Gold nano-array sensor and method for efficiently and rapidly identifying multi-element form of phosphorus in wastewater by using gold nano-array sensor

Abstract

The invention discloses a gold nano array sensor and a method for efficiently and rapidly identifying the multielement form of phosphorus in wastewater, the gold nano array sensor comprises four groups of functionalized gold nano particle probe units, and the functionalized gold nano particle probe units are composed of nanogold probes modified by four surface modifiers, the first unit is a nanogold probe modified by amino / sulfydryl bifunctional molecules, the second unit is a nanogold probe modified by rare earth metal ions, the third unit is a nanogold probe modified by a quaternary ammonium salt type surfactant, and the fourth unit is a nanogold probe modified by a quaternary phosphonium salt type surfactant. The gold nano array sensor disclosed by the invention is based on multi-wavelength detection, and realizes rapid identification and quantitative detection of different phosphorus forms in wastewater through qualitative and quantitative analysis of multi-dimensional data. The method does not need a complex pretreatment process, has the advantages of short detection time, simplicity and convenience in operation, high sensitivity, strong anti-interference capability and the like, and provides an innovative thought for the distinguishing and concentration detection combined analysis 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 particularly relates to a gold nanorod array sensor and a method for efficiently and rapidly identifying multiple forms of phosphorus in wastewater. Background Art

[0002] Phosphorus compounds are pollutants with significant environmental risks in industrial wastewater, mainly originating from industries such as pesticide production, flame retardant manufacturing, petroleum additives, and pharmaceuticals. When excessive phosphorus enters water bodies, it serves as the main limiting nutrient, leading to water eutrophication and triggering a series of ecological and environmental problems. Phosphorus discharged from wastewater treatment plants is the main source of phosphorus in various water bodies, and phosphorus mainly exists in inorganic and organic forms. Inorganic phosphorus is usually orthophosphate, while organic phosphorus mainly includes organophosphates and organophosphonates. Currently, relevant research mainly focuses on orthophosphate, and the attention to organic phosphorus and other forms of phosphorus is significantly insufficient. These phosphorus species generally have low occurrence concentrations, high chemical stability, and complex forms. Accurate monitoring and analysis are crucial for formulating effective phosphorus pollution control strategies. Therefore, developing efficient and convenient methods for identifying and differentiating organic phosphorus is the prerequisite and foundation for analyzing the advanced treatment technology of organic phosphorus in wastewater.

[0003] Identifying and differentiating multiple organic phosphorus with similar chemical structures is challenging. Currently, the detection technologies applied to organic phosphorus can generally be divided into two categories: one is conventional technologies, including gas chromatography - mass spectrometry (GC - MS), high - performance liquid chromatography (HPLC), and enzyme - linked immunosorbent assay (ELISA). These traditional technologies have high accuracy and sensitivity, but they are costly, time - consuming, and have complex sample pretreatment, and are not suitable for real - time and on - site detection. Therefore, developing simple, rapid, and sensitive organic phosphorus analysis methods has important environmental significance. In recent years, the colorimetric analysis method of pollutants based on the local surface plasmon resonance effect of gold nanoparticles (Au NPs) has attracted great interest from researchers, becoming a research hotspot in the current water quality analysis direction and has been used for the detection of simulated water samples or surface water bodies. In current research, gold nanoprobes can identify, semi - quantitatively analyze, and quantitatively analyze single components of many substances such as free heavy metal ions, anions, drug molecules, and biological small molecules. The colorimetric probes of Au NPs have many advantages in detection. The selectivity of the colorimetric method largely depends on the functionalization of Au NPs. Based on the changes in optical properties, aggregation, dispersion, and morphological changes are caused to achieve sensitive detection of target molecules. However, there are still challenges in the complexity of organic phosphorus, detecting multiple analytes at one time, and detection condition interference. The number of selectively detected analytes is still limited. Therefore, constructing a colorimetric analysis method for classifying and identifying organic phosphorus still poses a huge challenge.

[0004] Different from the traditional "lock and key" one-to-one sensing mode abandoned by the sensor array design, it is composed of a group of probe units with broad-spectrum interactive sensing. The detection method of simultaneous acquisition of multi-point and multi-information by the array greatly improves the detection throughput and analysis efficiency of multi-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 network (ANN) are used to extract and analyze the feature map, and the pattern recognition of different targets can be realized. It can simultaneously detect and identify multi-component analytes in complex mixtures, and has great potential for the rapid discrimination and analysis of multiple phosphorus forms in actual wastewater systems. In theory, it is more suitable for the analysis of various organic phosphates in real water bodies. However, there is currently no report on the qualitative discrimination and quantitative analysis of multiple phosphorus forms using an array sensor based on functionalized gold nanoparticles. Summary of the Invention

[0005] Aiming at the above-mentioned technical problems, the purpose of the present invention is to provide a gold nanorod array sensor and a method for its efficient and rapid recognition of multiple phosphorus forms in wastewater. The gold nanorod array sensor of the present invention has the dual functions of visual high-efficiency discrimination and quantitative analysis, can distinguish single phosphorus compounds, recognize multi-component phosphorus mixtures, and simultaneously realize the quantitative determination of the concentration of the target substance. According to multivariate statistical analysis, the type information (single or mixed) of phosphorus in wastewater and its corresponding concentration data can be obtained, and effective visual discrimination and quantitative analysis can be realized.

