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Quantitative Surface-Enhanced Raman Spectroscopy through the InterfaceAssisted Self-assembly of Three-Dimensional Silver Nanorod Substrates Siying Liu, Xiang-Dong Tian, Yun Zhang, and Jian-Feng Li Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.8b00488 • Publication Date (Web): 17 May 2018 Downloaded from http://pubs.acs.org on May 17, 2018

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Analytical Chemistry

Quantitative Surface-Enhanced Raman Spectroscopy through the Interface-Assisted Self-assembly of Three-Dimensional Silver Nanorod Substrates Si-Ying Liu,†, # Xiang-Dong Tian,*, †, # Yun Zhang,*, †, # Jian-Feng Li§ †

CAS Key Laboratory of Design and Assembly of Functional Nanostructures, and Fujian Provincial Key Laboratory of Nanomaterials, Fujian Institute of Research on the Structure of Matter, Chinese Academy of Sciences, Fuzhou 350002, China # Xiamen Institute of Rare Earth Materials, Haixi Institute, Chinese Academy of Sciences, Xiamen 361021, China § State Key Laboratory of Physical Chemistry of Solid Surfaces and Department of Chemistry, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China ABSTRACT: The realization of surface-enhanced Raman spectroscopy (SERS) to be a reliable quantitative analytical technique requires sensitive and reproducible enhancing substrates. Here, uniform three-dimensional (3D) Ag nanorod (AgNR) substrates with well-defined interlayer spacings are prepared through the air-liquid interface-assisted self-assembly of AgNR in a layer-by-layer manner. The correlation of the SERS performance with the 3D AgNR structures is performed by SERS mapping the substrates. SERS mapping reveals the excellent enhancement uniformity of the 3D substrates with the relative standard deviation (RSD) less than 10%. It finds that both of the number of layers (NL) and the length of the AgNR have effects on the SERS performance of the 3D AgNR substrates. It is demonstrated that the intergaps between layers contribute much to the SERS intensity of the 3D AgNR by creating the interlayer (out-of-plane) plasmonic coupling. The impact of the excitation wavelengths (532, 633 and 785 nm) on SERS performance is also determined. The optimal 3D AgNR structures achieved by the correlation study is further used to detect a set of related molecules (L-tryptophan (Trp), L-phenylalanine (Phe), urea and melamine). The 3D AgNR SERS of the analytes exhibits linear responses over wide concentration ranges. The sensitivity of the 3D AgNR SERS is proved by comparing to that of the current methods. Moreover, the 3D AgNR substrates maintain the performance stability during four weeks of storage.

SERS spectroscopy technique has wide applications in analytical chemistry, biosensing and imaging, as well as environmental and food safety inspection, due to the unique vibrational fingerprints and the exquisite detection sensitivity.14 Although there were great advances of SERS in past four decades, the realization of quantitative SERS analysis remains a challenge.5 There are two strategies to solve the problems. The first strategy is the addition of internal standards during the SERS detection, which can correct the fluctuations of SERS hot spots and variations of instrument factors, thus improving the detection reproducibility.6 However, the competition of targets and internal standards for the hot spots limits the wide applications of this method. Recently, SERS substrate with built-in calibration is prepared by trapping the internal standard in the nanoparticle interior, thus avoiding the competition with targets for the outside surface.7-9 Nevertheless, it is demonstrated that the buried internal standard cannot absolutely reflect the changes of the SERS hot spots in our recent study. 9 The IS strategy is mainly applied for the solution SERS substrates. The second strategy to realize quantitative SERS is the preparation of high-quality solid SERS substrates, which should meet the requirements of (1) high detection sensitivity, (2) uniform enhancement across large areas, (3) good reproducibility of the SERS measurements from batch to batch.10,11 AgFON substrates based on nanosphere lithography have been developed for quantitative detections.12 Recently,

