indicated the prepared 2D Au@Ag nanodot array had weak background interference during SERS detection. In this case, the prepared 2D Au@Ag nanodot array was used to detect THR in aqueous solution. Five characteristic Raman peaks for THR at 562, 929, 1146, 1384, and 1514 cm−1 were determined, which were in accordance with previous literature (Table S1). The strongest Raman peak at 1384 cm−1 was due to 13

CN stretching and symmetric CH3 deformation modes. The peak located at 562 cm−1 was assigned to the S−S stretching mode, while a peak at 929 cm−1 was attributed to C=S stretching and C-N stretching vibrations. The peaks at 1146 and 1514 cm−1 could be ascribed to the C-N stretching and the rocking CH3 modes. The SERS signals of these characteristic Raman peaks increased with the concentration of THR. Notably, the characteristic band at 1384 cm−1 was discerned down to 0.005 ppm THR concentration (Figure 5A1). Figure 5B1 showed that the logarithmic SERS intensity of THR at 1384 cm−1 band was in linear growth with an increase in the logarithmic THR concentration from 0.005 to 1.0 ppm. The fitted equation was y = 0.808x + 4.576 with a coefficient of determination (R2) of 0.980. Furthermore, Au@Ag nanodot 2D array was also employed for quantitative SERS analysis of a series of concentrations of TBZ dissolved in aqueous solution. As shown in Figure 5C1, the SERS spectra of TBZ absorbed on the 2D Au@Ag nanodot array showed several distinct Raman peaks. Among them, the most prominent enhanced signature peaks of TBZ molecules were found at 782 (C-S stretching, in-plane C=N bending) and 1009 cm−1 (C-N stretching, C-C stretching). The peak located at 1280 cm−1 was due to the ring stretching vibrations, and the peak at 1577 cm−1 was assigned to C=N stretching modes, while other peak assignments are listed in Table S1. Similarly, the intensity of these characteristic peaks also increased with TBZ concentrations ranging from 0.05 to 10 ppm. The linear relationship of the logarithmic SERS intensity at 782 cm−1 as a function of the logarithmic TBZ concentration is illustrated in Figure 5D1. The calibration curve was y = 0.847x + 3.726 with R2 of 0.973. In addition, the LOD and limit of quantitation (LOQ) of this approach were calculated using the equation of LOD = 3Sb + Yb and LOQ = 3.3LOD, respectively (Thomsen et al., 2003). In the formula, Sb represents the standard deviation of the spectrum intensity of the blank samples at Raman shift of 1384 or 782 cm−1, and Yb is the average intensity of the blank. The LOD values of our method for THR and TBZ in aqueous solutions were 0.0011 and 0.051 ppm, respectively, suggesting that the current SERS platform showed high sensitivity for sensing chemical contaminants at lower levels. The 14

current outcomes revealed that the intriguing interfacial self-assembly 2D Au@Ag nanodot array as a platform with high sensitivity, excellent repeatability, and low cost holds powerful potential applications for quantitative SERS applications.