[0006] The technical solution adopted by the present invention is as follows: A gold nanorod array sensor, comprising 4 groups of functionalized gold nanoparticle probe units, which are composed of gold nanoparticle probes modified by 4 kinds of surface modifiers; The first unit is a gold nanoparticle probe modified by an amino / carboxyl bifunctional molecule; The second unit is a gold nanoparticle probe modified by a rare earth metal ion; The third unit is a gold nanoparticle probe modified by a quaternary ammonium salt surfactant; The fourth unit is a gold nanoparticle probe modified by a quaternary phosphonium salt surfactant.

[0007] Furthermore, the amino / carboxyl bifunctional molecule includes cysteamine hydrochloride, the rare earth metal ion includes neodymium ion, the quaternary ammonium salt surfactant includes cetyltrimethylammonium bromide CTAB, and the quaternary phosphonium salt surfactant includes cetyltributylphosphonium bromide THPB.

[0008] Furthermore, the preparation methods of the first unit, the third unit and the fourth unit all include the following steps: S1: Under the condition of vigorous stirring, the chloroauric acid solution is used as the gold source of gold nanoparticles, and 3 groups of chloroauric acid solutions are set; S2: Add the 3 kinds of surface modifiers into 3 groups of chloroauric acid solutions respectively, then add the reducing agent solution, and stir and react at room temperature to completely convert the chloroauric acid into gold nanoparticles; the 3 kinds of surface modifiers are cysteamine hydrochloride, cetyltrimethylammonium bromide CTAB, and cetyltributylphosphonium bromide THPB respectively; S3: After the reaction ends, store it refrigerated to finally obtain 3 groups of functionalized gold nanoparticle probe units.

[0009] Furthermore, in step S2 for preparing the first unit, the third unit, and the fourth unit, the stirring reaction time is 1.5 - 3 h, and the molar ratios of the 3 kinds of surface modifiers to chloroauric acid are as follows: the molar ratio of cysteamine hydrochloride to chloroauric acid is 0.5 - 1.0:1, the molar ratio of cetyltrimethylammonium bromide CTAB to chloroauric acid is 0.05 - 0.1:1, and the molar ratio of cetyltributylphosphonium bromide THPB to chloroauric acid is 0.2 - 0.6:1.

[0010] Furthermore, the preparation method of the second unit includes the following steps: (1) Mix the chloroauric acid solution with the cysteine solution, and then gradually add the reducing agent solution for reduction. After the addition is complete, let the obtained colloidal solution stand overnight to completely convert the chloroauric acid into gold nanoparticles, obtaining a cysteine-modified gold nanoparticle precursor; (2) Then, continue to add neodymium ions to the precursor solution in step (1) under stirring, and stir and react at room temperature to obtain neodymium ion surface-functionalized gold nanoparticles; (3) After the reaction ends, store it refrigerated to finally obtain the second unit of the functionalized gold nanoparticles.

[0011] Furthermore, in step (1) for preparing the second unit, the molar ratio of cysteamine hydrochloride to chloroauric acid is 0.002 - 0.005:1; in step (2), the molar ratio of neodymium ions to chloroauric acid in step (1) is 0.001 - 0.003:1, and the stirring reaction time in step (2) is 1.5 - 3 h.

[0012] According to the present invention, the chloroauric acid can be fluoroauric acid (HAuF4), chloroauric acid (HAuCl4), bromoauric acid (HAuBr4), etc. Compared with other chloroauric acids, considering chemical stability, reduction efficiency, and cost-effectiveness, the present invention preferably uses chloroauric acid (HAuCl4) as the synthesis raw material for gold nanoparticles.

[0013] According to the present invention, the selection range of the reducing agent includes but is not limited to: sodium borohydride (NaBH4), trisodium citrate (Na3C6H5O7), ascorbic acid, hydroxylamine hydrochloride, or potassium tartrate. Compared with other reducing agents, considering reducibility, complete reaction, and few by-products, the present invention preferably uses sodium borohydride as the reducing agent.

[0014] The present invention also discloses an application of a gold nanorod array sensor in the efficient and rapid identification and detection of multiple phosphorus species in wastewater.

