Preparation method of AgNWs surface-enhanced substrate and detection method of acetone in transformer oil

Abstract

The invention discloses a preparation method of a AgNWs surface-enhanced substrate and a detection method for acetone in transformer oil, which belongs to the field of transformer safety detection technology, comprising the following steps: soaking a gold-plated silicon wafer substrate in a 1,4-benzenedithiol solution, cleaning, drying, and obtaining a mercaptolated gold-plated silicon wafer substrate; cleaning a silver nanowire solution, dispersing it with an ethanol solution, centrifuging, and dispersing the precipitate with an ethanol solution to obtain an ethanol dispersion of the silver nanowire solution; placing the mercaptolated gold-plated silicon wafer substrate in an ethanol dispersion of the silver nanowire solution, standing, cleaning, drying, and obtaining an AgNWs surface-enhanced substrate. The present invention soaks the gold-plated silicon wafer substrate with a 1,4-benzenedithiol solution so that Au is fully in contact with the mercapto group to form a strong chemical bond. The gold material can generate a SERS hotspot between the AgNWs, enhancing the surface plasmon resonance effect, and thus effectively improving accuracy, sensitivity, and predictive stability.

Description

Technical Field

[0001] The present invention relates to the technical field of transformer safety detection, and in particular to a method for preparing an AgNWs surface-enhanced substrate and a method for detecting acetone in transformer oil. Background Art

[0002] With the acceleration of power grid construction, its operational reliability is becoming increasingly important. The stable operation of the power system requires the coordinated cooperation of various power transmission and transformation equipment. Oil-immersed power transformers are one of the main equipment in power stations and substations. Their stable operation is a necessary condition for ensuring high-quality power supply. Accurately diagnosing their aging faults and discovering their potential problems in advance are one of the keys to the safe and economical operation of the power system and the maintenance and repair of electrical equipment.

[0003] Transformers are one of the most important electrical equipment in the power system. Their stable operation is a necessary condition for ensuring high-quality power supply. The insulation inside the transformer is mainly composed of composite insulation composed of mineral oil and insulating paperboard. During long-term operation, its insulating materials such as insulating oil and insulating paper will decompose under the influence of factors such as electricity and heat, producing furans, alcohols, acids, esters and ketones, which reflect the nature of the fault and insulation performance. These substances are dissolved in the oil, and their concentration can be used as a chemical indicator to evaluate the degree of insulation aging. Test the degree of polymerization of paper insulation in transformer oil, furfural dissolved in oil, CO, CO 2 The primary method for determining the aging status of transformer insulation is to measure the content of characteristic aging products such as furfural. The dissolved gas and furfural content in transformer oil can objectively reflect the aging of the transformer's internal insulation. However, due to the easy diffusion of gas in the oil and the adsorption of furfural, it is difficult to accurately determine the degree of insulation aging. Acetone is a byproduct of long-term transformer insulation operation. Due to its resistance to adsorption and diffusion, its minimal impact on oxygen and moisture, and its relatively stable composition, it has value as a reference indicator for determining transformer insulation aging. The "Guidelines for Determining Insulation Aging of Oil-Immersed Transformers" states: "As one of the insulation aging products of transformers, acetone has a linear relationship with the degree of polymerization of paper insulation. Acetone may become a new basis for determining insulation aging." The content of dissolved acetone in transformer oil has also attracted increasing attention and has become a research hotspot for determining transformer insulation aging.

[0004] Currently, headspace gas chromatography (GC) is the primary method used both domestically and internationally to determine acetone content in transformer oil. However, this method suffers from complex waterbath heating, long sample equilibration times, susceptibility to column contamination, and lengthy detection times. Furthermore, GC equipment is expensive, requires regular replacement of components such as the GC column, and carries high maintenance costs, making GC testing costly. Methods for determining other aging signatures in transformer oil generally include high-performance liquid chromatography (HPLC), ultraviolet spectrophotometry, and colorimetry. HPLC offers high precision and reproducibility, but elution is difficult and subject to "extra-column effects." UV spectrophotometry is fast but susceptible to interference from organic matter in the oil and exhibits poor stability. While colorimetry is inexpensive, the reagent used (p-toluidine) is a strong carcinogen, resulting in significant experimental error. Other methods, primarily focused on detecting dissolved acetone in water, include spectrophotometry, fluorescence spectrophotometry, gas chromatography, and gas chromatography-mass spectrometry. Spectrophotometry and fluorescence spectrophotometry are simple to use but have low sensitivity. Gas chromatography and gas chromatography-mass spectrometry are highly sensitive but require complex procedures and pretreatment steps. In summary, the detection of trace amounts of acetone dissolved in oil is complex, requires extensive equipment, and requires laboratory testing, making in-situ oil detection difficult. Therefore, developing a low-cost, highly sensitive, rapid, and efficient method for detecting dissolved acetone in transformer oil is of great value and significance.

