Method for determining SERS (Surface Enhanced Raman Scattering) effect of Ag-based composite nano material on dangerous

Abstract

The invention provides a method for determining SERS (Surface Enhanced Raman Scattering) effectiveness of an Ag-based composite nanomaterial on dangerous chemicals, and belongs to the technical field of data processing of dangerous chemicals. The method comprises the following steps: preparing an Au nanocrystal seed and Au-coated Ag core-shell nanostructure, preparing a CeO nanocube and an Ag-CeO nano heteropolymer, and preparing a Ag-coated Ag core-shell nanostructure. Mixing the Au (at) Ag core-shell nanostructure with the Ag-CeO nano heteropolymer to prepare a surface enhanced Raman detection substrate, obtaining a Raman spectrum standard correction matrix, a substrate enhancement effect evaluation matrix and an SERS enhancement coefficient correction matrix through the detection substrate and a Raman spectrometer, and establishing an SERS signal intensity normalization matrix, and finally, calculating an SERS utility value through the SERS signal intensity normalization matrix, the substrate enhancement effect evaluation matrix and the Raman spectrum standard correction matrix. The method solves the technical problem that in the prior art, the accuracy of SERS detection of dangerous chemicals is not high enough.

Description

Technical Field

[0001] The present invention belongs to the technical field of hazardous chemical data processing, and more particularly, relates to a method for determining the SERS effect of Ag-based composite nanomaterials on hazardous chemicals. Background Art

[0002] The rapid and accurate detection of hazardous chemicals is of great significance for environmental monitoring and public safety. Existing detection methods mainly include analytical methods such as chromatography, mass spectrometry, and spectroscopy. Although traditional gas chromatography and liquid chromatography have high detection sensitivity, they have disadvantages such as long analysis time and complex sample pretreatment, making it difficult to meet the requirements of rapid detection. Mass spectrometry technology has good selectivity, but the instrument cost is high, and it is easily interfered in complex matrices. Surface-enhanced Raman scattering (SERS) technology has shown great potential in the field of hazardous chemical detection due to its fingerprint spectrum characteristics and ultra-high sensitivity. However, the current SERS detection method still faces the problem of insufficient accuracy in quantitative analysis, which is mainly manifested in the following aspects: First, the enhancement effect of traditional SERS substrate materials is uneven, resulting in poor repeatability of detection signals; second, existing data processing methods cannot effectively eliminate the influence of instrument drift and matrix interference, affecting the reliability of quantitative analysis; third, there is a lack of systematic standardization and calibration methods, making it difficult to establish accurate quantitative relationships. Currently, commonly used SERS substrates mainly include noble metal nanoparticles, nanorods, and nanosheets. Although these materials have strong local surface plasmon resonance effects, their stability is poor, and they are prone to aggregation, affecting the repeatability of detection. To improve the detection accuracy, researchers have tried various improvement methods, such as using the internal standard method for calibration or using image processing technology to analyze the spatial distribution of SERS signals, but these methods are either complex in operation or cannot fundamentally solve the problem. In summary, there is a technical problem in the prior art that the accuracy of SERS detection of hazardous chemicals is not high enough. Summary of the Invention

[0003] In view of this, the present invention provides a method for determining the SERS effect of Ag-based composite nanomaterials on hazardous chemicals, which can solve the technical problem that the accuracy of SERS detection of hazardous chemicals in the prior art is not high enough.

[0004] The present invention is implemented as follows: The present invention provides a method for determining the SERS effect of Ag-based composite nanomaterials on hazardous chemicals, including the following steps: preparing Au nanoseeds and Au@Ag core-shell nanostructures, preparing CeO 2 nanocubes and Ag-CeO 2 nanohybrids, and combining the Au@Ag core-shell nanostructures with the Ag-CeO 2A surface-enhanced Raman detection substrate is prepared by mixing nanoheteropolymers. The Raman spectroscopy standard correction matrix, the substrate enhancement effect evaluation matrix, and the SERS enhancement coefficient correction matrix are obtained through the detection substrate and a Raman spectrometer, and a SERS signal intensity normalization matrix is established. Finally, the SERS utility value is calculated through the SERS signal intensity normalization matrix, the substrate enhancement effect evaluation matrix, and the Raman spectroscopy standard correction matrix.

[0005] Among them, the step of preparing Au nanoseeds is specifically to dissolve 10 millimoles of chloroauric acid in a solution containing 100 milliliters of ethylene glycol and 2 grams of polyvinylpyrrolidone, heat it to 100 degrees Celsius under magnetic stirring conditions, and slowly add 50 milliliters of an ethylene glycol solution containing 10 millimoles of sodium borohydride thereto. After reacting at a constant temperature for 15 minutes, it is cooled to room temperature to obtain the Au nanoseed solution.

[0006] Among them, the step of preparing the Au@Ag core-shell nanostructure is specifically to add 50 milliliters of an ethylene glycol solution containing 10 millimoles of silver nitrate to the Au nanoseed solution, heat it to 100 degrees Celsius under magnetic stirring conditions, and after reacting at a constant temperature for 20 minutes, it is cooled to room temperature to obtain the reaction solution of the Au@Ag core-shell nanostructure; ethanol is added to the reaction solution of the Au@Ag core-shell nanostructure, and it is centrifuged at 8000 revolutions per minute for 10 minutes. The precipitate is collected and redispersed with 15 milliliters of toluene, and the washing is repeated 2 to 4 times to obtain the purified Au@Ag core-shell nanostructure.

[0007] Among them, the step of preparing CeO 2 nanocubes is specifically to mix 15 milliliters of an aqueous cerium nitrate solution with a concentration of 16.7 millimoles per liter, 15 milliliters of toluene, 1.5 milliliters of oleic acid, and 0.15 milliliters of tert-butylamine, and place it in an autoclave for a constant temperature reaction at 180 degrees Celsius for 24 hours to obtain the reaction product of CeO 2 nanocubes; the reaction product of CeO 2 nanocubes is centrifuged at 2000 revolutions per minute for 10 minutes to remove solid impurities. 10 milliliters of ethanol is added to the upper layer liquid, and the precipitate is collected by centrifuging at 8000 revolutions per minute for 10 minutes to obtain the purified CeO 2 nanocubes.

[0008] Among them, the step of preparing the Ag-CeO 2 nanoheteropolymer is specifically to use the purified CeO 2The nanocubes were dispersed in 15 mL of ethylene glycol solution containing 0.2 mL of oleylamine and heated to 100 °C under nitrogen protection for a constant-temperature reaction for 30 minutes to obtain the first reaction system; 1.0 mL of a n-butyllithium hexane solution with a concentration of 2.2 mmol / L was injected into the first reaction system, and then a mixed solution of 5 mL of ethylene glycol and 1 mL of oleylamine containing 0.125 mmol of silver nitrate was injected to obtain the second reaction system; the second reaction system was stirred at room temperature for 10 minutes and then heated to 80 °C for a constant-temperature reaction for 1 hour, and further heated to 120 °C for a reaction for 2 hours to obtain the Ag-CeO 2 nanohybrid reaction solution; the Ag-CeO 2 nanohybrid reaction solution was collected by centrifugation at 8000 rpm for 10 minutes, washed 2 to 3 times with ethanol and then dispersed in toluene to obtain the Ag-CeO 2 nanohybrids.

[0009] Among them, the steps for preparing the surface-enhanced Raman detection substrate are specifically to mix the purified Au@Ag core-shell nanostructures and the Ag-CeO 2 nanohybrids in a mass ratio of 1:1, ultrasonically disperse for 15 minutes to obtain the surface-enhanced Raman detection substrate; the surface-enhanced Raman detection substrate was drop-coated on the surface of a conductive glass substrate, air-dried naturally and then placed in a drying oven at 60 °C for drying for 2 hours to obtain the detection substrate.

[0010] Among them, the steps for establishing the Raman spectrum standard correction matrix are specifically to measure the Raman spectrometer in the wavenumber range of 400 to 3000 to obtain the baseline intensity matrix and the instrument response matrix in the Raman spectrum standard correction matrix.

[0011] Among them, the steps for establishing the substrate enhancement effect evaluation matrix are specifically to prepare standard solutions of hazardous chemicals with concentrations of 1, 10, 50, 100, and 500 nmol / L respectively, measure the Raman signal intensities of the standard solutions of hazardous chemicals to obtain the substrate enhancement effect evaluation matrix.

[0012] Among them, the steps for establishing the SERS enhancement coefficient correction matrix are specifically to calculate the SERS enhancement coefficient correction matrix according to the substrate enhancement effect evaluation matrix and the Raman spectrum standard correction matrix; use a Raman spectrometer to measure the surface-enhanced Raman signal of the hazardous chemical to be measured, select the excitation wavelength of 532 nm, set the laser power to 5 mW, and the acquisition time to 10 seconds to obtain the Raman signal of the hazardous chemical to be measured; use the SERS enhancement coefficient correction matrix to normalize the Raman signal of the hazardous chemical to be measured to obtain the SERS signal intensity normalization matrix.

[0013] Among them, the steps of calculating the SERS utility value are specifically to subtract the Raman spectrum standard correction matrix from the product of the SERS signal intensity normalization matrix and the substrate enhancement effect evaluation matrix.

[0014] Optionally, the Raman spectrum standard correction matrix is obtained by performing a series of standard sample measurements on a Raman spectrometer in the wavenumber range of 400 to 3000. This matrix contains two important components, the baseline intensity matrix and the instrument response matrix. The baseline intensity matrix reflects the background signal intensity distribution of the instrument when no sample is present, while the instrument response matrix characterizes the sensitivity and response characteristics of the instrument in different wavenumber ranges. The acquisition of these two sub-matrices requires systematic measurement and mathematical processing of standard substances with known concentrations, and finally a standardized matrix that can correct the instrument system error is obtained.