ZnO nanorod array is used as template for the preparation of the hybrid SERS substrate, the quantification of which is demonstrated by the detection of xylene isomers.13 However, significant progresses have to be made in the substrate design to promote the applications of quantitative SERS as a routine analytical technique. 3D SERS substrates have recently attracted significant attentions due to the superior SERS performance.14 The increase of the third dimension on the 2D substrates effectively expands the detection volume and is beneficial to increase the number of hot spots available through the 3D plasmonic coupling.14-16 3D SERS substrates may allow the quantitative measurements featured with improved detection sensitivity and larger response range. However, the preparation of 3D SERS substrates is not trivial. The top-down nanofabrication approach is the most important way to prepare the high-quality 2D SERS substrates such as the two-dimensional array of dielectric nanospheres or nanopillars coated with a metallic film.12,17,18 However, the extension of the 2D nanofabrication to 3D morphology preparation is of high labor intensity and time consumption. The bottleneck of the high cost prevents the largescale manufacturing and applications of the 3D SERS substrates. At present, 3D SERS substrates are prepared through the template technique, where dielectric nanowires form the 3D scaffolds to guide the in-situ synthesis or adsorption of metal

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nanoparticles. For example, Ag nanoparticles are assembled on the electrospun nanofibers through the electrostatic attraction between them, preparing 3D SERS substrates for pH sensing. 19 Silica nanowires have been used as the 3D scaffolds for the insitu synthesis of Ag nanoparticles.20 The 3D SERS substrates exhibit high detection sensitivity to thiram.21 Although the template-mediated method can easily prepare 3D SERS substrates with low cost, the structure of the 3D substrates is disordered, including the random nanowire position and orientation and the ill-defined morphology of the metal nanoparticles. All these structural inhomogeneities prevent the employment of plasmonic coupling in a controlled manner. Evaporation induced self-assembly has been successfully developed to prepare Au nanorod superlattices as highperformance 3D SERS substrates.22 The vertically aligned Au nanorod 3D SERS substrates have been used for femtomolar detection of food contaminants, and for monitoring the intercellular signaling processes in biofilms.23 However, the coffee-ring effect during the drying process of the nanoparticle solution hampers the fabrication of large-area uniform nanostructures. Moreover, the long and delicate evaporation process restricts the scalable preparation of 3D substrates. Here we report a simple, fast and high throughput method for the preparation of 3D SERS substrates with quantitative performance. In this case, AgNRs with the diameter of 20 ± 1 nm and lengths from 53 nm to 245 nm are synthesized through the seed-mediated method as the self-assembly building blocks. 3D AgNR SERS substrates are fabricated through the air-liquid interface-assisted self-assembly in a layer-by-layer manner. AgNRs are self-assembled with the long axis parallel to the airliquid interface. Hence the thickness of 3D AgNR is precisely determined by the NL as a result of the high uniformity of the AgNR diameter. The impact of the thickness and the nanorod length of the 3D substrate on the SERS performance is systematically investigated through the SERS mapping at three laser lines (532, 633 and 785 nm). The optimized 3D substrate shows 6-fold, 14-fold and 37-fold signal increase compared to the 2D substrate (AgNR monolayer) under the 532, 633 and 785 nm laser excitations, respectively. SERS mapping proves that the SERS enhancement over large areas (55 by 55 μm2) is very uniform with the intensity RSD smaller than 10% provided that the NL is more than one layer. The optimized 3D substrate allows for the quantitative detection of urea, melamine, Trp and Phe with low detection limits. The limit detection (LOD) of urea is 5.0 × 10-5 M, about a 13-fold improvement of the sensitivity. The linear concentration ranges for melamine, Trp and Phe are 1.0 × 10-10-1.0 × 10-5 M, 1.6 × 10-5-1.0 × 10-2 M and 1.5 × 10-51.0 ×10-3 M, respectively. The highly SERS-active and uniform 3D substrates will greatly advance the application of SERS as a routine analytical technique.