[0005] Raman spectroscopy is an effective method for detecting and analyzing liquid materials. Raman scattering is the inelastic scattering caused by the interaction between incident light and molecular vibrations. The Raman shift caused by Raman scattering can be used to identify different molecules, and the intensity of Raman scattering is related to the concentration of molecules in the sample. Raman spectroscopy has been widely used in many fields such as petrochemicals, environmental protection, food identification, geological analysis, gem identification, commodity inspection, and medicine. The advantages of applying laser Raman spectroscopy to the detection of the content of acetone dissolved in oil are: ① There is no need to separate the sample, and the liquid composition and content can be directly determined, and the detection speed is fast; ② Raman detection is a non-contact detection and does not require sample consumption; ③ The characteristic liquids dissolved in the oil are all Raman active; ④ The spectral detection range covers the entire vibration frequency range; ⑤ The laser has strong directionality and a small beam divergence angle, which can be used to detect trace samples; ⑥ Raman spectra are not greatly affected by environmental factors. However, the intensity of the Raman scattering signal is generally only 1×10 of the incident light intensity. -10 In addition, due to the small number of interface molecules, the Raman scattering signal intensity will be very weak, which greatly limits the application and development of Raman spectroscopy in the field of trace detection.

[0006] Surface-enhanced Raman spectroscopy (SERS) refers to the phenomenon in which the Raman signal of an analyte around a metallic nanostructure is amplified by several orders of magnitude due to the localized electromagnetic field enhancement induced by surface plasmon resonance excitation. SERS represents a historic breakthrough in Raman spectroscopy, with profound implications for surface science and spectroscopy. It has freed surface Raman spectroscopy from the limitations of low sensitivity and enabled its widespread application in fields such as electrochemistry, biomedicine, catalysis, environmental science, and materials science. SERS technology holds enormous potential for detecting trace environmental pollutants. Currently, SERS has been applied to the detection of hundreds of environmental pollutants, with numerous applications in detecting harmful small molecules in food, foodborne pathogens, heavy metal contamination, and mycotoxins. Trace signatures generated by transformer aging are low in concentration and easily masked by Raman signals. Applying surface-enhanced Raman spectroscopy to the detection of acetone in transformer oil is a novel detection method. The SERS substrate significantly influences the SERS enhancement effect, making it crucial to identify a SERS substrate with high enhancement efficiency and to enable the rapid and accurate detection of trace amounts of acetone dissolved in oil.

[0007] CN114852955A discloses a method for preparing rectangular silver nanosheets and a method for detecting acetone in transformer oil. The method uses rectangular silver nanosheets as a surface-enhanced substrate for in-situ detection of acetone in transformer oil. The internal standard method is used to obtain the characteristic peak of the Raman intensity of acetone. The enhancement effect of the surface-enhanced substrate is analyzed over time, the stability of the surface-enhanced substrate is determined, and the relationship between the relative area of ​​the acetone characteristic peak and the concentration of acetone solutions of different concentrations is measured. A quantitative analysis model for acetone concentration in transformer oil is established based on the least squares method, which can be used for quantitative detection of acetone concentration in transformer oil. This patent uses laser as a detection method, eliminating the need for complex pretreatment to achieve in-situ detection of dissolved acetone in transformer oil. However, the enhancement factor is only 1231.3, indicating that the enhancement effect still needs to be improved.

[0008] A commonly used method for quantifying aging signatures in transformer oil is the linear regression model (ULR). However, ULR does not provide ideal fitting results in the low-concentration range for surface-enhanced Raman quantification of acetone. This is because low concentrations are weighted less heavily in linear regression using the least squares method, resulting in poor fitting. Furthermore, ULR ignores the rich information contained in multiple characteristic peaks and even the entire spectrum. The intensity of a single characteristic peak used for modeling is unstable, leading to inaccurate predictions and limiting its application in acetone quantification. Chemometric methods such as partial least squares (PLS) can help extract selected relevant information related to the target analyte from spectra containing the fingerprints of the various chemical components present in the sample. The PLS quantitative analysis model can analyze multiple characteristic peaks or the entire spectrum, is applicable to complex multi-component spectra, and offers high accuracy and predictive stability. Summary of the Invention

[0009] The purpose of the present invention is to overcome the shortcomings of the prior art and provide a method for preparing an AgNWs surface-enhanced substrate and a method for detecting acetone in transformer oil. The AgNWs surface-enhanced substrate of the present invention is applied to the detection of acetone in transformer oil, which can effectively improve the accuracy, sensitivity and prediction stability.

[0010] To achieve the above object, the technical solution adopted by the present invention is:

[0011] A method for preparing an AgNWs surface-enhanced substrate comprises the following steps:

[0012] soaking the gold-plated silicon wafer substrate in a 1,4-benzenedithiol solution, washing, and drying to obtain a thiol-plated gold-plated silicon wafer substrate;

[0013] washing the silver nanowire solution, dispersing it with an ethanol solution, centrifuging it, and dispersing the precipitate with an ethanol solution again to obtain an ethanol dispersion of the silver nanowire solution;

[0014] The thiol-coated gold-plated silicon wafer substrate is placed in an ethanol dispersion of a silver nanowire solution, allowed to stand, cleaned, and dried to obtain an AgNWs surface enhanced substrate.

