Lin Bao

Scopolamine and promethazine can be used as a substitute for heroin. It is relatively fast and simple to use surface-enhanced Raman spectroscopy (SERS) for the detection and monitoring of drug usage. Silver nanosol is an enhanced substrate that is commonly used in the SERS technique; the Raman signal of the sample is amplified by the substrate. However, for the detection of mixtures, the competitive adsorption of different components relative to the substrate will result in difficult qualitative identification of spectra. By taking advantage of this defect, the adsorbed components of a mixture were separated from silver nanoparticles by centrifugation, thus changing the mixing ratio of the two components in the mixture. As a result, the proportion of the components with strong adsorption in the mixture is relatively reduced. Thus, the components with weak adsorption can be displayed in the spectrum of the mixed solution.

Heroin is one of the most widely used narcotics in the world, and it is a key target to be monitored because of its addictive quality and the difficulty in quitting the addiction (1–6). After long-term use, heroin will cause serious damage to the nervous system of the human body, and will also adversely affect judgment, possibly causing harm to the addict or society (4,7,8). Some drug rehabilitation institutions use less harmful drug-like substances as substitutes to reduce the suffering of drug addicts and damage to their nervous system (9–14). For example, a mixture of buprenorphine, scopolamine, and promethazine, referred to as BSP, has been used because its toxicity is much lower than that of heroin (15). However, long-term use of BSP will still cause great damage to the human body (9,10). Because the price of BSP is low and it is easily accessible, it has become an alternative drug for some drug users. Therefore, it is necessary to engage in the detection and monitoring of this new type of drug abuse.

Surface-enhanced Raman spectroscopy (SERS) is a combination of Raman spectroscopy and nanotechnology, and it can enhance the Raman signal by 7–10 orders of magnitude when the tested sample is near or adsorbed on a substrate at the nanometer scale (16–19). The Raman spectrum of each sample is specific, and can be qualitatively identified as the fingerprint of the sample.

There are two popular viewpoints about the enhancement mechanism of SERS: One viewpoint is electromagnetic enhancement, and the other viewpoint is chemical enhancement (17,20). Electromagnetic enhancement generally refers to the enhancement of Raman signals by the strong electromagnetic field generated by the local surface plasmon (LSPR) excited by the rough surface of metal materials or the surface of metal nanoparticles (21). The chemical mechanism refers to the contribution of Raman scattering independent of the electromagnetic environment (such as plasma polaritons). The increase in SERS signal is usually attributed to electron transfer between the adsorbed molecule and the substrate. Current research results show that the two enhancement mechanisms generally play a role at the same time, and that signal amplification effect of electromagnetic enhancement is greater than that of chemical enhancement. Based on these enhancement phenomena, the SERS signal can be improved to some extent through substrate design or gap control (22–25).

Surface-enhanced spectroscopy as a drug detection technology has become increasingly mature (26–29). Because of its characteristics, it is more suitable for the detection of drugs in solution than many other analytical techniques. Compared with other detection technologies, the advantages of SERS lie in the simple operation of the instrument, the uncomplicated pretreatment of the sample before detection, the fast detection time, and the convenience of the portable instrument for the in situ detection of samples (30).

For SERS detection of mixtures, there are two problems associated with direct detection: One is the overlapping of peaks, and the other is competitive adsorption (31). Overlap of spectral peaks is most likely to occur when the molecular configurations of the components of the mixture are relatively similar.

There are some differences in the molecular configuration of the two components we tested. They were distinguished from the spectrum of the mixture as described in our previous studies (15). From the spectral observation, there is no chemical reaction of the two components after mixing; that is, no new substance is formed. The current study focuses on eliminating the interference of competitive adsorption in practical detection.

A BWS415-785H portable Raman spectrometer (B&W Tek, Inc.) was used to obtain the spectral data. The maximum working power of the Raman spectrometer was 0.3 W. The laser wavelength was 785 nm. After spectrum acquisition, the spectrum is smoothed and the baseline was corrected by the instrument software.

The morphology of nanoparticles was characterized by a high-resolution field emission scanning electron microscope (Hitachi Company). The dynamic light scattering test was measured by a PALS/90P particle size analyzer (Brookhaven Instruments Co., Ltd.). A Cary 4000 UV-vis spectrophotometer was also used (Agilent Technology Co., Ltd.).

