A gold nanoarray sensor and a method for efficiently and rapidly identifying multiple forms of phosphorus in wastewater

Abstract

The present invention discloses a gold nanoarray sensor and a method for efficiently and rapidly identifying multiple forms of phosphorus in wastewater. The gold nanoarray sensor includes four groups of functionalized gold nanoparticle probe units, each composed of four nanogold probes modified with surface modifiers. The first unit is a nanogold probe modified with an amino / thiol bifunctional molecule, the second unit is a nanogold probe modified with a rare earth metal ion, the third unit is a nanogold probe modified with a quaternary ammonium salt surfactant, and the fourth unit is a nanogold probe modified with a quaternary phosphonium salt surfactant. The gold nanoarray sensor of the present invention is based on multi-wavelength detection and achieves rapid identification and quantitative detection of different phosphorus forms in wastewater through qualitative and quantitative analysis of multidimensional data. The present invention does not require a complex pre-treatment process and has the advantages of short detection time, simple operation, high sensitivity, and strong anti-interference ability. It provides an innovative approach for the combined analysis of the differentiation and concentration detection of phosphorus species in industrial wastewater.

Description

Technical Field

[0001] The present invention relates to the field of detection and analysis of multiple forms of phosphorus in typical sewage and wastewater, and in particular to a gold nanoarray sensor and a method for efficiently and quickly identifying multiple forms of phosphorus in wastewater. Background Art

[0002] Phosphorus compounds are pollutants in industrial wastewater that pose significant environmental risks. They primarily originate from industries such as pesticide production, flame retardant manufacturing, petroleum additives, and pharmaceuticals. Excessive phosphorus enters water bodies, acting as a limiting nutrient and leading to eutrophication, which in turn triggers a range of ecological and environmental problems. Phosphorus discharged from wastewater treatment plants is the primary source of phosphorus in various water bodies, primarily in inorganic and organic forms. Inorganic phosphorus is typically orthophosphate, while organic phosphorus primarily includes organophosphate esters and organophosphonates. Current research on phosphorus has primarily focused on orthophosphate, with significantly less attention being paid to organic phosphorus and other forms. These phosphorus species generally occur at low concentrations, exhibit high chemical stability, and possess complex morphologies. Accurate monitoring and analysis are crucial for developing effective phosphorus pollution control strategies. Therefore, developing efficient and convenient methods for identifying and differentiating organic phosphorus is a prerequisite and foundation for developing advanced treatment technologies for organic phosphorus in wastewater.

[0003] Identifying and differentiating between diverse organophosphates with similar chemical structures is challenging. Current detection technologies for organophosphates can generally be divided into two categories: Conventional techniques, including gas chromatography-mass spectrometry (GC-MS), high-performance liquid chromatography (HPLC), and enzyme-linked immunosorbent assay (ELISA), offer high accuracy and sensitivity, but are costly, time-consuming, and require complex sample pretreatment, making them unsuitable for real-time and on-site detection. Therefore, the development of simple, rapid, and sensitive methods for organophosphate analysis is of great environmental significance. In recent years, colorimetric analysis of pollutants based on the localized surface plasmon resonance effect of gold nanoparticles (Au NPs) has attracted significant interest and has become a research hotspot in water quality analysis. These methods have been applied to simulated water samples and surface waters. In current research, gold nanoprobes have been shown to identify, perform semi-quantitative, and perform single-component quantitative analysis of a wide range of substances, including free heavy metal ions, anions, drug molecules, and small biomolecules. Colorimetric probes based on AuNPs offer numerous advantages in detection. The selectivity of colorimetric methods depends largely on the functionalization of the AuNPs, enabling sensitive detection of target molecules through changes in optical properties that induce aggregation, dispersion, and morphological changes. However, challenges remain regarding the complexity of organophosphorus analytes, the simultaneous detection of multiple analytes, and interference from detection conditions. The number of analytes that can be selectively detected remains limited, posing significant challenges in developing colorimetric assays capable of classifying and identifying organophosphorus analytes.

[0004] The sensor array design abandons the traditional "lock and key" one-to-one sensing mode and is composed of a group of probe units with broad-spectrum interactive sensing. The array's detection method of simultaneously acquiring multiple points and multiple information has greatly improved the detection throughput and analysis efficiency of multiple targets. Pattern recognition can provide information such as the type, concentration, and characteristics of the analyte. Then, chemometric methods such as principal component analysis (PCA), linear discriminant analysis (LDA), or artificial neural networks (ANN) are used to extract and analyze the characteristic graphs to achieve pattern recognition of different targets. It can simultaneously detect and identify multi-component analytes in complex mixtures and has great potential for application in the rapid identification and analysis of multiple forms of phosphorus in actual wastewater systems. In theory, it is more suitable for the analysis of various organic phosphorus in real water bodies. However, there are currently no reports on array sensors based on functionalized gold nanoparticles for the qualitative identification and quantitative analysis of multiple forms of phosphorus. Summary of the Invention

[0005] To address the aforementioned technical issues, the present invention aims to provide a gold nanoarray sensor and a method for efficiently and quickly identifying multiple forms of phosphorus in wastewater. The gold nanoarray sensor of the present invention combines the dual functions of visual and efficient differentiation with quantitative analysis. It can distinguish single phosphorus compounds, identify multiple phosphorus mixtures, and simultaneously quantify target concentrations. Based on multivariate statistical analysis, information on the phosphorus species (single or mixed) and their corresponding concentrations in the wastewater are obtained, enabling effective visual differentiation and quantitative analysis.

