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Mirror-like Plasmonic Capsules for Online Microfluidic Raman Analysis of Drug in Human Saliva and Urine Mengke Su, Yifan Jiang, Fanfan Yu, Ting Yu, Shanshan Du, Yue Xu, Lina Yang, and Honglin Liu ACS Appl. Bio Mater., Just Accepted Manuscript • DOI: 10.1021/acsabm.9b00425 • Publication Date (Web): 06 Aug 2019 Downloaded from pubs.acs.org on August 6, 2019

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ACS Applied Bio Materials

Mirror-like Plasmonic Capsules for Online Microfluidic Raman Analysis of Drug in Human Saliva and Urine Mengke Su,1 Yifan Jiang,1 Fanfan Yu,1 Ting Yu,1 Shanshan Du,1 Yue Xu,1 Lina Yang,*,1 and Honglin Liu*1,2,3 1School

of Food and Biological Engineering, Engineering Research Center of Bio-process, Ministry of Education, Hefei University of Technology, Hefei, Anhui 230009, China 2Molecular

Science and Biomedicine Laboratory, State Key Laboratory of Chemo/Bio-Sensing and Chemometrics, College of Chemistry and Chemical Engineering, College of Life Sciences, and Aptamer Engineering Center of Hunan Province, Hunan University, Changsha, Hunan 410082, China 3State

Key Laboratory of High Performance Ceramics and Superfine Microstructure, Shanghai, China

ABSTRACT: Plasmonic capsules are emerging for novel applications in biochemical sensing, tunable optics, targeted delivery and etc. Here we develop an online mirror-like plasmonic capsule microfluidic (PCM) through citrate-capped Au nanoparticle (GNP) arrays on three-dimensional (3D) oil/water (O/W)-two liquid interface without any inducers or promoters. PCM-based surfaceenhanced Raman scattering (PCM-SERS) system realizes multi-sample, multiplex, and high-throughput analysis of targeted molecules in complex media by a portable Raman device. Excellent O-in-W features of the GNP capsules ensures less surface contaminations of inner channel and avoids cross-contamination between different capsules. Sequential detection of five analytes in different capsules is easily achieved in about one minute, and both dual-analyte and triple-analyte detection in a single capsule demonstrate the excellent sensitivity even with analyte concentrations differed by two orders of magnitudes. The uniform distribution of GNPs at the two liquid interface makes excellent reproducibility of SERS signals. In addition, the O phase of the capsule filling produces fingerprint vibrations in SERS signals and is used as the inherent internal standard (IIS) to improve the quantitation of SERS detection. The O phase also as a good extraction agent realizes efficient separation and enrichment of an illicit drug, methamphetamine (MA), in human saliva and urine. By virtue of principal component analysis (PCA), PCM-SERS platform easily realizes autoclassification of trace MA, with concentrations down to ppm levels. This study promises great potentials of plasmonic capsules for in-situ monitoring molecular events in confined spaces, especially in multi-liquid systems.

KEYWORDES：plasmonic capsules, microfluidic, surface-enhanced Raman scattering, saliva, principal component analysis

1. INTRODUCTION Shell capsules or microspheres of various nanoparticles are emerging for widely use in food industry,1 microbiology,2 biomedicine,3 controlled drug release,4,5 catalysis,6 and other fields.7 These capsules are usually self-assembled by Pickering emulsification on the O/W liquid interface.8-10 Because the shell material is nanoparticle and is not affected by temperature, ionic strength and oil phase,6 the capsule is almost non-demulsifying and extremely stable.11,12 Moreover, the two-phase materials will not dissolve with each other, so the inner phase will hardly be lost and the loading rate has been greatly improved. Particularly, plasmonic capsules based on noble metal nanoparticles can act as novel SERS platforms and provide highly specific fingerprint vibration of targets.13,14 This kind of capsules promises good mechanical stability, loading efficiency and molecular sensing capability. Recently, we have developed a clean 3D plasmonic metal liquid as quantitative SERS analyzer and optimized its hotspot efficiency by accurately controlling the distribution density of nanoparticles at the two-liquid interface.15 3D capsule architectures of plasmonic arrays have advantages in SERS optical path arrangement compared to 2D horizontal plane array.16 Earlier, polymer-modified Ag nanocubes has been chosen as the building blocks to assemble hydrophobic liquid