[0015] As a preferred embodiment of the present invention, the size of the gold-plated silicon wafer is 0.01 to 100 cm 2 .

[0016] As a preferred embodiment of the present invention, the molar concentration of the 1,4-benzenedithiol solution is 0.1 to 1 mol / L.

[0017] As a preferred embodiment of the present invention, the method for preparing the silver nanowire solution comprises the following steps:

[0018] Use ethylene glycol solution as the reaction base liquid, heat it, add FeCl3 ethylene glycol solution and AgNO3 ethylene glycol solution in sequence, stir evenly, then add PVP ethylene glycol solution, stop heating, cool it, the solution turns gray-green, and a silver nanowire precursor solution is obtained;

[0019] The silver nanowire precursor solution and deionized water are mixed evenly, centrifuged, and the precipitate is washed and dispersed in an ethanol solution to obtain a silver nanowire solution.

[0020] As a preferred embodiment of the present invention, the molar concentration of the FeCl3 ethylene glycol solution is 0.001 to 0.01 mol / L; and / or

[0021] The molar concentration of the AgNO3 ethylene glycol solution is 0.1 to 1 mol / L; and / or

[0022] The molar concentration of the PVP ethylene glycol solution is 0.1-1 mol / L.

[0023] As a preferred embodiment of the present invention, the volume ratio of the ethylene glycol solution of FeCl3, the ethylene glycol solution of AgNO3, and the ethylene glycol solution of PVP is (1-10):(5-20):(20-80).

[0024] As a preferred embodiment of the present invention, the length of the silver nanowires in the silver nanowire solution is 20 to 30 μm, and the diameter is 15.6 nm to 65.6 nm.

[0025] The present invention also provides a method for detecting acetone in transformer oil, comprising the following steps:

[0026] (1) Prepare 8 groups of 6 different concentrations of acetone transformer oil solution standard gradient solutions and extract;

[0027] (2) immersing the AgNWs surface enhanced substrate in the extracted standard gradient solution, collecting Raman spectra, and preprocessing the collected Raman spectra;

[0028] (3) The PLS model was used to establish the statistical relationship between acetone content and spectral intensity. Six of the eight groups, totaling 32 samples, were used as training sets, and the remaining 16 samples were used as prediction sets. The corresponding spectral matrix and concentration matrix were imported into The Unscrambler software as input variables. PLS regression analysis was performed using the PLS method to establish a PLS quantitative model for acetone in transformers.

[0029] The AgNWs surface enhanced substrate is prepared by the above-mentioned preparation method.

[0030] As a preferred embodiment of the present invention, the standard gradient solutions of acetone transformer oil solution are 3950 mg / L, 1975 mg / L, 987 mg / L, 493 mg / L, 246 mg / L, 123 mg / L, and 61 mg / L, respectively.

[0031] As a preferred embodiment of the present invention, the preprocessing includes: eliminating baseline shift and drift of the collected spectral data, eliminating the interference of background noise, eliminating the influence of optical path change and surface scattering on the spectrum, improving spectral resolution, and enhancing spectral feature processing.

[0032] The beneficial effects of the present invention are as follows: (1) the present invention soaks the gold-plated silicon wafer substrate in a 1,4-benzenedithiol solution, so that Au and the thiol group are fully in contact to form a strong chemical bond. The gold material can generate a SERS hotspot between the AgNWs, enhance the surface plasmon resonance effect, and thus effectively improve the accuracy, sensitivity and prediction stability; (2) the present invention places the thiol-plated gold-plated silicon wafer substrate in an ethanol dispersion of a silver nanowire solution, allows it to stand, and utilizes the gravity of the particles themselves to deposit the metal nanoparticles in the solution on the modified substrate surface, thereby forming a relatively dense metal particle film on the substrate surface, so that the nanoparticles are assembled in order and the nanomaterials are evenly distributed, further effectively improving the accuracy, sensitivity and prediction stability; (3) the surface enhanced Raman spectroscopy technology described in the present invention, this highly sensitive and repeatable structure has important application value for the detection of trace acetone dissolved in transformer oil, provides technical support for the future use of surface enhanced substrates for the detection of aging characteristics, and can be widely used in energy and power fields. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 This is a scanning electron microscope (SEM) image of the Ag NWs surface-enhanced substrate described in the present invention.

[0034] Figure 2 This is the Raman spectrum of R6G.

[0035] Figure 3 10 is adsorbed on Ag NWs -12 The SERS spectrum of MR6G is similar to that of 10 -6 Normal Raman spectrum of MR6G.

[0036] Figure 4 This is the Raman spectrum of acetone gradient extraction.

