Intelligent screening method and device for sulfur / sulfonate surfactants, and equipment

Abstract

This invention belongs to the field of daily chemical product testing and analysis technology. It discloses an intelligent screening method, device, equipment, and storage medium for sulfur / sulfonate surfactants. The method involves pretreatment of the sample and high-resolution mass spectrometry (UHPLC-MS / MS) scanning, converting the sample into an mzXML file. All secondary mass spectrometry peaks in the file are screened to identify target secondary mass spectrometry peaks containing characteristic ions. The mass and peak intensity of all corresponding precursor ions are extracted. If the mass difference between two precursor ions is within the range of sulfur isotope mass difference and the peak intensity ratio is within a specified range, the precursor ion with the lower mass is selected as the quasi-molecular ion. A predicted molecular formula is generated, and matching structural information is retrieved from a database. Simulated fragmentation is used to obtain a simulated secondary mass spectrum, which is compared with the actual secondary mass spectrum to determine the predicted structure and identify sulfur / sulfonate surfactants. This intelligent processing of high-resolution mass spectrometry data improves data processing efficiency, sensitivity, and accuracy.

Description

Technical Field

[0001] This invention belongs to the field of daily chemical product testing and analysis technology, specifically relating to an intelligent screening method, device, equipment, and storage medium for sulfur / sulfonate surfactants. Background Technology

[0002] Sulfonate surfactants have two distinct parts: a hydrophilic (water-soluble) head and a hydrophobic (lipophilic) tail. The hydrophilic head, composed of sulfonate groups, interacts with water molecules, allowing the surfactant molecule to dissolve in water. The hydrophobic tail, composed of long-chain fatty acids, repels water molecules, enabling the surfactant molecule to form a thin film on the water surface. This structure allows sulfonate surfactants to act as a bridge between water and oils. When sulfonate surfactant molecules form a film on the water surface, they encapsulate water molecules within the film, reducing the attraction between water molecules. This makes it easier for water to wet the surface and allows for better interaction with other substances, such as cleaning dirt or increasing foam. Therefore, sulfonate surfactants are widely used in daily life. For example, they are commonly found in personal care products such as shampoos, shower gels, toothpastes, and facial cleansers because they produce rich foam and effectively remove grease and dirt. They are also used in laundry detergents, dish soaps, and other cleaning products to enhance detergency.

[0003] However, their use also comes with some potential hazards. Especially at high concentrations or with prolonged exposure, these compounds can cause skin and eye irritation. Long-term use of products containing sulfur / sulfonate surfactants can lead to dry skin and hair because they remove natural oils. Furthermore, individuals sensitive to these chemicals may experience dermatitis or other allergic reactions. From an environmental perspective, although sulfur / sulfonate surfactants are relatively biodegradable, their extensive use in aquatic bodies could have negative impacts on aquatic ecosystems.

[0004] There are various methods for analyzing sulfonate surfactants, each with its limitations. Traditional methods include spectrophotometry, electrochemical methods, and chromatography. A common method is the Methylene Blue Active Substances (MBAS) assay, which involves the determination of anionic surfactant salts that form a blue color with methylene blue dye by spectrophotometry. However, these methods often lack sufficient selectivity to distinguish between different anionic groups or alkyl chain structures, making them unsuitable for detailed analysis of alkyl and alkoxy ether sulfonates in complex mixtures.

[0005] In recent years, with technological advancements, triple quadrupole tandem mass spectrometry (TQMS) has been used to analyze characteristic ions of sulfonates in Prec (precursor ion scanning) mode. The presence of sulfonate surfactants in a sample is determined by comparing the precursor ion information scanned in each scanning channel. However, current techniques suffer from low mass spectrometry resolution, leading to a high false positive rate. Furthermore, the acquired data baseline is too high, resulting in numerous extraneous peaks and insufficient sensitivity. Even after software processing, the acquired data still requires manual interpretation to obtain results. Additionally, the targeted screening technique using TQMS can only target known components and cannot cover the structurally diverse sulfonate surfactants. Summary of the Invention

[0006] The purpose of this invention is to provide an intelligent screening method, device, equipment, and storage medium for sulfur / sulfonate surfactants, which can realize intelligent processing of high-resolution mass spectrometry data, improve data processing efficiency, reduce reliance on manual labor, and at the same time improve sensitivity and accuracy while reducing the false positive rate.