[0006] The technical solution adopted in the present invention is as follows:

[0007] A gold nanoarray sensor includes four groups of functionalized gold nanoparticle probe units, each composed of gold nanoprobes modified by four surface modifiers;

[0008] The first unit is a gold nanoparticle probe modified with amino / thiol bifunctional molecules;

[0009] The second unit is a gold nanoparticle probe modified with rare earth metal ions;

[0010] The third unit is a nanogold probe modified with a quaternary ammonium surfactant;

[0011] The fourth unit is a nanogold probe modified with a quaternary phosphonium salt surfactant.

[0012] Furthermore, the amino / carboxyl bifunctional molecule includes cysteamine hydrochloride, the rare earth metal ion includes neodymium ion, the quaternary ammonium salt surfactant includes hexadecyltrimethylammonium bromide (CTAB), and the quaternary phosphonium salt surfactant includes hexadecyltributylphosphonium bromide (THPB).

[0013] Furthermore, the preparation methods of the first unit, the third unit and the fourth unit all include the following steps:

[0014] S1: Under vigorous stirring conditions, haloauric acid solution was used as the gold source for gold nanoparticles, and three groups of haloauric acid solutions were set up;

[0015] S2: adding three surface modifiers to three groups of haloauric acid solutions respectively, then adding a reducing agent solution, stirring and reacting at room temperature to completely convert the haloauric acid into gold nanoparticles; the three surface modifiers are cysteamine hydrochloride, hexadecyltrimethylammonium bromide (CTAB), and hexadecyltributylphosphonium bromide (THPB);

[0016] S3: After the reaction is completed, the mixture is refrigerated and stored to finally obtain three groups of functionalized gold nanoparticle probe units.

[0017] Furthermore, in step S2 of preparing the first unit, the third unit, and the fourth unit, the stirring reaction time is 1.5-3 hours, and the molar ratios of the three surface modifiers to the haloauric acid are as follows: the molar ratio of cysteamine hydrochloride to the haloauric acid is 0.5-1.0:1, the molar ratio of hexadecyltrimethylammonium bromide CTAB to the haloauric acid is 0.05-0.1:1, and the molar ratio of hexadecyltributylphosphonium bromide THPB to the haloauric acid is 0.2-0.6:1.

[0018] Furthermore, the preparation method of the second unit includes the following steps:

[0019] (1) Mixing the haloauric acid solution with the cysteine ​​solution, and then adding the reducing agent solution dropwise for reduction. After the addition is completed, the resulting colloidal solution is allowed to stand overnight to allow the haloauric acid to be completely converted into gold nanoparticles, thereby obtaining a cysteine-modified gold nanoparticle precursor;

[0020] (2) Then, neodymium ions are added to the precursor solution of step (1) under stirring, and the mixture is stirred at room temperature to react to obtain gold nanoparticles functionalized with neodymium ions on the surface;

[0021] (3) After the reaction is completed, the product is refrigerated and stored to finally functionalize the second unit of the gold nanoparticles.

[0022] Furthermore, in step (1) of preparing the second unit, the molar ratio of cysteamine hydrochloride to haloauric acid is 0.002-0.005:1; in step (2), the molar ratio of neodymium ions to haloauric acid in step (1) is 0.001-0.003:1, and the stirring reaction time in step (2) is 1.5-3 hours.

[0023] According to the present invention, the haloauric acid can be fluoroauric acid (HAuF4), chloroauric acid (HAuCl4), or bromoauric acid (HAuBr4). Compared with other haloauric acids, chloroauric acid (HAuCl4) is preferred as the raw material for synthesizing gold nanoparticles in the present invention due to its chemical stability, reduction efficiency, and cost-effectiveness.

[0024] According to the present invention, the reducing agent may include, but is not limited to, sodium borohydride (NaBH4), trisodium citrate (Na3C6H5O7), ascorbic acid, hydroxylamine hydrochloride, or potassium tartrate. Compared to other reducing agents, sodium borohydride is preferred in the present invention due to its high reducibility, complete reaction, and low byproduct count.

[0025] The present invention also discloses the application of a gold nanometer array sensor in the efficient and rapid identification and detection of multiple forms of phosphorus in wastewater.