marbles or colloidosomes in two-phase system.17,18 These seminal reports demonstrate a versatile SERS technique and significantly expand the flexibility of SERS. But the selfassembly process of plasmonic capsules usually needs the use of neutralizers or inducers for surface modification but produces competitive adsorption with analytes on active sites. It is difficult to prepare uniform size microspheres by emulsification,19-21 the stability of the microspheres as SERS substrates still needs to be further improved. And the interference from experimental microenvironment also affects the SERS reliability.22,23 How to achieve high-throughput and quantitative Raman detection on plasmonic capsules remains a great challenge. Microfluidic-SERS can be divided into continuous flow platforms24-26 and segmented platforms.27-29 Either platform opens up new opportunities for system miniaturization and integration of detection tools, bringing the benefits of both technologies. SERS as a highly sensitive technique senses on a small volume and is very suitable for microfluidic platforms. Microfluidic analysis is carried out reproducibly with nanoliter volume, reduces the consumption of laboratory scale, avoids human error, and significantly improves signal reliability. However, signal reproducibility and stability are usually affected by random distribution and aggregation of particles in

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flow channel,28 the tedious on-off preparation, or the use of complex substrates.30,31 Some segmented platforms require nanoparticle pre-assembly with time-consuming steps and are vulnerable to surface contamination. The gradual adsorption of analyte molecules onto the channels makes them unable to be used for a long time.32 As an alternative, tiny plasmonic capsules acting as segmented microfluidic-SERS analyzer might be a great step towards rapid, non-destructive and stable Raman sensing. Developing a miniaturized, easy-to-prepare plasmonic capsules for microfluidic Raman analysis promises a higher capability that would allow plasmonic arrays to be used more efficiently and more easily. Here we show a facile, rapid and uniform strategy to fabricate homogeneous plasmonic mirror-like capsules as a microfluidicSERS detection system. Vigorously shaking of citrate-capped GNP sols and CHCl3 could easily realize the self-assembly of capsules without the need of any inducers or promoters. This capsules have outstanding properties of self-healing, orderly arrangement, long-term stability. The closure of individual capsules does not cause cross contamination between each other, and it has successfully realized continuous detection of R6G in a microchannel with gradient concentration. The organic phase filled with the capsules acts as IIS to eliminate the signal fluctuation caused by sample microenvironment. Compared to the aggregated sol-based microfluidic (ASM) system, PCMSERS platform has much higher sensitivity with reasonable reproducibility. This system could achieve sequential analysis of five different analytes in about 60 s and could also distinguish individual analytes in multiple detection. Combined with PCA algorithms, the MA, a common illicit drug, in human saliva was quantitatively analyzed and accurately classified according to concentrations. Our study implies a great potential of liquidstate plasmonic capsules as microfluidic-SERS analyzer in actual system.

2. EXPERIMENTAL SECTION Reagents. 99.9% of chloroauric acid (HAuCl4·4H2O) was obtained from Nanjing Chemical Reagent Co., Ltd. 98.5% of hydroxylamine hydrochloride (NH2OH·HCl), malachite green (MG), tetrathiafulvalene (TTF), Rhodamine 6G (R6G), Crystal violet (CV), and methylene blue (MB) were obtained from Shanghai Yuan Ye Biotechnology Co., Ltd. 99% of trisodium citrate (C6H5Na3O7·2H2O), hydrochloric acid (HCl), chloroform (CHCl3, 99.5%), sulfuric acid (H2SO4), sodium hydroxide (NaOH) and hydrogen peroxide (H2O2) were purchased from Sino pharm Chemical Reagent Co., Ltd. Methamphetamine (MA) was purchased from Sigma. All solutions were prepared with the ultrapure water of 18.2 MΩ cm. Apparatus. The as-prepared GNPs’ morphology, structure and properties were characterized by UV-2600 spectrophotometer (Shimadzu, Kyoto, Japan), Sirion 200 field emission scanning electron microscopy (FESEM) and JEOL 2010 transmission electron microscopy (TEM), respectively. Raman spectra were conducted on a homemade PCM-SERS analyzer (Figure S1). The Unsciambler X 10.4 software was used for PCA. Synthesis of Monodisperse GNP Sols. The monodisperse GNPs were prepared through a seeded growth method. First, preparation of GNPs seed solution with diameter of 15 nm. 30 mg trisodium citrate and 98.9 mL of water were added to a flatbottomed conical bottle and heated to boil (mixing speed is 200 rpm). And then, HAuCl4·3H2O (250 mM, 100 µL) was rapidly added into the above mixture and kept boiling for 7 min. A seed-

