Method and system for recognizing heavy metal ions and application thereof

Abstract

The application provides a heavy metal ion recognition method and a recognition system, a fluorescence sensing array is constructed according to Si points, the Si points have two emission centers; and heavy metal ions are recognized according to the fluorescence sensing array, the heavy metal ions are at least one kind, two Si points with similar Stokes shift emission centers are prepared, and two emission peaks are generated at 424nm and 517nm based on synchronous fluorescence. The combination ability of the -OH and -NH2 groups on the surface of the Si points to metal ions is different, so that the independent response of the two emission peaks is caused. The change of the two emission signals is processed into a unique 'fingerprint' by LDA, a metal ion sensing array is generated, and a plurality of heavy metal ions can be effectively recognized. As an attempt to explore a multi-target sensing array platform, the system provides a very valuable practical case for the field of simulation recognition and environmental monitoring.

Description

Technical Field

[0001] This application relates to the field of environmental monitoring technology, and in particular to a method, system and application for identifying heavy metal ions. Background Technology

[0002] Various transition metal ions, including Mn 2+ Fe 2+ / Fe 3+ Co 2+ Ni 2+ Cu 2+ and Zn 2+ Fe is an essential component of enzymes or pigments and plays a vital role in various human activities, such as enzyme-catalyzed reactions, gene transcription, and neurotransmission. Imbalances in these metal ions within the body can lead to various diseases. For example, the occurrence and development of Alzheimer's disease are related to Fe in the brain. 3+ Co 2+ Cu 2+ and Zn 2+ This is related to the imbalance. Furthermore, due to the rapid development of various industries such as metal manufacturing, papermaking, and mining, heavy metal ions are continuously released into the environment. Heavy metal ions are non-biodegradable and exhibit a trend of bioaccumulation and biomagnification in the food chain. Pollutants containing multiple heavy metal ions have synergistic effects and exhibit higher toxicological effects. These issues have prompted researchers to design various sensors aimed at simultaneously detecting and identifying metal ions with similar properties.

[0003] Atomic absorption spectroscopy, X-ray fluorescence spectroscopy, and inductively coupled plasma spectroscopy are the most commonly used and sensitive methods for metal detection. However, they also have limitations, such as time requirements, high cost, and reliance on specialized operators. In recent years, nanosensors have been widely used in metal detection due to their high sensitivity, ease of operation, low cost, and rapid response. These nanosensors can specifically detect individual metal ions, exhibiting high specificity. However, due to the limited acceptors of nanoparticles, one-to-many ion sensing systems are not common. Furthermore, to obtain a sufficiently specific response, metal ion sensing arrays typically require various nanomaterials or rely on multiple optical signals, which undoubtedly severely limits the sensor's sensitivity, response speed, and detection cost. Summary of the Invention

[0004] Therefore, it is necessary to provide a method, system and application for identifying heavy metal ions that has high detection sensitivity, fast speed and can realize the simultaneous detection of multiple heavy metal ions, addressing the shortcomings of existing technologies that cannot simultaneously detect multiple heavy metal ions and have poor sensitivity and response speed.

[0005] To solve the above problems, this application adopts the following technical solution:

[0006] One of the objectives of this application is to provide a method for identifying heavy metal ions, comprising the following steps:

[0007] A fluorescence sensing array is constructed based on Si points, wherein each Si point has two emission centers;

[0008] The heavy metal ions are identified based on the fluorescence sensing array, wherein the heavy metal ions are at least one type.

[0009] In some embodiments, the step of constructing the fluorescence sensing array based on Si points specifically includes the following steps:

[0010] After adding the Si point and the heavy metal ions to the buffer solution and incubating at room temperature, the fluorescence spectrum of the Si point was recorded.

[0011] Multiple parallel experiments were conducted based on the number of heavy metal ions to obtain a training data matrix.

[0012] The training data matrix is ​​processed and grouped to convert changes in fluorescence signals into "fingerprints" and "Euclidean distances," thereby generating a fluorescence sensing array.

[0013] In some embodiments, the Si points are prepared by the following method in the step of recording the fluorescence spectrum of the Si points after incubating the Si points and the heavy metal ions in a buffer solution at room temperature:

[0014] Mix 100-400 μL of phenyl acetate with 100-400 μL of DAMO, then add 300-1200 μL of ddH2O to obtain a mixed solution;

[0015] After transferring the mixed solution to a glass bottle in a microwave synthesizer, pre-stir for 1-5 min and react at 100-200℃ for 5-30 min;

[0016] The Si point mixture was mixed with acetonitrile at a volume ratio of 1:1 to 1:4, centrifuged at 8000 rpm for 10-30 min, then the precipitate was washed twice with acetonitrile and dried at 50-80℃ for 30 h to obtain Si point crystals. The obtained product was stored at 4℃ to obtain the Si points.