Potassium iodide (KI), silver nitrate (AgNO

) were purchased from Sinophram Chemical Reagent Co., Ltd. Scopolamine hydrobromide powder (1G) and promethazine hydrochloride powder (5G) were purchased from Dalian Meilun Biotechnology Co., Ltd.

The solutions of scopolamine and promethazine were obtained by diluting scopolamine hydrobromide and promethazine hydrochloride, respectively, with deionized water, are used to obtain solutions with different concentrations. Each solution is mixed with the substrate at the same time.

The preparation of the silver nano-substrate is as follows: Soluble silver salt nitrate (AgNO

) was used as an oxidant, and ascorbic acid was used as the reducing agent to prevent the aggregation of silver nanoparticles. Sodium citrate was used as the stable solution. Their concentrations in the initial solution were 0.168 mg/mL, 0.105 mg/mL, and 0.873 mg/mL. First, the water bath condition was prepared at 30 

C. Then, the three concentrations (soluble silver salt nitrate, ascorbic acid, and sodium citrate) were placed in the bath proportional to each other, then the solutions (sols) were stirred continuously for 15 min with a magnetic mixture and both sol and nanosol are used. Then, the temperature of the water bath was continually raised to the boiling state and stayed at that temperature level for 2 h until the color turned grayish-green. Then, the sol was refrigerated after cooling. Before using it, the sol needed to be centrifuged and purified to remove the smaller particles and improve the monodispersibility of the particles. Ultrasonic oscillation dispersion was performed before the test was used.

Figure 1 shows the SEM characterization of the silver sol substrate. The main process used is described in the literature (32). The silver nanoparticles are basically in a spherical state, and there is no mixing of other shapes of the substrate. Figure 2a shows the UV absorption spectrum, and the scanning range is from 300 nm to 800 nm. The absorption resonance peak is approximately 439 nm, which is consistent with the absorption peak of the silver sol. Figure 2b shows the statistical weight distribution of the particle size of the silver sol measured by dynamic light scattering (DLS) technology. Among them, 60 nm particles account for the largest proportion in the system, with its statistical weight being the total number of particles set to 100% and the statistical weight of other particle sizes compared with its value as the ordinate value of other particle sizes. It can be seen that several main particle sizes are distributed at 50–80 nm.

FIGURE 1: SEM image of silver sol substrate.

FIGURE 2: (a) Particle size distribution of silver sol; (b) UV-vis extinction spectra of silver sol.

 M) scopolamine were used to compare the mixture, as shown in Figures 3a and 3c. It should be noted that because the signal of scopolamine is weak, the intensity of scopolamine is exaggerated by about three times. When the molar concentration ratio of the two mixtures was 1:1 (1.5 x 10

 M), a weak Raman signal of scopolamine was detected at 1002 cm

. As shown in Figure 3b, the characteristic peaks in the mixture mainly belong to promethazine. However, in the previous study, when the concentration of the two components was the same, the spectrum was mainly the spectrum of scopolamine (15). The difference is that in our current study, the mixture was in contact with the silver nanoparticles at the same time; in the previous study, scopolamine was first added to the silver nanosol (nanosolution), and then the promethazine was subsequently added. From the trend of these two spectra, we can deduce that there is a competitive adsorption phenomenon when they are mixed simultaneously. Promethazine will mask the characteristic peak of scopolamine at the same concentration, which is not conducive to identifying the spectrum of the mixture. What is more troublesome is that in the actual mixing ratio, the concentration of scopolamine is much lower than that of promethazine. To enhance the signal of scopolamine, we added potassium iodide into the mixture system to increase the strength of scopolamine.