growth method was used to further synthesize GNPs with diameter of 100 nm. In brief, making the 15 nm GNPs as seeds, hydroxylamine hydrochloride as the reducing agent, mixed 1 mL seeds, 74.8 mL of water, 0.8 mL of hydroxylamine hydrochloride and 0.8 mL of 1% C6H5Na3O7·2H2O together for 5 minutes, rapidly injected 1600 µL of 1% HAuCl4, then stirring for one hour. The synthesis of larger GNPs is used 1 mL increased GNPs as seeds, followed by adding 37.4 mL water, 0.4 mL 100 mM NH2OH·HCl, 0.4 mL 1% sodium citrate, 650 rpm stirring 5 min, and finally adding 0.8 mL 1% HAuCl4, and stirring for 1 hours. Finally, the concentration of 100 nm monodisperses Au nanospheres (GNPs) was calculated to 1.1× 10-11 M by Haiss and co-workers’ theory.33 Finally, the UV and TEM were used to form the visual characterization of GNPs. The O Phase for Separating and Concentrating of Targets in Saliva or urine Samples. The extraction of MA from human saliva or urine can be divided into four steps. i, 1.6 mL of MAspiked urine or saliva; ii, adding 80 μL of 10% NaOH, 0.54 g of NaCl and 400 μL of CHCl3, and vigorously shaking for 2 minutes; iii, centrifuging at 10k rpm for 2 min to separate the organic and aqueous layers; iv, the bottom organic layer was used for subsequent capsule assembly and SERS analysis. After self-assembly, removing most of the O phase to obtain a capsule of 10 μL volume, which has the size meet the requirement of the capillary channel. Hydrophilic Treatment of the Vessels. Silicon wafer, quartz cuvettes and 10 mL glass reagent bottles were cleaned and hydroxylated through one hour of immersion into a boiling piranha solution (98% sulfuric acid and 30% hydrogen peroxide with a volume ratio of 3:7). Then, the vessels were immersed in a saturated NaOH solution for 12 hours. Finally, all glasses were repeatedly washed with water and dried in an oven of 60 °C. SERS Measurements on GNP Capsules. The mirror-like GNP capsule is rapid formed through intense oscillations of GNP sols and the O phase, and all of the GNPs in the aqueous phase can reach the interface. The analyte can be dissolved in either of the two phases. The laser wavelength is 785 nm, laser power is 15 mW, exposure time is 8 s. A quartz capillary with a square cross section has the dimensions of 1 mm × 1 mm × 10 cm and is used as the key part of microfluidic channel. The laser excitation is focused onto the inner sidewall of the microfluidic channel, and it is very close to the GNP array of the capsule.

3.

RESULTS AND DISCUSSION

3D O/W Interfacial PCM-SERS Platform. Mirror-like plasmonic capsules were prepared using citrate stabilized GNPs with diameter of ca. 100 nm and without other modification (Figure S2). Because of its excellent self-healing, the stability of SERS detection (Figure S3) and the uniformity of capsule size were ensured (Figure S4). Except the peak of the original GNPs, there is a peak from the longitudinal plasma resonance coupling at 886 nm (Figure S5). When the volume of GNP sols is 0.4 mL, the optimized SERS strength is obtained, in which the volume of O phase is fixed on 10 μL (Figure 1b and c). A representative characteristic band at 1351 cm-1 of R6G, which were assigned to xathenes ring stretching of C-C vibrations, used as relative SERS intensity analysis.34 When the volume is smaller than this, there are many cracks on the surface of PCM, which cannot form a dense nanofilm. When the volume is larger than this, folds appear on the surface of PCM (Figure 1a). Based on optical microscope photograph, SEM image (Figure S6) and In-situ synchrotron radiation small-angle X-ray scattering (SRSAXS) observations (Figure S7), it was concluded that an orderly arrangement of GNPs was formed at this time, which


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ACS Applied Bio Materials together with self-healing property ensures the stability of SERS signal.

