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. 2025 Feb 6;10(6):6258–6266. doi: 10.1021/acsomega.5c00168

Rapid and On-Site Approaches for Determination of Polycyclic Aromatic Hydrocarbons in Water and Air by Surface-Enhanced Raman Spectroscopy

Xinying Ni 1, Yile Wang 1, Mengping Zhang 1, Gengxin Cui 1, Xiao Meng 1, Wenwen Chen 1, Meng Jin 1, Hua Shao 1, Fang Zhang 1,*, Cuijuan Wang 1,*
PMCID: PMC11840630  PMID: 39989755

Abstract

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Polycyclic aromatic hydrocarbons (PAHs) represent a class of carcinogenic, teratogenic, and mutagenic aromatic organic pollutants that are ubiquitous in the environment. The rapid and on-site detection of PAHs remains a challenge. This study proposes point-of-use (POU) surface-enhanced Raman spectroscopy (SERS)-based strategies for the qualitative and quantitative analyses of PAHs in environmental water and air. The results demonstrate clear correlations between the signal intensity and the logarithmic concentration of PAHs in water (ranging from 2.5 to 100 ppb), with satisfactory recovery and reproducibility. A similar trend was observed for PAHs on glass fiber filters modified with silver nanoparticles (AgNPs@GF filter). Specifically, the limits of detection (LOD) for fluoranthene, phenanthrene, and pyrene in water were 0.7, 1.0, and 0.1 ppb, respectively, while the LOD for fluoranthene, phenanthrene, and pyrene on the AgNPs@GF filter were 9.11, 18.18, and 14.59 ppb. Recovery rates in spiked real water and filters ranged from 83% to 126%, and the entire detection process was completed within 1 min. These findings highlight the significant potential of this method as a powerful tool for rapid on-site analysis of PAHs in various environmental matrices.

1. Introduction

Polycyclic aromatic hydrocarbons (PAHs) are persistent organic pollutants characterized by the presence of two or more fused benzene rings.1,2 These compounds are known for their chemical stability, persistence in the environment, resistance to biodegradation, and capacity to accumulate within organisms. As a result, PAHs can be concentrated in biological systems through exposure to polluted water and air. Consequently, they are ubiquitous in various environmental media, including water,3 air,4 soil,5 organisms, and even the human body.6 Exposure to PAHs poses significant environmental and human health hazards.7 In fact, studies have demonstrated that PAHs exposure can lead to adverse health effects, such as carcinogenesis, mutagenesis, and teratogenicity, causing damage to the respiratory, circulatory, and nervous systems.8,9 In recognition of their potential risks, the United States Environmental Protection Agency (US-EPA) has identified PAHs with high volatility as priority substances and has implemented regulatory controls to limit their concentrations.10 Additionally, these PAHs have been listed in the Regional Convention on Long-Range Trans-Border Air Pollution (LRTAP). In 2004, the International Agency for Research on Cancer (IARC) established that fluoranthene and phenanthrene are possible human carcinogens; pyrene is a probable human carcinogen and the most potent PAH carcinogen in animal experiments.11,12 Therefore, it is extremely crucial to monitor PAHs concentrations over time in environmental water and air to effectively manage the risks they pose to the environment and human health.

The current detection methods for identifying PAHs mainly include liquid chromatography–mass spectrometry (LC-MS)13 and gas chromatography–mass spectrometry (GC-MS).14,15 While these techniques offer precise results, they are complex, time-consuming, laborious, and costly. Consequently, they are not suitable for an on-site application. Analytical methods need to undergo continuous refinement to meet the criteria of portability, high efficiency, and low cost. Surface-enhanced Raman spectroscopy (SERS) has emerged as a prominent spectroscopic technique and has been adopted in various analytical domains.16 SERS technique has been demonstrated to be one of the most sensitive tools for the detection, identification, and quantification of single or multiple molecules, even at ultralow concentrations.17−20 SERS combined with micro-Raman spectroscopy holds great promise for point-of-care testing (POCT). Recent literature describes the use of portable Raman devices, including forensic field SERS analysis,21 airborne volatile organic compounds monitoring,22 and nerve agent detection.23 Identifying, quantifying, and monitoring hazardous substances in ambient air and environmental water are crucial for pollution control and the protection of both the environment and human health. Generally, the rapid, reliable, ultrasensitive, and field-detectable detection of PAHs in air and water is vital for assessing potential hazards accurately. The practical applications of SERS for gaseous PAHs remain in their early stage. Enriching low concentrations of molecules and bringing them to the surface of the substrate for signal enhancement is a prerequisite for SERS. To enrich gaseous molecules, porous materials can be utilized. PAHs are predominantly adsorbed onto minute particles in the atmosphere and water, and the enrichment of airborne PAHs using filter membranes is a recommended strategy. Previous studies have employed various molecules, such as mercaptan, sulfhydryl group-substituted cyclodextrin, and humic acid, to modify the surface of SERS substrates, thereby enhancing the affinity between PAHs and SERS substrates.24−27 However, these modifiers may introduce interference during analysis and affect the sensitivity. Therefore, it is imperative to develop an effective SERS strategy for analyzing PAHs in both aqueous and atmospheric samples.