EXPERIMENTAL SECTION Reagents: N, N-dimethylformamide (DMF, 99%), Silver nitrate (AgNO3, 99%), ethanol (99%), dichloromethane (99%), cyclohexane (99%), and octane (99%) were purchased from Xilong Scientific. Poly(vinylpyrrolidone) (PVP, Mw55000), Gold chloride trihydrate (HAuCl4.3H2O, 99%), copper( Ⅱ ) chloride (CuCl2) and 4-mercaptobenzoic acid (4-MBA, 99%) were purchased from Sigma-Aldrich. Ascorbic acid (AA), Trp, Phe and melamine were purchased from Shanghai Aladdin Biochemical Technology Co., Ltd. Urea was purchased from Sinopharm Group Chemical Reagent Co., Ltd, Shanghai.

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Hexadecyltrimenthylammonium chloride (CTAC) was purchased from Energy Chemical. Synthesis of AgNRs: A three-step method to synthesize Au nanodecanedron seeds was used. The method can be found in the recent report of our group.24 A minor difference compared with the previous work was that in the first step we added 19.6 μL rather than 9.8 μL 0.1 M AgNO3 to the system. Thus, the size of 20 nm seeds can be obtained. For the further growth of AgNRs, we used a classic CTAC system. In a typical synthesis of AgNRs with length 200 nm, 8 mL of Au seeds was added to 5 mL of 80 mM CTAC solution, and heated at 60 °C for 5 min. Subsequently, 190 μL of 2 mM CuCl2 was added to the mixture and the heating was continued for 5 min at 60 °C. Then 4 mL of 10 mM AgNO3 was added to the mixture drop-by-drop and the reaction was continued for another 10 min at 60 °C. Finally, 2 mL of 0.1 M AA was added to the above solution drop by drop. The reaction system was left undisturbed at 60 °C for 6 hours. Different length of AgNRs were synthesized by adding different amount of AgNO3. Then the reaction solution was centrifuged at 7500 rpm for 20 min. In order to get the pure AgNRs, the depletion-induced flocculate method was used. And the PVP-coated AgNRs were obtained through the ligandexchange in 1% PVP/EtOH under sonication. At last, the clean PVP protected AgNRs in ethanol were used for further applications. TEM images of the AgNRs were collected through a FEI Tecnai G2 F20 microscope operated at 100 kV. Layer-by-layer assembly of 3D AgNRs mediated by the air-liquid interface: 200 μL of AgNR ethanol solution was diluted with 200 μL dichloromethane. Next, 200 μL cyclohexane and 30 μL of octane were added to the AgNR solution. 200 μL of the AgNR solution was injected onto the surface of water with a diameter of 2 cm. The AgNR monolayer was formed within 1 min and was kept undisturbed for 30 min to volatilize the octane solvent. The self-assembled monolayer was then transferred to silicon wafer or glass slide. When the AgNR monolayer on the silicon wafer or glass slide was dried, another assembly monolayer was stacked continuously. By repeating the process, we ultimately made 3D AgNR nanostructures with the layers of 2-20. Characterization of the 3D AgNR substrates: The SERS activity of the 3D AgNR substrates with 4-MBA as the probe was studied through the large-area SERS mapping (55 ×55 μm2 with 5 μm step) at three laser wavelengths. The SERS substrates with layers from 1 to 20 were soaked overnight in 1 mM of 4MBA ethanol solution and washed with ethanol to remove the unbound molecules and then got dried at room temperature. Raman spectra were recorded on a LabRAM Aramis Raman microscope of Horiba JY. The 532-nm, 633-nm, 785-nm extinction lines were focused at the substrate through a 10 × (NA=0.25) objective. The Raman scattering light was collected using the same objective. The power of the laser focused on the substrate was 0.76 mW (532 nm), 0.44 mW (633 nm), 4.34 mW (785 nm), respectively. The exposure time was 1 s for one mapping pixel. SEM images of the substrates were acquired using a Hitachi S4800 microscope operated at 5 kV. Extinction spectra of the 3D AgNRs were recorded on an Aglient Carry 5000 ultraviolet/visible/near-infrared spectrophotometer (UVvis-IR). Surface topology of substrates were examined using an AFM microscope (Multimode 8, Bruker) in the tapping mode in the air. The area of scan was 2 × 2 μm2. Quantitative SERS analysis of molecules: For urea, melamine, Trp and Phe detection, the 3D AgNR substrates were