Figure 1. (a) Microscope images with 20× objective lens of PCM with continuous gradient volumes of GNP sols (a1-a5: 0.1-0.5 mL). (b) SERS spectrum of 1 µM R6G with continuous gradient volumes of GNP sols. (c) Change of SERS relative intensity at 1351 cm-1 with continuous gradient volumes of GNP sols.

Mutually independent plasmonic capsules are first prepared using 10 µL of CHCl3, which contain R6G with various concentrations (Figure 2a). Subsequently, capsules are injected into microfluidic channel in sequence. Supplementary Movie 1 shows no residual and smooth flow situation of the capsule in microfluidic channel, and there was no significant effect of different flow rates on SERS detection results (Figure S8). The existence of W phase effectively avoids the volatilization of O phase and it is used to flush the channel. Ten spectra are collected on each capsule and the W phase between the capsules, respectively, with an integration time of 8 s. Figure S9 shows a blank sample. The band intensity at 1351 cm-1 (I1351) and the intensity ratio of I1351/665 were used for quantification analysis of R6G (Figure 2b). The SERS signals collected on each capsule are stable with an average relative standard deviation (RSD) of 4.4%. Other fingerprint bands of R6G show similar results (Figure S10). What’s more, the SERS platform is highly sensitive to the analyte. The difference of SERS intensity at 1351cm-1 is about 45 times between 0.5 μM R6G and the W phase blank control, and this alteration is the strong instantaneous on/off signal response. This fast on/off response is crucial for in situ sensing because it reduces the total detection time and reveals molecular information in the laser irradiated volume in real time. The insert in Figure 2b presented linear fittings of R6G quantitative detection on Raman intensity (I1351) and the normalized ratio (I1351/665), respectively. It is clear that the correlation coefficient of curve fitting was increased from 0.84 (intensity analysis) to 0.96 (ratio analysis) by using CHCl3 as IIS. Our previous studies have evidenced that the continuous O phase can be used as an IIS to correct the fluctuations of detection SERS signals caused by sample microenvironment.35 48 sequential collected SERS spectra of 0.4 μM R6G were used to plot a visual 2D spectral mapping (Figure 2c) and generated a 7.3% RSD of I1351/665 (Figure 2d ). This excellent stability should be attributed to the fact that the capsule occupies the entire channel and the distribution of GNPs on the nanofilm is uniform and regular within the laser spot range (20 µm).

Figure 2. The PCM-SERS analyzer for quantitative analysis. (a) Illustration on sequential detection of R6G with increased concentrations ranging from 0.1 to 0.8 μM. (b) SERS intensity at 1351 cm-1 collected on eight mutually independent plasmonic capsules and the corresponding blank spaces. The percentage represents RSD of 10 spectra collected from each capsule. The inset shows the plots of concentration-dependent SERS at 1351 cm-1 before (blue line) and after (red line) the IIS calibration, respectively. The 665 cm-1 band of CHCl3 was used as IIS for spectral calculation. (c) 2D SERS spectral mapping of 48 spectra by using the same R6G concentration of 0.4 μM collected sequentially. (d) Statistical histogram of normalized band intensity at 1351 cm-1 (I1351/665) as indicated by red virtual box in (c).

High-throughput Analysis on Sequential Capsules. The sequential detection of 10 μM TTF, 1 μM MG, 1 μM R6G, 0.1 μM CV and 0.1 μM MB in different capsules were examined in about one minute (Figure 3a). To estimate the stability of SERS detection, we reduce the velocity of ultrapure water injected into microchannel so that 10 spectra can be collected on each capsule. The original spectra are shown in Figure 3b. Among them, the bands at 500 cm-1 of TTF, 1168 cm-1 of MG,36 1310 cm-1 of R6G, 1614 cm-1 of CV, and 1027 cm-1 of MB were chosen to calculate the RSD of each spectral set. After calibrated by the IIS, the corresponding RSD values are 5.2%, 7.8%, 6.2%, 8.1% and 6.8%, respectively, and the overall average RSD is 6.8%. High-precision detection of different concentrations of samples without any sample contamination indicates that the small capsules have excellent encapsulation. Because the preparation of the capsule is offline, even if the concentration of the detected substance is high, cleaning the capsule with ultrapure water effectively avoids the contamination of the capsule (Figure S11-S13).