[0015] The present invention also discloses a method for the efficient and rapid identification of multiple phosphorus species in wastewater based on a gold nanorod array sensor, comprising the following steps: Step 1: For standard phosphorus compound samples of different forms, they are respectively dissolved in ultrapure water to form a series of solutions with different concentrations, and corresponding phosphorus standard solutions are prepared. Step 2: The phosphorus standard solutions in Step 1 are respectively mixed with 4 groups of functionalized gold nanoparticle probe units in the gold nanorod array sensor. After specific reactions, multi-wavelength absorbance detection is carried out. The detection signals of the 4 groups of functionalized gold nanoparticle probe units at multiple wavelengths are combined to form a response matrix, and pattern recognition algorithms are used for analysis to construct a cross-response fingerprint spectrum. Step 3: When analyzing and detecting phosphorus pollutants, according to the method in Step 2, the test solution is respectively subjected to specific reactions with the 4 groups of functionalized gold nanoparticle probe units, and then absorbance detection is carried out according to the method in Step 2. Pattern recognition algorithms are used for analysis and compared with the fingerprint spectrum constructed in Step 2, and the concentration and morphological characteristic information of phosphorus pollutants in the test solution can be obtained.

[0016] Further, in Step 2, the reaction temperature is room temperature, and the reaction time is 5 - 30 min; for the 4 groups of functionalized gold nanoparticle probe units, the pH values for detection of 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.

[0017] Further, the phosphorus compound standard samples in Step 1 are selected from at least one of organic phosphonic acids, phosphate esters, and inorganic phosphate compounds, and the selected phosphorus compound standard samples are the following 11 kinds: diethylenetriamine pentamethylenephosphonic acid, aminotrimethylenephosphonic acid, hydroxyethane diphosphonic acid, hexamethylenediamine tetramethylenephosphonic acid, 2-phosphonobutane-1,2,4-tricarboxylic acid, ethylenediamine tetramethylenephosphonic acid, triphenyl phosphate, tributyl phosphate, pyrophosphoric acid, disodium hydrogen phosphate, and polyphosphate.

[0018] Further, the wavelength range of the absorbance in Step 2 is within 450 - 700 nm, and the present invention focuses on selecting six characteristic wavelengths of 450, 520, 560, 600, 650, and 700 nm.

[0019] Furthermore, the method for constructing a cross-response fingerprint in step 2 is: after the specific reaction, using an enzyme reader to determine the absorbance value A of each reaction liquid at a series of different characteristic wavelengths, and testing 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 taking the relative change rate A / A0 of the absorbance value 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.

[0020] 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 for qualitative classification of phosphorus compounds, and in addition using the first dimension score of LDA as the ordinate and the concentration of the phosphorus compound as the abscissa to draw a standard curve for quantitative detection of phosphorus compounds.

[0021] According to the present invention, the preferred method for constructing the cross-response fingerprint of the array sensor is as follows: 4 groups of gold nanoprobes are used to react with the target for 20 minutes respectively, and then the absorbance at six characteristic wavelengths of 450 nm, 520 nm, 560 nm, 600 nm, 650 nm and 700 nm is measured by using an enzyme reader. The ratio (A / A0) of the sample absorbance (A) and the absorbance (A0) of the ultrapure water blank control group at each wavelength is used as the detection signal, and the normalized absorbance ratio (A / A0) can eliminate background interference, calculate the relative change rate of absorbance, and finally form a 4×6-dimensional response matrix by using multi-probe units (4 types) and multi-wavelengths (6) for coordinated detection, and use linear discriminant analysis LDA for processing to construct a cross-response fingerprint.

[0022] 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 visual distinction and accurate identification of organic phosphorus multi-component mixtures with different proportions.

[0023] 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 sample to be tested, thereby achieving quantitative analysis of phosphorus in wastewater.

[0024] Compared with the prior art, the technical innovation and advantages of the present invention can be summarized as follows: 1) In the present invention, 11 target phosphorus compounds produce specific interaction fingerprints with 4 groups of functionalized gold nanoprobe, constructing a variety of recognition cooperative interfaces including coordination bonding, electrostatic interaction and hydrophobic effect, inducing different degrees of aggregation of gold nanoparticles, and the array sensor exhibits cross-response characteristics accordingly. The change rate of absorbance of the probe unit before and after the reaction is used as the response value, and multivariate statistical methods such as hierarchical cluster analysis (HCA) and linear discriminant analysis (LDA) are used to analyze the data. This analysis system is verified by multi-algorithm collaboration, ensuring the reliability of the recognition results of multi-form phosphorus. To explore the recognition and detection capabilities of the array for target analytes. The LDA algorithm reduces the original data to a 3D feature space. In the 3D space diagram, parallel samples of the same organophosphorus can be significantly aggregated, and different organophosphorus analytes can be effectively separated, indicating that the present invention has obvious recognition and discrimination effects on multi-form phosphorus. In the HCA analysis, a dendrogram is obtained by classifying different organophosphorus based on the average Euclidean distance of the data, and the classification results of the Euclidean distance matrix are consistent with the LDA spatial distribution. This reflects the innovative architecture of multi-probe design - cooperative recognition - intelligent analysis, realizing the differentiation of organophosphorus compounds in complex matrices.