[0007] The first aspect of this invention discloses an intelligent screening method for sulfur / sulfonate surfactants, comprising:

[0008] The sample to be tested is pretreated and scanned by ultra-high performance liquid chromatography and high resolution mass spectrometry to obtain the raw data of the sample.

[0009] The raw data is converted into an mzXML format file. All secondary mass spectrometry peaks in the mzXML format file are filtered to select the target secondary mass spectrometry peaks containing characteristic ions.

[0010] Extract the primary mass spectrometry data corresponding to the target secondary mass spectrometry peak from the mzXML format file. The primary mass spectrometry data includes the mass of all parent ions and the peak intensity.

[0011] Calculate the mass difference between the two precursor ions. If the mass difference between the two precursor ions is within the range of the mass difference of sulfur isotopes, calculate the peak intensity ratio of the potential contents of these two precursor ions.

[0012] If the peak intensity ratio is within the specified range, the parent ion with lower mass among the two parent ions will be selected as the quasi-molecular ion of the potential target compound.

[0013] Based on the mass of the quasi-molecular ion of the potential target compound, the predicted molecular formula of the potential target compound is generated according to the molecular formula partitioning rules, and the matching structural information is retrieved from the database based on the predicted molecular formula.

[0014] Based on the matched structural information, simulated fragmentation was performed to obtain a simulated second-order mass spectrum;

[0015] The simulated secondary mass spectrum is compared with the actual secondary mass spectrum of the quasi-molecular ion, and the predicted structure of the potential target compound is determined based on the comparison results.

[0016] Based on the actual secondary mass spectrum of the quasi-molecular ion, the potential target compound was identified as a sulfate surfactant or a sulfonate surfactant.

[0017] A second aspect of this invention discloses an intelligent screening device for sulfur / sulfonate surfactants, comprising:

[0018] The scanning unit is used for sample pretreatment and ultra-high performance liquid chromatography-high resolution mass spectrometry scanning to obtain the raw data of the sample.

[0019] The filtering unit is used to convert the raw data into an mzXML format file, filter all secondary mass spectrometry peaks in the mzXML format file, and select the target secondary mass spectrometry peaks containing characteristic ions.

[0020] The extraction unit is used to extract primary mass spectrometry data corresponding to the target secondary mass spectrometry peak from the mzXML format file. The primary mass spectrometry data includes the mass and peak intensity of all parent ions.

[0021] The calculation unit is used to calculate the mass difference between two precursor ions. If the mass difference between the two precursor ions is within the range of sulfur isotope mass difference, the peak intensity ratio of the potential contents of these two precursor ions is calculated.

[0022] The selection unit is used to select the lower-mass parent ion of the two parent ions as the quasi-molecular ion of the potential target compound if the peak intensity ratio is within a specified ratio range.

[0023] The generation unit is used to generate a predicted molecular formula of the potential target compound according to the mass of the quasi-molecular ion and the molecular formula distribution rules, and to retrieve matching structural information from the database based on the predicted molecular formula.

[0024] The simulation unit is used to simulate fragmentation based on the matched structural information to obtain a simulated secondary mass spectrum.

[0025] The comparison unit is used to compare the simulated secondary mass spectrum with the actual secondary mass spectrum of the quasi-molecular ion, and to determine the predicted structure of the potential target compound based on the comparison results;

[0026] The identification unit is used to identify potential target compounds as sulfate surfactants or sulfonate surfactants based on the actual secondary mass spectrum of the quasi-molecular ion.

[0027] A third aspect of the present invention discloses an electronic device, including a memory storing executable program code and a processor coupled to the memory; the processor calls the executable program code stored in the memory to execute the intelligent screening method for sulfur / sulfonate surfactants disclosed in the first aspect.

[0028] The fourth aspect of the present invention discloses a computer-readable storage medium storing a computer program, wherein the computer program causes a computer to execute the intelligent screening method for sulfur / sulfonate surfactants disclosed in the first aspect.