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Analytical Chemistry soaked in aqueous solution of urea, melamine, Trp and Phe with different concentrations for 2 h, respectively. Then the substrates were washed for one minute and dried at room temperature. To guarantee the accuracy and reliability of the detection, the quantitative SERS analysis of these molecules was measured through the SERS mapping (20 × 20 μm2 with 5 μm step). All the Raman scattering lights were collected through a 10 × (NA=0.25) objective and the exposure time was 10 s. The 3D AgNR substrates which immersed in urea and melamine solution were collected through the 532-nm laser with the power of 3.07 mW. The 3D AgNR substrates immersed in Trp and Phe solution were obtained through the 785-nm laser with the power of 4.34 mW. For the normal Raman spectra of these molecules, the powders of the molecules were used and the spectra were shown in Figure S1.

RESULTS AND DISCUSSION Synthesis of AgNRs. A series of AgNRs with lengths from 53 to 245 nm and diameter of 22 ±1 nm were synthesized based on the modification of our previous reported method (Figure 1 and Figure S2A). The UV-vis-IR spectra show that LDPR of the AgNRs is tuned from 605 nm to 1510 nm (Figure 1J). The plasmon resonance modes have the linear relation with the AgNR lengths (Figure 1K). The uniform AgNRs with highly tunable plasmonic properties are well suitable as building blocks for the self-assembly of nanostructures.

Scheme 1. The layer-by-layer assembled 3D AgNR substrates for SERS detection. Self-assembly of 3D AgNR SERS substrates. The uniform 3D AgNR SERS substrates were fabricated through the airliquid interface-assisted self-assembly in a layer-by-layer

manner (Scheme 1). AgNR was assembled at the air-water interface to form uniform monolayer, where the long axis of the AgNRs was parallel to the interface. The monolayer was successively transferred to any solid substrate in a highly controlled manner, where the thickness of the 3D nanostructures was controlled by the NL (Figure 2). A set of digital photographs of the 3D AgNR array substrates (0.4 × 0.4 cm2) with NL from 2 to 20 supported on silicon wafers are shown in Figure 2A. SEM images of the AgNR 3D SERS substrates are shown in Figure 2B-H and Figure S2C-J, from which it can be seen that the surface of the different substrates is very uniform. The surface uniformity is further characterized in term of RMS roughness (Rq) measured by the Atomic Force Microscope (AFM) (Figure S3A-O). The small values of Rq prove the uniformity of the substrates. However, it should be noted that the surface roughness increases with the increase of the AgNR layers (Figure S3P). The in-plane AgNRs have a weak orientation with respect to the assembly interface (Figure 2B-H), resulting in the polarization insensitivity response.24 The

Figure 1. Transmission electron microscopy (TEM) and spectroscopic characterization of the AgNRs. TEM images of the AgNRs with length control: (A) 53 ± 3 nm, (B) 71 ± 4 nm, (C) 87 ± 5 nm, (D) 115 ± 7 nm, (E) 140 ± 9 nm, (F) 160 ±8 nm, (G) 176 ± 11 nm, (H) 201 ± 16 nm, (I) 245 ± 15 nm. (J) The extinction spectra of AgNRs. (K) The relationship of AgNRs resonance peaks with their lengths. The relationship of RW (resonance wavelength) and NRL (nanorod length) for the dipolar mode is: RW = 4.9 × NRL + 338.7 (R2: 0.997); the quadrupolar mode is: RW = 2.4 × NRL + 273.1 (R2: 0.998); and the octupolar mode is: RW = 1.2 × NRL + 350.5 (R2: 0.990). The scale bar is 200 nm for all the images.