Herein, we developed SERS-based strategies for determining three typical PAHs, namely, fluoranthene (Flu), phenanthrene (Phe), and pyrene (Pyr), in both water and air samples. Silver nanoparticles (AgNPs) are commonly used substrates for Raman spectroscopy, as they have sufficient stability and repeatability, wide spectral range, and unique surface plasmon properties.28 Specifically, to detect PAHs in water, we employed silver nanoparticles (AgNPs) and iodide ions, leading to a cleaner surface and enhanced PAH adsorption. Moreover, an ultrasensitive and reliable sampling and sensing platform was developed, comprising a glass fiber filter coated with AgNPs (AgNPs@GF filter), which served as both the absorber and the SERS substrate. This composite combines the specificity of the SERS fingerprint with enrichment capacity, followed by detection using a portable Raman instrument, thus enabling the specific, sensitive, and rapid detection of gaseous PAHs. The entire analysis procedure could be completed in 1 min, which is more efficient than traditional methods. The developed approach with absorber and SERS functions has great potential for providing a new way to rapidly detect PAHs in the air. The scheme of the above approach is displayed in Scheme 1.

Scheme 1. Scheme Showing the SERS Detection of PAHs in Environmental Water and Air.

Scheme 1

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2. Materials and Methods

2.1. Chemicals and Reagents

Silver nitrate (AgNO3), ≥ (99.8%), trisodium citrate dehydrate (≥99.0%), magnesium nitrate (Mg(NO3)2), and ethanol were purchased from Sinopharm Chemical Reagent (Shanghai, China). Potassium iodide (KI, ≥ 99.0%) was purchased from Aladdin Chemistry (Shanghai, China). Fluoranthene (Flu, 98%), phenanthrene (Phe, 95%), and pyrene (Pyr, 98%) were obtained from J&K Scientific (Beijing, China). Methanol (≥99.9%) was purchased from Sigma-Aldrich. Glass fiber filter (Φ40) was purchased from Nantong Jinnan Glass Instrument Hardware Factory (Nantong, China). Environmental water was collected from the Xiaoqing River located in Jinan, Shandong Province, China. Reagents were used without further purification, and deionized water (Millipore Milli-Q System, 18.2 MΩ/cm) was used in all of the experiments.

2.2. Instrumentation

The uniformity and morphology of the AgNPs were examined by transmission electron microscopy (TEM) performed on a TALOSF200S electron microscope (Thermo) with an accelerating voltage of 200 kV. The morphology and element composition of the AgNPs@GF filter were observed using a scanning electron microscope (SEM, Hitachi) equipped with an energy-dispersive spectrometry system. Absorbance measurements were conducted by using a Shimadzu 2600 ultraviolet–visible (UV–vis) spectrometer. SERS analyses were performed using a portable Raman system (QE Pro, Ocean Optics). The zeta potentials were tested on a Zetasizer instrument (NanoZS, Malvern, U.K.).

2.3. Synthetic Procedures of the AgNPs@GF Filter

The preparation of colloidal silver was conducted via reducing AgNO3 by sodium citrate, according to the method described by Lee and Meisel.29 Briefly, 100 mL of 1 mM AgNO3 was heated to its boiling point under vigorous stirring, followed by the addition of 3 mL of 1% sodium citrate. The mixture was kept boiling and stirred for 1 h. To obtain the AgNPs@GF filter, a piece of GF fiber was immersed in the AgNPs solution, and it was taken out and dried. The synthesized substrate was stored in a sealed container prior to utilization.