[0026] The present invention also discloses a method for efficiently and quickly identifying multiple forms of phosphorus in wastewater based on a gold nanoarray sensor, comprising the following steps:

[0027] Step 1: For different forms of phosphorus compound standards, dissolve them in ultrapure water into a series of solutions with different concentrations to prepare the corresponding phosphorus standard solutions;

[0028] Step 2: The phosphorus standard solution from step 1 is mixed with the four groups of functionalized gold nanoparticle probe units in the gold nanoarray sensor, respectively, and after a specific reaction, multi-wavelength absorbance detection is performed. The detection signals of the four groups of functionalized gold nanoparticle probe units at multiple wavelengths are combined to form a response matrix, which is analyzed using a pattern recognition algorithm to construct a cross-response fingerprint.

[0029] Step 3: When performing phosphorus pollutant analysis and detection, according to the method of step 2, the test solution is specifically reacted with the four groups of functionalized gold nanoparticle probe units respectively, and then absorbance detection is performed according to the method of step 2. The analysis is performed using a pattern recognition algorithm and compared with the fingerprint map constructed in step 2 to obtain the phosphorus pollutant concentration and morphological characteristic information in the test solution.

[0030] Furthermore, in step 2, the reaction temperature is room temperature and the reaction time is 5-30 min; the pH values ​​used for detection of the four groups of functionalized gold nanoparticle probe units, the first unit, the second unit, the third unit and the fourth unit are 5.0±0.5, 5.0±0.5, 9.0±0.5 and 11.0±1.0 respectively.

[0031] Furthermore, the phosphorus compound standard in step 1 is selected from at least one of organic phosphonic acid, phosphate and inorganic phosphate compounds, and the selected phosphorus compound standard is the following 11 kinds: diethylenetriaminepentamethylenephosphonic acid, aminotrimethylenephosphonic acid, hydroxyethylidenediphosphonic acid, hexamethylenediaminetetramethylenephosphonic acid, 2-phosphonobutane-1,2,4-tricarboxylic acid, ethylenediaminetetramethylenephosphonic acid, triphenyl phosphate, tributyl phosphate, pyrophosphoric acid, disodium hydrogen phosphate, and polyphosphate.

[0032] Furthermore, the absorbance in step 2 is within the range of 450-700 nm, and the present invention focuses on selecting six characteristic wavelengths of 450, 520, 560, 600, 650 and 700 nm.

[0033] Furthermore, the method for constructing a cross-response fingerprint map in step 2 is: after the specific reaction, use an enzyme reader to determine the absorbance value A of each reaction liquid at a series of different characteristic wavelengths, and test the absorbance value A0 of each group of probe units under the same reaction conditions with an equal amount of ultrapure water as a blank control group at the corresponding characteristic wavelength, and use the relative change rate of the absorbance value A / A0 as the detection signal; thereby obtaining a multidimensional vector of the detection results of different groups of probe units at different characteristic wavelengths, and using a pattern recognition algorithm for analysis to obtain information about the concentration and morphology of the target, and constructing a cross-response fingerprint map.

[0034] Furthermore, the pattern recognition algorithm in step 2 includes processing the data using a statistical classification method of linear discriminant analysis (LDA), using the first three principal component scores processed by LDA as coordinate axes to construct a three-dimensional standard fingerprint library for phosphorus compound detection, which is used for qualitative classification of phosphorus compounds. In addition, a standard curve is drawn using the first dimension score of LDA as the vertical axis and the concentration of the phosphorus compound as the horizontal axis for quantitative detection of phosphorus compounds.

[0035] According to the present invention, a preferred method for constructing a cross-response fingerprint for an array sensor involves reacting four sets of gold nanoprobes with a target for 20 minutes each. The absorbance at six characteristic wavelengths, 450 nm, 520 nm, 560 nm, 600 nm, 650 nm, and 700 nm, is then measured using a microplate reader. The ratio (A / A0) of the sample absorbance (A) at each wavelength to the absorbance of an ultrapure water blank control (A0) is used as the detection signal. Normalized absorbance ratios (A / A0) can be used to eliminate background interference, and the relative rate of change in absorbance is calculated. A 4×6-dimensional response matrix is ​​generated using multi-probe units (four types) and multi-wavelength (six) collaborative detection. This matrix is ​​then processed using linear discriminant analysis (LDA) to construct a cross-response fingerprint.

[0036] According to the present invention, a three-dimensional score space constructed based on the first three principal components of linear discriminant analysis (LDA) can realize the visual distinction and accurate identification of organophosphorus multi-component mixtures with different proportions.

[0037] According to the present invention, the quantitative analysis adopts the linear regression method of the first principal component score of LDA, and linear fitting is performed to obtain a linear equation. When the phosphorus content is 2.0-15.0 mg / L, its concentration has an excellent linear relationship with the first dimension score of LDA (R 2>0.97), showing good linear response characteristics within the test range. The calibration curve established based on this can predict the unknown concentration of the test sample, thereby achieving quantitative analysis of phosphorus in wastewater.