[0015] Optionally, the process of establishing the substrate enhancement effect evaluation matrix is to prepare a series of standard solutions of hazardous chemicals with different concentrations (1, 10, 50, 100, 500 nanomoles per liter), perform Raman spectrum measurements on samples of each concentration gradient, record the signal intensities of their characteristic peaks, and establish a corresponding relationship matrix between concentration and signal intensity through mathematical processing. This matrix not only reflects the enhancement effect of the surface-enhanced Raman substrate, but also contains information on the response linear range and detection sensitivity of samples at different concentrations, and can be used for quantitative analysis of the concentrations of subsequent unknown samples.

[0016] Optionally, the SERS enhancement factor correction matrix is obtained through mathematical operations based on the substrate enhancement effect evaluation matrix and the Raman spectrum standard correction matrix. This matrix comprehensively considers the instrument response characteristics and the substrate enhancement effect, and can accurately reflect the actual enhancement degree of the nanomaterial substrate on the Raman signal. Its calculation process involves matrix operations and mathematical transformations, and finally a standardized matrix that can accurately correct the signals of unknown samples is obtained. The establishment of this matrix is the key to realizing SERS quantitative analysis.

[0017] Optionally, the SERS signal intensity normalization matrix is obtained by performing mathematical operations on the original Raman signal of the sample to be measured and the SERS enhancement factor correction matrix. This process can eliminate the interference caused by factors such as instrument fluctuations and substrate inhomogeneity, making the measurement results have good repeatability and comparability. The normalized signal intensity can more accurately reflect the actual concentration level of the substance to be measured, providing a reliable data basis for subsequent quantitative analysis.

[0018] Optionally, the synthesis parameters of Au nanoseeds and Au@Ag core-shell nanostructures are optimized through a large number of experiments, including systematic regulation of key parameters such as reaction temperature, reaction time, and precursor concentration. The precise control of these parameters directly affects the morphology, size distribution, and surface plasmon resonance characteristics of the nanomaterials, and further affects the sensitivity and reproducibility of SERS detection. Therefore, strict quality control of the synthesized products is required through characterization means such as transmission electron microscopy and ultraviolet-visible spectroscopy.

[0019] Optionally, CeO 2 nanocubes and Ag-CeO 2 The preparation process parameters of the nanoheteropolymers are determined through systematic research, including reactant ratio, reaction temperature, reaction time, etc. The selection of these parameters is based on an in-depth understanding of reaction kinetics and thermodynamics. By precisely controlling the synthesis conditions, nanomaterials with specific morphology and size can be obtained, and the surface properties of the nanomaterials can be regulated, thus providing high-quality substrate materials for subsequent SERS detection.

[0020] Compared with the prior art, a method for determining the SERS effect of a hazardous chemical using an Ag-based composite nanomaterial provided by the present invention successfully solves the problem of insufficient accuracy in quantitative analysis in the SERS detection of hazardous chemicals by designing a novel Ag-based composite nanomaterial and establishing a multiple matrix correction system. In terms of material design, a composite strategy of Au@Ag core-shell structure combined with CeO 2 nanocubes not only provides a stable hot spot structure, but also enhances the adsorption ability of target molecules through the surface chemistry of CeO 2 , achieving a significant enhancement and stability of the detection signal. In terms of data processing, a multiple matrix correction system including a Raman spectrum standard correction matrix, a substrate enhancement effect evaluation matrix, and a SERS enhancement coefficient correction matrix is established. Through systematic mathematical processing, influencing factors such as instrument drift and matrix interference are effectively eliminated, significantly improving the accuracy of quantitative analysis. By introducing a SERS signal intensity normalization matrix, the comparability of data under different batches and different detection conditions is achieved, providing the possibility for establishing a unified detection standard. The method of the present invention significantly improves the repeatability and reliability of detection while maintaining the ultra-high sensitivity advantage of SERS technology, and solves the technical problem of insufficient accuracy in the SERS detection of hazardous chemicals existing in the prior art. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 is a flowchart of the method of the present invention.

[0022] Figure 2 is the ultraviolet-visible absorption spectrum diagram in Example 2.

[0023] Figure 3 Standard curve of 2,4-dinitrotoluene in Example 2 and determination results of actual samples

[0024] Figure 4 Influence diagram of different interfering ions on determination results in Example 2

[0025] Figure 5 Stability test results diagram of detection substrate during 30-day storage in Example 2

[0026] Figure 6 Preparation diagram of Au seeds in the synthesis of Au@Ag core-shell nanoparticles in Example 3, including two sub-diagrams, where a) is a TEM diagram; b) is a HRTEM diagram

[0027] Figure 7 Au@Ag core-shell nanoparticles in Example 3, including two sub-diagrams, where a) is a TEM diagram; b) is a HRTEM diagram

[0028] Figure 8 SERS spectrogram of pyridine on the surface of AuAg alloy nanostructures with different Au / Ag ratios in Example 3 Detailed implementation manners

[0029] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention

[0030] The present invention provides a method for determining the SERS effect of Ag-based composite nanomaterials on hazardous chemicals, which is characterized by including the following operating steps S01. Prepare Au nanoseeds. Dissolve 10 millimoles of chloroauric acid in a solution containing 100 milliliters of ethylene glycol and 2 grams of polyvinylpyrrolidone, heat it to 100 degrees Celsius under magnetic stirring conditions, slowly add a 50-milliliter ethylene glycol solution containing 10 millimoles of sodium borohydride thereto, cool to room temperature after reacting at a constant temperature for 15 minutes to obtain the Au nanoseed solution S02. Prepare Au@Ag core-shell nanostructures. Add a 50-milliliter ethylene glycol solution containing 10 millimoles of silver nitrate to the Au nanoseed solution, heat it to 100 degrees Celsius under magnetic stirring conditions, cool to room temperature after reacting at a constant temperature for 20 minutes to obtain the reaction solution of Au@Ag core-shell nanostructures S03. Purify the Au@Ag core-shell nanostructures. Add ethanol to the reaction solution of Au@Ag core-shell nanostructures, centrifuge at 8000 revolutions per minute for 10 minutes, collect the precipitate and redisperse it with 15 milliliters of toluene, and repeat the washing 2 to 4 times to obtain the purified Au@Ag core-shell nanostructures S04. Preparation of CeO 2 nanocubes. Mix 15 mL of an aqueous cerium nitrate solution with a concentration of 16.7 mmol / L, 15 mL of toluene, 1.5 mL of oleic acid, and 0.15 mL of tert-butylamine, and place them in an autoclave for a constant-temperature reaction at 180 °C for 24 hours to obtain the CeO 2 nanocube reaction product; S05. Purify the CeO 2 nanocubes. Centrifuge the CeO 2 nanocube reaction product at a speed of 2000 rpm for 10 minutes to remove solid impurities. Add 10 mL of ethanol to the upper liquid and centrifuge at a speed of 8000 rpm for 10 minutes to collect the precipitate, obtaining the purified CeO 2 nanocubes; S06. Preparation of Ag-CeO 2 nanohybrids. Disperse the purified CeO 2 nanocubes in 15 mL of ethylene glycol solution containing 0.2 mL of oleylamine, and heat to a constant temperature of 100 °C under nitrogen protection for 30 minutes to obtain the first reaction system; S07. Inject 1.0 mL of a 2.2 mmol / L n-butyllithium n-hexane solution into the first reaction system, and then inject a mixed solution of 5 mL of ethylene glycol and 1 mL of oleylamine containing 0.125 mmol of silver nitrate to obtain the second reaction system; S08. Stir the second reaction system at room temperature for 10 minutes, then heat to a constant temperature of 80 °C for 1 hour, and continue to heat to 120 °C for 2 hours to obtain the Ag-CeO 2 nanohybrid reaction solution; S09. Centrifuge the Ag-CeO 2 nanohybrid reaction solution at a speed of 8000 rpm for 10 minutes to collect it, wash it with ethanol 2 to 3 times, and then disperse it in toluene to obtain the Ag-CeO 2 nanohybrids; S10. Establish a Raman spectroscopy standard calibration matrix, measure the Raman spectrometer in the range of 400 to 3000 wavenumbers, and obtain the baseline intensity matrix and instrument response matrix in the Raman spectroscopy standard calibration matrix; S11. Establish a substrate enhancement effect evaluation matrix. Prepare standard solutions of hazardous chemicals with concentrations of 1, 10, 50, 100, and 500 nmol / L respectively, measure the Raman signal intensity of the hazardous chemical standard solutions, and obtain the substrate enhancement effect evaluation matrix; S12. Prepare a surface-enhanced Raman detection substrate by combining the purified Au@Ag core-shell nanostructure with the Ag-CeO2 The nanoheteropolymers are mixed in a mass ratio of 1:1 and ultrasonically dispersed for 15 minutes to obtain the surface-enhanced Raman detection substrate; S13. Establish an SERS enhancement factor correction matrix, which is calculated based on the substrate enhancement effect evaluation matrix and the Raman spectrum standard correction matrix; S14. Drop-coat the surface-enhanced Raman detection substrate on the surface of a conductive glass substrate, allow it to dry naturally, and then dry it in an oven at 60 °C for 2 hours to obtain the detection substrate; S15. Perform Raman spectrum measurement. Use a Raman spectrometer to measure the surface-enhanced Raman signal of the hazardous chemical to be detected. The excitation wavelength is selected as 532 nm, the laser power is set at 5 mW, and the acquisition time is 10 s to obtain the Raman signal of the hazardous chemical to be detected; S16. Establish an SERS signal intensity normalization matrix, and perform normalization processing on the Raman signal of the hazardous chemical to be detected by using the SERS enhancement factor correction matrix to obtain the SERS signal intensity normalization matrix; S17. Calculate the SERS utility value, which is the product of the SERS signal intensity normalization matrix and the substrate enhancement effect evaluation matrix minus the Raman spectrum standard correction matrix.

[0031] The specific implementation manners of the above steps are described in detail below.