3.6. Spike test of fungicides in fruit juices THR and TBZ are among the commonly used fungicides in agriculture production to prevent fungal diseases both during fruit development and postharvest storage. In this study, to further validate the practical application of the fabricated 2D Au@Ag nanodot array, it was coupled with the SERS technique to analyze THR and TBZ fungicides spiked in pear, apple, and orange juices. Figure 5A2A4 and Figure 5C2-C4 showed the average SERS spectra of THR and TBZ in these juice samples. Notably, the SERS intensities of THR and TBZ were lower than those detected in the standard solutions, which might be resulted from the interferences of the food components, such as sugars, pectins, vitamins, and proteins in fruit juices. These food components were likely to compete with the fungicides for the limited binding sites on the substrate, increasing the distance between the substrate surface and the analyte and thus decreased the enhancement ability of the SERS substrate. The observation was in accordance with other reports (Saute and Narayanan, 2013; Alsammarraie and Lin, 2017). Nonetheless, the distinctive peaks of THR at 1384 cm−1 and of TBZ at 782 cm−1 can still be clearly distinguished. Their SERS intensities were decreased with the reduction of THR concentration from 2.5 to 0.05 ppm, and with the decrease of TBZ concentrations from 10 to 0.5 ppm in fruit juices, respectively. The calibration curves of SERS intensities versus the concentrations of THR and TBZ are plotted in Figure 5B2-B4 and Figure 5D2-D4. The data suggested that R2 for all the calibration curves were higher than 0.96, revealing the 2D Au@Ag nanodot array substrate coupled with the SERS technique had potential as a simple and effective method for sensing THR and TBZ in juice samples. Besides, the LODs were calculated as 0.0052, 0.013, and 0.059 ppm for THR, and 0.10, 0.18, and 0.68 ppm for TBZ in pear, apple, and orange juices, respectively. The difference in LODs may be due to 15

different food components contained in these juice samples (Alsammarraie & Lin, 2017). Nonetheless, the LODs and LOQs values were lower than the MRLs for THR (7 ppm) and TBZ (5 ppm) in fruits prescribed by the USA Environmental Protection Agency (EPA, 2019). In addition, the currently developed SERS method was also compared with other reported SERS methods for pesticide detections in fruit juices (Table S2). It was found that most of these methods applied pure silver or gold nanostructures as SERS-active substrates, which might not achieve a low detection limit in some cases. In the current study, the bimetallic 2D Au@Ag nanodot array was established as a novel SERS substrate. As demonstrated in our previous study, the closely packed Au@Ag NPs could generate intensive “hot spots” for SERS analysis (Wang et al., 2019c). Therefore, the LODs of our proposed method can be highly comparable with or even much lower than those already reported results. The recoveries of THR and TBZ from fruit juices were calculated according to the ratio of the measured value against spiked content (Table 1). Results indicated that the recovery of the currently developed method was in the range of 76% − 134%. Therefore, the 2D Au@Ag nanodot array platform coupled with the SERS technique can act as an alternative approach for rapidly sensing fungicides in fruit juices. Nevertheless, in this study, only fungicides in freshly prepared fruit juices were detected. As fruit juices would undergo complex processing steps, for example, juices would be subjected to sterilization prior to aseptic packaging and used as a flavoring ingredient or dessert, the sterilization or other treatments may affect the efficacy of the method. Therefore, to reduce the interference from food components and the effect of chemical transformation of fruit juices, the development of efficient sample pre-treatment steps, such as solid-phase extraction, should be considered for achieving more accurate detection in future studies. Furthermore, due to the narrow band spectra, the SERS technique is more convenient for simultaneously sensing multi-analytes (Li et al., 2019). In the current study, it was found that the 2D Au@Ag nanodot array substrate showed excellent SERS activity for both THR and TBZ. Therefore, 16

the substrate was used to simultaneously detect dual-fungicides (THR and TBZ) in pear juice. As shown in Figure S2, both the Raman characteristic peaks of THR at 562, 929, 1146, 1384 and 1514 cm−1, as well as those of TBZ at 782, 1010, 1280 and 1577 cm−1 could be clearly distinguished. These results revealed that the 2D Au@Ag nanodot array substrate also showed powerful potential for simultaneously sensing multi-analytes in real samples.