[0029] The beneficial effects of this invention are as follows: Raw data of the sample is obtained by mass spectrometry scanning; the raw data is converted into an mzXML file; all secondary mass spectrometry peaks in the file are filtered to select target secondary mass spectrometry peaks containing characteristic ions; primary mass spectrometry data corresponding to the target secondary mass spectrometry peaks is extracted, including the mass and peak intensity of all precursor ions; the mass difference between two precursor ions is calculated; if the mass difference between the two precursor ions is within the range of sulfur isotope mass difference, the peak intensity ratio of the potential precursor ions is calculated; if the peak intensity ratio is within a specified range, the precursor ion with the lower mass is selected. As a quasi-molecular ion for potential target compounds, based on the mass of the quasi-molecular ion and according to molecular formula distribution rules, a predicted molecular formula is generated. Matching structural information is retrieved from a database, and simulated fragmentation is performed based on this matching structural information to obtain a simulated secondary mass spectrum. This simulated secondary mass spectrum is compared with the actual secondary mass spectrum of the quasi-molecular ion to determine the predicted structure of the potential target compound. Based on the actual secondary mass spectrum of the quasi-molecular ion, the potential target compound is identified as a sulfate surfactant or a sulfonate surfactant. This enables intelligent processing of high-resolution mass spectrometry data, improving data processing efficiency, reducing manual reliance, and simultaneously increasing sensitivity and accuracy while reducing false positive rates. Furthermore, by setting the sulfur isotope mass difference range and specifying peak intensity ratio ranges, the efficiency of non-target screening can be effectively improved in large mass spectrometry datasets. In addition, the precise mass measurement of high-resolution mass spectrometry further ensures the certainty of the compound's molecular formula, significantly reducing the probability of potential compound structures. Moreover, combining secondary mass spectrometry data and simulated fragmentation secondary mass spectrometry analysis simplifies the compound structure identification process. This invention is widely applicable to the identification of sulfur / sulfonate surfactants, expanding the screening scope. Attached Figure Description

[0030] The accompanying drawings illustrate specific examples of the technical solutions described in this invention and, together with the detailed embodiments, form part of the specification, serving to explain the technical solutions, principles, and effects of this invention.

[0031] Unless otherwise specified or defined, the same reference numerals in different figures represent the same or similar technical features, and different reference numerals may be used to represent the same or similar technical features.

[0032] Figure 1 This is a flowchart of an intelligent screening method for sulfur / sulfonate surfactants disclosed in an embodiment of the present invention;

[0033] Figure 2 This is the secondary chromatogram of the characteristic ion m / z = 79.9567 disclosed in the embodiments of the present invention in an R language data processing program;

[0034] Figures 3 to 5 This is a schematic diagram of the structures of the three potential quasi-molecular ions disclosed in the embodiments of the present invention;

[0035] Figure 6 This is a schematic diagram of the structure of an intelligent screening device for sulfur / sulfonate surfactants disclosed in an embodiment of the present invention;

[0036] Figure 7 This is a schematic diagram of the structure of an electronic device disclosed in an embodiment of the present invention.

[0037] Explanation of reference numerals in the attached figures:

[0038] 601. Scanning unit; 602. Filtering unit; 603. Extraction unit; 604. Calculation unit; 605. Selection unit; 606. Generation unit; 607. Simulation unit; 608. Comparison unit; 609. Recognition unit; 701. Memory; 702. Processor. Detailed Implementation

[0039] Unless otherwise specified or defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art. When combined with the technical solutions of the invention in a real-world scenario, all technical and scientific terms used herein may also have meanings corresponding to the purpose of achieving the technical solutions of the invention. The terms "first," "second," etc., used herein are merely for distinguishing names and do not represent a specific number or order. The term "and / or," as used herein, includes any and all combinations of one or more of the associated listed items.

[0040] It should be noted that when a component is considered "fixed" to another component, it can be directly fixed to the other component or there can be an intervening component; when a component is considered "connected" to another component, it can be directly connected to the other component or there can be an intervening component; when a component is considered "mounted" on another component, it can be directly mounted on the other component or there can be an intervening component; when a component is considered "placed" on another component, it can be directly placed on the other component or there can be an intervening component.

[0041] Unless otherwise specified or defined, the terms "described" or "the" as used herein refer to the technical features or technical content mentioned or described prior to the relevant section, which may be the same as or similar to the technical features or technical content mentioned herein. Furthermore, the terms "comprising" and "having," and any variations thereof, as used herein, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the steps or units listed, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to such processes, methods, products, or apparatus.

[0042] This invention discloses an intelligent screening method for sulfur / sulfonate surfactants, which can be implemented through computer programming. The executing entity of this method can be an electronic device such as a computer, laptop, or tablet, or an intelligent screening device for sulfur / sulfonate surfactants (hereinafter referred to as an intelligent screening device) embedded in an electronic device; this invention does not limit this. The electronic device or intelligent screening device contains executable program code, which is invoked to execute the intelligent screening method for sulfur / sulfonate surfactants. To facilitate understanding of this invention, specific embodiments will be described in more detail below with reference to the accompanying drawings. Figure 1 As shown, the method includes the following steps 110-180:

[0043] 110. Perform mass spectrometry scanning on the sample to be tested to obtain the raw data of the sample.