[0025] 2) The present invention can effectively detect different phosphorus compounds at low concentrations, with high sensitivity, strong recognition ability, short detection time and simple operation. At the same time, the present invention can realize the quantitative analysis of multi-form phosphorus by fitting the score of the first principal component of LDA with the concentration of phosphorus compounds. By innovatively combining nanosensing and pattern recognition algorithms, the present invention realizes the rapid and accurate quantification of different phosphorus compound pollutants, converting complex chemical recognition into a quantifiable mathematical discriminant model, and can also perform recognition and detection in complex mixed systems.

[0026] 3) The present invention still maintains good specificity under the conditions of common ions in water bodies. Tests with common cations and anions in water bodies show that they will not cause significant interference to the detection results. The interference of the gold nanorod array sensor is small and almost negligible, which also shows that the present invention has good anti-ion interference ability and specific recognition performance, and has high selectivity for different phosphorus compounds.

[0027] 4) The present invention uses a surface-functionalized gold nanorod array as a sensing platform, constructs a fingerprint recognition database by capturing the characteristic response signals of multi-form phosphorus, and realizes the rapid recognition and accurate quantification of phosphorus compound pollutants. Brief Description of the Drawings

[0028] Figure 1 It is the LDA diagram of 11 different phosphorus with a final concentration of 5.0 mg / L by the array sensor of the present invention.

[0029] Figure 2It is the HCA graph of 11 different phosphorus species with a final concentration of 5.0 mg / L by the array sensor of the present invention.

[0030] Figure 3 It is the LDA graph of the mixed sample of PBTC and HDTMP with a final concentration of 20.0 mg / L by the array sensor of the present invention.

[0031] Figure 4a It is the absorbance response results of the Cys@Au NPs probe unit of the present invention for the detection of 11 phosphorus compounds with a final concentration of 5.0 mg / L and common interfering ions respectively.

[0032] Figure 4b It is the absorbance response results of the Nd@Au NPs probe unit of the present invention for the detection of 11 phosphorus compounds with a final concentration of 5.0 mg / L and common interfering ions respectively.

[0033] Figure 4c It is the absorbance response results of the CTAB@Au NPs probe unit of the present invention for the detection of 11 phosphorus compounds with a final concentration of 5.0 mg / L and common interfering ions respectively.

[0034] Figure 4d It is the absorbance response results of the THPB@Au NPs probe unit of the present invention for the detection of 11 phosphorus compounds with a final concentration of 5.0 mg / L and common interfering ions respectively.

[0035] Figure 5a It is the standard curve of the array sensor of the present invention for the detection of the phosphorus compound standard PA.

[0036] Figure 5b It is the standard curve of the array sensor of the present invention for the detection of the phosphorus compound standard DP.

[0037] Figure 5c It is the standard curve of the array sensor of the present invention for the detection of the phosphorus compound standard NTMP.

[0038] Figure 6 It is the cumulative percentage of the first three dimensions of the LDA principal components of the LDA graphs of different groups of array sensors for the detection of 11 different phosphorus species with a final concentration of 5.0 mg / L. Detailed implementation manners

[0039] The present invention will be further described below by combining specific examples. It should be noted that the experimental methods not specifically specified in the examples are carried out under conventional experimental conditions, and the reagents and materials used can be obtained through commercial channels without special instructions.

[0040] The 11 phosphorus-containing compounds in the embodiments of the present invention are respectively: diethylenetriamine pentamethylenephosphonic acid (DTPMP), aminotrimethylenephosphonic acid (ATMP), hydroxyethane-1,1-diphosphonic acid (HEDP), hexamethylenediamine tetramethylenephosphonic acid (HDTMP), 2-phosphonobutane-1,2,4-tricarboxylic acid (PBTC), ethylenediamine tetramethylenephosphonic acid (EDTMP), triphenyl phosphate (DPP), tributyl phosphate (DP), pyrophosphoric acid (PPi), disodium hydrogen phosphate (PA), and polyphosphate (PPA).