FIGURE 3: SERS spectra of (a) promethazine 10 ppm (3.5 x 10

 M); (b) mixture at concentration ratio of 1:1 (1.5 x 10

To improve the signal of scopolamine in the mixed solution in Figure 3, we added potassium iodide (1 M). As shown in Figure 4, the signal of scopolamine at 1002 cm

 increases with the addition of electrolytes, but it greatly decreases compared with the detection of scopolamine at the same concentration alone. Moreover, the concentration ratio of the silver sol we used is further increased, and the signal should be stronger in theory than what is shown in Figure 4. The characteristic peaks of promethazine in the spectrum of the mixed solution are basically all displayed. Promethazine of the same concentration was added to the electrolytes for independent detection and is compared with the mixture spectrum, as shown in Figure 5. The position and intensity of the peak of the mixture spectrum are almost the same as that of promethazine alone. Table I compares the intensity of the mixture spectrum with that of promethazine when it is separately detected in several main characteristic peaks. The results show that the signal of promethazine was dominant even though both of them were enhanced. This further shows that the enhanced signal of the two is mainly caused by the molecules adsorbing on the silver nanoparticles. The addition of electrolytes did not change the adsorption ratio of the two but further reduced the distance between nanoparticles and enhanced their signal.

FIGURE 4: SERS spectra of mixture at concentration ratio of 1:1 (1.5 x 10

FIGURE 5: Comparison of SERS spectra between mixture and promethazine.

In the mixture with the same concentration, the signal of scopolamine is weak, which is not conducive to spectral recognition. The more difficult problem is that the concentration of promethazine with strong adsorption is much higher than that of scopolamine in the actual ratio. It can predict the difficulty of actual detection. To verify this assumption, we mixed them according to the actual ratio, in which the mass concentration of scopolamine is 10 ppm (3.3 x 10

 M), and the doping of promethazine is 1670 ppm (5.9 x 10

 M). Through SERS detection, as shown in Figure 6a, scopolamine in the actual ratio cannot be identified in the Raman spectrum. Only the characteristic peaks of promethazine can be identified, which is consistent with the expected results.

FIGURE 6: SERS spectra of mixture (a) original solution (promethazine: 5.9 ́ 10

 M) (b) the first centrifugation, (c) the second centrifugation, and (d) the last centrifugation.

According to the experimental verification, the nanoparticles in the silver sol are relatively easy to separate from the solution, as shown in Figure 8. For example, most of the nanoparticles will be located at the bottom of the tube after high-speed centrifugation. Figure 8a shows the original sol solution, and the supernatant after centrifugation is shown in Figure 8b. We used this method in combination with the “defects” of competitive adsorption to separate the components of the mixture in solution. After the mixed solution was added to the silver sol and then centrifuged, the silver sol traveled to the bottom of the centrifuge tube. Some samples adsorbed on the silver nanoparticles were separated from the mixed solution.

FIGURE 8: (a) Silver sol before centrifugation, and (b) silver sol after centrifugation.

The adsorption of promethazine is stronger than that of scopolamine. Thus, promethazine should be the main component separated. The proportion of mixture in the remaining supernatant changed: The proportion of promethazine decreased, and the relative concentration of scopolamine increased. After repeating this several times, the characteristic peak of scopolamine can be seen in the mixed solution.

First, we centrifuged the mixed solution at a high speed for 20 min and removed the supernatant for detection. The results as shown in Figure 6b indicate that there was no signal of scopolamine. The signal intensity of promethazine greatly changed, indicating that the concentration of promethazine changed accordingly. However, the signal intensity of promethazine in the supernatant increased because the relationship between concentration and signal intensity in the higher concentration range is not necessarily consistent. This is mainly because of the intensity saturation effect in SERS detection.

After the first centrifugation, the supernatant was again mixed with concentrated silver sol and prepared for the second centrifugation. After the second centrifugation, the supernatant was removed for testing, and the results are shown in Figure 6c. The 1034 cm

 signal intensity for promethazine changed, indicating that the concentration also changed, but the main peak at 1002 cm

 for scopolamine still did not appear. On this basis, we continued to centrifuge the supernatant mixture of the previous step, and the supernatant after centrifugation was detected, as shown in Figure 6d. The signal of scopolamine was finally detected, and the signal strength of promethazine was much weaker. At the concentration of the mixture according to the actual use ratio, it was finally detected that both existed in the spectrum.

In the mixed solution, according to the actual ratio, we selected 1002 cm

 so we can clearly see the change of the spectrum of scopolamine in the process, which is shown in Figure 6. Figure 7 displays the results in a column chart. Although the first three times have weak intensity, they are below the detection limit so they can be regarded as the absence of scopolamine. The fourth time is the success of the actual detection of scopolamine.