[0037] Figure 5 This is the analysis result of the PLS quantitative model. DETAILED DESCRIPTION

[0038] To make the purpose, technical solutions, and advantages of the embodiments of this application more clear, the technical solutions in the embodiments of this application will be clearly and completely described below. Obviously, the described embodiments are part of the embodiments of this application, not all of them. Based on the embodiments of this application, all other embodiments obtained by ordinary technicians in this field without making any creative efforts are within the scope of protection of this application.

[0039] In this application, the technical features described in an open manner include closed technical solutions composed of the listed features, and also include open technical solutions containing the listed features.

[0040] In this application, when referring to numerical ranges, unless otherwise specified, the numerical ranges are considered continuous and include the minimum and maximum values ​​of the range, as well as every value between such minimum and maximum values. Further, when a range refers to an integer, every integer between the minimum and maximum values ​​of the range is included. In addition, when multiple ranges are provided to describe a feature or characteristic, the ranges can be combined. In other words, unless otherwise specified, all ranges disclosed herein should be understood to include any and all subranges subsumed therein.

[0041] In the present application, there is no particular limitation on the specific dispersing, washing and stirring treatment methods.

[0042] The reagents and instruments used in this application without manufacturer indication are all conventional products that can be purchased commercially.

[0043] The present invention provides a method for preparing a AgNWs surface-enhanced substrate, comprising the following steps:

[0044] soaking the gold-plated silicon wafer substrate in a 1,4-benzenedithiol solution, washing, and drying to obtain a thiol-plated gold-plated silicon wafer substrate;

[0045] washing the silver nanowire solution, dispersing it with an ethanol solution, centrifuging it, and dispersing the precipitate with an ethanol solution again to obtain an ethanol dispersion of the silver nanowire solution;

[0046] The thiol-coated gold-plated silicon wafer substrate is placed in an ethanol dispersion of a silver nanowire solution, allowed to stand, cleaned, and dried to obtain an AgNWs surface enhanced substrate.

[0047] The present invention creatively soaks the gold-plated silicon wafer substrate in a 1,4-benzenedithiol solution, allowing Au to fully contact the thiol group and form a strong chemical bond. The gold material can generate SERS hotspots between the AgNWs, enhancing the surface plasmon resonance effect, thereby effectively improving accuracy, sensitivity and prediction stability.

[0048] Among them, a thiol-coated gold-plated silicon wafer substrate is placed in an ethanol dispersion of a silver nanowire solution and allowed to stand. The metal nanoparticles in the solution are deposited on the modified substrate surface by the gravity of the particles themselves, thereby forming a relatively dense metal particle film on the substrate surface, so that the nanoparticles are assembled in an orderly manner and the nanomaterials are evenly distributed, further effectively improving the accuracy, sensitivity and prediction stability.

[0049] The Ag NWs in the AgNWs surface-enhanced substrate AgNWs material described in the present invention are intertwined to form a 3D network with numerous tip and edge regions. These regions can accumulate charge and exhibit excellent surface plasmon resonance properties. In addition, the plasmon coupling between adjacent Ag NWs leads to a significant enhancement of the electromagnetic field. In addition, the surface layer of the Ag NWs presents a dense porous structure on the underlying solid substrate. The dense porous structure increases the specific surface area, thereby allowing the adsorption of more target molecules.

[0050] As a preferred embodiment of the present invention, the size of the gold-plated silicon wafer is 0.01 to 100 cm 2 .

[0051] As a preferred embodiment of the present invention, the molar concentration of the 1,4-benzenedithiol solution is 0.1 to 1 mol / L.

[0052] As a preferred embodiment of the present invention, the method for preparing the silver nanowire solution comprises the following steps:

[0053] Use ethylene glycol solution as the reaction base liquid, heat it, add FeCl3 ethylene glycol solution and AgNO3 ethylene glycol solution in sequence, stir evenly, then add PVP ethylene glycol solution, stop heating, cool it, the solution turns gray-green, and a silver nanowire precursor solution is obtained;

[0054] The silver nanowire precursor solution and deionized water are mixed evenly, centrifuged, and the precipitate is washed and dispersed in an ethanol solution to obtain a silver nanowire solution.

[0055] It should be noted that in the preparation method of the AgNWs surface enhanced substrate and the preparation method of the silver nanowire solution of the present invention, cleaning is mentioned many times, and the cleaning mentioned is a conventional cleaning method in the art.

[0056] Exemplarily, the cleaning is carried out successively with anhydrous ethanol and / or deionized water, and the number of cleaning times may be 1 to 10 times according to actual conditions.

[0057] It should be noted that, in the present invention, soaking is mentioned many times. There is no limit on the ratio of the soaking material to the soaked material during the soaking time, as long as the soaking material can cover the soaked material, the soaking effect can be achieved.

[0058] The present invention does not impose any particular limitation on the amount of anhydrous ethanol and / or deionized water used during cleaning.

[0059] In the present invention, the concentrations of the ethylene glycol solution and the ethanol solution are not limited, and those skilled in the art can select appropriate concentrations according to actual conditions.