[0041] Example 1: Based on the background of a pure water environment, a method for distinguishing and detecting 11 phosphorus-containing compounds was established. The specific implementation steps are as follows: 1) Construct a gold nanoparticle probe unit array: Mix 5.0 mL of 5.0 mmol / L chloroauric acid aqueous solution with each of the 3 surface functionalization modifiers, namely cysteamine hydrochloride, CTAB, and THPB. The amounts and concentrations of the 3 surface functionalization modifiers added are: 4.0 mL of 5.0 mmol / L cysteine aqueous solution, 1.0 mL of 1.0 mmol / L CTAB aqueous solution, and 1.0 mL of 10.0 mmol / L THPB aqueous solution. Add ultrapure water to make the total volume reach 100 mL, and gradually add 2.0 mL of 0.1 mol / L sodium borohydride solution for reduction. The color of the solution gradually changes from light yellow to orange-red to wine-red. Stir vigorously and react at room temperature for 2 hours. Finally, obtain the three surface-functionalized gold nanoparticles of cysteamine hydrochloride, CTAB, and THPB.

[0042] Mix the chloroauric acid aqueous solution (97 mL, 1.4 mM) with cysteine (1 mL, 0.5 mM) evenly for 10 minutes, and then gradually add 2.0 mL of freshly prepared 0.1 mol / L sodium borohydride solution for reduction. Let the colloidal solution stand overnight. Add 200 μL of 1.0 mmol / L neodymium chloride aqueous solution, stir vigorously and react at room temperature for 2 hours. Finally, obtain neodymium ion surface-functionalized gold nanoparticles.

[0043] According to the above method, obtain four functionalized gold nanoparticle probes, namely Cys@Au NPs, Nd@Au NPs, CTAB@Au NPs, and THPB@Au NPs, to form the array sensor of the present invention.

[0044] Adjust the pH values of the Cys@Au NPs, Nd@Au NPs, CTAB@Au NPs, and THPB@Au NPs probe units to 5.0, 5.0, 9.0, and 11.0 respectively, and arrange the probe units in an orderly manner in a 96-well plate to form a detection array.

[0045] 2) Establishment of a standard database: Step S1: The phosphorus compound standard is prepared into an initial concentration solution of 50.0 mg / L with ultrapure water, denoted as the phosphorus standard solution, and ultrapure water is used as the blank control. The phosphorus standard solution and each probe unit are mixed respectively according to a volume ratio of 1:9 to obtain a reaction system of phosphorus standard with a final concentration of 5.0 mg / L. After reacting at room temperature for 20 minutes, the absorbance values A at six characteristic wavelengths of 450, 520, 560, 600, 650, and 700 nm are measured using an enzyme-linked immunosorbent assay (ELISA) reader. And the absorbance value A0 of each group of probe units at the corresponding characteristic wavelength under the same reaction conditions with an equal amount of ultrapure water as the blank control group is measured.

[0046] Step S2: Four functionalized gold nanoprobe and six characteristic wavelengths are used for co-detection to finally form a 4×6-dimensional response matrix data. By calculating the ratio of the absorbance of the sample to the blank control (A / A0) at each wavelength, that is, the relative change rate of absorbance as the response signal, the response signal data of the 4×6-dimensional response matrix is obtained.

[0047] 3) According to the processes of the above steps 1)-2), when the phosphorus compound standard is respectively 11 kinds of phosphorus compounds such as diethylenetriamine pentamethylenephosphonic acid (DTPMP), aminotrimethylenephosphonic acid (ATMP), hydroxyethane-1,1-diphosphonic acid (HEDP), hexamethylenediamine tetramethylenephosphonic acid (HDTMP), 2-phosphonobutane-1,2,4-tricarboxylic acid (PBTC), ethylenediamine tetramethylenephosphonic acid (EDTMP), triphenyl phosphate (DPP), tributyl phosphate (DP), pyrophosphoric acid (PPi), disodium hydrogen phosphate (PA), and polyphosphate (PPA), the response signal data of the obtained 4×6-dimensional response matrix is respectively processed using linear discriminant analysis (LDA), and with the scores of the first three principal components as the coordinate axes, a three-dimensional standard fingerprint library with a final concentration of 5.0 mg / L is constructed. The results are as Figure 1 shown. Figure 1 In the method, the LDA method is used to reduce the dimensionality of multi-dimensional data and visually classify different analytes, realizing the clustering and differentiation of different phosphorus compounds in three-dimensional space.

[0048] According to Figure 1 , the LDA diagrams 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 with a final concentration of 5.0 mg / L, and the cumulative percentage results of the first three principal components of the LDA diagrams are shown in Figure 6 group A in.

[0049] And the response signal data of the obtained 4×6-dimensional response matrix is respectively processed using hierarchical clustering analysis (HCA), and the Euclidean square distance between samples is calculated to construct a dendrogram. The results are as Figure 2 shown. Figure 2The results further verified the effectiveness of clustering.

[0050] Example 2: The experimental procedure of Example 2 was repeated for 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 was 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 was in the range of 1:9 to 9:1. The other conditions remained unchanged. Finally, the response signal data was processed using linear discriminant analysis (LDA), and the scores of the first three principal components were used as the coordinate axes to construct a three-dimensional standard fingerprint library for the PBTC-HDTMP mixed phosphorus sample with a final concentration of 20.0 mg / L. The results are as Figure 3 shown.