Conclusions A facile approach for high-throughput fabrication of core-shell Au@Ag 2D nanodot array as a SERSactive substrate was successfully demonstrated for sensing dual-fungicides in fruit juices in the current study. The designed 2D plasmonic array was realized through the strategy of self-assembly nanoparticles at the cyclohexane/water interface with ethanol as the inducer. The closely packed plasmonic array with gaps around 3 nm between the neighboring nanoparticles provided abundant “hot spots” for the SERS analysis. The well-ordered 2D Au@Ag nanodot array was demonstrated to show high SERS activity for detecting THR and TBZ in fruit juices with low LOD and LOQ values, which were far below the acceptable residue tolerances in fruits prescribed by the USA EPA. Nevertheless, further researches are still needed for exploring the application of the developed method as a possible future detection avenue. Firstly, further optimization of the size and shape of metal nanoparticles is essential to improve the sensitivity and uniformity of the plasmonic array. Secondly, the development of some efficient sample extraction methods can achieve more accurate detection in future studies. Moreover, although our results demonstrated the feasibility of using the current SERS platform for multi-pesticides analysis, the simultaneously quantitative analysis of multi-analytes is still a great challenge since different molecules would compete for the limited binding sites on the substrate. The application of chemometrics algorithms should be a desirable avenue to differentiate and quantify multi-analytes. It is anticipated that this novel SERS platform should have a versatile opportunity for sensing a variety of chemical contaminants in the future. 17

Acknowledgments The authors are grateful to the National Key R&D Program of China (2018YFC1603404) for its support. This research was also supported by the Fundamental Research Funds for the Central Universities (2018MS056, 2017MS075), the Common Technical Innovation Team of Guangdong Province on Preservation and Logistics of Agricultural Products (2019KJ145, 2019KJ101) and the Innovation Centre of Guangdong Province for Modern Agricultural Science and Technology on Intelligent Sensing and Precision Control of Agricultural Product Qualities.

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Table 1. Results of recovery experiments for detecting thiram and thiabendazole in fruit juices using 2D Au@Ag nanodot array coupled with the SERS technique. Analyte

Food matrix

Thiram

Pear juice

Apple juice

Orange juice

Thiabendazole

Pear juice

Apple juice

Orange juice

Spiked (ppm)

Detected (ppm)

Recovery (%)

1.0

1.09 ± 0.19

109

0.5

0.67 ± 0.08

134

0.1

0.11 ± 0.03

110

1.0

0.84 ± 0.03

84

0.5

0.57 ± 0.04

117

0.1

0.12 ± 0.01

120

1.0

1.12 ± 0.13

112

0.5

0.41 ± 0.06

82

0.1

0.09 ± 0.01

90

5.0

5.24 ± 0.94

105

1.0

0.76 ± 0.08

76

0.5

0.55 ± 0.13

110

5.0

6.29 ± 0.70

126

1.0

1.09 ± 0.29

109

0.5

0.44 ± 0.10

88

5.0

4.64 ± 0.53

93

1.0

1.31 ± 0.22

131

0.5

0.41 ± 0.10

82

Note: the recovery was calculated according to the ratio of the measured value against spiked content.

25

Figure captions Figure 1. Scheme of preparation of interfacial self-assembly core-shell 2D Au@Ag nanodot array for SERS sensing dual-fungicides in fruit juices. Figure 2. (A) UV-Vis absorption spectra of (a) Au NPs, (b) Au@Ag NPs, and (c) Au@Ag NPs colloid after interfacial self-assembly, (d) the Au@Ag array transferred onto a glass slide, the insets are the corresponding appearance pictures. UV-Vis spectra of Au@Ag NPs after interfacial self-assembly under different (B) inducers and (C) organic phases, the insets indicate the assembly efficiency of Au@Ag NPs under the corresponding conditions. Figure 3. TEM images of (A) Au NPs and (B) Au@Ag NPs, (C) the HAADF-STEM image of Au@Ag NPs, the HAADF-STEM-EDX elemental mapping of (D) Au, (E) Ag and (F) their superimposed image, and (G) SEM image of interfacial self-assembly 2D Au@Ag nanodot array on silicon wafer, the inset is the corresponding enlarged view. Figure 4. (A) SERS spectra of 10−7 M R6G collected from the 2D Au@Ag nanodot array for Raman mapping (at 633 nm excitation, laser power 4.25 mW, 50× objective with a numerical aperture of 0.5, exposure time 1 s). (B) (a) The optical image of the 2D Au@Ag nanodot array for Raman mapping in (A), and the corresponding Raman maps targeting the R6G signal at (b) 612, (c) 1183 and (d) 1363 cm−1. (C) the SERS intensity distribution of the peak at 612 cm−1 collected from 50 randomly selected spots in 6 batches of 2D Au@Ag nanodot arrays (at 633 nm excitation, laser power 4.25 mW, 50× objective with a numerical aperture of 0.5, exposure time 10 s). Figure 5. SERS spectra of thiram (THR) in (A1) water, (A2) pear juice, (A3) apple juice, and (A4) orange juice with different concentrations collected from the 2D Au@Ag nanodot array. (B1-B4) the corresponding logarithmic SERS intensity of THR at 1384 cm−1 as a function of the logarithmic THR concentration. SERS spectra of thiabendazole (TBZ) in (C1) water, (C2) pear juice, (C3) apple juice, 26