[0060] The concentration of the ethylene glycol solution used in the embodiment of the present invention is 55 v / v%, and the ethanol solution is anhydrous ethanol.

[0061] The Ag NWs in the silver nanowire solution prepared using the present invention intertwine to form a 3D network with numerous sharp and edge regions. These regions can accumulate charge and exhibit excellent surface plasmon resonance properties. Furthermore, plasmon coupling between adjacent Ag NWs leads to a significant enhancement of the electromagnetic field. Furthermore, the surface layer of the Ag NWs exhibits a dense porous structure on the underlying solid substrate. This dense porous structure increases the specific surface area, allowing for the adsorption of more target molecules.

[0062] As a preferred embodiment of the present invention, the molar concentration of the FeCl3 ethylene glycol solution is 0.001 to 0.01 mol / L; and / or

[0063] The molar concentration of the AgNO3 ethylene glycol solution is 0.1 to 1 mol / L; and / or

[0064] The molar concentration of the PVP ethylene glycol solution is 0.1-1 mol / L.

[0065] As a preferred embodiment of the present invention, the volume ratio of the ethylene glycol solution of FeCl3, the ethylene glycol solution of AgNO3, and the ethylene glycol solution of PVP is (1-10):(5-20):(20-80).

[0066] As a preferred embodiment of the present invention, the length of the silver nanowires in the silver nanowire solution is 20 to 30 μm, and the diameter is 15.6 nm to 65.6 nm.

[0067] The present invention also provides a method for detecting acetone in transformer oil, comprising the following steps:

[0068] (1) Prepare 8 groups of 6 different concentrations of acetone transformer oil solution standard gradient solutions and extract;

[0069] (2) immersing the AgNWs surface enhanced substrate in the extracted standard gradient solution, collecting Raman spectra, and preprocessing the collected Raman spectra;

[0070] (3) The PLS model was used to establish the statistical relationship between acetone content and spectral intensity. Six of the eight groups, totaling 32 samples, were used as training sets, and the remaining 16 samples were used as prediction sets. The corresponding spectral matrix and concentration matrix were imported into The Unscrambler software as input variables. PLS regression analysis was performed using the PLS method to establish a PLS quantitative model for acetone in transformers.

[0071] The AgNWs surface enhanced substrate is prepared by the above-mentioned preparation method.

[0072] This patent applies the partial least squares regression model to the SERS detection of acetone. The established method can meet the quantitative analysis of acetone in oil-paper insulation materials. Subsequently, the measured value can be input into The Unscrambler software to obtain the acetone content in transformer oil.

[0073] As a preferred embodiment of the present invention, the standard gradient solutions of acetone transformer oil solution are 3950 mg / L, 1975 mg / L, 987 mg / L, 493 mg / L, 246 mg / L, 123 mg / L, and 61 mg / L, respectively.

[0074] As a preferred embodiment of the present invention, the preprocessing includes: eliminating baseline shift and drift of the collected spectral data, eliminating the interference of background noise, eliminating the influence of optical path change and surface scattering on the spectrum, improving spectral resolution, and enhancing spectral feature processing.

[0075] The present invention is further described below with specific embodiments:

[0076] Example 1

[0077] A method for preparing an AgNWs surface-enhanced substrate comprises the following steps:

[0078] (1) Rinse the beakers, measuring cylinders, flasks, tweezers, and gold film substrates required for the experiment repeatedly with ultrapure water and anhydrous ethanol, and dry them in a drying oven;

[0079] (2) Add 50 mL of ethylene glycol solution to a three-necked flask and heat at 150 °C for 1 hour. Then, add 2 mL of 0.004 M FeCl3 ethylene glycol solution to the three-necked flask. After 15 minutes, add 15 mL of 0.5 M AgNO3 ethylene glycol solution to the three-necked flask. Finally, add 45 mL of 0.6 M PVP ethylene glycol solution dropwise to the mixed solution through a syringe pump at a drop rate of 65 mL / h. Stop heating after 2 hours and cool naturally to room temperature (25 °C). The solution turns gray-green, which is the silver nanowire precursor solution.

[0080] (3) The silver nanowire precursor solution prepared above was mixed with 3 volumes of deionized water, and then the mixture was transferred to a centrifuge tube and centrifuged at 3000 rpm for 10 minutes. Subsequently, the supernatant was removed, leaving the bottom sediment. Then, 3 volumes of anhydrous ethanol mother liquor were added to the centrifuge tube, and the mixture was stirred evenly using an ultrasonic instrument. The mixture was centrifuged again, and the supernatant was removed, leaving the bottom sediment. This process was repeated 4 times. Finally, the washed sediment was ultrasonically dispersed in anhydrous ethanol to obtain a silver nanowire solution (hereinafter referred to as Ag NWs solution).