2.4. SERS Analysis

Stock solutions of Flu, Phe, and Pyr, each at 10 ppm, were prepared by dissolving the respective solid compounds in ethanol. Subsequently, their required working solutions were formulated by diluting the stock solution with water. 10 μL of KI solution, 10 μL of standard solution, and 20 μL of Mg(NO3)2 were added into 1 mL of AgNPs, followed by mixing for 5 s. The wavelength of the excitation light of the portable Raman system (QE Pro, Ocean Optics) was 785 nm, the laser power was set at 200 mW, the acquisition time was 5 s, and each sample was detected 3 times.

In this study, for environmental water, the SERS enhancement factor (EF) is 3.18 × 106, with CSERS and CRS values of 0.02 and 5000 mg/L, respectively. For air, the EF is 1.17 × 106, and the values of CSERS and CRS are 0.05 and 10000 mg/L, respectively.

3. Results and Discussion

3.1. Characterization of AgNPs and AgNPs@GF Filter

According to the TEM results (Figure 1A), the AgNPs are spherical and uniformly distributed. After the salt solution was added to the colloidal AgNPs, aggregations were observed. The average diameter of the AgNPs was measured to be approximately 49.5 ± 0.5 nm (Figure 1B). Figure 1C displays the SEM images of the unmodified glass fiber filter and the amplified view of the AgNPs@GF filter, respectively. The filter exhibited a 3D mesh structure with AgNPs distributed uniformly across the fibers. This configuration ensures dual functions of both sample adsorption and SERS activity.

Figure 1.

Figure 1

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(A) TEM image of AgNPs before (i) and after aggregation (ii). (B) Size distribution of AgNPs. (C) SEM images of blank glass filter (i) and AgNPs@GF (ii). (D) UV–vis spectra of AgNPs colloids and AgNPs mixed stepwise with KI, 1 ppm of Flu, and salt. (E) SERS spectra of the solutions depicted in panel (D). (F) SERS spectra of a blank glass filter, AgNPs@GF filter, and 1 ppm of Flu on AgNPs@GF filter. All tests were conducted utilizing a 785 nm laser, with a power output of 200 mW and an integration time of 5 s.

Figure 1D shows the UV–vis spectra of the reaction solution in its initial state and after the aggregation process. In the case of a solution containing only 10 μL of AgNPs, the absorption band was observed to occur at a wavelength of 411 nm. After adding 10 μL of 1 mM KI and10 μL of 5 ppm Flu to the AgNPs solution, the absorption band changed slightly. Following the addition of 20 μL of 1 mM Mg(NO3)2 to the mixed solution, a notable shift was observed (green line, Figure 1D), indicating the occurrence of aggregation.

The effect of KI and Mg(NO3)2 was investigated by adding 10 μL of KI, 10 μL of 5 ppm Flu, and 20 μL of Mg(NO3)2 to the AgNPs solution. As shown in Figure 1E, the characteristic peaks associated with Flu were observable exclusively when KI and Mg(NO3)2 were introduced. No obvious signal of Flu appeared without KI or Mg(NO3)2, which suggests that KI and Mg(NO3)2 play significant roles in Flu sensing. Three weak Raman bands at 834 cm–1, 958 cm–1, and 1035 cm–1 also existed in AgNPs solution without Flu, which may be caused by citrate or its decomposition products. The electron-rich cloud structure of I– is capable of effectively interacting with the multiconjugated ring structure of the electron-rich cloud of PAHs, thereby inducing the coadsorption of PAHs on the surface of AgNPs.30 The intense SERS signal of PAHs was obtained without other signal interference after AgNPs aggregated with Mg(NO3)2.31Figure 1F shows the SERS spectra of a blank glass fiber filter and the AgNPs@GF. After adding 5 μL of KI and 5 μL of Flu solution to the AgNPs@GF, obvious signals can be observed, which confirmed the SERS activity.