[0032] The specific implementation manner of step S01 is to prepare Au nanoseeds. By dissolving chloroauric acid in a mixed solution of ethylene glycol and polyvinylpyrrolidone, a reduction reaction is carried out under the conditions of controlling the temperature and stirring speed. In this step, polyvinylpyrrolidone is used as a protective agent based on its good steric hindrance effect and surface activity, which can effectively control the growth direction and size distribution of nanocrystals. The stirring speed is controlled at 500 revolutions per minute, and the reaction temperature is controlled at 100 °C by a constant temperature water bath. During the reaction, a pH meter is used to monitor the acidity and alkalinity of the solution in real time, and the pH value is maintained between 6.5 and 7.5. After the reaction, the particle size distribution of the nanocrystals is measured by dynamic light scattering method, and the particle size is controlled within the range of 15 to 20 nm, and the dispersion coefficient is less than 0.2.

[0033] The specific implementation of step S02 is to prepare Au@Ag core-shell nanostructures. This step is to prepare the core-shell structure by surface growth method based on Au nanoseeds, using silver nitrate as the silver source and in-situ reduction in ethylene glycol solution. During the reaction process, the displacement of the plasma resonance peak is monitored in real time by ultraviolet-visible spectrophotometer. When the resonance peak is stable at about 430 nm, it indicates that the shell growth is completed. The reaction temperature is controlled by a PID control system, and the temperature fluctuation is controlled within the range of plus or minus 0.5 degrees Celsius. The stirring speed is maintained at 400 revolutions per minute. After the reaction, the morphology of the core-shell structure is observed by transmission electron microscope, and the shell thickness is controlled within the range of 5 to 8 nm.

[0034] The specific implementation of step S03 is to purify the Au@Ag core-shell nanostructures. The centrifugal separation technology is used to remove impurities and unreacted substances in the reaction system. The centrifugation process uses a programmable temperature-controlled centrifuge with the temperature set at 25 degrees Celsius. High-purity extraction of the product is achieved by repeating the centrifugation and redispersion processes. After each centrifugation, the absorbance of the supernatant is measured by ultraviolet-visible spectrophotometer. When the absorbance is less than 0.01, it indicates that the impurities are completely removed. The final product is dispersed in toluene, and the purity of the product is determined to be greater than 98% by thermogravimetric analysis.

[0035] The specific implementation of step S04 is to prepare CeO 2 nanocubes, which is carried out in a high-pressure reaction kettle by solvothermal method. During the reaction process, the temperature and pressure are controlled by an intelligent control system, and the heating rate is set at 2 degrees Celsius per minute. The morphology of the product is controlled by adjusting the ratio of cerium nitrate, oleic acid and tert-butylamine during the preparation process. The pressure during the reaction is controlled within the range of 2 to 3 MPa. The formation process of the crystal structure is monitored in real time by X-ray diffractometer. When the full width at half maximum of the diffraction peak is stable and conforms to the characteristics of the cubic crystal system, it indicates that the reaction is completed.

[0036] The specific implementation of step S05 is to purify CeO 2 nanocubes. The differential centrifugation technology is used to separate particles of different sizes. First, the aggregates and large-size impurities are removed by low-speed centrifugation, and then the target product is collected by high-speed centrifugation. During the centrifugation process, the density gradient centrifugation technology is used, and a more precise size separation is achieved by establishing an ethanol concentration gradient. The size uniformity of the final product is characterized by scanning electron microscope, and the side length is distributed within the range of 50 to 60 nm.

[0037] The specific implementation of steps S06 and S07 is to prepare Ag-CeO 2The preliminary steps of the nanoheteropolymer are carried out under nitrogen protection and programmed temperature rise. Oleylamine is used as a reducing agent and stabilizer in this process. By controlling the oxygen content in the reaction atmosphere to be less than 10 ppm, the uniform nucleation of silver nanoparticles is ensured. During the reaction process, an electrochemical workstation is used to monitor the reduction potential of the system. When the potential stabilizes at -0.4 V, the next reaction is carried out.

[0038] The specific implementation of step S08 is to complete the preparation of Ag-CeO 2 The preparation of the nanoheteropolymer adopts a stepwise temperature rise strategy. The growth and assembly of silver nanoparticles are controlled at different temperature segments. The change of surface ligands is monitored in real time by infrared spectroscopy. When the intensity ratio of characteristic peaks reaches the set value, the temperature is raised. The whole process is precisely controlled by a program temperature control system, and the temperature error is controlled within the range of plus or minus 1 degree Celsius.

[0039] The specific implementation of step S09 is to collect and purify Ag-CeO 2 The nanoheteropolymer is separated by high-speed centrifugation technology, and ethanol is used for repeated washing to remove residual organic matter. During the washing process, the conductivity of the washing solution is monitored by a conductivity meter. When the conductivity is lower than 10 microsiemens per centimeter, the washing is stopped. The final product is characterized by transmission electron microscopy and energy spectrum analysis for its morphology and composition.

[0040] The specific implementation of step S10 is to establish a Raman spectroscopy standard correction matrix. This step adopts a multivariate statistical analysis method. A correction model is established by systematic measurement of standard samples. During the measurement process, the laser power fluctuation is controlled within the range of plus or minus 1%. An automatic focusing system is used to ensure the accuracy of the focal position. The obtained data is processed by principal component analysis for dimensionality reduction, and the principal components with a contribution rate greater than 95% are retained.

[0041] The specific implementation of steps S11 and S12 is to establish a substrate enhancement effect evaluation system and prepare a detection substrate. A standard solution is prepared by a precision pipetting system, and the concentration gradient is selected based on a logarithmic distribution. The ultrasonic dispersion system is used to ensure the uniformity of the substrate material. The power is controlled at 100 W during the dispersion process, and the time is 15 minutes. During this period, a temperature feedback control system is used to prevent overheating.

[0042] The specific implementation of step S13 is to establish a SERS enhancement coefficient correction matrix. A mathematical model is established by combining multiple linear regression and partial least squares method. The optimal number of principal components is determined by cross-validation. The prediction ability of the model is evaluated by the root mean square error and the determination coefficient, and it is required that the root mean square error is less than 5% and the determination coefficient is greater than 0.99.

[0043] The specific implementation of step S14 is to prepare a detection substrate. The micro-droplet technology is used to construct a detection area on the surface of conductive glass. The surface wettability of the substrate is monitored by a contact angle measuring instrument to ensure that the contact angle is within the range of 45 to 60 degrees. The drying process uses a programmed temperature rise with a heating rate of 1 degree Celsius per minute. Finally, the surface morphology and roughness of the substrate are characterized by an atomic force microscope.

[0044] The specific implementation of step S15 is to perform Raman spectroscopy measurement. A confocal Raman spectrometer is used for measurement. A 532-nanometer laser is selected as the excitation light source. The precise positioning of the sample is achieved through an optical microscopy system. An autofocus system is used to maintain the stability of the focal length during the measurement process. The spectra are collected 10 times at each sample point and averaged.

[0045] The specific implementations of steps S16 and S17 are to establish a SERS signal intensity normalization matrix and calculate the SERS utility value. Multidimensional data analysis methods are used to process the spectral data. The background noise is removed by wavelet transform. The Savitzky-Golay smoothing algorithm is used to preprocess the spectra with a smoothing window set to 11 points and an order of 3. Finally, the final SERS utility value is calculated through the established mathematical model. The entire calculation process uses an iterative optimization algorithm with a convergence condition set to a relative error less than 0.1%.

[0046] In the implementation process of each of the above steps, precise instrument control and data analysis methods are adopted. Through multiple characterization means and strict quality control, the accuracy and repeatability of the measurement results are ensured. The establishment of the entire method is based on the basic principle of surface-enhanced Raman scattering, combining advanced technologies in multiple disciplinary fields such as nanomaterial synthesis, surface modification, spectral analysis, and data processing, realizing highly sensitive detection of hazardous chemicals.

[0047] The calculation of the Raman spectroscopy standard correction matrix is expressed as follows: ; In the formula, is the Raman spectroscopy standard correction matrix; is the element of the baseline intensity matrix, represents the wave number point, represents the number of measurements; is the instrument response coefficient; is the correction factor; is the identity matrix; is the number of wave number sampling points; is the number of measurement repetitions; The calculation of the substrate enhancement effect evaluation matrix is expressed as follows: ; In the formula, is the matrix for evaluating the substrate enhancement effect; is the Raman signal intensity at the th concentration; is the baseline signal intensity; is the th standard solution concentration; is the reference concentration; is the enhancement factor; is the standard deviation of the Gaussian distribution; is the number of concentration gradients; The calculation of the SERS enhancement coefficient correction matrix is expressed as follows: ; In the formula, is the SERS enhancement coefficient correction matrix; is the partial derivative of the enhancement effect with respect to the concentration; is the inverse matrix of the standard correction matrix; is the correction coefficient; is the eigenvalue; is the eigenvector; is the number of eigenvalues; The calculation of the SERS signal intensity normalization matrix is expressed as follows: ; In the formula, is the SERS signal intensity normalization matrix; is the sample signal intensity; is the background signal intensity; is the phase angle; is the weight coefficient; is the correction term; is the number of correction terms; The calculation of the SERS utility value is expressed as follows: ; In the formula, is the SERS utility value; is the compensation coefficient; is the error compensation term; is the number of compensation terms; Description of the parameter acquisition method: Obtained by measuring standard samples, with a range of 0.8 - 1.2; Obtained by experimental calibration, with a range of 0.1 - 0.3; Obtained by fitting a curve, with a range of 1.5 - 2.5; Obtained by statistical analysis, with a range of 0.2 - 0.5; Obtained by an optimization algorithm, with a range of 0.4 - 0.6; Obtained through signal analysis, with a range of 0 to 2π; Obtained through weighted analysis, with a range of 0 to 1; Obtained through error analysis, with a range of 0.05 to 0.15.

[0048] Explanation of the equation construction principle: The Raman spectroscopy standard calibration matrix adopts a matrix multiplication structure, considering the systematic errors of baseline drift and instrument response; the substrate enhancement effect evaluation matrix adopts a form combining exponential and Gaussian distributions, reflecting the non-linear characteristics of signal enhancement; the SERS enhancement coefficient calibration matrix introduces partial derivatives and eigen-decomposition, improving the accuracy and robustness of calibration; the SERS signal intensity normalization matrix adopts a complex form, considering the phase information of the signal and multiple correction terms; the SERS utility value calculation synthesizes multiple matrix operations and error compensation, achieving high-precision quantitative analysis.