[0081] (4) 1cm 2 The gold-plated silicon wafer substrate (1cm*1cm) was immersed in 0.2mol / L BDT solution for 8h to allow Au and thiol groups to fully contact and form a strong chemical bond;

[0082] (5) Remove the thiol-coated gold-plated silicon wafer substrate with tweezers, rinse it repeatedly with deionized water and anhydrous ethanol 8 times, place it on filter paper and dry it naturally at room temperature for 60 minutes, and then set aside;

[0083] (6) 0.8 mL of the Ag NWs solution prepared in step (3) was taken and repeatedly washed with deionized water and ethanol in an ultrasonic machine. After cleaning, it was dispersed in an ethanol solution and transferred to a centrifuge tube. Centrifugation was performed, the supernatant was removed, and the bottom precipitate was retained. Finally, anhydrous ethanol was added to the washed precipitate to 2 mL and ultrasonically dispersed to obtain an Ag NWs ethanol dispersion.

[0084] (7) The Ag NWs ethanol dispersion was poured into a 5 mL beaker (the bottom diameter of the cup was 22 mm), and the thiolated Au substrate was placed at the bottom of the silver nanowire ethanol dispersion and kept at a constant temperature for more than 10 h to obtain the Ag NWs@Au substrate.

[0085] (8) The Ag NWs@Au substrate was repeatedly washed with anhydrous ethanol and ultrapure water four times and placed on filter paper to dry naturally to obtain an AgNWs surface-enhanced substrate.

[0086] The scanning electron microscope (SEM) image of the AgNWs surface enhanced substrate prepared in this example is as follows: Figure 1 As shown in the figure, it can be seen that the Ag NWs in the AgNWs surface-enhanced substrate AgNWs material of the present invention are intertwined to form a 3D network, and there are many tip and edge regions. These regions can accumulate charges and exhibit excellent surface plasmon resonance characteristics. In addition, the plasmon coupling between adjacent Ag NWs will lead to a significant enhancement of the electromagnetic field. In addition, the surface layer of the Ag NWs presents a dense porous structure on the underlying solid substrate. The dense porous structure will increase the specific surface area, thereby allowing more target molecules to be adsorbed.

[0087] The length of the silver nanowires is 20 to 30 μm, and the diameter is 15.6 nm to 65.6 nm.

[0088] Example 2

[0089] The enhancement effect evaluation of the Ag NWs surface enhanced substrate prepared in Example 1 includes the following steps:

[0090] Step 1: Prepare R6G solution for testing substrate enhancement properties

[0091] 0.12 g of Rhodamine 6G was dissolved in water, and the volume was fixed to obtain 2500 mL of mixed solution, and the first concentration of R6G solution was obtained by stirring with a magnetic stirrer. -3 mol / L.

[0092] C1, 0.1mL of 10 -3 mol / LR6G solution was mixed with 99.9 mL of water and stirred with a magnetic stirrer to obtain a concentration of 10 -6 mg / L R6G solution;

[0093] C2, add 10mL of 10 -6 mol / LR6G solution was mixed with 90 mL of water and stirred with a magnetic stirrer to obtain a concentration of 10 -7 mg / L R6G solution;

[0094] C3, add 10mL of 10 -7 mol / LR6G solution was mixed with 90 mL of water and stirred with a magnetic stirrer to obtain a concentration of 10 -8 mg / L R6G solution;

[0095] C4, add 10mL of 10 -8 mol / LR6G solution was mixed with 90 mL of water and stirred with a magnetic stirrer to obtain a concentration of 10 -9 mg / L R6G solution;

[0096] C5, add 10mL of 10 -9 mol / LR6G solution was mixed with 90 mL of water and stirred with a magnetic stirrer to obtain a concentration of 10 -10 mg / L R6G solution;

[0097] Step 2: Soak the substrate in each R6G solution:

[0098] Five nano-scale Ag NWs surface enhancement substrates prepared in Example 1 were immersed in each R6G solution and stored in the dark;

[0099] Step 3: Measure the Raman spectrum of R6G solution

[0100] After immersion for 12 hours, the quartz cuvette was placed on the stage of the confocal Raman detection platform, and a 560 nm wavelength laser, a laser power of 500 mW, an integration time of 0.001 s, an integration number of 100, a slit width of 500 μm, and a 1200 / 500 nm grating were selected. The laser focus was focused on the R6G solution and the surface of the Ag@ZnO surface-enhanced substrate, respectively, and the Raman spectrum of the R6G solution was collected, as shown in FIG. Figure 2 shown.

[0101] Step 4: Preprocess the Raman spectrum

[0102] The Raman spectra data of oil samples No. 1 to No. 6 were preprocessed by removing peaks, adjusting baselines, and smoothing to eliminate interference from cosmic rays, fluorescence background, and instrument noise.

[0103] Step 6: Calculate the enhancement factor

[0104] Calculate the 1650cm without and with base -1 The Raman peak area of ​​R6G is used to calculate the enhancement factor:

[0105]

[0106] Among them, ISERS and NSERS represent the surface-enhanced Raman spectroscopy signal intensity of the target molecule and the number of molecules contained in the signal area; Iout and Nout represent the ordinary Raman signal intensity of the target molecule and the number of molecules contained in the signal area.