[0038] Compared with the prior art, the technical innovation and advantages of the present invention can be summarized as follows:

[0039] 1) In this study, 11 target phosphorus compounds interacted with four functionalized gold nanoparticle probes to generate specific interaction fingerprints. Multiple recognition interfaces, including coordination bonding, electrostatic interactions, and hydrophobic effects, were constructed, inducing differential aggregation of the gold nanoparticles. This resulted in the array sensor exhibiting cross-responsiveness. The response values ​​were calculated by measuring the absorbance changes of the probe units before and after the reaction. The data were analyzed using multivariate statistical methods such as hierarchical cluster analysis (HCA) and linear discriminant analysis (LDA). This analysis system, validated through multiple algorithms, ensured the reliability of the multivariate phosphorus identification results. This approach was used to investigate the array's ability to identify and detect target analytes. The LDA algorithm reduced the raw data dimensionality to a three-dimensional feature space. In this 3D spatial plot, replicate samples of the same organophosphorus were clearly clustered, and different organophosphorus analytes were effectively separated, demonstrating the present invention's robust ability to identify and discriminate multivariate phosphorus species. In HCA analysis, the organophosphorus species were classified based on their average Euclidean distance, resulting in a dendrogram. The Euclidean distance matrix classification results were consistent with the LDA spatial distribution. This embodies the innovative architecture of multi-probe design-cooperative identification-intelligent analysis, which enables the differentiation of organophosphorus compounds in complex matrices.

[0040] 2) This invention effectively detects different phosphorus compounds at low concentrations, with high sensitivity, strong recognition capabilities, short detection times, and simple operation. Furthermore, it can quantitatively analyze multivariate forms of phosphorus by fitting the LDA first-dimensional principal component scores to the concentrations of phosphorus compounds. Through the innovative combination of nanosensing and pattern recognition algorithms, this invention achieves rapid and accurate quantification of different phosphorus compound pollutants, transforming complex chemical identification into a quantifiable mathematical discriminant model, enabling identification and detection even in complex mixed systems.

[0041] 3) The present invention maintains good specificity in the presence of common ions in water. Tests on common cations and anions in water show that they do not significantly interfere with the detection results. The interference of the gold nanoarray sensor is small and almost negligible. This also shows that the present invention has good resistance to ion interference and specific recognition performance, and has high selectivity for different phosphorus compounds.

[0042] 4) The present invention uses surface-functionalized gold nanoarrays as a sensing platform to capture the characteristic response signals of phosphorus multi-morphs and construct a fingerprint recognition database to achieve rapid identification and accurate quantification of phosphorus compound pollutants. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 This is the LDA graph of the array sensor of the present invention for 11 different phosphorus species at a final concentration of 5.0 mg / L.

[0044] Figure 2 1 is the HCA graph of the array sensor of the present invention for 11 different phosphorus species at a final concentration of 5.0 mg / L.

[0045] Figure 3 This is the LDA graph of the array sensor of the present invention for a mixed sample of PBTC and HDTMP with a final concentration of 20.0 mg / L.

[0046] Figure 4a These are the absorbance response results of the Cys@Au NPs probe unit of the present invention when detecting 11 phosphorus compounds at a final concentration of 5.0 mg / L and common miscellaneous ions.

[0047] Figure 4b These are the absorbance response results of the Nd@Au NPs probe unit of the present invention when detecting 11 phosphorus compounds with a final concentration of 5.0 mg / L and common miscellaneous ions.

[0048] Figure 4c These are the absorbance response results of the CTAB@Au NPs probe unit of the present invention when detecting 11 phosphorus compounds with a final concentration of 5.0 mg / L and common miscellaneous ions.

[0049] Figure 4d These are the absorbance response results of the THPB@Au NPs probe unit of the present invention when detecting 11 phosphorus compounds with a final concentration of 5.0 mg / L and common miscellaneous ions.

[0050] Figure 5a This is the standard curve for the detection of phosphorus compound standard PA by the array sensor of the present invention.

[0051] Figure 5b This is the standard curve for the detection of phosphorus compound standard DP by the array sensor of the present invention.

[0052] Figure 5c This is the standard curve for the detection of the phosphorus compound standard NTMP by the array sensor of the present invention.

[0053] Figure 6 It is the percentage of the first three-dimensional accumulation of the LDA principal components of the LDA graph of 11 different phosphorus species at a final concentration of 5.0 mg / L detected by different groups of array sensors. DETAILED DESCRIPTION

[0054] The present invention is further described below with reference to specific examples. It should be noted that the experimental methods not specifically specified in the examples were all performed under conventional experimental conditions, and the reagents and materials used were all commercially available unless otherwise specified.

[0055] The 11 phosphorus-containing compounds in the embodiments of the present invention are: diethylenetriaminepentamethylenephosphonic acid (DTPMP), aminotrimethylenephosphonic acid (ATMP), hydroxyethylidenediphosphonic acid (HEDP), hexamethylenediaminetetramethylenephosphonic acid (HDTMP), 2-phosphonobutane-1,2,4-tricarboxylic acid (PBTC), ethylenediaminetetramethylenephosphonic acid (EDTMP), triphenyl phosphate (DPP), tributyl phosphate (DP), pyrophosphoric acid (PPi), disodium hydrogen phosphate (PA), and polyphosphate (PPA).