[0017] In some embodiments, in the step of recording the fluorescence spectrum of the Si point after incubating the Si point and the heavy metal ions in a buffer solution at room temperature, the steady-state fluorescence spectrum of the Si point has two emission centers at 424 nm and 517 nm, and its fluorescence intensity reaches its maximum value when the excitation wavelengths are 340 nm and 430 nm, respectively.

[0018] In some embodiments, the heavy metal ions include Fe. 2+ Fe 3+ Cu 2+ Co 2+ Ni 2+ Zn 2+ and Mn 2+ .

[0019] In some embodiments, the step of performing multiple parallel experiments based on the number of heavy metal ions to obtain a training data matrix specifically includes the following steps:

[0020] Five parallel experiments were conducted for each of the seven individual heavy metal ions, resulting in a training data matrix with two emission channels × seven metal ions × five repetitions.

[0021] In some embodiments, the steps of processing and grouping the data in the training data matrix, converting changes in fluorescence signals into "fingerprints" and "Euclidean distances," and generating a fluorescence sensing array specifically include the following steps:

[0022] The training data matrix was processed and grouped using linear discriminant analysis and hierarchical clustering analysis. "Fingerprints" and "Euclidean distances" were obtained using IBM SPSS Statistical 27.0 software, and the data was processed using GraphPad Prism 8.0 software to generate a fluorescence sensor array.

[0023] A second objective of this application is to provide a heavy metal ion identification system, comprising:

[0024] A fluorescence sensing array unit is used to construct a fluorescence sensing array based on Si points, wherein each Si point has two emission centers;

[0025] The identification unit is used to identify heavy metal ions based on the fluorescence sensing array, wherein the heavy metal ions are at least one type.

[0026] A third objective of this application is to provide an application of the aforementioned heavy metal ion identification system in environmental monitoring.

[0027] The present application adopts the above technical solution, and its beneficial effects are as follows:

[0028] This application provides a method and system for identifying heavy metal ions. A fluorescence sensing array is constructed based on Si points, each Si point having two emission centers. The array identifies heavy metal ions, at least one of which is present. This invention prepares two Si points with emission centers having similar Stokes shifts, and generates two emission peaks at 424 nm and 517 nm based on synchronous fluorescence. The -OH and -NH2 groups on the surface of the Si points have different binding abilities to metal ions, resulting in independent responses from the two emission peaks. The changes in the two emission signals are processed into unique "fingerprints" using LDA, generating a metal ion sensing array capable of effectively identifying multiple heavy metal ions. As a research attempt to explore a multi-target sensing array platform, this system provides a valuable practical case for the fields of simulation identification and environmental monitoring. Attached Figure Description

[0029] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments of this application or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0030] Figure 1 This is a schematic diagram of the structure of the dual-emission sensor array based on Si points provided in Embodiment 1 of this application.

[0031] Figure 2 This is a schematic diagram illustrating the optimization of silicon dot synthesis conditions provided in Embodiment 1 of this application.

[0032] Figure 3 This is a schematic diagram of the spectral and structural characterization of the Si point provided in Embodiment 1 of this application.

[0033] Figure 4 The high-resolution X-ray photoelectron spectrum of the silicon dot provided in Embodiment 1 of this application.

[0034] Figure 5 This is a schematic diagram illustrating the study of the fluorescence properties of the Si point provided in Example 1 of this application.

[0035] Figure 6 This is a schematic diagram illustrating the identification of 200 μM metal ions using thermal imaging, LDA, and HCA, as provided in Example 1 of this application.

[0036] Figure 7 This is a schematic diagram of the identification of metal ions of different concentrations based on Si points using LDA and HCA, provided in Example 1 of this application.

[0037] Figure 8 Zn at different concentrations provided in Example 1 of this application2+ Fe 2+ Fe 3+ Co 2+ The corresponding typical LDA scoring chart.

[0038] Figure 9 Cu at different concentrations provided in Example 1 of this application 2+ Ni 2+ and Mn 2+ Typical LDA scoring chart.