[0049] Specifically, the Raman spectroscopy standard calibration matrix The establishment process is first based on the basic principle of Raman scattering. By performing 50 repeated measurements on pure standard samples in the wavenumber range of 400 to 3000, a baseline intensity matrix is obtained. This matrix reflects the background signal distribution of the instrument at different wavenumber points, where each element represents the baseline intensity value at a specific wavenumber. Multiple repeated measurements ensure the statistical reliability of the data; then the instrument response coefficient is introduced. This coefficient is obtained by calibrating the response curve of a known concentration of rhodamine 6G standard solution at different wavenumbers. During the calibration process, 5 different concentration gradients (1, 10, 50, 100, 500 nanomoles per liter) are used for systematic measurement. By analyzing the response linearity at each wavenumber point, the response characteristics of the instrument over the entire spectral range are obtained; then considering the possible systematic drift caused by long-term use of the instrument, a correction factor and the product term of the identity matrix are introduced, where is optimized using the least squares method. Through iterative calculation, the sum of the squared residuals between the theoretical spectrum and the measured spectrum of the standard sample is minimized. This process is repeated until the convergence condition is met (the change in residuals is less than 0.1%); the finally formed standard calibration matrix can effectively compensate for the non-linear characteristics of instrument response, eliminate the influence of baseline drift, and ensure the stability and repeatability of long-term measurements.

[0050] Specifically, the substrate enhancement effect evaluation matrix is constructed based on the physical mechanism of surface-enhanced Raman scattering. First, by measuring the Raman signal intensity of standard solutions with different concentrations, and establishing the signal enhancement multiple by the ratio of the baseline signal intensity Obtained by repeating the measurement of the blank substrate 20 times under the same test conditions (laser power 5 mW, acquisition time 10 s) and taking the average value; the enhancement factor is introduced Taking it as a power term takes into account the non-linear effect caused by the synergistic effect of electromagnetic field enhancement and chemical enhancement The value of is obtained by optimizing through a genetic algorithm. In the optimization process, the Pearson correlation coefficient between the maximized fitting curve and the experimental data is used as the objective function, the population size is set to 100, the number of iterations is 1000 generations, the crossover probability is 0.8, and the mutation probability is 0.1; the Gaussian distribution function term is introduced based on the experimental observation that the signal enhancement effect shows a bell-shaped distribution with the change of concentration, where the reference concentration is selected as 100 nmol / L as the optimal working point, and the standard deviation is obtained by maximum likelihood estimation of 20 groups of repeated experimental data; the final form of this matrix can not only accurately describe the enhancement effect of the substrate, but also effectively characterize the dynamic range of concentration response and detection sensitivity

[0051] Specifically, for the derivation process of the SERS enhancement coefficient correction matrix first, based on the dynamic response characteristics of the enhancement effect, the sensitivity information is obtained by calculating the partial derivative of the enhancement effect with respect to concentration This partial derivative reflects the instantaneous response characteristics of the signal intensity with the change of concentration. The five-point difference method is used in the calculation process, and two adjacent points on the left and right of each concentration point are taken for numerical differentiation to improve the accuracy of the derivative calculation; then the inverse matrix of the standard correction matrix is introduced for systematic error correction. The LU decomposition method is used in the matrix inversion process to ensure the stability of numerical calculation; in order to further improve the reliability of the correction, the eigen-decomposition term is introduced, where the eigenvalues and eigenvectors are obtained by singular value decomposition (SVD). In the SVD process, the original data matrix is first centered and standardized, then the covariance matrix is calculated, and finally the eigen-decomposition of the covariance matrix is performed. The number of eigenvalues is determined by the cross-validation method. Specifically, the data set is randomly divided into a training set (80%) and a validation set (20%), and the optimal value is determined by minimizing the prediction error of the validation set; the optimization of the correction coefficient adopts the L-BFGS algorithm, with the mean square error between the corrected signal and the theoretical value as the objective function. The Wolfe criterion is used to determine the step size during the iteration process, and the convergence condition is set as the relative error less than 0.01% or the maximum number of iterations reaches 1000 times

[0052] Specifically, the SERS signal intensity normalization matrix In the establishment process, background interference in the actual sample measurement is first considered. By subtracting the background signal to eliminate the Raman scattering contribution of the substrate material itself, where is obtained by performing 50 repeated measurements on the blank substrate under the same test conditions and smoothing using the moving average method (window size is 5); then the SERS enhancement coefficient correction matrix is used for preliminary normalization to eliminate the influence of instrument response and substrate enhancement effect; considering the possible phase difference of the signal, a complex term is introduced, where the phase angle is calculated by performing the Hilbert transform on the signal. The FFT algorithm is used to improve the calculation efficiency during the transformation process, and the Hanning window function is used to reduce spectral leakage; finally, a multiple correction term is introduced to handle the non-linear interference, where the correction term is obtained by wavelet transform. Specifically, the Daubechies wavelet basis is used, and the decomposition level is 3. The characteristic coefficients are extracted through threshold processing (using the soft threshold method, and the threshold is taken as 3 times the standard deviation of the noise); the optimization of the weight coefficient adopts the principal component analysis method. First, the covariance matrix is constructed, then the eigenvalues and eigenvectors are calculated, and the number of principal components with a cumulative contribution rate reaching 95% is selected as the value. Finally, the weight coefficients of each principal component are determined through regression analysis.

[0053] Specifically, the derivation of the SERS utility value calculation equation is the core of the entire method. First, the normalized signal intensity is multiplied by the substrate enhancement effect evaluation matrix, and this step realizes the conversion of the signal intensity to the actual concentration; then the standard correction matrix is subtracted to eliminate the residual systematic error; considering the possible random fluctuations in the actual detection process, an error compensation term is introduced, where the error compensation term is obtained by the Bootstrap method. Specifically, 1000 resampling with replacement is performed on the original data, the deviation between each sampling result and the overall average value is calculated, and the error distribution characteristics are obtained through kernel density estimation; the optimization of the compensation coefficient adopts the cross-validation method. The data set is divided into 10 parts in chronological order, and models are established using 9 parts of the data in turn, and the remaining 1 part is used for verification. The optimal compensation coefficient value is determined by minimizing the root mean square error of the validation set; the number of compensation terms is determined through the Akaike information criterion (AIC) to avoid overfitting problems while ensuring the goodness of fit of the model.

[0054] A specific Embodiment 1 of the present invention is provided below. The specific implementation manners of each step in this Embodiment 1 are described in detail as follows. The specific implementation manner of step S01 is to prepare Au nanoseeds. The purpose of this step is to obtain Au nanoseeds with uniform particle size and good dispersibility as the base material for subsequent preparation of the core-shell structure. In the preparation process, first, 10 millimoles of chloroauric acid is dissolved in a solution containing 100 milliliters of ethylene glycol, and then 2 grams of polyvinylpyrrolidone is added. The use of polyvinylpyrrolidone as a protective agent in this step is based on its good steric hindrance effect and surface activity. The carbonyl functional group in the polyvinylpyrrolidone molecule can form a coordination interaction with the surface of Au nanoparticles, thereby effectively controlling the growth direction and size distribution of the nanocrystals. Before adding sodium borohydride, the reaction temperature needs to be stabilized at 100 degrees Celsius. The temperature control uses a digital PID control system with a temperature control accuracy of plus or minus 0.1 degree Celsius. The stirring speed is controlled at 500 revolutions per minute, and the precise adjustment of the rotation speed is achieved through a variable-frequency motor. During the stirring process, a paddle-type stirring paddle is used to ensure the uniform mixing of the solution. During the reaction process, a pH meter is used to monitor the acidity and alkalinity of the solution in real time, and the pH value is maintained between 6.5 and 7.5. The pH adjustment uses a 0.1 molar per liter sodium hydroxide solution, and the addition rate is controlled by a micro-injection pump. During the reaction process, the change of the plasma resonance peak is monitored in real time by a UV-visible spectrophotometer. When the absorption peak is stable at 520 nanometers, it indicates that the growth of Au nanocrystals is completed. After the reaction, the particle size distribution of the nanocrystals is measured by a dynamic light scattering instrument. It is required that the particle size is controlled within the range of 15 to 20 nanometers, and the polydispersity coefficient is less than 0.2. The morphology of the particles is observed by a transmission electron microscope, and it is required that the particles are spherical and have clear edges.

[0055] The specific implementation of step S02 is to prepare Au@Ag core-shell nanostructures. The purpose of this step is to grow a uniform silver shell layer on the surface of gold nanoseeds, thereby forming a composite nanomaterial with a core-shell structure. The preparation process uses the surface growth method. 50 mL of ethylene glycol solution containing 10 mmol of silver nitrate is added dropwise to the gold nanoseed solution through a constant flow pump at a rate of 2 mL per minute. During the dropping process, the temperature of the solution is kept constant at 100 °C. The temperature is regulated by a digital PID feedback control system with a control accuracy of ±0.1 °C. The stirring speed is controlled at a constant speed by a program, and the rotation speed is maintained at 400 revolutions per minute, which is achieved by an electric stirrer. The stirring paddle is made of polytetrafluoroethylene material to avoid metal ion contamination. During the reaction process, the plasma resonance peak shift of the solution is monitored in real time by a UV-visible spectrophotometer. When the resonance peak gradually moves from 520 nm and stabilizes at about 430 nm, it indicates that the growth of the silver shell layer is completed. The test process uses a flow cell for real-time monitoring with a sampling interval of 30 seconds. Parameters such as the temperature, pH value, and stirring speed during the entire reaction process are recorded and regulated in real time through a data acquisition system. After the reaction, the morphology of the core-shell structure is observed by high-resolution transmission electron microscopy, and the thickness of the silver shell layer is required to be uniform, controlled within the range of 5 to 8 nm. The elemental distribution of the core-shell structure is confirmed by energy spectrum analysis.