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Figure 2. (A) The pictures of the assembled substrates with layers from 1 to 20. (B-H) SEM images of the 3D AgNR substrates with NL of (B) 2, (C) 4, (D) 6, (E) 9, (F) 10, (G) 12, (H) 20, respectively. Insets: The cross-section images of the 3D AgNR (labeled with red dashed line) and the high-resolution images of the surface of the substrates. (I) The relationship of the NL and the cross-section thickness. The scale bar is 10 μm for the large-area images. The scale bar for both cross-section and high-resolution images is 500 nm.

polarization insensitivity is beneficial to achieve uniform SERS enhancement across the AgNR 3D substrates. The cross-section of the substrates discloses the well-defined interlayer configuration due to the highly uniform diameter of the AgNRs. The thickness of the 3D nanostructures is well correlated with the NL with a constant value of 28 nm per layer (Figure 2I). This number is slightly higher than the diameter 22 nm of AgNRs, indicating that the thickness of PVP is about 3 nm (supported by TEM in Figure S2B). It thus indicates that the neighboring layer of AgNR is separated by PVP with the thickness of 6 nm. PVP not only protects the AgNR to stabilize the plasmonic properties of the substrates, but also provides enough gaps for more analytes. SERS properties of the AgNR 3D nanostructure. When the desired NL were achieved, we examined the SERS activity of the 3D AgNR nanostructures with 4-MBA as the probe molecule through the large-area SERS mapping (55 × 55 μm2 with 5 μm step) at three laser wavelengths. The results demonstrate that the 3D AgNR substrates have large-area SERS enhancement uniformity at the three lasers (Figure S4-S6). The RSD of the SERS enhancement is improved by less than 10% when the NL is more than one, showing the superiority of 3D substrates over the 2D substrate (2D: AgNR monolayer) (Table S1). Moreover, the comparison of the enhancement reproducibility with other SERS substrates prepared by different methods was shown in Table S2, further indicating the excellent reproducibility of the 3D substrates. The average SERS intensity obtained from the SERS mapping for each substrate is used to study the impact of NL on the SERS performance at the three laser wavelengths, as shown in Figure 3A, from which it can be seen that the SERS intensity first increases steeply with increasing NL, but then reaches saturation with further addition of layers. The reason of the intensity saturation can be understood from penetration depth of light in the 3D substrates. The transmittance is considerably

decreased when the layer number is four at 532 and 633 nm light (Figure 3F). The limited penetration depth of light in the 3D AgNR substrates is the major reason for the intensity saturation. The excitation wavelengths also have impact on the SERS performance of the substrates. It shows that the excitation efficiency with wavelengths of 532 and 633 nm are fairly good, and much higher than that of 785 nm (Figure 3A). The normalized ASEF of the substrates was achieved by dividing the SERS intensity with the NL (Figure 3B). Although the intensity saturation occurs after six AgNR layers, the ASEF reaches maximum when the NL is three. The ASEF with NL of 6 was approximately 1.20 ×105. The maximum ASEF is 2.26 × 105 with NL of 3 (details of the calculation shown in SI including Table S3-4 and Figure S8). The ASEF reaches maximum values at three layers with the excitation of 532 and 633 nm possibly due to that (1) two intergaps are formed between the AgNR layers and (2) 99% light flux is utilized by the first three layers of AgNR. Compared to the 2D substrate, the SERS intensity increases by a factor of 6.09, 14.03 and 37.37 at 532, 633 and 785 nm, respectively (Table S5). The extinction spectra of the substrates with different NL exhibit the shift of the resonance wavelength in response to the interlayer plasmonic coupling (Figure 3C-E). The broad resonance peaks between 1200 nm and 3000 nm are narrowed to give a clear observation. And all the peaks are vertically translated for clarity (Figure 3D). The LDPR of the AgNR with length of 201 nm is at 1300 nm (Figure 1J). However, the extinction peak of the AgNR monolayer is red-shifted to 1914 nm due to the plasmonic coupling within this layer (defined as the intralayer plasmonic coupling).25 The resonance wavelength first continues red shift until the NL reach to three, and then switches to blue shift when the NL are more than three (Figure 3D and 3E). It is clear that the addition of one AgNR layer on top of another layer forms the interlayer gap. Therefore, the NL-