[0056] Example 1: Based on the pure water environment, a method for distinguishing and detecting 11 phosphorus-containing compounds was established. The specific implementation steps are as follows:

[0057] 1) Construction of gold nanoparticle probe unit array:

[0058] 5.0 mL of 5.0 mmol / L chloroauric acid solution was mixed with three surface functionalization modifiers: cysteamine hydrochloride, CTAB, and THPB. The amounts and concentrations of the three surface functionalization modifiers were: 4.0 mL of 5.0 mmol / L cysteine ​​solution, 1.0 mL of 1.0 mmol / L CTAB solution, and 1.0 mL of 10.0 mmol / L THPB solution. Ultrapure water was added to each solution to bring the total volume to 100 mL. 2.0 mL of 0.1 mol / L sodium borohydride solution was then added dropwise for reduction, with the solution color gradually changing from light yellow to orange-red to wine-red. The reaction was stirred at high speed at room temperature for 2 hours. This yielded surface-functionalized gold nanoparticles: cysteamine hydrochloride, CTAB, and THPB.

[0059] Aqueous chloroauric acid (97 mL, 1.4 mM) and cysteine ​​(1 mL, 0.5 mM) were mixed for 10 minutes. Then, 2.0 mL of freshly prepared 0.1 mol / L sodium borohydride solution was added dropwise for reduction. The colloidal solution was allowed to stand overnight. Then, 200 μL of 1.0 mmol / L aqueous neodymium chloride solution was added and the mixture was stirred at high speed at room temperature for 2 hours to obtain gold nanoparticles functionalized with neodymium ions.

[0060] According to the above method, four functionalized gold nanoparticle probes, Cys@Au NPs, Nd@Au NPs, CTAB@Au NPs and THPB@Au NPs, were obtained to constitute the array sensor of the present invention.

[0061] The pH of the Cys@Au NPs, Nd@Au NPs, CTAB@Au NPs, and THPB@Au NPs probe units were adjusted to 5.0, 5.0, 9.0, and 11.0, respectively, and the probe units were arranged in an orderly manner in a 96-well plate to form a detection array.

[0062] 2) Establishment of standard database:

[0063] Step S1: Prepare a phosphorus compound standard solution with ultrapure water to an initial concentration of 50.0 mg / L, designated as the phosphorus standard solution. Ultrapure water serves as a blank control. Mix the phosphorus standard solution with each probe unit at a volume ratio of 1:9 to obtain a final phosphorus standard concentration of 5.0 mg / L. After reacting at room temperature for 20 minutes, measure the absorbance (A) at six characteristic wavelengths: 450, 520, 560, 600, 650, and 700 nm using a microplate reader. The absorbance (A0) of each probe unit group at the corresponding characteristic wavelengths, obtained under the same reaction conditions using an equal amount of ultrapure water as a blank control, is also measured.

[0064] Step S2: Four functionalized gold nanoprobes and six characteristic wavelengths are used for collaborative detection to ultimately form a 4×6-dimensional response matrix. The response signal data of the 4×6-dimensional response matrix is ​​obtained by calculating the ratio of the sample absorbance to the blank control at each wavelength (A / A0), that is, the relative change rate of absorbance, as the response signal.

[0065] 3) According to the process of steps 1)-2) above, when the phosphorus compound standards used were 11 phosphorus compounds, namely diethylenetriaminepentamethylenephosphonic acid (DTPMP), aminotrimethylenephosphonic acid (ATMP), hydroxyethylidenediphosphonic acid (HEDP), hexamethylenediaminetetramethylenephosphonic acid (HDTMP), 2-phosphonobutane-1,2,4-tricarboxylic acid (PBTC), ethylenediaminetetramethylenephosphonic acid (EDTMP), triphenyl phosphate (DPP), tributyl phosphate (DP), pyrophosphate (PPi), disodium hydrogen phosphate (PA) and polyphosphate (PPA), the response signal data of the obtained 4×6 dimensional response matrix were processed by linear discriminant analysis (LDA), and the first three principal component scores were used as coordinate axes to construct a three-dimensional standard fingerprint library with a final concentration of 5.0 mg / L. The results are as follows: Figure 1 shown. Figure 1 The LDA method is used to reduce the dimensionality of multidimensional data and visually classify different analytes, thereby achieving clustering and differentiation of different phosphorus compounds in three-dimensional space.

[0066] according to Figure 1The LDA graphs of the four groups of Cys@Au NPs, Nd@Au NPs, CTAB@Au NPs and THPB@Au NPs probe units of the present invention for 11 different phosphorus species at a final concentration of 5.0 mg / L are shown in the following table. The cumulative percentages of the first three principal components of the LDA graphs are shown in the table. Figure 6 Group A in .

[0067] The response signal data of the obtained 4×6 dimensional response matrix were processed using hierarchical cluster analysis HCA, and the Euclidean square distance between samples was calculated to construct a dendrogram. The results are shown in the figure. Figure 2 shown. Figure 2 The results further verified the effectiveness of clustering.