3.2. Raman Characterization and Assay Optimization

Herein, the Raman fingerprints of the solid standards and the SERS spectra of the solutions were compared for rapid identification. Due to the condensed aromatic ring structure of PAHs, all carbon atoms in their molecules are coplanar, resulting in strong out-of-plane C–C and C–H bending modes. The low wavenumber peaks (300–1000 cm–1) are mainly due to C–C bending, while C–H bending causes the Raman peaks in the mid-wavenumber regions (1200–1600 cm–1).32Figure 2A shows the chemical structures of Flu, Phe, and Pyr; the Raman reference spectra of solid standards; and the SERS spectra of solutions. The distinctive Raman peaks associated with the standard Flu are predominantly centered at 668, 1015, and 1423 cm–1, the signal of the 668 cm–1 shift was attributed to the C–H bending, the signal of the 1015 cm–1 shift was attributed to the C–H rock + C–C stretch, and the signal of the 1423 cm–1 shift was attributed to the C–C stretch/ring stretch.33 The peaks of Phe are located at 543, 708, and 1037 cm–1, the signal of the 543 cm–1 shift was attributed to the C–C bending, and the signals of the 708 and 1037 cm–1 shift were attributed to the C–H bending. The characteristic Raman spectral shifts of Pyr are located at 588, 1066, and 1237 cm–1, the signal of the 588 cm–1 shift was attributed to the ring breathing, and the signals of the 1066 and 1237 cm–1 shifts were attributed to the C–H bending.32 There is no significant change in the SERS spectra compared to the Raman spectra, providing a good basis for rapid identification. Although the characteristic peaks of these three PAHs are very close, which consist of carbon and hydrogen atoms at similar ratios, using SERS spectra obtained on AgNPs, differentiation can still be achieved by identifying characteristic peaks.32

Figure 2.

Figure 2

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(A) Reference Raman spectra of the Flu, Phe, and Pyr standard and the SERS spectra of corresponding anhydrous ethanol solutions (1 ppm). (B) SERS spectra of Flu with different concentrations of KI. (C) SERS intensity (668 cm–1 peak) of Flu with different concentrations of KI. (D) SERS spectra of Flu with different concentrations of Mg(NO3)2. (E) SERS intensity (668 cm–1 peak) of Flu was calculated with different concentrations of Mg(NO3)2. (F) TEM image of AgNPs aggregated by various levels of Mg(NO3)2.

The effects of KI and Mg(NO3)2 on the detection of PAHs were investigated in order to optimize the sensitivity. Various concentrations of KI (0.1, 0.5, 1, 5, 10, 100, and 200 mM) were employed to investigate their impact on the SERS intensity of 1 ppm Flu. The results showed that the highest signal intensity was obtained by using a 1 mM KI solution (Figure 2B,C). KI plays a role in the removal of impurities from the surface of AgNPs. Insufficient KI concentration precludes complete impurity removal. Conversely, excessive I– concentration disrupts AgNP colloidal stability and impedes PAH adsorption.34,35

Figure 2D,E illustrate the influence of varying Mg(NO3)2 concentrations on the SERS intensity of Flu. The highest signal intensity was observed after adding 1 mM of Mg(NO3)2. It has been demonstrated that positively charged cations from concentrated inorganic salts can destroy the stable structure of negatively charged AgNP colloids, thereby forming SERS “hot spots” through the agglomeration of AgNPs.36 Furthermore, the addition of Mg(NO3)2 also promoted silver colloid aggregation, which produced numerous SERS “hot spots” and significantly enhanced the Raman signal of Flu.37−39 However, the enhancement of the SERS signal at higher Mg(NO3)2 doses (1.5 mM) was suppressed. Consequently, 1 mM Mg(NO3)2 was selected as the optimal concentration for subsequent experiments. Figure 2F presents the TEM images of AgNPs before and after aggregation. Upon the addition of salt, the particle gaps became smaller and fused, and the dispersed NPs in the colloidal solution agglomerated. According to Figure S1, the surface potentials of AgNPs + KI, AgNPs + Mg(NO3)2, and AgNPs + KI + Mg(NO3)2 were negative, but when KI and Mg(NO3)2 were added in AgNPs, its negative ζ potential changed from around −30 mV to −20 mV, indicating the AgNP colloids’ stable negative structure was destroyed, which was helpful to form SERS “hot spots.”

3.3. Quantitative Analysis of Flu, Phe, and Pyr in Water

As displayed in Figure 3A, the SERS shifts of Flu, Phe, and Pyr in water are consistent with the standard Raman spectra, with the exception of slight shifts that may be attributed to the charge transfer between the PAHs and AgNPs.27

Figure 3.

Figure 3

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(A–C) SERS spectra of Flu, Phe, and Pyr with increasing concentrations. (D–F) Plot of the peak at 668 cm–1, 708 cm–1, and 588 cm–1 versus the logarithmic concentrations of Flu, Phe, and Pyr in water. (G–I) Repeatability of SERS detection of 1 ppm of Flu in water.

Flu, Phe, and Pyr concentration-signal trends were observed in the range of 2.5–100 ppb (Figures 3A–C). The plots between signal intensity and logarithmic concentrations showed a clear linear dependence (R2 = 0.975/0.936/0.958) (P < 0.001), which satisfied the requirements of quantitative detection (Figures 3D–F).