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Analytical Chemistry dependent resonance-wavelength shift indicates the effect of the interlayer plasmonic coupling.

The addition of the third and more layers (AgNR layer without absorbing the MBA) decreases the SERS intensity due to the absorption of the excitation light and Raman emission by these layers. However, the weak SERS signal of MBA still can be detected even after five layers. It is interesting that the 532nm light cannot penetrate the five layers of AgNR (Figure 3F). It suggests that the near-field interaction in the 3D AgNR can go deeper than the far-field response expected.26 Impact of AgNR length on the SERS performance. We further studied the SERS performance of the 3D AgNR with different lengths at the optimal layer number of 6. The lengths of the AgNR were changed from 53 nm to 245 nm, with the LDPR covering the wavelengths range of 605-1510 nm (Figure S7A). AgNR with length shorter than 148 nm (Figure 4A-E) show random arrangement in each intralayer of the 3D nanostructures, leading to uncompact surface compared to the longer AgNR (Figure S7B-F). The SERS intensity of the substrate continuously increases with the increase of the AgNR length at 532-nm excitation, where a maximum of 3-fold intensity increase is obtained (Figure 4F).

Figure 3. (A) SERS Intensity of the AgNR substrates with different NL under three lasers of 532, 633, 785 nm, respectively. (B) The normalized ASEF of the substrates in Figure 3A. (C) The UV-visNIR spectra of the AgNR substrates with the NL of 1-12. (D) The UV-vis-NIR spectra of the substrates from the wavelength region between 1200 nm to 3000 nm (as indicated by the red dashed line in Figure 3C). (E) The relationship between the resonance wavelength and the NL. (F)The light transmittance of the substrates in Figure 3C at three wavelengths of 532, 633, 785 nm. (G) The relationship of SERS intensity from the first bottom layer with the increase of the layers on top of it (at 532-nm excitation).

The confirmation of the 3D plasmonic coupling. Besides the increase of the detection volume, the 3D AgNR substrates can achieve more hot spots through the 3D plasmonic coupling. For the 3D AgNR substrates, the plasmonic coupling includes the intralayer (in-plane) plasmonic coupling within each layer and the interlayer (out-of-plane) plasmonic coupling between layers, which together form the 3D plasmonic coupling. Therefore, one type of hot spots supported by the intralayer plasmonic is the gaps among AgNR in each layer, the other type of hot spots supported by the interlayer plasmonic is the gaps between two layers of AgNR. To further measure the enhancement effect of the interlayer hot-spot, we add the second AgNR layer (without absorbing the MBA reporter) on top of the first layer adsorbed with the MBA (Figure 3G). It finds that the SERS intensity of the MBA increases by a factor of 3.3 after the addition of the second layer. It indicates that the SERS intensity of MBA from the first layer is greatly improved by the formation of the interlayer hot-spots. Therefore, it indicates that the interlayer (out-of-plane) coupling is very effective to improve the SERS performance.

Figure 4. (A-E) SEM images of the 3D AgNR substrates with AgNR lengths of (A) 53 nm, (B) 69 nm, (C) 79 nm, (D) 88 nm, (E) 121 nm, respectively. Insets: The cross-section images of the 3D AgNR (labeled with red dashed line). (F) Normalized SERS Intensity of 6 assembled layers with different lengths. All the scale bars are 500 nm.