[0039] Figure 10 The zeta potential of the Si point in the presence of different metal ions is provided in Example 1 of this application.

[0040] Figure 11 This is a schematic diagram illustrating the ability of the dual-emission sensor array provided in Embodiment 1 of this application to identify metal ions from a mixture.

[0041] Figure 12 This is a schematic diagram illustrating the ability of the dual-emission sensor array provided in Embodiment 1 of this application to identify metal ions in a real sample.

[0042] Figure 13 This is a schematic diagram of a heavy metal ion identification system provided in Embodiment 2 of this application. Detailed Implementation

[0043] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0044] In the description of this application, it should be understood that the terms "upper", "lower", "horizontal", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, and are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this application.

[0045] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this application, "multiple" means two or more, unless otherwise explicitly specified.

[0046] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments.

[0047] The method and system for identifying heavy metal ions provided in this application prepared two Si points with emission centers having similar Stokes shifts, and generated two emission peaks at 424 nm and 517 nm based on synchronous fluorescence. The -OH and -NH2 groups on the surface of the Si points have different binding abilities to metal ions, resulting in independent responses from the two emission peaks. The changes in the two emission signals are processed into unique "fingerprints" using LDA to generate a metal ion sensing array capable of effectively identifying seven heavy metal ions. As a research attempt to explore a multi-target sensing array platform, this system provides a valuable practical case for the fields of simulation identification and environmental monitoring.

[0048] The chemicals, materials, instruments, and characterization methods involved in this application are as follows:

[0049] Chemicals and materials

[0050] Cobalt chloride and potassium chloride were purchased from Shanghai Maclean Biotechnology Co., Ltd. Calcium chloride and ammonium sulfate were supplied by Xilong Chemical Co., Ltd. Manganese acetate, nickel chloride, zinc chloride, N-(β-aminoethyl)-γ-aminopropylmethyldimethoxysilane (DAMO), tris(hydroxymethyl)aminomethane hydrochloride (Tris-HCl), and phenyl acetate were all purchased from Sigma. Magnesium chloride was purchased from Shanghai Aladdin Biotechnology Co., Ltd. Sodium chloride was purchased from Qieshen Biotechnology Co., Ltd. Sodium dihydrogen phosphate was purchased from Sangon Biotech (Shanghai) Co., Ltd. Sodium carbonate and ferrous sulfate were purchased from Sinopharm Chemical Reagent Co., Ltd. Copper sulfate was purchased from Shanghai Lingfeng Chemical Reagent Co., Ltd.

[0051] Instruments and characterization

[0052] Microwave system (bio-stimulator) + Si points were synthesized. Their size and morphology were characterized using a JEOL-F200 microscope (JEOL Ltd.). UV-Vis absorption spectra were recorded using a U-3900H spectrophotometer. Fluorescence and synchronous fluorescence spectra were obtained using a Hitachi F-7100 fluorescence spectrophotometer. Fourier transform infrared (FT-IR) spectra of the samples were acquired using a Nicoleti S20 (Thermo Scientific) FTIR spectrometer. To obtain the X-ray photoelectron spectra (XPS) of the samples, a K-Alpha spectrometer (Thermo Scientific) was used.

[0053] Example 1

[0054] Please see Figure 1The diagram shows the structure of a dual-emission sensor array based on Si points. (A) is a schematic diagram of the synthesis of the dual-emission Si points, and (B) is a fluorescence sensing system used to identify various metal ions.

[0055] The method for identifying heavy metal ions provided in this application includes the following steps S10 to S20, and the implementation of each step is described in detail below.

[0056] S10: Construct a fluorescence sensing array based on Si points, wherein each Si point has two emission centers.

[0057] Preparation and purification of Si points

[0058] The Si points were prepared using a microwave-assisted method, as detailed below:

[0059] Specifically, 200 μL of phenyl acetate was mixed with 200 μL of DAMO, and then 600 μL of ddH2O was added. The mixture was transferred to a glass vial in a microwave synthesizer, pre-stirred for 2 min, and reacted at 200 °C for 20 min. The Si-point mixture was thoroughly mixed with acetonitrile at a volume ratio of 1:4 and centrifuged at 8000 rpm for 15 min. The precipitate was then washed twice with acetonitrile and dried at 70 °C for 30 h to obtain Si-point crystals. The obtained product was stored at 4 °C for subsequent experiments.