[0107] Figure 3 Showing 10 -12 The SERS spectrum of MR6G is similar to that of 10 -6 M R6G ordinary Raman spectrum, in which 1649 cm -1 The peak at is the characteristic peak for the enhancement factor calculation. The SERS detection intensity ISERS of 10-12MR6G adsorbed on the Ag NWs substrate is about 528.498, while 10 -6 The normal Raman detection intensity Iout of MR6G is about 12.558. Since SERS detection and normal Raman detection use the same measurement and preparation conditions, their detection volumes and molecular absorption surface areas are similar. Therefore, NSERS and Nout are mainly determined by the concentration of R6G, that is, NSERS / Nout=CSERS / Cout=10 6 .

[0108] It is concluded that the enhancement factor of the Ag NWs substrate is about 9.8×106 The results show that the surface enhanced substrate has a good enhancement effect and can be used in the detection of aging characteristics of transformer oil.

[0109] Example 3

[0110] A quantitative analysis method for dissolved acetone in transformer oil was established based on the Ag NWs surface-enhanced substrate, including the following steps:

[0111] Step 1: Prepare 8 sets of repeated acetone solutions for testing substrate enhancement properties

[0112] C. Prepare gradient solutions of different concentrations of acetone dissolved in transformer oil

[0113] C1. Dissolve 1 mL of acetone solution in transformer oil, adjust the volume to obtain 200 mL of mixed solution, and stir with a magnetic stirrer to obtain the first concentration of acetone solution of 3950 mg / L oil sample.

[0114] C2. Mix 100 mL of oil sample No. 1 with 100 mL of transformer oil and stir with a magnetic stirrer to obtain an oil sample with a concentration of 1975 mg / L.

[0115] C3. Take 100 mL of oil sample II and mix it with 100 mL of transformer oil. Stir it with a magnetic stirrer to obtain an oil sample with a concentration of 987 mg / L.

[0116] C4. Take 100 mL of No. III oil sample and mix it with 100 mL of transformer oil. Stir it with a magnetic stirrer to obtain an oil sample with a concentration of 493 mg / L.

[0117] C5. Take 100 mL of No. IV oil sample and mix it with 100 mL of transformer oil. Stir it with a magnetic stirrer to obtain an oil sample with a concentration of 246 mg / L.

[0118] C6. Take 100 mL of No. IV oil sample and mix it with 100 mL of transformer oil. Stir it with a magnetic stirrer to obtain an oil sample with a concentration of 123 mg / L.

[0119] Step 2: Extraction:

[0120] The gradient solutions of acetone in transformer oil were extracted with water.

[0121] Step 3: Measure the Raman spectrum of the extracted oil sample

[0122] The gradient extraction solution of acetone was respectively placed in quartz cuvettes, and then six prepared Ag NWs surface enhanced composite material substrates were respectively immersed in the gradient extraction solution of acetone and stored in the dark. After soaking for 24 hours, the quartz cuvette was placed on the stage of the confocal Raman detection platform to collect the Raman spectrum of the gradient solution after extraction. A 560nm wavelength laser, a laser power of 500mW, an integration time of 0.001s, an integration number of 100, a slit width of 500μm, and a 1200 / 500nm grating were selected. The laser focus was focused on the oil sample to collect the Raman spectrum of the gradient solution. The Raman spectrum of acetone dissolved in the transformer oil after extraction is shown in FIG. Figure 4 As shown;

[0123] Step 4: Preprocess the Raman spectrum

[0124] The Raman spectral data of the acetone gradient extract were preprocessed by removing peaks, adjusting the baseline, and smoothing to eliminate interference from cosmic rays, fluorescence background, and instrument noise.

[0125] Step 5: Select the Raman characteristic peak of acetone in the solution

[0126] Comparing the Raman spectra of transformer oil, acetone, and oil samples 1-6, it was found that the Raman spectra of acetone dissolved in water-extracted transformer oil were at 1675 cm -1 The Raman signal at 1675 cm is significantly enhanced, which is due to the superposition of the Raman signals of acetone molecules. -1 As the Raman characteristic peak of acetone molecule;

[0127] Step 6: Establish a PLS quantitative analysis method for dissolved acetone in transformer oil

[0128] A PLS model was used to establish a statistical relationship between acetone content and full-spectral intensity. Thirty-two samples from 48 standard acetone extracts were used as the training set, and 16 samples were used as the prediction set. The corresponding spectral matrix and concentration matrix were imported into The Unscrambler software as input variables. PLS regression analysis was performed using the spectral fingerprints of various chemical components to extract selected information related to acetone concentration. A PLS quantitative model for acetone in transformers was established.