[0068] Example 2. The experimental process of Example 2 is repeated in Example 1, with the only difference being that in the reaction system of step S1, the phosphorus standard with a final concentration of 5.0 mg / L is replaced with a mixed phosphorus sample of PBTC-HDTMP with a final concentration of 20.0 mg / L, and the molar ratio of PBTC to HDTMP is in the range of 1:9 to 9:1. The other conditions remain unchanged. Finally, the response signal data is processed using linear discriminant analysis (LDA), and the first three principal component scores are used as coordinate axes to construct a three-dimensional standard fingerprint library of the PBTC-HDTMP mixed phosphorus sample with a final concentration of 20.0 mg / L. The results are as follows: Figure 3 shown.

[0069] from Figure 3 It can be seen that the mixture of different concentrations of various organophosphorus species can also maintain a certain degree of differentiation.

[0070] Example 3. Experimental process of Example 3 to construct a gold nanoparticle probe unit array. Example 1 was repeated, and the pH of the Cys@Au NPs, Nd@Au NPs, CTAB@Au NPs, and THPB@Au NPs probe units were adjusted to 5.0, 5.0, 9.0, and 11.0, respectively, and the probe units were arranged in an orderly manner in a 96-well plate to form a detection array.

[0071] Example 3 Tests the response signals of different probe units to different substances:

[0072] Step A, test the response signal to the detection of foreign ions: prepare an aqueous solution of foreign ions, mix the foreign ion solution with each probe unit in a volume ratio of 1:9 to form a foreign ion reaction system, react at room temperature for 20 minutes, and use a microplate reader to measure the absorbance values ​​at two characteristic wavelengths of 520nm and 650nm. Calculate the ratio A of the absorbance of each group of probe units to the foreign ion reaction system at a wavelength of 650nm to the absorbance at a wavelength of 520nm. 650 / A 520, and calculate the ratio of the absorbance at 650nm wavelength to the absorbance at 520nm wavelength of each probe unit under the same reaction conditions with an equal amount of ultrapure water as the blank control group A 650 0 / A 520 0 .

[0073] Step B, test the response signal for the detection of phosphorus compounds: The phosphorus compound is prepared with ultrapure water to an initial concentration of 50.0 mg / L, recorded as the phosphorus compound solution, and ultrapure water is used as a blank control. The phosphorus compound solution is mixed with each probe unit in a volume ratio of 1:9 to obtain a reaction system with a final concentration of 5.0 mg / L phosphorus standard. After reacting at room temperature for 20 minutes, the absorbance values ​​at two characteristic wavelengths of 520nm and 650nm are measured using an enzyme marker. Calculate the ratio A of the absorbance of each group of probe units to the reaction system of phosphorus compounds at a wavelength of 650nm to the absorbance at a wavelength of 520nm 650 / A 520 , and calculate the ratio of the absorbance at 650nm wavelength to the absorbance at 520nm wavelength of each probe unit under the same reaction conditions with an equal amount of ultrapure water as the blank control group A 650 0 / A 520 0 .

[0074] According to the experimental process of the response signal of the impurity ion detection in step A above, the impurity ion is K + 、Na + Mg 2+ , Ca 2+ 、Cu 2+ 、Zn 2+ 、Cd 2+ 、Ni 2+ , Pb 2+ Cr 3+ or Fe 3+ Cations, the anions they bind to are all Cl - The final concentration of heteroionic cations in the reaction system is 0.1 mM. The absorbance ratio difference A tested in the experimental process of step A of Example 3 is 650 / A 520 -A 650 0 / A 520 0 The specific type of heterocation is plotted as the ordinate and the abscissa.

[0075] According to the experimental process of the response signal of the above step A for the detection of impurity ions, the impurity ion is Cl - 、NO3 - 、SO42- or CO3 2- Anions, the cations they bind to are all Na + The final concentration of heteroionic anions in the reaction system is 0.1 mM. The absorbance ratio difference A tested in the experimental process of step A of Example 3 is 650 / A 520 -A 650 0 / A 520 0 The specific type of heteroanion is plotted as the ordinate and the specific type of heteroanion is plotted as the abscissa.

[0076] According to the experimental process of the response signal of the phosphorus compound detection in step B above, the absorbance ratio difference A tested in the experimental process of step B of Example 3 is 650 / A 520 -A 650 0 / A 520 0 The specific types of phosphorus compounds are plotted as the ordinate and the abscissa.

[0077] According to the above process, the response data of the four probe units of Cys@Au NPs, Nd@Au NPs, CTAB@Au NPs and THPB@Au NPs to 11 phosphorus compounds at a final concentration of 5.0 mg / L and common miscellaneous ions are shown in Figure 4a 、 Figure 4b 、 Figure 4c and Figure 4d As shown in the figure, the response signals of the four probe units of the present invention to the detection of common impurity ions at a concentration of 0.1 mM are all very low, while the response signals to the detection of 11 phosphorus compounds at a final concentration of 5.0 mg / L all maintain good specificity. Therefore, the presence of common cations and anions in water will not significantly interfere with the detection results of the present invention.