[0060] Further, please refer to Figure 2 The following optimizations were made to the silicon dot synthesis conditions provided in this embodiment. (A) Phenyl acetate concentration; (B) Reaction temperature; (C) Reaction time. It is understood that using benzene-rich ring-rich substances as reactants is a fundamental method for preparing multi-emission-center nanomaterials; in this embodiment, phenyl acetate was selected. Dual-emission Si dots were prepared using a microwave-assisted method. The reaction conditions, including the concentration of phenyl acetate, reaction temperature, and reaction time, were optimized to obtain Si dots with high fluorescence intensity.

[0061] In this embodiment, the steady-state fluorescence spectrum of the Si point has two emission centers at 424 nm and 517 nm, and its fluorescence intensity reaches its maximum value when the excitation wavelengths are 340 nm and 430 nm, respectively.

[0062] Synthesis and characterization of dual-emission Si points

[0063] To further verify the dual emission center of the Si point in this application, the synthesis and characterization of the dual emission Si point are as follows:

[0064] Please see Figure 3The following are spectral and structural characterizations of Si points. (A) Fluorescence emission spectra of Si points at different excitation wavelengths from 310 nm to 520 nm. (B) Fluorescence excitation spectra of Si points at different emission wavelengths from 370 nm to 610 nm. (C) Synchronous fluorescence spectra of Si points with different Stokes shifts. (D) TEM image of nanoscale Si points (scale: 10 nm), inset: size distribution of Si points in TEM. (E) FTIR of Si points. (F) Full-scale XPS spectra of Si points.

[0065] Constructing sensor arrays using fluorescent nanomaterials with multiple emission centers offers significant application potential by providing multidimensional information using simple instruments such as single materials and fluorescence spectrometers. Using benzene-rich compounds as reactants is a fundamental method for preparing multi-emission-center nanomaterials; in this work, phenyl acetate was chosen. Dual-emission Si points were prepared using a microwave-assisted method. The concentration, reaction temperature, and reaction time of phenyl acetate were optimized to obtain Si points with high fluorescence intensity (S1). Figure 3 The steady-state fluorescence spectrum of the Si point shown in (A) has two emission centers at 424 nm and 517 nm. The fluorescence intensity reaches its maximum value when the excitation wavelengths are 340 nm and 430 nm, respectively. Figure 3 The fluorescence excitation spectrum at point B in the image shows two excitation peaks, further confirming the existence of two emission centers at the Si point. The two emission centers exhibit similar Stokes shifts, making them suitable for synchronous fluorescence, with an 80 nm Stokes shift being the optimal condition. Figure 3 (C)

[0066] Please see Figure 4 The values ​​are high-resolution X-ray photoelectron spectroscopy (XPS) spectra of silicon dots. Among them: (A) is the C1s XPS spectrum; (B) is the N1s XPS spectrum; (C) is the O1s XPS spectrum; (D) is the Si2p XPS spectrum.

[0067] Please see Figure 5 The following are studies on the fluorescence properties of Si points. (A) The effect of different ions on the fluorescence of Si points. (B) The dependence of the fluorescence intensity of Si points on the pH of the buffer solution. (C) The photostability of Si points after 1 h at excitation wavelengths of 340 nm and 430 nm. (D) The change in fluorescence intensity of Si points stored at 4 °C over time.

[0068] according to Figure 4 The diameter of the spherical Si dot, as measured by transmission electron microscopy (TEM) image shown in (D), is approximately 2.3 nm. From FTIR... Figure 4 (E) and XPS spectrum ( Figure 4 China F and Figure 5 It can be seen that the surface of the Si points is rich in hydrophilic groups such as -OH and -NH2, exhibiting good dispersibility and potential for biological applications. Furthermore, incubation with different ions does not cause any predictable changes in the fluorescence spectrum of the Si points. Figure 5 (A), thus indicating good chemical stability. We also investigated the effect of pH on the fluorescence of Si sites; increasing pH resulted in almost no change in fluorescence intensity after excitation at wavelengths of 340 nm and 430 nm (…). Figure 5 (B). Even after 2 hours of continuous irradiation, the fluorescence at the Si point remained almost unchanged, thus exhibiting good photostability. Figure 5 (C). This further verifies that the stability of the Si point remains unaffected under long-term storage conditions. Figure 5 (D). The stability of these Si points is crucial for biosensing of complex samples.