The 3D AgNR SERS substrates at 785 nm excitation show similar intensity trend as the 633-nm case, where the SERS intensity is nearly unchanged when the AgNR length longer than 80 nm. Among the three excitation lights, the excitation of the SERS substrates at 633 nm shows highest efficiency across the AgNR lengths. When the AgNR length is shorter than 85 nm, the substrates excited at 785-nm show better performance than they do at 532-nm light. However, the 532-nm laser is very suitable for the long AgNR (> 200 nm) 3D SERS substrates.



The excitation of the different plasmonic modes of the 3D nanostructures at the three laser lines should be the cause of differences in SERS intensity. However, the detailed theoretical calculation is desired to clarify the relationship between plasmonic modes of the substrates and the excitation lasers. Quantitative SERS analysis of biomolecules. To better understand the performance of the 3D AgNR substrates, two kinds of biomolecules were quantificationally detected through the SERS mapping of the substrates (20 × 20 μm2). Urea is the principal end product of protein degradation and an important indicator of kidney health.27 The colorimetric method is the most commonly used procedure, but the whole process is time consuming.28,29 Therefore, it is highly desired to realize the detection of urea through the quantitative SERS method. The average SERS spectra of each concentration of urea were shown in Figure 5A. The peak at 1009 cm-1 was assigned to the N–C– N bond stretching vibration, and the intensities of the peak have a linear relationship with the concentration from 0.125 mM to 300 mM (Figure 5B). The detection range covers the concentrations of 2.1-7.1 mM expected in a normal adult.30 Based on the 3σ rule, LOD is calculated to be 0.05 mM, which is much lower than the reported literature (Table S6).31 The normalized color intensities of the SERS mapping are correlated with the concentrations to provide a visual depiction of the Figure 5B (Figure 5C-J).

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the 3D AgNR substrate provides the same detection sensitivity for the two amino acids possibly due to the structural similarity between them. The LOD is 5.38 μM and 10.6 μM for Phe and Trp, respectively. This result indicates that it is possible to detect a group of molecules together, realizing the highthroughput quantitative analysis.

Figure 6. SERS spectra of Phe (A) and Trp (C) at different concentrations. SERS intensity of Phe (B) and Trp (D) at 1000 cm1 and 1010 cm-1, respectively, as a function of the concentration.

Quantitative SERS analysis of melamine. Melamine is an organic compound and has been illegally used as non-protein nitrogen additive to increase the apparent protein content.34 The ingestion of melamine-adulterated food can lead to severe kidney damage to children.35 Therefore, the safety limits of melamine are 8 and 20 mM for infant formula in China and the USA, respectively.36 SERS has been extensively applied for the detection of melamine.37,38 However, the quantitative SERS detection of melamine is still a challenge. Here the melamine was quantitative detected by the 3D AgNR substrate from 10 -5 M to 10-10 M through the peak intensities of 686 cm-1 (Figure 7 A and B). The SERS spectra of melamine are dominated by the peak at 686 cm-1, corresponding to the ring breathing mode of melamine (Figure 7A). The LOD of the detection is 26 pM, showing about 4-fold improvement of the sensitivity.39 Figure 5. (A) SERS spectra of different concentrations (125 μM, 250 μM, 1 mM, 5 mM, 30 mM, 50 mM, 100 mM, 300 mM) of urea. (B) The intensity of 1009 cm-1 as a function of the concentrations of urea. (C-J) The SERS mapping images of the intensity at 1009 cm-1.