[0078] Example 4: The experimental steps of Example 4 are repeated as in Example 1, with the only difference being that "in step 2) S1, the final concentration of the phosphorus compound standard in the reaction system is changed", and the other conditions remain unchanged.

[0079] The standard curves were drawn using the first dimension score of LDA as the ordinate and the concentration of phosphorus compounds as the abscissa. The standard curves of the array sensor of the present invention for the detection of different phosphorus compound standards PA, DP and NTMP were shown in Figure 1. Figure 5a 、 Figure 5b and Figure 5c The result of Figure 5a-5c It can be seen that when the content of phosphorus compound standards is 2.0-15.0 mg / L, its concentration has an excellent linear relationship with the first dimension score of LDA (R2 >0.97), showing good linear response characteristics within the test range.

[0080] Example 5. The experimental steps of Example 5 are repeated as in Example 1, with the only difference being that "in the preparation process of the Nd@Au NPs probe unit, the aqueous solution of neodymium chloride is replaced with an aqueous solution of europium chloride of the same molar concentration, and finally the Eu@AuNPs probe unit is obtained."

[0081] Example 5 The pH values ​​of four probe units, namely Cys@Au NPs, Eu@Au NPs, CTAB@Au NPs and THPB@Au NPs, were adjusted to 5.0, 5.0, 9.0 and 11.0, respectively, and the probe units were arranged in order in a 96-well plate to form a detection array.

[0082] The four probe units of Cys@Au NPs, Eu@Au NPs, CTAB@Au NPs, and THPB@Au NPs in Example 5 were used as array sensors to detect the LDA graphs of 11 different phosphorus species at a final concentration of 5.0 mg / L. The experimental process was similar to steps 2) to 3) in Example 1. The detection results at different characteristic wavelengths were analyzed using a pattern recognition algorithm to obtain the cumulative percentages of the first three principal components of the LDA, see Figure 6 Group B in .

[0083] Example 6. The experimental steps of Example 6 are repeated in Example 1, with the only difference being that: Example 7 uses three probe units, Nd@AuNPs, CTAB@Au NPs, and THPB@Au NPs, as array sensors to detect the LDA graphs of 11 different phosphorus species at a final concentration of 5.0 mg / L. The experimental process refers to steps 2) to 3) of Example 1. The detection results at different characteristic wavelengths are analyzed using a pattern recognition algorithm to obtain the cumulative percentages of the first three principal components of the LDA, see Figure 6 Group C in .

[0084] Figure 6 In group A, group B, and group C, the first column represents the first-dimensional principal component score of the LDA graph, the second column represents the sum of the first-dimensional principal component score and the second-dimensional principal component score of the LDA graph, and the third column represents the sum of the first-dimensional principal component score, the second-dimensional principal component score, and the third-dimensional principal component score of the LDA graph.

[0085] By comparing the cumulative percentages of the first three principal components of LDA, it can be seen that the cumulative values ​​of Group B and Group C are lower than those of Group A, indicating that the array sensor of the present invention has good centrality in distinguishing 11 types of phosphorus with little overlap, which is conducive to classification and has clear classification boundaries.

[0086] The above contents are merely several embodiments of the present invention and are not intended to limit the present invention in any form. It should be noted that for other persons skilled in the art, without departing from the concept and scope of the present invention, slight changes or modifications to the above disclosed technical contents are equivalent to equivalent implementation cases and fall within the scope of the technical solution.

Claims

1. A method for efficient and rapid identification of multiple forms of phosphorus in wastewater based on gold nanoarray sensors, characterized in that The gold nanoarray sensor includes four groups of functionalized gold nanoparticle probe units, which are composed of nanogold probes modified by four surface modifiers; The first unit is a gold nanoparticle probe modified with an amino / thiol bifunctional molecule, wherein the amino / carboxyl bifunctional molecule includes cysteamine hydrochloride; The second unit is a gold nanoparticle probe modified with rare earth metal ions, including neodymium ions; The third unit is a nano-gold probe modified with a quaternary ammonium surfactant, wherein the quaternary ammonium surfactant includes hexadecyltrimethylammonium bromide (CTAB); The fourth unit is a nano-gold probe modified with a quaternary phosphonium salt surfactant, wherein the quaternary phosphonium salt surfactant includes hexadecyltributylphosphonium bromide THPB; The method comprises the following steps: Step 1: For different forms of phosphorus compound standards, dissolve them in ultrapure water into a series of solutions with different concentrations to prepare the corresponding phosphorus standard solutions; Step 2: The phosphorus standard solution of step 1 is mixed with the four groups of functionalized gold nanoparticle probe units in the gold nanoarray sensor respectively, and after a specific reaction, multi-wavelength absorbance detection is performed. The detection signals of the four groups of functionalized gold nanoparticle probe units at multiple wavelengths are combined to form a response matrix, and analyzed using a pattern recognition algorithm to construct a cross-response fingerprint. Step 3: When performing phosphorus pollutant analysis and detection, according to the method of step 2, the test solution is specifically reacted with the four groups of functionalized gold nanoparticle probe units respectively, and then absorbance detection is performed according to the method of step 2. The analysis is performed using a pattern recognition algorithm and compared with the fingerprint map constructed in step 2 to obtain the phosphorus pollutant concentration and morphological characteristic information in the test solution.