[0069] Multidimensional sensing of metal ions

[0070] In this embodiment, the step of constructing a fluorescence sensing array based on Si points specifically includes the following steps:

[0071] Si point (1 mg / mL) and metal ions (Fe) 2+ Fe 3+ Cu 2+ Co 2+ Ni 2+ Zn 2+ and Mn 2+ The fluorescence spectra of the Si points were then recorded. Five parallel experiments were performed for each of the seven individual metal ions. A training data matrix with two emission channels × seven metal ions × five replicates was obtained. Linear discriminant analysis (LDA) and hierarchical cluster analysis (HCA) were used to process and group the data. "Fingerprints" and "Euclidean distances" were obtained using IBM SPSS Statistical 27.0 software, and the data were processed using GraphPad Prism 8.0 software to generate the fluorescence sensing array.

[0072] Please see Figure 6 To identify metal ions at a concentration of 200 μM using thermal imaging, LDA, and HCA. (A) Fluorescence spectra in the presence of seven metal ions. (B) Thermal imaging of seven metal ions identified from a dual-emission Si point. (C) LDA plot of seven metal ions identified using a dual-channel sensor array. (D) HCA tree diagram of a multi-dimensional sensor array for seven metal ions.

[0073] Validation of a dual-channel sensor array for metal ion identification

[0074] In this embodiment, Fe, which has similar properties, was selected. 2+ Fe 3+ Cu 2+ Co 2+ Ni 2+ Zn 2+ Mn 2+ Seven metal ions were used as detection targets. The fluorescence response of the dual-emission Si site was investigated in the presence of each metal ion at a concentration of 200 μM, and significant changes in the emission intensity of each Si site were observed. Figure 6 As shown in (A). It is noteworthy that the fluorescence at the Si point is affected by Cu. 2+ Ni 2+ Fe 3+ Co 2+ and Fe 2+ Five metal ions were quenched, while Zn 2+ and Mn 2+ The presence of [something] enhances the fluorescence of the Si sites. A single signal is insufficient for specific recognition of these seven metal ions. For example... Figure 6 As shown in (B), due to the presence of metal ions, the changes in fluorescence intensity of the two emission peaks at the Si point are represented by color intensity and summarized into a thermogram, which allows for a direct visual observation of the differences in the analyte responses. However, the thermogram cannot provide accurate identification of metal ions.

[0075] Please see Figure 7 This image shows LDA and HCA diagrams for identifying metal ions of different concentrations based on Si points. The images show LDA plots for identifying seven metal ions at (A) 100 μM and (B) 500 μM. The HCA dendrograms for identifying seven metal ions based on Si points at (C) 100 μM and (D) 500 μM.

[0076] Furthermore, multivariate statistical analysis, including linear discriminant analysis (LDA) and principal component analysis (PCA), was performed on the fluorescence pattern response to accurately distinguish metal ions. Both LDA and PCA are commonly used dimensionality reduction statistical techniques. LDA is a "supervised" technique that maximizes separation between multiple classes by calculating a linear discriminant factor. PCA is a linear, "unsupervised" statistical and pattern recognition technique that transforms the multivariate matrix of the original dataset into a set of principal components. A training matrix of 2 emission channels × 7 metal ions × 5 repetitions was constructed by performing 5 repeated measurements on 7 metal ions at a concentration of 200 μM, and then a predictive model was built using LDA. When the metal ion concentration was varied (100 and 500 μM) to test the recognition capability of the sensor array, each metal ion was observed to aggregate in a separate cluster, making them easily identifiable. Figure 7These results demonstrate the possibility of accurately identifying seven metal ions at different levels using a dual-channel sensor array. HCA is a powerful statistical method that attempts to group data into specific groups based on a similarity metric. Figure 6 The HCA pattern shown in Figure D indicates that in 35 cases (7 metal ions × 5 replicates), 7 metal ions were correctly differentiated, with no misclassifications. The LDA and HCA results demonstrate the robustness of the Si-point-based sensor array for metal ion identification.

[0077] S20: Identify heavy metal ions based on the fluorescence sensing array, wherein the heavy metal ions are at least one type.

[0078] Please see Figure 8 , representing Zn at different concentrations 2+ Fe 2+ Fe 3+ Co 2+ Corresponding typical LDA score plot. (AD) Si point pairs for Zn at different concentrations. 2+ Fe 2+ Fe 3+ and Co 2+ Fluorescence spectra of the response. (EH)Si points for different concentrations of Zn. 2+ Fe 2+ Fe 3+ and Co 2+ Typical LDA score plot of the dual-channel response mode. (IL) Discriminant factor 1 and Zn 2+ Fe 2+ Fe 3+ and Co 2+ The linear relationship between the logarithms of concentrations.