analytes. The multiplex spectrum contains both the fingerprint bands assigned to CV (418, 434, 719, 794, 915, 972, 1392 and 1614 cm-1) and the bands assigned to R6G (400, 567, 608, 632, 1085, 1123 and 1643 cm-1), indicating that the PCM-SERS platform has a good ability to identify the fingerprints of dualanalyte in a capsule. Similarly, mutually independent capsules with the same molecular number of CV and R6G were separately pushed into flow channel as the reference. In the generated individual SERS spectra of CV (green line in Figure 4a), the peaks at 794, 915, 1392 and 1614 cm-1 assigned to the ring C-H bending, ring skeletal vibration of radical orientation, N-phenyl stretching and ring C-C stretching vibrations, respectively, could be clearly discriminated.37 In individual spectrum of R6G (magenta line in Figure 4a), 608 cm-1 assigned to in plane C-C-C bending vibration, 770 cm-1 attributed to out of plane C-H bending, 1310 cm-1 assigned to in plane xanthene ring breathing, and 1123 cm-1 assigned to the C-H bending and N-H bending vibration of xanthene ring.34 It can be clearly seen that the ratio of these band strength of dual-analyte to singleanalyte are less than 1 (Figure 4b). This is due to the competitive adsorption between the two substances to be measured, which results in the corresponding decrease in SERS peak strength.

Figure 3. (a) Sequential analysis of 10 μM TTF, 1 μM MG, 1 μM R6G, 0.1 μM CV and 0.1 μM MB in individual capsules, respectively. (b) Normalized SERS spectra of each analyte by using 665 cm-1 band of CHCl3 as IIS. All of the sample volumes were 10 μL. (c) Comparative study of the average intensity of 1351 cm-1 of 0.5 μM R6G and (d) the variation of RSD in 10 spectra collected sequentially in ASM and PCM detection systems.

Meanwhile, for a comparative study, 0.5 μM R6G detection was performed on conventional ASM system. Such system exhibits a signal intensity of 6 times lower than PCM system (Figure 3c) and a slightly better repeatability with RSD=4.5% (Figure 3d). The huge difference in sensitivity is mainly due to much smaller overall density of GNPs and analytes in the excitation volume in ASM system, and the better signal repeatability should attribute to the uniform dispersion of GNPs in ASM system. In general, the PCM system shows much better sensitivity with an acceptable repeatability compared to ASM system. In addition, because plasmonic capsules was assembled on the O/W interface, the solvation shell of GNPs was not destroyed and the GNPs would not contact the microchannel wall directly,[15] so the degree of pollution is smaller than ASM system under the similar conditions. Consequently, PCM-SERS platform has excellent signal reproducibility to ensure reliable high-throughput analysis of multiple analyte samples (5 sample/1 min), and it promises sequential detection of multiple sample inputs compared to the existing platforms that normally uses a single sample input to protect the substrate from contamination. Multiplex Detection in Single Capsule. The CV and R6G were used as model molecules to examine multiplex detection in one capsule of our 3D PCM-SERS detection system. A capsule containing 0.5 μM CV and 5 μM R6G generates a multiple spectrum of fingerprint signals containing two

Figure 4. Simultaneous determination of multiple analytes in one capsule. (a) SERS spectra of coexisting CV and R6G (black line) referred to sole CV (green line) and sole R6G (magenta line) in individual capsules, respectively. (b) Corresponding SERS peak strength ratio of multiplex and reference SERS peak intensity of CV and R6G. The ratio between the peak intensity and the reference spectral peak is determined by two components. (c) One capsule for detecting two analytes with huge differences in concentration, 0.05 μM R6G and 1 μM CV. (d) One capsule for detecting three analytes with huge differences in concentration, 2 μM TTF, 5 μM R6G and 1 μM CV. The Raman bands indicated by green, blue and magenta lines are assigned to CV, TTF and R6G, respectively.

What’s more, the concentrations of CV (1 μM) and R6G (0.05 μM) differ by two orders of magnitude were also successfully explored in one capsule by PCM-SERS system (Figure 4c). The results indicate that PCM-SERS system has a superior ability to mixtures, even when one analyte is submerged by another, it still has its own fingerprint. Triple analytes including 2 μM TTF, 5 μM R6G and 1 μM CV in one capsule were tested simultaneously by PCM-SERS system (Figure 4d). Furthermore, spectra of multicomponent samples with arbitrary concentrations are used to mimic real-life scenarios of high through-put analysis/diagnosis of multiple


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ACS Applied Bio Materials samples (Figure S14). The results evidenced its potential application prospects of PCM-SERS system in complex multicomponent real environments. Rapid and Efficient Detection of Low Raman-active MA.