2. The method according to claim 1, wherein The preparation methods of the first unit, the third unit and the fourth unit all include the following steps: S1: Under vigorous stirring conditions, haloauric acid solution was used as the gold source for gold nanoparticles, and three groups of haloauric acid solutions were set up; S2: adding three surface modifiers to three groups of haloauric acid solutions respectively, then adding a reducing agent solution, stirring and reacting at room temperature to completely convert the haloauric acid into gold nanoparticles; the three surface modifiers are cysteamine hydrochloride, hexadecyltrimethylammonium bromide (CTAB), and hexadecyltributylphosphonium bromide (THPB); S3: After the reaction is completed, the mixture is refrigerated and stored, and finally three groups of functionalized gold nanoparticle probe units are obtained; The preparation method of the second unit comprises the following steps: (1) Mixing the haloauric acid solution with the cysteine ​​solution, and then adding the reducing agent solution dropwise for reduction. After the addition is completed, the resulting colloidal solution is allowed to stand overnight to allow the haloauric acid to be completely converted into gold nanoparticles, thereby obtaining a cysteine-modified gold nanoparticle precursor; (2) Then, neodymium ions are added to the precursor solution of step (1) under stirring, and the mixture is stirred at room temperature to react to obtain gold nanoparticles functionalized with neodymium ions on the surface; (3) After the reaction is completed, the product is refrigerated and stored to finally functionalize the second unit of the gold nanoparticles.

3. The method according to claim 2, wherein The haloauric acid is fluoroauric acid, chloroauric acid or bromoauric acid; the reducing agent is at least one of sodium borohydride, trisodium citrate, ascorbic acid, hydroxylamine hydrochloride and potassium tartrate; In step S2 of preparing the first unit, the third unit, and the fourth unit, the stirring reaction time is 1.5-3 hours, and the molar ratios of the three surface modifiers to the haloauric acid are as follows: the molar ratio of cysteamine hydrochloride to the haloauric acid is 0.5-1.0:1, the molar ratio of hexadecyltrimethylammonium bromide (CTAB) to the haloauric acid is 0.05-0.1:1, and the molar ratio of hexadecyltributylphosphonium bromide (THPB) to the haloauric acid is 0.2-0.6:1; In step (1) of preparing the second unit, the molar ratio of cysteamine hydrochloride to haloauric acid is 0.002-0.005:1; in step (2), the molar ratio of neodymium ions to haloauric acid in step (1) is 0.001-0.003:1, and the stirring reaction time in step (2) is 1.5-3 hours.

4. The method according to claim 1, wherein In step 2, the reaction temperature is room temperature and the reaction time is 5-30 min; the pH values ​​used for detection of the four groups of functionalized gold nanoparticle probe units, the first unit, the second unit, the third unit and the fourth unit are 5.0±0.5, 5.0±0.5, 9.0±0.5 and 11.0±1.0 respectively.

5. The method according to claim 1, wherein The phosphorus compound standard in step 1 is selected from at least one of organic phosphonic acid, phosphate and inorganic phosphate compounds, and the selected phosphorus compound standard is the following 11 kinds: diethylenetriaminepentamethylenephosphonic acid, aminotrimethylenephosphonic acid, hydroxyethylidenediphosphonic acid, hexamethylenediaminetetramethylenephosphonic acid, 2-phosphonobutane-1,2,4-tricarboxylic acid, ethylenediaminetetramethylenephosphonic acid, triphenyl phosphate, tributyl phosphate, pyrophosphoric acid, disodium hydrogen phosphate, and polyphosphate.

6. The method according to claim 1, wherein The absorbance band in step 2 is within the range of 450-700 nm. The method for constructing a cross-response fingerprint map in step 2 is: after the specific reaction, use an enzyme reader to measure the absorbance value A of each reaction solution at a series of different characteristic wavelengths, and test the absorbance value A0 of each group of probe units under the same reaction conditions with an equal amount of ultrapure water as a blank control group at the corresponding characteristic wavelength, and use the relative change rate of the absorbance value A / A0 as the detection signal; thereby obtaining a multidimensional vector of the detection results of different groups of probe units at different characteristic wavelengths, and using a pattern recognition algorithm for analysis to obtain information about the concentration and morphology of the target, and constructing a cross-response fingerprint map.

7. The method according to claim 1, wherein The pattern recognition algorithm in step 2 includes processing the data using a statistical classification method of linear discriminant analysis (LDA), using the first three principal component scores processed by LDA as coordinate axes to construct a three-dimensional standard fingerprint library for phosphorus compound detection for qualitative classification of phosphorus compounds. In addition, a standard curve is drawn using the first dimension score of LDA as the ordinate and the concentration of the phosphorus compound as the abscissa for quantitative detection of phosphorus compounds.

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