[0079] Please see Figure 9 , representing Cu at different concentrations 2+ Ni 2+ and Mn 2+ Typical LDA score plot. (AC) Si point pairs for Cu at different concentrations. 2+ Ni 2+ and Mn 2+ Fluorescence spectra of the response. (DF)Si point pairs for Cu at different concentrations. 2+ Ni 2+ and Mn 2+ Typical LDA score map obtained from dual-channel fluorescence response. (GI) Discriminant factor 1 and Cu 2+ Ni 2+ and Mn 2+ The linear relationship between the logarithms of concentrations.

[0080] Detection of metal ions using dual-emission Si points

[0081] The concentration-dependent fluorescence response of Si points to different metal ions was evaluated by measuring the fluorescence effect of dual-emission Si points on different metal ion concentrations (1-1000 μM). Figure 8 and Figure 9 As shown, the metal ion Cu 2+ Fe 2+ Ni 2+ Fe 3+ and Co 2 + Fluorescence emission intensity was quenched at 424 nm and 517 nm, while Mn 2+ and Zn 2+ Both enhanced fluorescence emission intensity. Furthermore, Fe... 2+ and Fe 3+ It exhibits higher fluorescence quenching efficiency at 424 nm than at 517 nm, which is consistent with Co. 2+ Conversely, for Cu 2+ and Ni 2+ The fluorescence quenching efficiencies at 424 nm and 517 nm are similar, while Mn 2+ and Zn 2+ The fluorescence efficiency improvements at 424 nm and 517 nm were similar. The different fluorescence responses of Si sites to these seven metal ions at 424 nm and 517 nm offer great potential for accurate metal ion identification. Furthermore, Figure 8 EH and Figure 9 DF shows two-dimensional plots resulting from fluorescence changes caused by different concentrations of metal ions, representing two typical factors. LDA plots for different concentrations were differentiated. A good linear relationship exists between factor 1 score and metal ion concentration, as shown in Table S1. Table S1 shows the linear range and R0 of the detection of seven metal ions from discriminant factor 1 using a dual-channel sensor array based on Si points. 2 .

[0082] Table S1

[0083]

[0084]

[0085] Based on the fluorescence response described above, it can be seen that the Si-point-based sensor array can identify different metal ions at different concentrations. To investigate the interaction between metal ions and Si points, the surface potential before and after the addition of metal ions was studied.

[0086] Identification properties of mixtures

[0087] Please see Figure 10The zeta potential of the Si point is given by different metal ions. Due to the -OH and -NH2 groups on the Si surface, the zeta potential of the Si point is -6.8 mV. The zeta potential changes upon the addition of metal ions, with most of them becoming positively charged. This result demonstrates the interaction between metal ions and the Si point.

[0088] Please see Figure 11 This demonstrates the ability of a dual-emission sensor array to identify metal ions from a mixture. The multi-channel sensor array pairs (A) a mixture of Co... 2+ and Zn 2+ (B) Mixed Cu 2+ and Fe 3+ , and (C) mixed Ni 2+ and Fe 2+ The standard scoring chart. Mixed values ​​are as follows: a: 1 / 9, b: 2 / 8, c: 3 / 7, d: 4 / 6, e: 5 / 5, f: 6 / 4, g: 7 / 3, h: 8 / 2, and i: 9 / 1. (D) Multichannel sensor array for Fe 2+ Co 2+ and Zn 2+ Standard score chart for the mixture. The mixture is as follows: a: 1 / 2 / 7, b: 2 / 2 / 6, c: 1 / 4 / 5, d: 4 / 4 / 2, e: 2 / 6 / 2, f: 6 / 2 / 2, g: 4 / 1 / 5, h: 6 / 1 / 3, i: 3 / 6 / 1, k: 7 / 2 / 1. The total metal ion concentration is maintained at 500 μM.