[0056] The specific implementation of step S03 is to purify the Au@Ag core-shell nanostructures. The purpose of this step is to remove the unreacted substances and impurities in the reaction system and obtain a high-purity target product. The purification process is carried out using a programmable temperature centrifuge with a constant temperature of 25 °C. First, the reaction solution is centrifuged at a speed of 8000 revolutions per minute for 10 minutes. The choice of centrifugal force is based on the Stokes sedimentation principle, which can effectively separate the target product and impurities. After centrifugation, the supernatant is discarded, and 15 mL of toluene is added to the precipitate and redispersed using an ultrasonic processor. The ultrasonic power is set at 100 W, and a dot matrix ultrasonic probe is used. Each treatment lasts for 2 minutes with an interval of 30 seconds, and the process is repeated 3 times to ensure that the sample is fully dispersed. The above centrifugation and redispersion processes are repeated 2 to 4 times. After each centrifugation, the absorbance of the supernatant is measured by a UV-visible spectrophotometer. When the absorbance value is less than 0.01, it indicates that the impurities have been completely removed. Finally, the purity of the product is determined by thermogravimetric analysis, and the required purity is greater than 98%, and the impurity content is less than 2%.

[0057] The specific implementation of step S04 is to prepare CeO 2Nanocubes. In this step, the solvothermal method is used. 15 mL of an aqueous cerium nitrate solution with a concentration of 16.7 mmol / L is mixed with 15 mL of toluene, 1.5 mL of oleic acid, and 0.15 mL of tert-butylamine. During the mixing process, mechanical stirring is employed at a rotation speed of 300 revolutions per minute. After mixing evenly, it is transferred to a high-pressure reaction kettle lined with polytetrafluoroethylene. The volume of the reaction kettle is 50 mL, and the filling degree is controlled at 60%. The reaction temperature is set at 180 °C, and the heating rate is 2 °C per minute, controlled by a programmed temperature rise system. The reaction pressure is monitored in real time through a pressure sensor and controlled within the range of 2 to 3 MPa. During the reaction process, samples are taken every 2 hours through a sampling valve, and the evolution process of the crystal structure is tracked by an X-ray diffractometer. When the characteristic peaks of the cubic crystal system appear in the diffraction pattern and the full width at half maximum tends to be stable, it indicates that the reaction is complete.

[0058] The specific implementation of step S05 is to purify CeO 2 Nanocubes. In this step, differential centrifugation technology is used to separate particles of different sizes. First, the reaction product is centrifuged at a rotation speed of 2000 revolutions per minute for 10 minutes to remove large-size aggregates and impurities. An angle rotor is used during the centrifugation process, and the centrifuge tubes are made of polypropylene. The centrifugation temperature is controlled at 25 °C. After collecting the supernatant, 10 mL of ethanol is added, and then it is centrifuged at a rotation speed of 8000 revolutions per minute for 10 minutes to collect the target product. During the centrifugation process, density gradient centrifugation technology is used. By establishing an ethanol concentration gradient of 20% to 80%, precise separation of particle sizes is achieved. The final product is characterized by scanning electron microscopy and transmission electron microscopy. It is required that the side length of the nanocubes is distributed in the range of 50 to 60 nm, with a uniform morphology and complete crystal planes.

[0059] The specific implementations of step S06 and step S07 are to prepare Ag-CeO 2 In the initial stage of preparing the nanoheteroaggregate, first disperse the purified CeO 2 Nanocubes in 15 mL of ethylene glycol solution containing 0.2 mL of oleylamine. Ultrasonic treatment is used during the dispersion process, with a power of 200 W, in intermittent mode, working for 2 minutes and pausing for 1 minute, repeating 5 times. Then, it is heated to 100 °C under nitrogen protection. The purity of nitrogen is greater than 99.999%, and the flow rate is controlled at 100 mL per minute. The reaction kettle is a four-necked flask equipped with a thermometer, a gas inlet tube, a condenser reflux tube, and a syringe interface. The temperature control uses an intelligent temperature control system with an accuracy of ±0.5 °C. After reacting at a constant temperature for 30 minutes, 1.0 mL of a 2.2 mmol / L n-butyllithium hexane solution is injected into the reaction system at an injection rate controlled at 0.5 mL per minute. Subsequently, a mixed solution of 5 mL of ethylene glycol and 1 mL of oleylamine containing 0.125 mmol of silver nitrate is injected. During the whole process, an electrochemical workstation is used to monitor the reduction potential of the system. When the potential stabilizes at -0.4 V, the next reaction is entered.

[0060] The specific implementation of step S08 is to complete the preparation of Ag-CeO 2 nanohybrids. A programmed temperature rise strategy is adopted. First, stir at room temperature for 10 minutes with a stirring speed of 300 revolutions per minute, then increase the temperature to 80 °C at a heating rate of 2 °C per minute, and keep the temperature constant for 1 hour. During this period, a Fourier transform infrared spectrometer is used to monitor the change of surface ligands in real time. When the intensity ratio of the carboxyl characteristic peak reaches 1.5, continue to increase the temperature to 120 °C. The temperature is precisely controlled by a program temperature control system during the heating process, and the temperature error is controlled within the range of plus or minus 1 °C. React at 120 °C for 2 hours, and monitor the growth of silver nanoparticles by sampling analysis during the reaction process.

[0061] The specific implementation of step S09 is to collect and purify Ag-CeO 2 nanohybrids. The products are separated by high-speed centrifugation technology. The reaction solution is centrifuged at a speed of 8000 revolutions per minute for 10 minutes. The centrifuge tube is made of polypropylene resistant to organic solvents, and the centrifugation temperature is controlled at 20 °C. After collecting the precipitate, it is washed with ethanol. Each time, 20 ml of ethanol is added, ultrasonically dispersed for 2 minutes, and then centrifuged and separated. Repeat 2 to 3 times. During the washing process, the conductivity change of the washing solution is monitored by a conductivity meter. When the conductivity drops below 10 microsiemens per centimeter, stop washing. The final product is redispersed in 15 ml of toluene, and the morphology and composition of the product are characterized by transmission electron microscopy and energy spectrum analysis. It is required that silver nanoparticles are evenly distributed on the surface of CeO 2 nanocubes, and the particle size distribution is uniform.

[0062] The specific implementation of step S10 is to establish a Raman spectroscopy standard correction matrix. This step is based on multivariate statistical analysis methods, and a correction model is established through systematic measurement of standard samples. During the Raman spectroscopy acquisition process, a laser with a wavenumber range of 400 to 3000 wavenumbers is used as the light source, and an automatic focusing system is used to ensure the accuracy of the focal position. The deviation of the focal plane is controlled within the range of plus or minus 1 micron. For each standard sample, 100 data points are collected, and the integration time for each data point is 1 second. Through the standard correction matrix for data processing, where the baseline intensity matrix elements are obtained through repeated measurement of the blank substrate, the instrument response coefficient is calibrated by a standard rhodamine 6G solution, and the correction factor is determined through iterative optimization. The least squares method is used in the optimization process, and the iteration termination condition is that the residual change is less than 0.1%.

[0063] The specific implementation manners of steps S11 and S12 are to establish a substrate enhancement effect evaluation matrix and prepare a detection substrate. Standard solutions of hazardous chemicals with concentrations of 1, 10, 50, 100, and 500 nanomoles per liter are prepared through a precise pipetting system. During the preparation process, A-grade volumetric flasks and microinjectors are used to ensure that the preparation accuracy is within plus or minus 0.1%. The prepared standard solutions are injected into the detection cell through an autosampler, and each concentration is measured 10 times repeatedly to obtain the substrate enhancement effect evaluation matrix , where is the Raman signal intensity at different concentrations, is the baseline signal intensity, and the enhancement factor is obtained by optimizing through the genetic algorithm, and the optimization objective is to maximize the correlation coefficient between the fitting curve and the experimental data

[0064] The specific implementation manner of step S13 is to establish a SERS enhancement coefficient correction matrix , and the spectral data is processed using the eigenvalue decomposition method, where is calculated by the five-point difference method, is solved using the LU decomposition method, the eigenvalues and eigenvectors are obtained by singular value decomposition, and the correction coefficient is determined through cross-validation, requiring that the root mean square error of prediction is less than 5% and the coefficient of determination is greater than 0.99

[0065] The specific implementation manner of step S14 is to prepare a detection substrate. The detection area is constructed on the surface of a conductive glass substrate using the micro-droplet technique. The droplet volume is 2 microliters, which is controlled by a high-precision micro syringe. During the droplet process, the substrate temperature is maintained at 25 degrees Celsius, and the relative humidity is controlled between 40% and 50%. The surface wettability of the substrate is monitored through a contact angle measuring instrument to ensure that the contact angle is within the range of 45 to 60 degrees. The drying process uses a programmed temperature increase with a heating rate of 1 degree Celsius per minute. Finally, the surface morphology and roughness of the substrate are characterized by an atomic force microscope, requiring that the surface roughness is within 5 nanometers

[0066] The specific implementation manner of step S15 is to perform Raman spectroscopy measurement. A confocal Raman spectrometer is used for measurement. The excitation light source selects a laser with a wavelength of 532 nanometers, the spot diameter is controlled at 2 microns, and the power is set at 5 milliwatts. An autofocus system is used to maintain the stability of the focal length, and the optical path deviation is controlled within plus or minus 0.5 microns. The acquisition time is set to 10 seconds. To eliminate the influence of random noise, each sample point is measured 10 times repeatedly and the average value is taken. Data processing is performed through the SERS signal intensity normalization matrix , where is the sample signal intensity, is the background signal intensity, and the phase angle Obtained by Fourier transform, the weight coefficients Determined by principal component analysis.

[0067] The specific implementation manners of step S16 and step S17 are to calculate the final SERS utility value , the wavelet transform is adopted for noise reduction in the data processing process, the Daubechies 4th order wavelet basis function is selected, the decomposition level is 4 layers, the threshold selection adopts the principle of maximum and minimum values, the soft threshold method is adopted when reconstructing the signal, and then the Savitzky-Golay smoothing algorithm is used to preprocess the spectrum, the smoothing window is set to 11 points, the order is 3, and the compensation coefficient Optimized and obtained by the bootstrap method, the confidence interval is established by resampling 1000 times, the required confidence level reaches 95%, the whole calculation process adopts the iterative optimization algorithm, and the convergence condition is that the relative error is less than 0.1%.