FIGURE 7: SERS intensity of mixture at 1002 cm

We used simple experimental conditions to identify the spectrum of a solution mixture and utilized the disadvantageous SERS detection conditions to create a means of separating mixtures. This solves the problem that the strong adsorption component in the mixture can inhibit the weak adsorption component in the Raman spectrum. It should be noted that in the process of continuous centrifugation, the mixed solution is diluted to a certain extent. Although the relative concentration ratio of scopolamine is increasing, the concentration of scopolamine itself is decreasing, and therefore, the number of centrifugations needs to be properly controlled. The amount of silver sol used for centrifugation also requires optimization. Compared with other methods of separating mixtures, the procedure described herein is simple, and it is not only a feasible new method for the SERS detection of solution mixtures, but also for a rapid screening of new alternative drugs.

This work was supported by the National Natural Science Foundation of China( Grant No. 31871873), Inner Mongolia University for the Nationalities (Grant No. NMDYB18006), and the Inner Mongolia Autonomous Region Natural Science Foundation of China (Grant No. 2018LH08055).

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 is with the National Laboratory of Science and Technology at the Harbin Institute of Technology in Harbin, China. 

 is with the National Laboratory of Science and Technology at the Harbin Institute of Technology in Harbin, China, and the College of Physics and Electronic Information at the Inner Mongolia Universities for Nationalities. 

 is with the Affiliated Hospital at Inner Mongolia University for the Nationalities. Direct correspondence to Wuliji Hasi at 

Articles

SERS can be used for the detection and monitoring of drugs as pure compounds and mixtures. A demonstration of a sample preparation method used to detect components with weak substrate adsorption in the spectrum of a mixed solution is shown.

Analysis of a Mixture Solution Using Silver Nanoparticles Based on Surface-Enhanced Raman Spectroscopy (SERS)

A simple method for phenobarbital detection was established. Based on the density functional theory (DFT), the geometry optimization and spectra calculation were performed using Gaussian software on a Becke, 3-parameter, Lee-Yang-Parr (B3LYP) level for phenobarbital. The results from theoretical analysis were compared with experimental results, and the Raman frequencies and their vibrational modes were assigned. A silver colloid surface-enhanced Raman scattering (SERS) substrate, with uniform size and good monodispersity, was prepared, and samples were detected without any pretreatment. The detection conditions were optimized. A linear relationship was obtained between concentration and Raman intensity over the 12–100 µg/mL concentration range. The limit of detection (LOD) was 12 µg/mL, and the recovery rate was between 94.2% and 111.2%. This method shows great practical potential for the identification of phenobarbital.

	Phenobarbital is a representative long-acting barbiturate. It has sedative, hypnotic, and anticonvulsant effects. If used improperly (including excessive and long-term use), it may threaten human health. Large doses can inhibit the cardiovascular and respiratory systems, and even can lead to paralysis of the respiratory center of the medulla oblongata. Long-term use can lead to dependence. Psychotropic drugs make the body dependent and can harm human health. Therefore, the use of such drugs should be strictly monitored and controlled.

	Raman spectroscopy offers fast, simple, repeatable, qualitative, and quantitative analysis in a noninvasive way. It does not require complex sample preparation, or data analysis (1–3). However, the signal is weak. Thus, surface-enhanced Raman spectroscopy (SERS) is used to overcome problems related to low sensitivity (4,5). It is widely used in pharmaceutical analysis (6,7). Yokoyama and Yamada (8,9) describe a flexible substrate based on SERS for biochemical analysis. However, there is no optimization of the experimental parameters, quantitative analysis, and assignment of the characteristic peaks.

	We examined the Raman spectra of phenobarbital using the droplet detection mode (10). Some of Raman characteristic peaks of phenobarbital were assigned, and the Raman peak at 666 cm

 was used as the basis for stability analysis and quantitative analysis. The experimental conditions were then optimized. The linear quantitative range was 12–100 µg/mL. The main devices and procedures are shown in Figure 1.


	Figure 1: Schematic diagram of the method proposed for the phenobarbital detection process.