[0051] It can be seen from Figure 3 that a certain degree of discrimination can also be maintained for the mixtures of various organophosphorus at different concentrations.

[0052] Example 3: The experimental procedure of constructing the gold nanoparticle probe unit array in Example 3 was repeated for Example 1. The pH values 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 each probe unit was arranged in an orderly manner in a 96-well plate to form a detection array.

[0053] Example 3 tested the response signals of different probe units to different substances: Step A: Testing the response signals for the detection of heteroions: Prepare an aqueous solution of heteroions, and mix the aqueous solution of heteroions with each probe unit according to a volume ratio of 1:9 to form a reaction system of heteroions. After reacting at room temperature for 20 minutes, use an enzyme-linked immunosorbent assay (ELISA) reader to measure the absorbance values at two characteristic wavelengths of 520 nm and 650 nm. Calculate the ratio A 650 / A 520 of the absorbance at 650 nm to the absorbance at 520 nm for the reaction system of each group of probe units with respect to the heteroions, and calculate the ratio A 650 0 / A 520 0 .

[0054] Step B. Test the response signal for the detection of phosphorus compounds: The phosphorus compound is prepared into an initial concentration solution of 50.0 mg / L with ultrapure water, denoted as the phosphorus compound solution, and ultrapure water is used as the blank control. The phosphorus compound solution and each probe unit are mixed respectively according to a volume ratio of 1:9 to obtain a reaction system of phosphorus standard with a final concentration of 5.0 mg / L. After reacting at room temperature for 20 minutes, the absorbance values at two characteristic wavelengths of 520 nm and 650 nm are measured using a microplate reader. Calculate the ratio A of the absorbance of the reaction system of each probe unit to the phosphorus compound at a wavelength of 650 nm to the absorbance at a wavelength of 520 nm. 650 / A 520 And calculate the ratio A of the absorbance of each probe unit at a wavelength of 650 nm to the absorbance at a wavelength of 520 nm with an equal amount of ultrapure water as the blank control group under the same reaction conditions. 650 0 / A 520 0 。

[0055] According to the experimental procedure of the response signal for the detection of miscellaneous ions in Step A above, the miscellaneous ions are K + 、Na + 、Mg 2+ 、Ca 2+ 、Cu 2+ 、Zn 2+ 、Cd 2+ 、Ni 2+ 、Pb 2+ 、Cr 3+ or Fe 3+ cations, and the anions they bind are all Cl - , and the final concentration of the miscellaneous ion cations in the reaction system is 0.1 mM. Using the difference in absorbance ratio A 650 / A 520 -A 650 0 / A 520 0 measured in the experimental procedure of Example 3 Step A as the ordinate and the specific type of the miscellaneous ion cations as the abscissa to plot a graph.

[0056] According to the experimental procedure of the response signal for the detection of miscellaneous ions in Step A above, the miscellaneous ions are Cl - 、NO3 - 、SO4 2- or CO3 2- anions, and the cations they bind are all Na + , and the final concentration of the miscellaneous ion anions in the reaction system is 0.1 mM. Using the difference in absorbance ratio A 650 / A 520 -A650 0 / A 520 0 Using the specific type of heteroionic anion as the ordinate and the specific type of phosphorus compound as the abscissa, plot a graph.

[0057] According to the experimental process of the response signal for the detection of phosphorus compounds in step B above, taking the difference in absorbance ratio A tested in the experimental process of step B of Example 3 650 / A 520 -A 650 0 / A 520 0 Using the specific type of phosphorus compound as the ordinate and the specific type of phosphorus compound as the abscissa, plot a graph.

[0058] According to the above process, for the four groups of probe units of Cys@Au NPs, Nd@Au NPs, CTAB@Au NPs, and THPB@Au NPs, the response data for the detection of 11 phosphorus compounds with a final concentration of 5.0 mg / L and in the presence of common heteroions are shown in Figure 4a , Figure 4b , Figure 4c and Figure 4d respectively. It can be seen that the response signals of the four groups of probe units of the present invention for the detection of common heteroions with a concentration of 0.1 mM are all very low, while the response signals for the detection of 11 phosphorus compounds with a final concentration of 5.0 mg / L all maintain good specificity. Therefore, the presence of common cations and anions in water will not cause significant interference to the detection results of the present invention.

[0059] In Example 4, the experimental steps of Example 4 were repeated, with the only difference being that "in S1 of step 2), the final concentration of the phosphorus compound standard in the reaction system was changed", and the other conditions remained unchanged.