[0068] Precise instrument control and data analysis methods are adopted in the implementation process of all steps. There are strict quality control indicators for each link. The accuracy and repeatability of the measurement results are ensured through multiple characterization means. The establishment of the whole method is based on the basic principle of surface-enhanced Raman scattering, and combines advanced technologies in multiple disciplinary fields such as nanomaterial synthesis, surface modification, spectral analysis and data processing, realizing highly sensitive detection of hazardous chemicals. The detection limit can reach 1 nanomole per liter, the linear range covers 5 orders of magnitude, the relative standard deviation is less than 5%, and the repeatability and stability are good, providing a reliable analysis method for the rapid detection of hazardous chemicals. The innovation point of this method is that through multiple matrix operations and corrections, the interferences of factors such as instrument drift and uneven substrates are effectively eliminated, and the accuracy and reliability of detection are significantly improved.

[0069] All parameters involved in the method have been strictly optimized and verified, including the synthesis conditions of nanomaterials, surface modification parameters, spectral acquisition parameters and data processing parameters, etc. The selection of these parameters is based on a large amount of experimental data and theoretical calculations, ensuring the scientificity and reliability of the method. At the same time, this method also has good versatility and scalability, and can be applied to the detection of different types of hazardous chemicals by adjusting relevant parameters, providing important technical support for practical applications.

[0070] The technical principle of the present invention is based on the synergistic effect of surface-enhanced Raman scattering effect and multiple mathematical matrices. At the material design level, the Au@Ag core-shell structure generates a strong electromagnetic field enhancement effect through the synergistic effect of the core and the shell. The gold core provides a stable plasmon resonance basis, while the silver shell layer provides a stronger local field enhancement. CeO 2The introduction of nanocubes not only provides a regular surface structure, but also its unique oxygen vacancies and surface defects can enhance the interaction with target molecules, improving the selectivity and sensitivity of detection. In the design of the calibration system, the Raman spectroscopy standard calibration matrix effectively corrects the systematic error by considering the instrument response characteristics and baseline drift. The substrate enhancement effect evaluation matrix introduces a non-linear response term and a Gaussian distribution function to accurately describe the dynamic characteristics of signal enhancement. The SERS enhancement coefficient calibration matrix realizes the dimensionality reduction processing and feature extraction of complex data through eigenvalue decomposition and matrix operations. The synergistic effect of these matrices constructs a complete mathematical model that can accurately reflect various physical and chemical processes during the detection process, thus ensuring the accuracy of quantitative analysis. The technical solution of the present invention forms a logically rigorous and complete detection method through the organic combination of material structure design and mathematical model construction, providing a scientific and effective solution to the accuracy problem in SERS quantitative analysis.

[0071] To better understand and implement the present invention, the following provides Example 2 of a specific application scenario of the present invention: The method of the present invention is used to detect nitrobenzene hazardous chemicals in water, and the specific implementation process is as follows.

[0072] First, prepare Au nanoseeds. Dissolve 0.394 grams of chloroauric acid in 100 milliliters of ethylene glycol, add 2 grams of polyvinylpyrrolidone, set the stirring speed to 500 revolutions per minute, heat to 100 degrees Celsius, and then dropwise add a 50-milliliter ethylene glycol solution of 0.378 grams of sodium borohydride at a rate of 2 milliliters per minute. During the reaction, the pH value is maintained at 7.2. After reacting for 15 minutes, naturally cool to room temperature. Dynamic light scattering tests show that the average particle size of the obtained Au nanoseeds is 17.5 nanometers, and the polydispersity coefficient is 0.156.

[0073] Continue to prepare the Au@Ag core-shell nanostructure. Dissolve 0.850 grams of silver nitrate in 50 milliliters of ethylene glycol, and dropwise add the Au nanoseed solution under stirring at 400 revolutions per minute while controlling the temperature at 100 degrees Celsius. Ultraviolet-visible spectroscopy monitoring shows that the surface plasmon resonance peak gradually moves from 520 nanometers to 432 nanometers. After reacting for 20 minutes, cool the product. Observation with a high-resolution transmission electron microscope shows that the thickness of the silver shell layer is uniform, with an average of 6.8 nanometers.

[0074] As Figure 2 shown, the ultraviolet-visible absorption spectra of Au nanoseeds and the Au@Ag core-shell structure are presented, showing the change in the surface plasmon resonance peak from 520 nanometers to 432 nanometers, confirming the successful preparation of the core-shell structure.

[0075] Purify and perform subsequent synthesis according to the steps of the present invention to prepare Ag-CeO 2The nanoheteropolymer, and the final product was characterized to show that CeO 2 The side length of the nano - cube is 54 nm, and silver nanoparticles are uniformly distributed on its surface with a particle size ranging from 15 to 20 nm.

[0076] The Raman spectroscopy standard calibration matrix was established by using the said method , and the baseline intensity matrix was obtained through 100 repeated measurements. The calibration value of the instrument response coefficient is 0.986, and the optimized value of the correction factor is 0.187.

[0077] A series of 2,4 - dinitrotoluene standard solutions with concentrations of 1, 10, 50, 100, and 500 nmol / L were prepared, and the enhancement factor evaluation matrix in was measured. The value of the enhancement factor is 1.876, and the standard deviation is 0.325. The experimental data are shown in Table 1 below:

[0078] The SERS enhancement coefficient calibration matrix was obtained through calculation. The main eigenvalues are distributed between 0.856 and 0.998, and the correction coefficient takes the value of 0.458. The cross - validation result shows that the root - mean - square error of prediction is 3.8%, and the determination coefficient is 0.996. The content of 2,4 - dinitrotoluene in the wastewater of a chemical plant was determined by using the method of the present invention. Each sample was measured 10 times repeatedly, and the data after being processed by the SERS signal intensity normalization matrix are shown in Table 2 below: Table 2 Processed data table

[0079] The finally calculated SERS utility value indicates that the detection limit of this method for 2,4 - dinitrotoluene is 0.8 nmol / L, the linear range is from 1 to 500 nmol / L, the relative standard deviation between batches is 4.2%, the relative standard deviation within batches is 3.5%, and the spike recovery rate of the method is between 96.5% and 104.5%.

[0080] As Figure 3 shown, the standard curve of 2,4 - dinitrotoluene and the measurement results of actual samples are presented. A good linear relationship is shown in the double - logarithmic coordinate system, and the measurement results of actual samples are highly consistent with the standard curve.

[0081] In the study of sample matrix effects, the interferences of common ions (such as sodium ions, potassium ions, calcium ions, chloride ions, sulfate ions, etc.) were investigated. The results showed that when the concentration of interfering ions was 100 times that of the analyte, the relative errors of the measurement results were all less than 5%. In addition, this method also had good selectivity. For nitrobenzene compounds with similar structures, accurate quantification could be achieved through the identification of characteristic Raman peaks.

[0082] As Figure 4 shown, the effects of different interfering ions on the measurement results were presented. When the concentration of all ions was 100 times that of the analyte, the recovery rate of the method remained above 95%.

[0083] The durability test showed that when the prepared detection substrate was stored at room temperature for 30 days, its SERS activity did not decrease significantly, and the relative standard deviation of the signal intensity was less than 6%. In practical applications, this method could be directly used for the rapid detection of nitrobenzene compounds in environmental water samples such as surface water and industrial wastewater. Moreover, the sample pretreatment was simple, and the entire detection process could be completed within 30 minutes.

[0084] As Figure 5 shown, the stability test results of the detection substrate during the 30-day storage period were presented. The change in the relative signal intensity was within 6%, indicating good stability.

[0085] Compared with traditional detection methods, the method of the present invention had significant advantages, as specifically compared in Table 3 below: Table 3 Comparison table of detection effects

[0086] The method of the present invention solved the problems existing in traditional detection methods, such as insufficient detection sensitivity, long analysis time, and large sample consumption. By designing a new type of Ag-based composite nanomaterial and establishing a multiple matrix correction system, the accuracy and reliability of detection were significantly improved. Especially, it had obvious advantages in matrix interference suppression, repeatability improvement, and operation simplicity, providing a practical new method for the rapid screening and quantitative analysis of hazardous chemicals in environmental water samples. The successful development of the method of the present invention not only deepened the understanding of the surface-enhanced Raman scattering mechanism theoretically but also provided important technical support for environmental monitoring and safety warning in practice.

[0087] Example 3 of a more detailed experimental process is provided below to implement the experimental steps in the method for determining the SERS effect of Ag-based composite nanomaterials on hazardous chemicals.

[0088] Table 4 lists the chemical reagents used in this example. All organic reagents were not purified without special instructions. The reaction apparatus for the experiment was a reflux reaction apparatus equipped with magnetic stirring, heating, and atmosphere protection functions. Among them, a three-necked flask, a spherical condenser, a silica gel stopper, a thermocouple sleeve, etc. constituted the reflux reaction apparatus. The magnetic stirring electric heating mantle provided heating and stirring functions. High-purity N2 (≥99.999%) was used as the protective atmosphere in the experiment.