[0044] To screen out as many sulfur / sulfonate surfactants as possible, the pretreatment process of all samples will minimize losses. First, methanol is mixed with the sample, vortexed and then sonicated for 10-15 minutes. After cooling to room temperature, the sample is filtered through a 0.22μm filter membrane to prepare the sample for testing.

[0045] Then, the ultra-high performance liquid chromatography (UPLC) coupled with high resolution mass spectrometry (HRMS) was used to scan the sample under preset mass spectrometry conditions. These preset conditions included selecting a cyano column, using Full-scan / AIF mode, and selecting negative ion mode. The chromatographic and mass spectrometric data of the sample were acquired under these preset conditions in RAW file format, also known as raw data.

[0046] Among these advancements, the use of polar-selective cyano columns based on sulfur / sulfonate surfactants can significantly improve chromatographic separation and enhance identification accuracy. Furthermore, combining ultra-high performance liquid chromatography with high-resolution mass spectrometry (UPLC-HRMS) can improve the identification accuracy of sulfur / sulfonate surfactants and reduce false positives.

[0047] In some embodiments, the preset mass spectrometry conditions further include:

[0048] H-ESI ion source, negative ion detection mode;

[0049] Spray voltage: 2500V;

[0050] Sheath gas: Nitrogen, flow rate 45 Arb;

[0051] Assist gas: nitrogen, flow rate 11 Arb, temperature 300℃;

[0052] Purge gas: Nitrogen 0Arb;

[0053] Ion transfer tube temperature: 350℃;

[0054] Evaporation temperature: 300℃;

[0055] S-lens RF level: 50;

[0056] Full-scan scan range: 75-1125 Da;

[0057] AIF scan range: 50-200 Da.

[0058] 120. Convert the raw data into an mzXML format file, filter all secondary mass spectrometry peaks in the mzXML format file, and select the target secondary mass spectrometry peaks containing characteristic ions.

[0059] In this embodiment of the invention, an R language data processing program is used to perform data processing. To facilitate the import of raw data into R Studio software and to perform data filtering using the R language data processing program, the raw data needs to be converted into an mzXML format file. To achieve the purpose of this invention, the R language packages used include xcms, mzR, faahko, pander, MSnbase, magrittr, dplyr, BiocStyle, and RMSPeak. Specifically, the ProteoWizard-MSConvert software can be used to convert the raw data into an mzXML format file, and then imported into R Studio software for data filtering.

[0060] Among them, the sulfonic acid group and the sulfate group in the hydrophilic head of the sulfur / sulfonate surfactant are its functional groups, so the fragment ion [SO3] with a mass-to-charge ratio of m / z = 79.9567 can be set. - Fragment ions [HSO4] with m / z = 96.9588 - As the characteristic ion, the target secondary mass spectrum peak containing the characteristic ion is selected by screening and filtering the secondary mass spectrum peaks.

[0061] 130. Extract the primary mass spectrometry data corresponding to the target secondary mass spectrometry peak from the mzXML format file. The primary mass spectrometry data includes the mass and peak intensity of all parent ions.

[0062] First, the time corresponding to the target secondary mass spectrometry peak containing the characteristic ion is determined. Then, all the parent ion information in the primary mass spectrometry peak within the corresponding time period, namely the mass and peak intensity of the parent ion, are selected as primary mass spectrometry data.

[0063] 140. Iterate through all the parent ions and combine them in pairs. Calculate the mass difference between each pair of parent ions. If the mass difference between the two parent ions is within the range of sulfur isotope mass difference, calculate the peak intensity ratio of the two parent ions. If the peak intensity ratio is within the specified range, select the parent ion with the lower mass as the quasi-molecular ion of the potential target compound.