The linear correlation variations observed among the three PAHs are most probably attributable to their differing aromatic ring counts, chemical structures, and dipole moments. These factors are recognized to induce variations in the affinity of various PAH molecules toward substrate surfaces, ultimately resulting in distinct apparent SERS activities.40 The limits of detection (LOD) for Flu, Phe, and Pyr in water were calculated to be 0.7, 1, and 0.1 ppb, respectively. The strong linear relationship between SERS intensities at trace-level concentrations, coupled with the low LOD values, underscores the feasibility of employing this method for quantitative detection of PAHs in water at trace levels. The water samples spiked with three concentrations of Flu (1 ppm) were tested in 14 parallel experiments using the same batch substrate, showing satisfactory repeatability with RSDs < 10% (Figures 3G–I). As shown in Figure S2, we synthesized ten batches of substrates and used them for SERS detection of 1 ppm Flu. The RSD was 13.04%, which shows good batch-to-batch reproducibility.

3.4. SERS Detection Using the AgNPs@GF Filter

In accordance with the NIOSH method,41 PAHs in aerosol form were collected on glass fiber filter paper. In brief, the sampling clip with the glass fiber filter paper is opened at the sampling location, and the air sampling pump is set to a specific flow rate, followed by collecting air samples over a period of time. In this study, the Flu, Phe, and Pyr solutions (5 μL) were respectively dropped onto the AgNPs@GF filter to simulate the filer, which had completed the air sampling procedure, followed by SERS detection. A significant positive correlation was observed between signal intensity and concentration, as illustrated in Figure 4A–C. For determining Flu by the AgNPs@GF filter, a regression equation was derived as ISERS = 1090.181 log CFlu/ppb – 1355.214, exhibiting a high correlation coefficient of 0.967 (Figure 4D). Similarly, as shown in Figure 4E,F, they demonstrate high correlations of Phe and Pyr, and the correlation coefficients were 0.973 and 0.957, respectively. Using this approach, the LOD of Flu, Phe, and Pyr were calculated to be 9.11, 18.18, and 14.59 ppb, which are sufficient to meet the requirements for route detection.

Figure 4.

Figure 4

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(A–C) SERS spectra stacked in the order of increasing concentration of Flu, Phe, and Pyr using the AgNPs@GF filter. (D–F) Plots of the 668, 708, and 588 cm–1 intensity versus the logarithmic concentrations of Flu, Phe, and Pyr, respectively. (G–I) Signal intensity variations with 23 random spots. (J, K) Storage stability: 7 days. (L, M) Stability of the AgNPs@GF filter under continuous laser radiations.

3.5. Analytical Performance

This study used a solution of 1 ppm of Flu to test the SERS performance of the AgNPs@GF filter. It is crucial to ensure the substrate’s thermal stability and spatial uniformity to obtain a reliable SERS response. The point-to-point uniformity was evaluated by analyzing the 668 cm–1 peak intensity, which exhibited an RSD of 12.77% (Figure 4G–I), indicating good spatial homogeneity. Figure 4J,K illustrate the storage stability of the AgNPs@GF filter following sampling. The AgNPs@GF filters were subjected to the SERS assay at various time points for 7 days. The results showed a slow decline, with an RSD of only 7.45%, indicating good storage stability. The signal remained stable after 10 laser irradiations at the same point with a relative standard deviation (RSD) of 13.49% (Figure 4L,M).

Considering PAHs frequently coexist with triphenylene in the real environment, benzene, toluene, and ethylbenzene were added to the mixture, as illustrated in Figure 5A. No interference signals of benzene, toluene, or ethylbenzene were detected by applying the present substrate. This finding underscores the efficacy of the substrate in this experimental setting, highlighting its notable anti-interference properties. According to Figure 5B,C, the characteristic SERS peaks of these three PAHs are discernible and separable, where the characteristic peaks for each PAH are labeled with different symbols. Although the signal intensity of all three PAHs in complex mixtures is diminished as a consequence of competition between individual PAHs, the capacity to rapidly, effortlessly, and economically identify the three individual PAHs in complex mixtures renders it a prospective instrument for the expeditious detection of PAHs in the field. Furthermore, the SERS spectra of a mixture of the three PAHs were also detected, thereby demonstrating the feasibility of the proposed method in complex mixtures.

Figure 5.