Phe and Trp as the essential amino acids in human body, are essential for all organisms. However, the quantitative analysis of amino acids requires multiple reaction steps.32 Here the two amino acids were detected through the SERS analysis in a labelfree way. The recorded mean SERS spectra of Phe and Trp at different concentrations are presented in Figure 6 A and C. The peaks at ~1000 cm-1 can be assigned to the aromatic group of the amino acids.33 SERS intensity of Phe at 1000 cm−1 over the concentration range from 0.015 mM to 1 mM is plotted in Figure 6B, where the liner relationship further confirms the high reproducibility and sensitivity of the 3D AgNR substrate. The peak intensity at 1010 cm-1 for Trp concentrations from 0.016 mM to 10 mM was plotted in Figure 6D. It is interesting that

Figure 7. (A) SERS spectra of melamine at different concentrations from 10-10 M to 10-5 M and the peak intensity at 686 cm-1 as a function of the melamine concentration (B).

The quantitative performance of the 3D AgNR substrate is compared to that of other detection methods based on the LOD values of the four analysts (Table S7). The wide linear response range and the excellent detection sensitivity of 3D AgNR SERS make it an attractive technique for quantitative analysis.


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Analytical Chemistry Besides the sensitivity, the stability of SERS substrates determines to a large extent the practical application of SERS analysis. Therefore, the long-term stability of the substrate is tested by monitoring the SERS intensity of the MBA reporter, the UV-vis-IR spectra and SEM images of the substrate (Figure S9). The 3D AgNR substrate shows virtually unchanged SERS intensity during four weeks of storage in ambient conditions. The conclusion is also supported by the highly reproducible extinction spectra and stable surface structure of the substrate (Figure S9).

CONCLUSION In summary, we have demonstrated that the 3D AgNR SERS substrates can be prepared on arbitrary solid surfaces through the air-liquid interface-mediated self-assembly. The 3D AgNR SERS substrates have well-defined interlayer nanostructures with uniform inter-gaps of 6 nm. The 3D AgNR SERS substrates achieve higher Raman enhancement and detection reproducibility than the conventional 2D substrates verified by the SERS mapping method. 3D plasmonic coupling is the major reason for the superior SERS performance. It is demonstrated that interlayer (out-of-plane) coupling is very effective to improve the SERS performance. Both the NL and AgNR length as well as the excitation wavelengths have impact on the performance of the 3D AgNR substrates. The optimal NL should be slightly higher than the NL of 4 where the light transmittance of the 3D AgNR just reach 0%. Compared to 785 nm light, 532 and 633 nm are more efficient as the excitation lasers. Compared to the effect of NL on SERS performance, the impact of AgNR length is small. 3D AgNR SERS has wide linear response range and excellent detection sensitivity proved by the quantitative detection of the four analytes. It is known that the development of SERS is accompanying and driven by the evolution of the SERS substrates.40 Therefore, we expect the 3D SERS substrates with low cost and high activity, reproducibility and stability will advance the practical applications of quantitative SERS technique.

ASSOCIATED CONTENT Supporting Information The Supporting Information is available free of charge on the ACS Publications website. Normal Raman spectra of the molecules (urea, melamine, Phe and Trp); TEM image of the thickness of PVP of AgNRs; SEM images of other substrates; AFM topographic images of substrates with layers from 1-20; SERS spectra and mapping images of 1-20 layer of AgNR under three lasers (532 nm, 633 nm and 785 nm, respectively); UV-vis-NIR spectra of AgNRs and SEM images of other 3D substrates with longer lengths; the details of the calculation of ASEF; the stability of the 3D AgNR substrate; table of RSD of SERS mapping intensity under three lasers (532 nm, 633 nm and 785 nm); table of the comparison of the enhancement reproducibility among different SERS substrates; table of the parameters for the calculation of ASEF and the ASEF of all substrates with different layers; table of the comparison between 2D and 3D AgNR SERS substrates; table of the calculation of LODs for the different molecules; table of the comparison of the sensitivity of the 3D AgNR SERS with other methods.

AUTHOR INFORMATION Corresponding Author * Email: [email protected] and [email protected]

Notes The authors declare no competing financial interest.

ACKNOWLEDGMENT We appreciate the help from Yi Pin to edit the English writing. This research was funded by NSFC (21503231 and 31400699), NSF of Fujian Province (2015J01031 and 2014J01142).

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