and (C4) orange juice with different concentrations collected from the 2D Au@Ag nanodot array. (D1D4) the corresponding logarithmic SERS intensity of TBZ at 782 cm−1 as a function of the logarithmic TBZ concentration.

27

Figure 1. Scheme of preparation of interfacial self-assembly core-shell 2D Au@Ag nanodot array for SERS sensing dual-fungicides in fruit juices.

28

Figure 2. (A) UV-Vis absorption spectra of (a) Au NPs, (b) Au@Ag NPs, and (c) Au@Ag NPs colloid after interfacial self-assembly, (d) the Au@Ag array transferred onto a glass slide, the insets are the corresponding appearance pictures. UV-Vis spectra of Au@Ag NPs after interfacial self-assembly under different (B) inducers and (C) organic phases, the insets indicate the assembly efficiency of Au@Ag NPs under the corresponding conditions.

29

Figure 3. TEM images of (A) Au NPs and (B) Au@Ag NPs, (C) the HAADF-STEM image of Au@Ag NPs, the HAADF-STEM-EDX elemental mapping of (D) Au, (E) Ag and (F) their superimposed image, and (G) SEM image of interfacial self-assembly 2D Au@Ag nanodot array on silicon wafer, the inset is the corresponding enlarged view.

30

Figure 4. (A) SERS spectra of 10−7 M R6G collected from the 2D Au@Ag nanodot array for Raman mapping (at 633 nm excitation, laser power 4.25 mW, 50× objective with a numerical aperture of 0.5, exposure time 1 s). (B) (a) The optical image of the 2D Au@Ag nanodot array for Raman mapping in (A), and the corresponding Raman maps targeting the R6G signal at (b) 612, (c) 1183, and (d) 1363 cm−1. (C) the SERS intensity distribution of the peak at 612 cm−1 collected from 50 randomly selected spots in 6 batches of 2D Au@Ag nanodot arrays (at 633 nm excitation, laser power 4.25 mW, 50× objective with a numerical aperture of 0.5, exposure time 10 s).

31

Figure 5. SERS spectra of thiram (THR) in (A1) water, (A2) pear juice, (A3) apple juice, and (A4) orange juice with different concentrations collected from the 2D Au@Ag nanodot array. (B1-B4) the corresponding logarithmic SERS intensity of THR at 1384 cm−1 as a function of the logarithmic THR concentration. SERS spectra of thiabendazole (TBZ) in (C1) water, (C2) pear juice, (C3) apple juice, and (C4) orange juice with different concentrations collected from the 2D Au@Ag nanodot array. (D1D4) the corresponding logarithmic SERS intensity of TBZ at 782 cm−1 as a function of the logarithmic TBZ concentration. 32

Highlights  A 2D Au@Ag nanodot array was constructed at the biphase system for SERS analysis.

 The 2D Au@Ag nanodot array can generate vigorous electromagnetic fields.  The assay is capable of measuring fungicides in fruit juices with low LOD values.  SERS provides a rapid and sensitive way of detecting contaminants in foods.

33