[0089] In this embodiment, the ability of dual-emission Si points to distinguish different metal ions in a mixture was investigated. Co with different molar ratios was collected. 2+ Zn 2+ Cu 2+ / Fe 3+ and Ni 2+ / Fe 2+ Fluorescence response in the presence of mixtures (9:1, 8:2, 7:3, 6:4, 5:5, 4:6, 3:7, 2:8, 1:9). The total metal ion concentration was maintained at 500 μM during the measurement process. A new LDA model was established using the raw data. Figure 11 As shown in AC, for different molar ratios of Co 2+ / Zn 2+ Cu 2+ / Fe 3+ or Ni 2+ / Fe 2+ The mixture was well distinguished. Furthermore, the mixture containing Fe was also investigated. 2+ Co 2+ and Zn 2+Identification of mixtures with different molar ratios (1:2:7, 2:2:2:6, 1:4:5, 4:4:4:2, 2:6:2, 6:2:2, 4:4:1:5, 6:1:3, 3:6:1, 7:2:1). Figure 11 As shown in (D), Fe can be distinguished from mixtures containing different molar ratios. 2+ Co 2+ and Zn 2+ These results indicate that the Si point has good identification performance for mixtures of metal ions.

[0090] Real sample analysis

[0091] Please see Figure 12 This is represented by a dual-emission sensor array capable of identifying metal ions in real samples. (A) Identification of metal ions and interfering ions on a dual-channel array platform. (C) In a buffer solution containing interfering ions (Na₂O₃). 2+ K + Mg 2+ Ca 2+ The (D)LDA diagram distinguishes seven metal ions at a concentration of 200 μM.

[0092] like Figure 12 As shown in A and B, Na + K + Mg 2+ Ca 2+ CO3 2- SO4 2- NO3 - PO4 3- While various ions are indistinguishable from one another, they are well separated from the studied metal ions. Therefore, this Si-point-based sensor detection method exhibits good selectivity for these seven metal ions. Furthermore, since various metal cations exist in real water samples, the influence of coexisting ions on the recognition of these seven metal ions was investigated. Four common metal ions, K... + Na + Mg 2+ and Ca 2+ The molar ratio of the seven metal ions to the seven individual metal ions was 1:1. Using the seven metal ions as the training group and the seven metal ions in the coexisting ion sample as the test group, LDA analysis was performed on the resulting changes in dual emission signals. By comparison... Figure 12 The "fingerprint" of the LDA diagram shown in C indicates that the training and test data completely overlap, suggesting that the presence of coexisting ions in the dual-channel sensor array based on Si points has no significant impact on the identification of the seven metal ions, and that it has good anti-interference ability when identifying these seven metal ions.

[0093] Furthermore, this application explores the potential application of dual-emission Si points in real-world sample analysis. Using tap water containing various inorganic ions as the medium, seven metal ions under study were identified. Seven metal ions at a concentration of 200 μM were added to tap water and detected using dual-emission Si points. The scores of typical factors 1 and 2 obtained through LDA analysis are shown below. Figure 12 As shown in D. In the LDA plot, we can observe seven non-overlapping independent clusters, which fully demonstrates that the Si-point-based sensing array has high feasibility in identifying these seven metal ions in tap water.

[0094] The method for identifying heavy metal ions provided in this application constructs a fluorescence sensing array based on Si points, each Si point having two emission centers. The method identifies heavy metal ions, at least one of which is present, using this fluorescence sensing array. This invention prepares two Si points with emission centers having similar Stokes shifts and generates two emission peaks at 424 nm and 517 nm based on synchronous fluorescence. The -OH and -NH2 groups on the surface of the Si points have different binding abilities to metal ions, resulting in independent responses from the two emission peaks. The changes in the two emission signals are processed into unique "fingerprints" using LDA, generating a metal ion sensing array capable of effectively identifying multiple heavy metal ions. As a research attempt to explore a multi-target sensing array platform, this system provides a valuable practical case for the fields of simulation identification and environmental monitoring.

[0095] Example 2

[0096] Please see Figure 13 A heavy metal ion identification system provided in this application includes:

[0097] A fluorescence sensing array unit 110 is used to construct a fluorescence sensing array based on Si points, wherein the Si points have two emission centers;

[0098] The identification unit 120 is used to identify heavy metal ions based on the fluorescence sensing array, wherein the heavy metal ions are at least one type.

[0099] For a detailed explanation of its implementation, please refer to Example 1, which will not be repeated here.