) and sodium citrate was purchased from Sinopharm Chemical Reagent Co., Ltd. Sodium hydroxide (NaOH) and potassium iodide (KI) were purchased from Xilong Chemical Co., Ltd. An injectable phenobarbital solution (0.1 mg/mL) and phenobarbital powder were purchased from Tianjin Jin Yao Pharmaceutical Co., Ltd. Hydrochloric acid (HCl) was purchased from Tianjin Kermel Chemical Reagent Co., Ltd.

	We used a model BWS415-785H portable Raman spectrometer (B&W Tek, Inc.). The laser wavelength was 785 nm. The probe distance was 5.9 mm, and the spectral resolution was less than 3 cm

. The laser power was 120 mW, and the spectral integration time was 5 s. The data were analyzed by B&W Tek, Inc. embedded software for smoothing and background correction.

Sample Treatment and Preparation of Silver Colloid

	The 0.1-mg/mL of phenobarbital injectable solution served as the stock solution. This solution was diluted with deionized water at 12, 20, 30, 50, 70, and 100 µg/mL. The silver nitrate powder was dissolved in deionized water (11) and heated. When the solution boiled, the sodium citrate solution with a mass fraction of 1% was immediately added, and then boiled for 1 h. This solution was then cooled from room temperature to 4 °C, and protected from light.

	Based on the electromagnetic (EM) enhancement theory, the SERS intensity is dependent on the resonance frequency of the noble metal substrate. The plasmon resonance frequency depends on the size of the nanoparticles, especially for gold and silver nanoparticles (12–15). The morphology and size of the silver nanoparticles were characterized by scanning electron microscopy (SEM), as shown in Figure 2. As can be seen from the map, the silver nanoparticles are spherical and have uniform morphology. The average size of silver nanoparticles was about 50 nm, and its main particle size distribution ranged from 50 to 80 nm by dynamic light scattering analysis.


	Figure 2: Size distribution of silver nanoparticles (inset: SEM picture of silver nanoparticles).

	Raman spectra were performed with the B3LYP hybrid functional with the 6-31g (d, p) basis set. The structure of the optimized phenobarbital molecule is shown in Figure 3. To attribute the Raman characteristic peaks of phenobarbital, we collected the Raman spectra of powder and the SERS spectra of phenobarbital, and compared their Raman spectra with DFT calculation, as shown in Figure 4. It can be seen from the graph that the main Raman peaks in phenobarbital are 625 cm

. These peaks are basically matched to the Raman peaks of the solid powder and the Raman peaks of the SERS in the aqueous solution. The deviation of displacement is caused by different external conditions. The theoretical model is the case of a single phenobarbital in the vacuum, and the solid and SERS spectra are the results of the solid and liquid phase. The matching and attribution of the specific Raman characteristic peaks of phenobarbital are shown in Table I.


	Figure 3: Optimized structure of phenobarbital.

	Adding coagulant can change the dispersion state of the nanoparticle sol. This addition breaks the balance potential of the sol system so that the sol particles aggregate (16). It results in more SERS hotspots with good enhancement effects. Thus, we selected 0.1 M (NaOH), acid (HCl) 0.1 M, and neutral (KI) 0.1 M coagulants. The results were collected under the same experimental conditions and show that the Raman spectra of hydrochloric acid coagulant do not induce characteristic peaks (Figure 5). The spectrum with KI coagulation has only subtle peaks at 1002 cm

. These phenomena are probably due to the theory of Hofmeister; some ions will destroy the structure of macromolecules and the denaturation strength of chloride ions in the sequence is greater than that of iodine ions, which is consistent with the experimental results. Although a certain degree of migration occurred in the 655 cm

, the spectrum with sodium hydroxide has all strong peaks in phenobarbital. Thus, all subsequent experiments used 0.1 M NaOH as the coagulant. The coagulant, sample, and silver colloid volume ratios were 1:1:1.


	Figure 4: Raman analysis of phenobarbital: theory-calculated, powder, and SERS spectra of an aqueous solution (0.1 mg/mL).