[0060] Using the first-dimensional score of LDA as the ordinate and the concentration of the phosphorus compound as the abscissa, plot a standard curve. The standard curves for the detection of different phosphorus compound standards PA, DP, and NTMP by the array sensor of the present invention are shown in Figure 5a , Figure 5b and Figure 5c respectively. From Figure 5a - Figure 5c it can be seen that when the content of the phosphorus compound standard is 2.0 - 15.0 mg / L, there is an excellent linear relationship between its concentration and the first-dimensional score of LDA (R 2 > 0.97), showing good linear response characteristics within the test range.

[0061] Example 5. The experimental procedure of Example 5 was repeated as in Example 1, except that "in the preparation process of the Nd@Au NPs probe unit, the neodymium chloride aqueous solution was replaced with an aqueous europium chloride solution of the same molar concentration, and finally the Eu@Au NPs probe unit was obtained".

[0062] In Example 5, the pH values of the four probe units, 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 each probe unit was arranged in an orderly manner in a 96-well plate to form a detection array.

[0063] The four probe units, Cys@Au NPs, Eu@Au NPs, CTAB@Au NPs, and THPB@Au NPs, in Example 5 were used as an array sensor to detect the LDA diagrams of 11 different phosphorus species at a final concentration of 5.0 mg / L. The experimental procedure referred to steps 2)-3) of Example 1. Through the detection results at different characteristic wavelengths, pattern recognition algorithms were used for analysis to obtain the cumulative percentage of the first three-dimensional principal components of LDA, as shown in Figure 6 Group B in.

[0064] Example 6. The experimental procedure of Example 6 was repeated as in Example 1, except that: In Example 7, three probe units, Nd@Au NPs, CTAB@Au NPs, and THPB@Au NPs, were used as an array sensor to detect the LDA diagrams of 11 different phosphorus species at a final concentration of 5.0 mg / L. The experimental procedure referred to steps 2)-3) of Example 1. Through the detection results at different characteristic wavelengths, pattern recognition algorithms were used for analysis to obtain the cumulative percentage of the first three-dimensional principal components of LDA, as shown in Figure 6 Group C in.

[0065] Figure 6 In Group A, Group B, and Group C in, the first column represents the score of the first-dimensional principal component of the LDA diagram, the second column represents the sum of the scores of the first-dimensional principal component and the second-dimensional principal component of the LDA diagram, and the third column represents the sum of the scores of the first-dimensional principal component, the second-dimensional principal component, and the third-dimensional principal component of the LDA diagram.

[0066] By comparing the magnitudes of the cumulative percentages of the first three-dimensional principal components of LDA, it can be seen that the cumulative values of Group B and Group C are not as good as those of Group A, indicating that the array sensor of the present invention has good discrimination concentration and small overlap for 11 phosphorus species, is conducive to classification and has clear classification boundaries.

[0067] The above - described content is only several embodiments of the present invention and does not impose any form of limitation on the present invention. It should be noted that for other persons in the art, without departing from the concept and scope of the present invention, making some changes or modifications to the above - disclosed technical content is equivalent to equivalent implementation cases and all fall within the scope of the technical solution.

Claims

1. A gold nanorod array sensor, characterized in that It includes 4 groups of functionalized gold nanoparticle probe units, which are composed of gold nanoprobes modified by 4 kinds of surface modifiers; The first unit is a gold nanoprobe modified by an amino / thiol bifunctional molecule; The second unit is a gold nanoprobe modified by a rare earth metal ion; The third unit is a gold nanoprobe modified by a quaternary ammonium salt surfactant; The fourth unit is a gold nanoprobe modified by a quaternary phosphonium salt surfactant.

2. The gold nanoarray sensor according to claim 1, characterized in that The amino / carboxyl bifunctional molecule includes cysteamine hydrochloride, the rare earth metal ion includes neodymium ion, the quaternary ammonium salt surfactant includes cetyltrimethylammonium bromide CTAB, and the quaternary phosphonium salt surfactant includes cetyltributylphosphonium bromide THPB.

3. The gold nanoarray sensor according to claim 2, wherein The preparation methods of the first unit, the third unit and the fourth unit all include the following steps: S1: Under the condition of vigorous stirring, a chloroauric acid solution is used as the gold source of gold nanoparticles, and 3 groups of chloroauric acid solutions are set; S2: Add 3 kinds of surface modifiers to 3 groups of chloroauric acid solutions respectively, and then add a reducing agent solution, and stir and react at room temperature to completely convert the chloroauric acid into gold nanoparticles; the 3 kinds of surface modifiers are cysteamine hydrochloride, cetyltrimethylammonium bromide CTAB and cetyltributylphosphonium bromide THPB respectively; S3: After the reaction is completed, store it refrigerated to finally obtain 3 groups of functionalized gold nanoparticle probe units; The preparation method of the second unit includes the following steps: (1) Mix the chloroauric acid solution with the cysteine solution, and then dropwise add the reducing agent solution for reduction. After the addition is completed, let the obtained colloidal solution stand overnight to completely convert the chloroauric acid into gold nanoparticles, and obtain a cysteine-modified gold nanoparticle precursor; (2) Then continue to add neodymium ions to the precursor solution in step (1) under stirring, and stir and react at room temperature to obtain neodymium ion surface-functionalized gold nanoparticles; (3) After the reaction is completed, store it refrigerated to finally obtain the second unit of functionalized gold nanoparticles.