[0100] The heavy metal ion identification system provided in this application constructs a fluorescence sensing array based on Si points, each Si point having two emission centers. The system identifies heavy metal ions, at least one of which is present. This invention prepares two Si points with emission centers having similar Stokes shifts and generates two emission peaks at 424 nm and 517 nm based on synchronous fluorescence. The -OH and -NH2 groups on the surface of the Si points have different binding abilities to metal ions, resulting in independent responses from the two emission peaks. The changes in the two emission signals are processed into unique "fingerprints" using LDA, generating a metal ion sensing array capable of effectively identifying multiple heavy metal ions. As a research attempt to explore a multi-target sensing array platform, this system provides a valuable practical case for the fields of simulation identification and environmental monitoring.

[0101] It is understood that the technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0102] The above are merely preferred embodiments of this application, and only specifically describe the technical principles of this application. These descriptions are only for explaining the principles of this application and should not be construed as limiting the scope of protection of this application in any way. Based on this explanation, any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application, as well as other specific embodiments of this application that can be conceived by those skilled in the art without creative effort, should be included within the scope of protection of this application.

Claims

1. A method for identifying heavy metal ions, characterized in that, Includes the following steps: A fluorescence sensing array is constructed based on Si points, wherein each Si point has two fluorescence emission centers; The heavy metal ions, specifically Fe, are identified based on the fluorescence sensing array. 2+ Fe 3+ Cu 2+ Co 2+ Ni 2+ Zn 2+ and Mn 2+ At least one of them; The steps for constructing a fluorescence sensing array based on Si points specifically include the following: After adding the Si point and the heavy metal ions to the buffer solution and incubating at room temperature, the fluorescence spectrum of the Si point was recorded. Multiple parallel experiments were conducted based on the quantity of the heavy metal ions to obtain a training data matrix. The training data matrix is ​​processed and grouped to convert changes in fluorescence signals into "fingerprints" and "Euclidean distances," thereby generating a fluorescence sensing array. In the step of recording the fluorescence spectrum of the Si point after incubating it with the heavy metal ions in a buffer solution at room temperature, the Si point is prepared by the following method: Mix 100-400 μL of phenyl acetate with 100-400 μL of N-(β-aminoethyl)-γ-aminopropylmethyldimethoxysilane, and then add 300-1200 μL of ddH2O to obtain a mixed solution. After transferring the mixed solution to a glass bottle in a microwave synthesizer, pre-stir for 1-5 min and react at 100-200ºC for 5-30 min; The Si point mixture was mixed with acetonitrile at a volume ratio of 1:1 to 1:4, centrifuged at 8000 rpm for 10-30 min, then the precipitate was washed twice with acetonitrile and dried at 50-80ºC for 30 h to obtain Si point crystals. The obtained product was stored at 4ºC to obtain the Si points.

2. The method for identifying heavy metal ions as described in claim 1, characterized in that, In the step of recording the fluorescence spectrum of the Si point after adding the Si point and the heavy metal ions to the buffer solution and incubating at room temperature, the steady-state fluorescence spectrum of the Si point has two fluorescence emission centers at 424 nm and 517 nm, and its fluorescence intensity reaches its maximum value when the excitation wavelengths are 340 nm and 430 nm, respectively.

3. The method for identifying heavy metal ions as described in claim 1, characterized in that, The step of obtaining a training data matrix by conducting multiple parallel experiments based on the quantity of the heavy metal ions specifically includes the following steps: Five parallel experiments were conducted for each of the seven individual heavy metal ions, resulting in a training data matrix with two emission channels × seven metal ions × five repetitions.

4. The method for identifying heavy metal ions as described in claim 3, characterized in that, The steps of processing and grouping the data in the training data matrix, converting changes in fluorescence signals into "fingerprints" and "Euclidean distances," and generating a fluorescence sensing array specifically include the following steps: The training data matrix was processed and grouped using linear discriminant analysis and hierarchical clustering analysis. "Fingerprints" and "Euclidean distances" were obtained using IBM SPSS Statistical 27.0 software, and the data was processed using GraphPad Prism 8.0 software to generate a fluorescence sensor array.

5. A heavy metal ion identification system for performing the heavy metal ion identification method according to claim 1, characterized in that, include: A fluorescence sensing array unit is used to construct a fluorescence sensing array based on Si points, wherein each Si point has two fluorescence emission centers. The identification unit is used to identify heavy metal ions, wherein the heavy metal ions are Fe, based on the fluorescence sensing array. 2+ Fe 3+ Cu 2+ Co 2+ Ni 2+ Zn 2+ and Mn 2+ At least one of them.

6. The application of a heavy metal ion identification system as described in claim 5 in environmental monitoring.

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