[0089] Reagents and Their Specifications Used in Table 4

[0090] The specific test method is described in detail as follows: Preparation of Au@Ag Core-Shell Nanostructures At room temperature, 10 mmol of HAuCl4·xH2O was dissolved in a solution containing 100 ml of ethylene glycol and 2 g of PVP. Under magnetic stirring, the solution was heated to 100.0 °C. 10 mmol of NaBH4 was dissolved in 50 ml of ethylene glycol and slowly added to the above solution, and the temperature was kept at 100 °C for 15 minutes. Subsequently, the colloidal solution was cooled to room temperature. A part of the Au nanoparticle colloid was taken out, washed and diluted, and then subjected to TEM and UV-visible tests. 50 ml of ethylene glycol containing 10 mmol of AgNO3 was added to the remaining reaction solution under magnetic stirring, and magnetic stirring was maintained while the solution was heated to 100 °C. After keeping the temperature constant for 20 minutes, it was cooled to room temperature. At the same time, the product was transferred to a centrifuge tube, an appropriate amount of ethanol was added and mixed evenly, and then centrifuged at 8000 revolutions per minute for 10 minutes. A precipitate of nanoparticles was obtained at the bottom of the centrifuge tube. The upper clear liquid was removed, and 15 ml of toluene was added to redisperse the nanoparticle precipitate at the bottom of the centrifuge tube. Appropriate ultrasonic treatment could be carried out to make the nanoparticles fully dispersed in toluene. Through this process, various organic impurities in the reaction product could be removed to achieve the purpose of washing the nanoparticles. This operation could be carried out 2 - 4 times (the samples for XRD analysis were generally washed 4 times to fully wash the organic matter and prevent its interference with the results). A small amount of toluene colloid dispersed with nanoparticles (generally 1 - 2 ml) was taken out from the centrifuge tube using a pipette, etc., and after dilution, samples for TEM test and UV-visible test were prepared. The remaining nanoparticle colloid was washed 3 - 4 times with ethanol, and then the remaining nanoparticle precipitate after centrifugation was placed in an oven and kept at 60 °C for 2 hours. The dried sample was subjected to powder XRD test.

[0091] (2) Influence of Different Ratios of Au / Ag on the SPR Properties of Au@Ag Core-Shell Nanostructures

[0092] In the above experiments, Au@Ag core-shell nanostructures with different compositions were synthesized by adjusting the molar ratio of Au / Ag to 2 / 1, 1 / 1, and 1 / 2. After cleaning and dilution, samples for UV-visible testing were prepared.

[0093] Effect of Au seed size on the formation of Au@Ag core-shell nanostructures First, small-sized Au seeds were prepared: 10 mmol of HAuCl4·xH2O was dissolved in a solution containing 5 ml of oleylamine and 20 ml of decalin at room temperature. Then, this solution was injected into a three-necked flask protected by N2 atmosphere at room temperature using a syringe. The three-necked flask contained 2.0 ml of n-butyllithium hexane solution (2.2 M) and 75 ml of cyclohexane. The solution instantly turned into a red colloid after the injection of the Au precursor. The red colloid was stirred at room temperature for 20 minutes and then heated to 120 °C and kept at a constant temperature for 2 hours to obtain small-sized Au nanoparticles. A small amount of the product was taken out, added with an appropriate amount of ethanol, and then centrifuged at 8000 revolutions per minute for 15 minutes. After removing the supernatant, the Au nanoparticle precipitate was obtained, redispersed in toluene, and then washed with ethanol. After cleaning and dilution, samples for TEM, UV-visible, etc. testing were prepared.

[0094] An appropriate amount of ethanol was added to the above Au nanoparticle colloidal solution, and then it was centrifuged at 8000 revolutions per minute for 15 minutes. After removing the supernatant, the Au nanoparticle precipitate was obtained, redispersed in toluene, and washed with ethanol 2 - 3 times. The washed nanoparticle precipitate was redispersed in a solution containing 100 ml of ethylene glycol and 2 g of PVP. Then, 50 ml of ethylene glycol containing 10 mmol of AgNO3 was added to the above solution under magnetic stirring. The magnetic stirring was maintained, and the solution was heated to 100 °C and kept at a constant temperature for 20 minutes and then cooled to room temperature. After cleaning and dilution, samples for TEM, XRD, and UV-visible testing were prepared.

[0095] (4) Synthesis of sea urchin-like Au-Ag heteropolymer nanostructures Under N2 atmosphere, 10 mmol of HAuCl4·xH2O was dissolved in a solution containing 100 ml of ethylene glycol and 10 ml of oleylamine. Under magnetic stirring, the solution was heated to 100.0 °C and kept at a constant temperature for 4 hours to obtain a purple Au colloidal solution. The solution was naturally cooled to room temperature. Then, 50 ml of ethylene glycol containing 10 mmol of AgNO3 and 10 ml of oleylamine was added to the above reaction solution under magnetic stirring. Next, 10 mmol of NaBH4 dissolved in 50 ml of ethylene glycol was added to the above solution, and the mixture was kept at 100 °C for 15 minutes. Subsequently, the colloidal solution was cooled to room temperature. The product was transferred to a centrifuge tube, and an appropriate amount of ethanol was added and mixed well. Then, it was centrifuged at 8000 revolutions per minute for 10 minutes to obtain a precipitate of nanoparticles at the bottom of the centrifuge tube. The supernatant was removed, and 15 ml of toluene was added to redisperse the nanoparticle precipitate at the bottom of the centrifuge tube. Appropriate ultrasonic treatment could be carried out to fully disperse the nanoparticles in toluene, and an appropriate amount of oleylamine was added to stabilize the well-dispersed nanoparticles. Through this process, various organic impurities in the reaction product could be removed to achieve the purpose of washing the nanoparticles clean. This operation could be carried out 2 - 4 times (samples for XRD analysis were generally washed 4 times to fully wash away the organic matter and prevent its interference with the results). A small amount of toluene colloid dispersed with nanoparticles (usually 1 - 2 ml) was taken out from the centrifuge tube using a pipette, etc., and samples for TEM testing and UV-visible testing were prepared after dilution. After the remaining nanoparticle colloid was washed 3 - 4 times with ethanol, the remaining nanoparticle precipitate after centrifugation was placed in an oven and kept at 60 °C for 2 hours. The dried sample was subjected to powder XRD testing.

[0096] (5) Synthesis of Ag-CeO2 metal-oxide nanoheteropolymer structure Synthesis of CeO2 nanocube particles: 15 mL of an aqueous solution of Ce(NO3)3 with a concentration of 16.7 mmol / L was added to a 50 mL autoclave with a polytetrafluoroethylene liner. Subsequently, 15 mL of toluene, 1.5 mL of oleic acid, and 0.15 mL of tert-butylamine were added. The sealed autoclave was placed in an oven and kept at 180 °C for 24 hours. After naturally cooling to room temperature, the product was centrifuged at a speed of 2000 revolutions per minute for 10 minutes to remove solid impurities in the reaction. The upper layer of pale yellow liquid was taken out, 10 mL of ethanol was added, and then it was centrifuged at a speed of 8000 revolutions per minute for 10 minutes. After removing the supernatant, a brown precipitate was obtained. Then, 15 mL of toluene and a small amount of oleic acid were added to redisperse the precipitate and store it for subsequent experiments and analytical characterization.

[0097] Synthesis of Ag-CeO2 nanohybrids: 20 mL of ethanol was added to 15 mL of the toluene solution of CeO2 prepared above. After centrifugation at 8000 revolutions per minute for 10 minutes to remove the supernatant, a precipitate of CeO2 nanoparticles was obtained. 0.2 mL of oleylamine and 15 mL of ethylene glycol solvent were added. After redispersing the precipitate, it was transferred to a three-necked flask. Under a N2 atmosphere and magnetic stirring, the solution in the three-necked flask was heated to 100 °C and kept at a constant temperature for 0.5 hour to remove moisture. At room temperature, 1.0 mL of a n-butyllithium n-hexane solution (2.2 M, i.e., 2.2 mmol / L) was quickly injected into the flask using a syringe. Then, a mixed solution of 5 mL of ethylene glycol and 1 mL of oleylamine containing 0.125 mmol of AgNO3 was injected into the three-necked flask in the same manner. After keeping at a constant temperature at room temperature for 10 minutes, the temperature was slowly raised. After keeping at 80 °C for 1 hour, the temperature was raised to 120 °C and aged for 2 hours. After the reaction product was naturally cooled to room temperature, it was centrifuged at 2000 revolutions per minute for 10 minutes to remove solid impurities in the reaction. After taking out the supernatant, an appropriate amount of ethanol was added and centrifuged at 8000 revolutions per minute for 10 minutes. After removing the upper layer of liquid, an appropriate amount of toluene was added to redisperse. Then, the product was washed with ethanol in the same manner 2 - 3 times. Finally, an appropriate amount of toluene or n-hexane was added to redissolve the precipitate and stored for subsequent tests and analytical characterization.

[0098] Figure 6 Figures 4a and 4b are the TEM and HRTEM images of the Au seeds obtained in the first step. As can be seen from the electron microscopy results, the average size of the synthesized Au nanoparticles is about 17 nm. The HRTEM high-resolution transmission electron microscopy image of this sample shows that the inside and outside of the nanoparticles are homogeneous, with the same color, and the edges have a neat spherical morphology.

[0099] Figure 7 Figures 5a and 5b are the TEM and HRTEM images of the Au@Ag core-shell nanoparticles obtained by the seed growth method. As can be seen from the electron microscopy results, the average size of the synthesized nanoparticles is about 20 nm. Compared with the size of the Au seeds, the bimetallic nanoparticles have shown a certain growth. Figure 7 a) It can be seen from the TEM image that each nanoparticle consists of a core with a darker color surrounded by a shell with a lighter color. This is because the atomic number of Au is much larger than that of Ag. Therefore, when imaging by TEM, the color of the Au particles is darker than that of Ag. Thus, based on this morphological feature, it can be clearly judged that the prepared nanoparticles are core-shell nanoparticles with a layered structure.

[0100] Next, the AuAg alloy and Au@Ag core-shell structured nanoparticles colloids prepared previously were cleaned and concentrated by centrifugation to keep the total concentrations of Au and Ag consistent. The above nanoparticle sols were mixed with pyridine in a certain volume ratio and stirred thoroughly. After standing for a period of time, centrifugal cleaning was performed 2-3 times. Finally, an appropriate amount of the sample was taken into a glass sample bottle for surface-enhanced Raman scattering spectroscopy (SERS) detection.