Figure 5. The PCM-SERS analyzer for tracing MA in standard solutions. (a) SERS spectra of MA with gradient increasing concentrations from 0 to 100 ppm, dissolved in CHCl3 (Insert is the molecule structure of MA). (b) A Langmuir fitting relationship between the I993/665 values and MA concentrations. (c) 2D SERS spectral mapping of 60 ppm MA. (d) Statistical histograms of I993/665 values.

The illicit drug methamphetamine (MA), which is a serious threat to public safety and human health, has relative low Raman activity. Here MA was used as an example to examine the potentials of PCM-SERS system in practical detection. Chloroform containing 0-100 ppm MA standard solutions was first used as to assemble different batches of capsules. The gradient SERS spectra were collected sequentially in our platform. It should be noted that the detection process is less than 10 minutes excluding sample preparation time. The peaks at 993 and 1203 cm-1 were attributed to MA molecules of the out-of-plane bending of C-C-C ring stretching and the phenylC stretching by comparing with blank sample.38 The peak of 0.1 ppm MA is clear, and its strength increases steadily with the increase of MA content (Figure 5a). The relationship between SERS intensities of the most distinguishable peak 993 cm-1 and MA concentrations matches a Langmuir fitting with a correlation coefficient (R2) of 0.98 (Figure 5b). Among them, the regions i from 0.1-10 ppm and ii from 10-100 ppm show the linear correlation with the R2 values of 0.99 and 0.94, respectively (Figure S15). To examine SERS reproducibility, spectra were sequentially collected on a capsule (60 ppm MA), and further normalization of I993/665 generated a uniform 2D spectral map (Figure 5c). The corresponding RSD of the characteristic peak intensity at 993 cm-1 (red virtual box in Figure 5c) is 7.8% (Figure 5d). The above results demonstrated an excellent SERS quantitation and high-throughput analysis capability of PCM-SERS platform for low Raman-active MA.

Reliable Microfluidic-SERS for Analyzing MA in Human Saliva and Urine.

Figure 6. PCA-assisted PCM-SERS analyzer for precise tracing MA in real human saliva. (a) Schematic procedures for separation and concentration of MA from saliva: (i) human saliva with certain MA; (ii) the addition of NaOH and NaCl; (iii) the addition of CHCl3 and centrifugation; (iv) assemble into capsule. (b) SERS spectra of MA with gradient increasing concentrations from 0 to 100 ppm. (c) A linear relationship of I993/665 against MA concentrations. (d) 3D PCA scores plotting of the SERS spectra under different MA concentrations.

A 10-minute pretreatment was used to extract MA from human saliva (Figure 6a). It should be noted that the use of CHCl3 as an extraction agent largely avoids the interference. The extractant from the saliva generated unique SERS spectra on PCM-SERS platform (Figure 6b). The SERS intensities of MA fingerprints gradually increased as increasing the concentration of MA in saliva. The main MA vibrational features at 993 cm-1 was well-resolved. It should be noted that the extractant from pure saliva samples without the addition of MA produced blank spectrum but with several peaks which should be attributed to the impurities extracted from saliva (Figure S16a), these impurities can also be adsorbed on the surface of GNPS and produce SERS impurity peaks. The SERS intensity of impurity peaks did not change significantly with the increase of MA addition, while the SERS intensity of some reported characteristic peaks of MA increased with the increase of MA addition, so we can confirm that MA was successfully extracted from saliva samples (Figure S16b).38 This results evidenced the capability of SERS analyzer for ultratrace sensing in unknown complex samples. To examine SERS reproducibility, 40 spectra were sequentially acquired on a single capsule containing 100 ppm MA. The normalization of