[0064] It should be noted that, according to the provisions of Commission Decision 2002 / 657 / EC of 12 August 2002 implementing Council Directive 96 / 23 / EC concerning the performance of analytical methods and the interpretation of result, regarding mass spectrometry identification, the maximum permissible limit for a relative ion peak intensity ratio below 10% is ±50%, and the theoretical value of the sulfur isotope mass difference is 1.99580. Therefore, in this embodiment of the invention, the sulfur isotope mass difference range is set to [1.99475, 1.99685]. However, due to... 34 S and 32 The relative peak intensity ratio of S is 4.52%, and the set value should be 4.52% ± 50%, that is, the specified peak intensity ratio range is set to [2.26%, 6.78%]. Therefore, the precursor ions can be further filtered and screened using the isotopic mass difference range of sulfur. If the mass difference between the two precursor ions is within the range of [1.99475, 1.99685], the next step isotopic ratio test is performed, that is, the peak intensity ratio of the potential precursor ions containing these two precursor ions is calculated. If the peak intensity ratio is within [2.26%, 6.78%], the precursor ion with the lower mass is selected as the quasi-molecular ion. Here, the peak intensity ratio of the two precursor ions refers to the ratio obtained by dividing the peak intensity of the precursor ion with the higher mass by the peak intensity of the precursor ion with the lower mass.

[0065] In this embodiment of the invention, the quasi-molecular ions that meet the criteria selected by a computer program are shown in Table 1 below.

[0066] Table 1 shows the quasi-molecular ions that meet the screening criteria.

[0067]

[0068] 150. Based on the mass of the quasi-molecular ion of the potential target compound, generate the predicted molecular formula of the potential target compound according to the molecular formula partitioning rules, and retrieve the matching structural information from the database based on the predicted molecular formula.

[0069] Specifically, the mass of the quasi-molecular ion can be input into Xcalibur software, and a predicted molecular formula of the potential target compound can be generated according to a defined molecular formula allocation rule. In this embodiment of the invention, the defined molecular formula allocation rule is: C 0-100 H 0-100 O 3-100 N 0-3 S1-2 The reason for this is that the purpose of this invention is to find sulfur / sulfonate surfactants, therefore the theoretical molecular formula should have more than 3 oxygen atoms. At the same time, attention should be paid to the parameter settings in the Xcalibur software; for example, the charge should be set to negative, and the degree of unsaturation (RDBE) should be greater than 0.5, because the unsaturation of sulfuric acid sulfonate ions is 0.5, while the error range is 5 ppm.

[0070] By searching the predicted molecular formula in the PubChem database, matching structural information (International Chemical Identifier, InChI) is obtained, which is the possible structural formula.

[0071] 160. Based on the matched structural information, simulated fragmentation is performed to obtain a simulated secondary mass spectrum.

[0072] The simulated fragmentation can employ one or more methods, resulting in simulated secondary mass spectra that can also include one or more fragments. Specifically, the InChI structural information is imported into Mass Froniter software and / or the CFM-ID website for simulated fragmentation to obtain simulated secondary mass spectra. These spectra include simulated fragment ion information such as structure, precise mass, and fragmentation pathway. When using Mass Froniter software, it is important to select the negative ion mode. Furthermore, when simulating fragmentation on the CFM-ID website, since the original data was obtained in negative ion mode, the ion source should be an ESI source.

[0073] 170. Compare the simulated secondary mass spectrum with the actual secondary mass spectrum of the quasi-molecular ion, and determine the predicted structure of the potential target compound based on the comparison results.

[0074] After simulated fragmentation, the simulated second-order mass spectrum of each quasi-molecular ion is compared with the actual second-order mass spectrum of the quasi-molecular ion. The predicted structure of the potential target compound is determined based on the comparison results. When there are multiple simulated second-order mass spectra of the quasi-molecular ion, each simulated second-order mass spectrum needs to be compared with the actual second-order mass spectrum. Specifically, the comparison result is the number of mass peak matches. The simulated second-order mass spectrum of each quasi-molecular ion is compared with the actual second-order mass spectrum of the quasi-molecular ion to count the number of mass peak matches between the simulated and actual second-order mass spectra of each quasi-molecular ion. The structure information corresponding to the quasi-molecular ion with the highest number of mass peak matches is determined as the predicted structure of the potential target compound. The structure with the highest number of mass peak matches indicates that the structure best matches the actual situation.

[0075] To obtain the actual secondary mass spectrum of the quasi-molecular ions of the potential target compounds, the samples will be re-analyzed using ultra-high performance liquid chromatography coupled with high resolution mass spectrometry (UPLC-HRMS). The mass spectrometry conditions will be reset to Parallel reaction monitoring (PRM) mode, while the ionization mode will remain negative ion mode. The mass of the potential quasi-molecular ions will then be imported into the UPLC-HRMS inclusion list.