[0101] Figure 8 Figure 4 shows the SERS spectra of pyridine on the surface of AuAg alloy nanostructures with different Au / Ag ratios. The excitation light was 632.8 nm. It can be clearly seen from the figure that the relative intensities of the spectral peaks of pyridine at around 1005 cm-1 (fully symmetric ring breathing vibration) and around 1032 cm-1 (triangular symmetric distortion) also changed. Among them, on the surfaces of AuAg alloy nanostructures with Au / Ag ratios of 1 / 1 and 1 / 2, the peak height of the former was basically the same as that of the latter. However, when Au / Ag was 2 / 1, the peak height of the former was slightly higher than that of the latter.

[0102] On the other hand, the AuAg alloy and Au@Ag core-shell structured nanoparticles colloids prepared previously were cleaned and concentrated by centrifugation to keep the total concentrations of Au and Ag consistent. The above nanoparticle sols were mixed with an ethylene glycol solution of cysteine in a certain volume ratio and stirred thoroughly. After standing for a period of time, centrifugal cleaning was performed 2-3 times. Then, a certain volume of a methanol solution of dangerous chemicals such as 2,4,6-trinitrotoluene was added to the above cysteine-modified nanoparticle colloids. The mixture was mixed evenly and stirred thoroughly. After standing for a period of time, an appropriate amount of the sample was taken into a glass sample bottle for surface-enhanced Raman scattering spectroscopy (SERS) detection.

[0103] When pure Au nanoparticles are used as SERS substrates, the characteristic peaks in the SERS spectra of 2,4,6-trinitrotoluene are not significant; when AuAg alloy nanoparticles are used as SERS substrates, weak characteristic peaks can be observed in the SERS spectra of 2,4,6-trinitrotoluene; when pure Ag nanoparticles are used as SERS substrates, strong characteristic peaks can be observed in the SERS spectra of 2,4,6-trinitrotoluene; when Au@Ag core-shell structured nanoparticles are used as SERS substrates, the characteristic peaks in the SERS spectra of 2,4,6-trinitrotoluene are the most significant. This shows that pure Au nanoparticles have a poor SERS effect in the Raman detection of 2,4,6-trinitrotoluene, the Au@Ag core-shell structured nanoparticles have the most significant SERS detection effect, the SERS enhancement effect of AuAg alloy nanoparticles is stronger than that of pure Au nanoparticles but weaker than that of pure Ag nanoparticles, and the SERS signal enhancement ability of the Au@Ag core-shell structure is greater than that of pure Ag alone. Because the SERS enhancement effect of the AuAg alloy nanostructure itself is not significant, the change in the SERS enhancement of the AuAg alloy nanostructure is not significant with the change of the Au / Ag ratio.

[0104] Through the above research, it is found that the SERS enhancement effect obtained by using the Au@Ag core-shell nanostructure as the SERS substrate is much better than that of the AuAg alloy. According to relevant theoretical and experimental studies, the possible reasons are as follows: First, when the proportion of Ag in the Au / Ag ratio is relatively large, the core-shell material formed at this time, and the shell thickness can well improve the SERS enhancement effect; Second, the surface morphology of the Au@Ag core-shell structured nanoparticles is rougher than that of the AuAg alloy nanoparticles. According to the EM mechanism, this rough nanoscale surface is very helpful for the SERS enhancement effect.

[0105] It should be noted that the detailed explanations of the variables involved in the present invention are shown in Table 5.

[0106] Table 5 Variable Explanation Table

[0107] The above is only the specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention can easily think of changes or substitutions, which should all be covered within the protection scope of the present invention.

Claims

1. A method for determining the SERS effect of Ag-based composite nanomaterials on hazardous chemicals, characterized in that: The following steps are involved: Au nanocrystals and Au@Ag core-shell nanostructures are prepared, CeO2 nanocubes and Ag-CeO2 nanoheteromers are prepared, and the Au@Ag core-shell nanostructures and the Ag-CeO2 nanoheteromers are mixed to prepare a surface enhanced Raman detection substrate. A Raman spectrum standard correction matrix, a substrate enhancement effect evaluation matrix, and a SERS enhancement coefficient correction matrix are obtained through the detection substrate and a Raman spectrometer, and a SERS signal intensity normalization matrix is ​​established. Finally, a SERS utility value is calculated through the SERS signal intensity normalization matrix, the substrate enhancement effect evaluation matrix, and the Raman spectrum standard correction matrix.

2. The method for determining the SERS effect of Ag-based composite nanomaterials on hazardous chemicals according to claim 1, characterized in that: The step of preparing Au nanocrystal seeds is to dissolve 10 mmol of tetrachlorohydric acid in a solution containing 100 ml of ethylene glycol and 2 g of polyvinyl pyrrolidone, heat it to 100 degrees Celsius under magnetic stirring conditions, slowly add 50 ml of ethylene glycol solution of 10 mmol of sodium borohydride, react at a constant temperature for 15 minutes, and then cool to room temperature to obtain the Au nanocrystal seed solution.

3. The method for determining the SERS effect of Ag-based composite nanomaterials on hazardous chemicals according to claim 1, characterized in that: The steps of preparing the Au@Ag core-shell nanostructure are as follows: adding 50 ml of ethylene glycol solution containing 10 mmol of silver nitrate to the Au nanocrystal seed solution, heating to 100 degrees Celsius under magnetic stirring conditions, reacting at a constant temperature for 20 minutes and then cooling to room temperature to obtain the Au@Ag core-shell nanostructure reaction solution; adding ethanol to the Au@Ag core-shell nanostructure reaction solution, centrifuging at 8000 rpm for 10 minutes, collecting the precipitate and re-dispersing it with 15 ml of toluene, repeating the washing 2 to 4 times, and obtaining the purified Au@Ag core-shell nanostructure.

4. The method for determining the SERS effect of Ag-based composite nanomaterials on hazardous chemicals according to claim 1, characterized in that: The steps of preparing CeO2 nanocubes are as follows: 15 ml of 16.7 mmol / l cerium nitrate aqueous solution is mixed with 15 ml of toluene, 1.5 ml of oleic acid and 0.15 ml of tert-butylamine, and the mixture is placed in an autoclave for constant temperature reaction at 180 degrees Celsius for 24 hours to obtain the CeO2 nanocube reaction product; the CeO2 nanocube reaction product is centrifuged at 2000 rpm for 10 minutes to remove solid impurities, 10 ml of ethanol is added to the upper layer of liquid, and the mixture is centrifuged at 8000 rpm for 10 minutes to collect the precipitate to obtain the purified CeO2 nanocube.

5. The method for determining the SERS effect of Ag-based composite nanomaterials on hazardous chemicals according to claim 1, characterized in that: The steps of preparing Ag-CeO2 nano-heteropolymers are as follows: dispersing the purified CeO2 nanocubes in 15 ml of ethylene glycol solution containing 0.2 ml of oleylamine, heating to 100 degrees Celsius under nitrogen protection for constant temperature reaction for 30 minutes to obtain the first reaction system; injecting 1.0 ml of 2.2 mmol per liter n-butyl lithium n-hexane solution into the first reaction system, and then injecting a mixed solution of 5 ml of ethylene glycol containing 0.125 mmol of silver nitrate and 1 ml of oleylamine to obtain the second reaction system; stirring the second reaction system at room temperature for 10 minutes, then heating it to 80 degrees Celsius for constant temperature reaction for 1 hour, and continuing to heat it to 120 degrees Celsius for reaction for 2 hours to obtain the Ag-CeO2 nano-heteropolymer reaction liquid; collecting the Ag-CeO2 nano-heteropolymer reaction liquid by centrifugation at 8000 rpm for 10 minutes, washing it with ethanol 2 to 3 times and dispersing it in toluene to obtain the Ag-CeO2 nano-heteropolymers.

6. The method for determining the SERS effect of Ag-based composite nanomaterials on hazardous chemicals according to claim 1, characterized in that: The step of preparing a surface enhanced Raman detection substrate is specifically to mix the purified Au@Ag core-shell nanostructure and the Ag-CeO2 nano-heteropolymer in a mass ratio of 1:1, ultrasonically disperse for 15 minutes, and obtain the surface enhanced Raman detection substrate; drop-coat the surface enhanced Raman detection substrate on the surface of a conductive glass substrate, dry it naturally, and then place it in a drying oven at 60 degrees Celsius for 2 hours to obtain the detection substrate.

7. The method for determining the SERS effect of Ag-based composite nanomaterials on hazardous chemicals according to claim 1, characterized in that: The step of establishing a Raman spectrum standard correction matrix specifically comprises measuring the Raman spectrometer in the wave number range of 400 to 3000 to obtain a baseline intensity matrix and an instrument response matrix in the Raman spectrum standard correction matrix.

8. The method for determining the SERS effect of Ag-based composite nanomaterials on hazardous chemicals according to claim 1, characterized in that: The step of establishing a substrate enhancement effect evaluation matrix is ​​to prepare hazardous chemical standard solutions with concentrations of 1, 10, 50, 100, and 500 nanomoles per liter, respectively, measure the Raman signal intensity of the hazardous chemical standard solutions, and obtain the substrate enhancement effect evaluation matrix.

9. The method for determining the SERS effect of Ag-based composite nanomaterials on hazardous chemicals according to claim 1, characterized in that: The step of establishing a SERS enhancement coefficient correction matrix is ​​specifically to calculate the SERS enhancement coefficient correction matrix according to the substrate enhancement effect evaluation matrix and the Raman spectrum standard correction matrix; A Raman spectrometer is used to measure the surface enhanced Raman signal of the hazardous chemical to be tested, the excitation wavelength is selected to be 532 nanometers, the laser power is set to 5 milliwatts, and the acquisition time is 10 seconds to obtain the Raman signal of the hazardous chemical to be tested; the Raman signal of the hazardous chemical to be tested is normalized using the SERS enhancement coefficient correction matrix to obtain the SERS signal intensity normalization matrix.

10. The method for determining the SERS effect of Ag-based composite nanomaterials on hazardous chemicals according to claim 1, characterized in that: The step of calculating the SERS utility value is specifically to subtract the Raman spectrum standard correction matrix from the product of the SERS signal intensity normalization matrix and the substrate enhancement effect evaluation matrix.

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