	The SERS spectra of different concentrations of phenobarbital were obtained (Figure 6). The laser power was 120 mW, and the integration time was 5 s. All measurements were performed over five replicates and averaged. Above 12 µg/mL, the Raman signal of the sample could still be detected at 666 cm

. The detection limit of phenobarbital in aqueous solution was 12 µg/mL. In the past, the judgment of the detection limit for the substance is more concentrated on one of the most discernible characteristic peaks. The experiment can also have 666 cm

 peaks at lower concentration could be detected. But for the sake of being precise, this article uses 666 cm

 as the quantitative analysis peak, and the combination of 1002 cm

 appears simultaneously as the criterion for determining the LOD.

	A stable and repeatable SERS signal is important when using silver aggregates. The 666 cm

 peak was selected for stability analysis. We selected three different concentrations of phenobarbital solution under the same conditions. These were repeated over 15 experiments in 5 min. The standard deviations at 80 µg/mL and 50 µg/mL were both less than 5% and approximately 5% at 20 µg/mL (Figure 7). Figure 7 shows that the silver aggregates have good repeatability.


	Figure 5: SERS spectra of phenobarbital sodium using different aggregating agents.

	Figure 8 shows the linear relationship between the concentration of phenobarbital and Raman intensity at 666 cm

 from 12 to 100 µg/mL. The fitting equation is 

 is the intensity of the Raman peak at 666 cm

 in the SERS spectrum of the phenobarbital sodium and 

 is the concentration of phenobarbital sodium. To ensure the accuracy of the data, all spectra were collected five times and averaged. The correlation coefficient is 0.9955, suggesting a good fit.


	Figure 6: SERS spectra of different concentrations of aqueous phenobarbital.

	To test the accuracy and reliability of this method, we detected three different concentrations (16 µg/mL, 60 µg/mL, and 90 µg/mL) of the spiked samples. The SERS spectra were collected using a portable Raman spectrometer, and each sample was measured three times. We selected the 666 cm

 characteristic peak intensity values to fit the formula above. We then calculated the corresponding concentration value, and calculated the corresponding recovery rate and relative standard deviation (Table II). The data indicate that SERS can accurately detect phenobarbital sodium. The recovery rate was 94.2%–111.2%, and the average relative standard deviation is about 5%. SERS detection of phenobarbital is accurate, simple, and efficient. This technology offers real time and rapid detection of phenobarbital.


	Figure 7: Reproducibility of NaOH-induced silver aggregates in solution.

	We used SERS to detect phenobarbital in an injectable solution. First, the hydrogen phenobarbital Raman peaks were assigned to determine the characteristic peak. We then induced aggregation with sodium hydroxide. The aqueous solution of sodium hydroxide increased the SERS signal and lowered the detection limits. We used linear fitting for semiquantitative analysis, and then calculated the recovery rate. The detection limit of phenobarbital is based on the signal at 666 cm

 in the range of 12–100 µg/mL. The best fit curve is 

= 0.9955). The recovery rate was 94.2–111.2%. This method is rapid, accurate, nondestructive, and easy. It is useful for the detection of phenobarbital in an injectable solution.

	This work was supported by the National Natural Science Foundation of China (Grant No. 31871873) and the Inner Mongolia Autonomous Region Natural Science Foundation of China (Grant No.2018LH08055).


	Figure 8: Calibration curve for phenobarbital.

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Optical Diagnostics and Sensing XV: Toward Point-of-Care Diagnostics

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Optical Diagnostics and Sensing XVI: Toward Point-of-Care Diagnostics

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 is with the National Key Laboratory of Science and Technology on Tunable Laser at the Harbin Institute of Technology, in Harbin, China, and the College of Physics and Electronics information, at the Inner Mongolia University for Nationalities, in Inner Mongolia Tongliao, China. 

 are with the National Key Laboratory of Science and Technology on Tunable Laser at the Harbin Institute of Technology, in Harbin, China. 

 is with the Affiliated Hospital at the Inner Mongolia University for Nationalities, in Inner Mongolia Tongliao, China. Direct correspondence to: Wuliji Hasi at 

This SERS method is rapid, accurate, nondestructive, and easy

Lin Bao

Articles

Analysis of a Mixture Solution Using Silver Nanoparticles Based on Surface-Enhanced Raman Spectroscopy (SERS)

Quantitative Detection of Phenobarbital in an Injectable Solution Based on Surface-Enhanced Raman Spectroscopy