Figure 5

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(A) SERS spectra of benzene, toluene, ethylbenzene, and PAHs. (B) SERS spectra of a mixture of aqueous PAHs detected by colloidal AgNPs solution. (C) SERS spectra of a mixture of PAHs on an AgNPs@GF filter.

To further estimate the applicability of this SERS method, the recoveries of three PAHs in real water samples were investigated. The average recoveries were 89.22–99.70% in water samples (n = 3) (Table S1). The recoveries of Flu on the AgNPs@GF filter were investigated using the standard addition method, ranging from 83.63 to 125.80% (n = 3), sufficient for POCT application. The developed SERS-based strategies offer promising avenues for the POCT of PAHs (Table 1).

Table 1. Recovery of Spiked PAHs Detected by the AgNPs@GF Filtera.

PAHs spiked (ppb) found ± SD (ppb) recovery (%) RSD (%)
Flu 1000 1258.00 ± 111.52 125.80 8.86
400 344.17 ± 27.29 86.04 7.93
100 101.11 ± 3.13 101.11 3.09
  1000 1114.64 ± 78.73 111.46 7.06
Phe 400 371.40 ± 4.89 92.85 1.32
  100 95.67 ± 4.03 95.67 4.21
  1000 1104.98 ± 81.64 110.50 7.39
Pyr 400 398.08 ± 12.95 99.52 3.26
  100 83.63 ± 3.47 83.63 4.15
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a

SD, Standard deviation; RSD, relative standard deviation.

Table S2 provides a comparative overview of previously used detection methodologies based on SERS, SPES, and LCS. The principal advantages of this POCT assay include improved detection efficiency and no need for pretreatment procedures, and it facilitates on-site detection, thereby enhancing biomonitoring of PAHs exposure. This method also has limitations. Compared to some methods, it has a slightly higher LOD. In conclusion, this method represents a credible POCT alternative for rapidly monitoring PAHs exposure.

4. Conclusions

In conclusion, this study presents SERS-based strategies for determining three typical PAHs, namely, Flu, Phe, and Pyr, in environmental water and air. Iodide ions were employed to modify the surface of the AgNPs, leading to a cleaner surface and enhanced PAHs adsorption. Moreover, an ultrasensitive and reliable sensing composite was developed comprising a glass fiber filter coated with AgNPs (AgNPs@GF filter), which served as both the absorber and the SERS substrate. This substrate combines the specificity of the SERS fingerprint with enrichment capacity, thereby enabling the specific, sensitive, and rapid detection of gaseous PAHs, with satisfactory recovery rates in spiked real water and filter samples. The entire detection process could be completed within 1 min without preprocessing. The applicability of the proposed method was confirmed in complex mixtures and real-world samples. The developed POU strategies may provide effective alternatives toward point-of-care identification and quantification of PAHs in environmental matrices. The primary limitation of this study is that we focused on three representative PAHs, which may not fully capture the diversity of PAHs present in the environment. Future research should include more PAHs. In the future, POCT technologies will evolve toward higher efficiency, accuracy, and diversity to meet the demand for real-time monitoring.

Acknowledgments

This work was supported by the National Key Research and Development Program of China [grant numbers 2022YFC2503202]; the Natural Science Foundation of Shandong Province [grant numbers ZR2023MH146, ZR2017YL002]; the Medical and Health Science and Technology Development Plan of Shandong Province [grant numbers 202112070425]; Traditional Chinese Medicine Project of Shandong Province [grant numbers 2021M152]; the Clinical Medical Science and Technology Innovation Plan of Jinan [grant number 202225062]; and the Academic Promotion Program of Shandong First Medical University [grant number 2019QL001].

Supporting Information Available

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acsomega.5c00168.

  • Description of calculation of method detection limits, analytical enhancement factor, and synthesis of AgNPs; and supporting figures SERS spectra of Flu with ten batches substrate, zeta potential of I (PDF)

Author Contributions

† X.N. and Y.W. contributed equally to this work. X.N.: Methodology and writing—original draft. Y.W.: Methodology and data curation. M.Z.: Writing—review and editing. G.C.: Validation. X.M., W.C., and M.J.: Software. H.S.: Funding acquisition and supervision. F.Z.: Funding acquisition and project administration. C.W.: Funding acquisition, conceptualization, writing—review and editing, and supervision.

The authors declare no competing financial interest.

Supplementary Material

ao5c00168_si_001.pdf (300.5KB, pdf)

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