I993/665 by IIS generated a 2D mapping (Figure S17a), and corresponding RSD of the relative SERS intensity at 993 cm-1 is 7.3% (Figure S17b). The average intensity at 993 cm-1 after IIS calibration was fitted as a function related to MA concentration. The regression equation is y=0.0055x+0.41628, and the correlation coefficient was 0.99 (Figure 6c). The online microfluidic SERS rapid detection method based on plasmonic capsules will greatly improve its practical application performance if it can be combined with the spectral algorithm of automatic recognition and classification. Hence, PCA algorithm was carried out to distinguish the spectral profiles and realized the auto-classification of each collected spectrum (Figure 6d). Firstly, we collected 20 spectra in MA of each concentration (0, 1, 10, 20, 40, 60, 80 and 100 ppm) in saliva samples by the same pretreatment and PCM-SERS. The PCA recognition could obviously cluster these data into seven groups by the first three principal components, PC1, PC2 and PC3, which represent scores of 94%, 5% and 1%, respectively. The loadings of variables (Raman shift in our study) on each PC could illustrate the variable contributions for classification. The loadings plot of each PC is shown in Figure S18. And there was no overlap in the data clustering, indicating an outstanding capability of PCA-assisted PCM-SERS platform for tracing drug in saliva.

classification of MA with different concentrations in human saliva. We believe that the PCM-SERS system provides a solid foundation for rapid, efficient, on-site, ultra-trace and quantitative detection in different fields, such as food safety, biomedicine and public safety. It also lights up the possibilities of plasmonic capsules for monitoring molecular events in confined spaces, especially in multi-liquid systems.

ASSOCIATED CONTENT Supporting Information Homemade PCM-SERS analyzer. Characterization of GNP sols. Self-healing property ensures the stability of SERS detection. Optical images of capsule self-healing process. UV-Vis absorbance spectrum of the capsule. SEM observations on plasmonic optimized capsule. One-dimensional SR-SAXS scattering curves. Effect of flow rate change on SERS detection. SERS spectra of blank capsule. RSD of SERS strength variation at different peak locations of 0.5 µM R6G. 10-4 M MB for assembling capsule. SERS spectra of four separate capsules of 10-4 M MB, sample 1, sample 2 and a blank. Time-lapse spectra of four separate capsules in the same channel. Spectra of multi-component samples containing arbitrary concentrations of CV and R6G. Linear relations of regions ⅰ and ⅱ. Comparison of theoretical blank sample and salivary blank sample. 2D SERS spectral mapping of 100 ppm MA in actual system. Loadings plot of PC1, PC2 and PC3. MA detection in multiple human saliva samples and urine samples. Real detection and recovery test of saliva and urine samples.

AUTHOR INFORMATION Corresponding Author *E-mail: [email protected] (H.L.) *E-mail: [email protected] (L.Y.)

Notes Figure 7. Real detection and recovery test of saliva samples with gradient-increased MA addition in three parallel samples.

Furthermore, the PCM-SERS strategy generated a recovery of MA ranging from 57.7% to 81.3% and the statistical value is 67.4% ± 6.2% in saliva samples with gradient-increased MA addition (Figure 7). The data imply that the method is stable and the RSD is 9.2%. If the MA extraction method in complex saliva samples can be further optimized, the sensitivity of SERS detection will be further improved. MA detection in multiple human saliva samples and urine samples has also been successfully completed (Figure S19-20). The data indicated that PCM-SERS strategy was reliability for analyzing real biological samples and it has great potential to be developed into a practical on-spot analyzer for detecting drugs in complex media.

4. CONCLUSIONS This study constructed the mirror-like plasmonic capsules as microfluidic-SERS platform for high-throughput, high sensitivity and high reproducibility detection. This kind of plasmonic capsules avoided mutual contamination between individual capsules and realized multiplex identification and quantitation of chemicals in complex samples. This online SERS analyzer realized continuously detection of R6G in a microchannel with concentrations from 0.1 to 0.8 μM. The use of O phase as IIS eliminated the SERS fluctuations caused by sample microenvironments. This analyzer realized the sequential detection of five different analytes in about one minute and obtained the RSD of less than 5%. By virtue of PCA recognition, we have successfully realized the auto-

The authors declare no competing financial interest.

ACKNOWLEDGMENTS This work was supported by the NSFC (21874034, U1632116 and 11705044), the Fundamental Research Funds for the Central Universities (JZ2017HGPA0166), Key Research and Development Project of Anhui Province (1704a07020067), and Key Projects of Applied Basic Research of Hunan Province (2016JC2065). Special thanks to the Opening Project of State Key Laboratory of High Performance Ceramics and Superfine Microstructure (SKL201808SIC).

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