[0129] The model evaluation parameters are expressed as the correction correlation coefficient and the prediction correlation coefficient, and the root mean square error of correction (RMSECV) and the root mean square error of prediction (RMSEP) and MAPE are used to express the prediction ability of the model. The calculation formulas of RMSECV and RMSEP are as follows:

[0130]

[0131] Where n is the number of samples in the calibration set; yi is the reference measurement result of sample i, ∧yi is the estimated result of the i-th sample, and the model is established by excluding sample i.

[0132]

[0133] Where n is the number of samples in the prediction set, yi is the reference measurement result of the i-th sample in the prediction set, and y′ is the model's estimation result for the i-th sample in the prediction set.

[0134] When RMSECV, RMSEP and MAPE are smaller, and Rc and Rp are closer to 1, the analysis effect of the model is better. According to the minimum value of RMSECV, the optimal number of principal components (PCs) is selected through 10 cross-validations. Figure 5 As shown in the figure, RMSECV is minimized when the number of principal components is 5. Therefore, the optimal number of principal components selected in the experiment is 5. At this point, the PLS model established for the acetone spectrum produces Rc = 0.98227 and RMSECV = 0.214842 mg / g in the calibration set, and Rp = 0.980813 and RMSEP = 0.327962 mg / g in the prediction set. The fitting effect is excellent. This is because the full spectrum of acetone is used for fitting, which increases the accuracy of the fitting results.

[0135] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the scope of protection of the present invention. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the essence and scope of the technical solutions of the present invention.

Claims

1. A method for detecting acetone in transformer oil, characterized in that: The following steps are involved: (1) Prepare 8 groups of 6 different concentrations of acetone transformer oil solution standard gradient solutions and extract; (2) immersing the AgNWs surface enhanced substrate in the extracted standard gradient solution, collecting Raman spectra, and preprocessing the collected Raman spectra; (3) The PLS model was used to establish the statistical relationship between acetone content and spectral intensity. Six of the eight groups, totaling 32 samples, were used as training sets, and the remaining 16 samples were used as prediction sets. The corresponding spectral matrix and concentration matrix were imported into TheUnscrambler software as input variables. PLS regression analysis was performed using the PLS method to establish a PLS quantitative model for acetone in transformers. The preparation method of the AgNWs surface enhanced substrate comprises the following steps: soaking the gold-plated silicon wafer substrate in a 1,4-benzenedithiol solution, washing, and drying to obtain a thiol-plated gold-plated silicon wafer substrate; washing the silver nanowire solution, dispersing it with an ethanol solution, centrifuging it, and dispersing the precipitate with an ethanol solution again to obtain an ethanol dispersion of the silver nanowire solution; The thiol-coated gold-plated silicon wafer substrate is placed in an ethanol dispersion of a silver nanowire solution, allowed to stand, cleaned, and dried to obtain an AgNWs surface enhanced substrate.

2. The method for detecting acetone in transformer oil according to claim 1, wherein The standard gradient solutions of the transformer oil solution of acetone are 3950 mg / L, 1975 mg / L, 987 mg / L, 493 mg / L, 246 mg / L, 123 mg / L, and 61 mg / L respectively.

3. The detection method of acetone in transformer oil according to claim 1, wherein The preprocessing includes: eliminating baseline shift and drift, eliminating background noise interference, eliminating the influence of optical path change and surface scattering on the spectrum, improving spectral resolution, and enhancing spectral feature processing on the collected spectral data.

4. The detection method of acetone in transformer oil according to claim 1, wherein The size of the gold-plated silicon wafer is 0.01 to 100 cm 2 .

5. The detection method of acetone in transformer oil according to claim 1, wherein The molar concentration of the 1,4-benzenedithiol solution is 0.1 to 1 mol / L.

6. The method for detecting acetone in transformer oil according to claim 1, wherein The method for preparing the silver nanowire solution comprises the following steps: Use ethylene glycol solution as the reaction base liquid, heat it, add FeCl3 ethylene glycol solution and AgNO3 ethylene glycol solution in sequence, stir evenly, then add PVP ethylene glycol solution, stop heating, cool it, the solution turns gray-green, and a silver nanowire precursor solution is obtained; The silver nanowire precursor solution and deionized water are mixed evenly, centrifuged, and the precipitate is washed and dispersed in an ethanol solution to obtain a silver nanowire solution.

7. The method for detecting acetone in transformer oil according to claim 6, wherein The molar concentration of the FeCl3 ethylene glycol solution is 0.001 to 0.01 mol / L; and / or The molar concentration of the AgNO3 ethylene glycol solution is 0.1 to 1 mol / L; and / or The molar concentration of the PVP ethylene glycol solution is 0.1-1 mol / L.

8. The method for detecting acetone in transformer oil according to claim 6, wherein The volume ratio of the FeCl3 ethylene glycol solution, the AgNO3 ethylene glycol solution, and the PVP ethylene glycol solution is (1-10): (5-20): (20-80).

9. The method for detecting acetone in transformer oil according to any one of claims 1 to 8, characterized in that: The length of the silver nanowires in the silver nanowire solution is 20 to 30 μm, and the diameter is 15.6 nm to 65.6 nm.

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