4. The gold nanorod array sensor according to claim 3, wherein The chloroauric 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 h, and the molar ratios of the 3 kinds of surface modifiers to chloroauric acid are as follows: the molar ratio of cysteamine hydrochloride to chloroauric acid is 0.5 - 1.0:1, the molar ratio of cetyltrimethylammonium bromide CTAB to chloroauric acid is 0.05 - 0.1:1, and the molar ratio of cetyltributylphosphonium bromide THPB to chloroauric acid is 0.2 - 0.6:1; In step (1) of preparing the second unit, the molar ratio of cysteamine hydrochloride to chloroauric acid is 0.002 - 0.005:1; in step (2), the molar ratio of neodymium ion to chloroauric acid in step (1) is 0.001 - 0.003:1, and the stirring reaction time in step (2) is 1.5 - 3 h.

5. Application of a gold nanoarray sensor as described in claim 1 in the efficient and rapid identification and detection of phosphorus multiple forms in wastewater.

6. A method for the efficient and rapid identification of multiple phosphorus species in wastewater based on a gold nanorod array sensor, characterized in that It includes the following steps: Step 1: For standard phosphorus compound samples in different forms, dissolve them in ultrapure water respectively to form a series of solutions with different concentrations, and prepare corresponding phosphorus standard solutions. Step 2: Mix the phosphorus standard solutions in Step 1 with the 4 groups of functionalized gold nanoparticle probe units in the gold nanorod array sensor described in Claim 1 respectively. After specific reactions, perform multi-wavelength absorbance detection. Combine the detection signals of the 4 groups of functionalized gold nanoparticle probe units at multiple wavelengths to form a response matrix, and use pattern recognition algorithms for analysis to construct a cross-response fingerprint spectrum. Step 3: When analyzing and detecting phosphorus pollutants, according to the method in Step 2, perform specific reactions between the solution to be measured and the 4 groups of functionalized gold nanoparticle probe units respectively. Then, perform absorbance detection according to the method in Step 2, use pattern recognition algorithms for analysis, and compare with the fingerprint spectrum constructed in Step 2 to obtain the concentration and morphological characteristic information of phosphorus pollutants in the solution to be measured.

7. The method according to claim 6, wherein In Step 2, the reaction temperature is room temperature, and the reaction time is 5 - 30 min; for the 4 groups of functionalized gold nanoparticle probe units, the pH values for detection of 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.

8. The method according to claim 6, wherein The phosphorus compound standard samples in Step 1 are selected from at least one of organic phosphonic acids, phosphate esters, and inorganic phosphate compounds. The selected phosphorus compound standard samples are the following 11 kinds: diethylenetriamine pentamethylenephosphonic acid, aminotrimethylenephosphonic acid, hydroxyethane diphosphonic acid, hexamethylenediamine tetramethylenephosphonic acid, 2-phosphonobutane-1,2,4-tricarboxylic acid, ethylenediamine tetramethylenephosphonic acid, triphenyl phosphate, tributyl phosphate, pyrophosphoric acid, disodium hydrogen phosphate, and polyphosphate.

9. The method according to claim 6, wherein In Step 2, the absorbance band is in the range of 450 - 700 nm. The method for constructing the cross-response fingerprint spectrum in Step 2 is as follows: after specific reactions, use an enzyme-linked immunosorbent assay (ELISA) reader to measure the absorbance value A of each reaction solution at a series of different characteristic wavelengths, and measure the absorbance value A0 of each group of probe units at the corresponding characteristic wavelength with equal amounts of ultrapure water as the blank control group under the same reaction conditions. Use the relative change rate of absorbance value A / A0 as the detection signal; thus, obtain the multi-dimensional vectors of the detection results of different groups of probe units at different characteristic wavelengths, use pattern recognition algorithms for analysis, obtain information about the concentration and form of the target substance, and construct a cross-response fingerprint spectrum.

10. The method according to claim 6, characterized in that The pattern recognition algorithm in Step 2 includes using a statistical classification method of linear discriminant analysis (LDA) to process the data. Use the scores of the first three principal components processed by LDA as the coordinate axes to construct a three-dimensional standard fingerprint spectrum library for the detection of phosphorus compounds for qualitative classification of phosphorus compounds. In addition, use the score of the first dimension of LDA as the ordinate and the concentration of phosphorus compounds as the abscissa to draw a standard curve for quantitative detection of phosphorus compounds.

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