[0076] Specifically, actual fragment ion information can be obtained through the following method: importing the mass of the quasi-molecular ion of the potential target compound into the inclusion list of UPLC-HRMS to obtain the actual secondary mass spectrum of the quasi-molecular ion of the potential target compound in PRM mode.

[0077] 180. Based on the actual secondary mass spectrum of the quasi-molecular ion, identify the potential target compound as a sulfate surfactant or a sulfonate surfactant.

[0078] Specifically, if the actual secondary mass spectrum of the quasi-molecular ion contains both a pre-defined first fragment ion and a second fragment ion, the potential target compound is a sulfate surfactant. If the actual secondary mass spectrum of the quasi-molecular ion contains only the pre-defined first fragment ion and not the second fragment ion, the potential target compound is a sulfonate surfactant. The pre-defined first fragment ion refers to the fragment ion with m / z = 79.9567, and the second fragment ion refers to the fragment ion with m / z = 96.9588. Finally, the identification results of the target compound as either a sulfate surfactant or a sulfonate surfactant, along with their predicted structures, are output as screening results. By predicting the structure, a possible structural formula can be provided in addition to identifying sulfur / sulfonate surfactants, making the identification more accurate.

[0079] In a real-world sample case, the raw data file obtained by the instrument was converted to an mzXML format file using ProteoWizard-MSConvert software. This file was then imported into an R language data processing program for screening, yielding information on 20 potential quasi-molecular ions (including retention time, precise mass, and peak intensity). First, a secondary chromatogram of the characteristic ion with m / z = 79.9567 was obtained, as shown below. Figure 2 As shown.

[0080] The peak times of characteristic ions are obtained by chromatogram. In this invention, the centwave function in the xcms package of R language is used to obtain a total of 6 peaks. Then, the primary mass spectrometry data corresponding to the times of these 6 peaks are screened and filtered.

[0081] Taking one peak as an example, this peak has information on 818 precursor ions (including precise mass and peak intensity). The precursor ions are further filtered using the sulfur isotope mass difference of 1.99475-1.99685. Finally, the peak intensity ratio of the two precursor ions containing sulfur isotopes is calculated. If the ratio is between 2.26% and 6.78%, the precursor ion with the smaller mass is selected as the quasi-molecular ion. Ultimately, three precursor ions are selected from the 818 precursor ions as quasi-molecular ions for potential target compounds, with masses of 309.1742, 297.153, and 265.1479, respectively. The masses of the quasi-molecular ions are then used in Xcalibur software for molecular formula allocation, following the established allocation rule of C... 0-100 H 0-100 O 3-100 N 0-3 S 1-2 The charge was chosen to be negative, with an unsaturation degree (RDBE) greater than 0.5 and an error range of 5 ppm. The final molecular formulas obtained were C0. 14 H 29 O5S, C 16 H 25 O3S, C 12 H 25 O4S uses the obtained molecular formula to search for possible molecular structures on the Pubchem website.

[0082] The InChI molecules containing structural information were imported into Mass Froniter software and / or the CFM-ID website for simulated fragmentation to obtain potential fragment ion information, i.e., simulated secondary mass spectra. The masses of the obtained potential quasi-molecular ions were imported into the inclusion list, and the actual secondary mass spectra of the sample were obtained in PRM mode of the instrument's UPLC-HRMS.

[0083] The actual obtained secondary mass spectrometry information was matched with the secondary mass spectrometry information simulated by MassFroniter software and / or the CFM-ID website to determine the predicted structures of the three potential precursor ions, such as... Figures 3 to 5 As shown. Furthermore, based on their actual secondary mass spectra, their categories are sulfate, sulfonate, and sulfonate, respectively.

[0084] The above steps were repeated, and all peaks were analyzed. A total of 19 sulfur / sulfonate compounds were ultimately found in this sample, and their details are shown in Table 2 below.

[0085] Table 2. Basic information on the compounds obtained from this sample.

[0086]

[0087]

[0088] In addition, 20 products were selected as research subjects. These were mainly personal care products such as shampoos, shower gels, and facial cleansers. Ten products had labels indicating the use of sulfur / sulfonate surfactants, and were designated as positive samples. The other ten samples did not indicate the use of sulfur / sulfonate surfactants, and were designated as negative samples. Screening using this method revealed that some positive samples, despite only indicating the presence of sodium lauryl sulfate or sodium laureth sulfate on their labels, contained various other sulfur / sulfonate surfactants. Low levels of sulfur / sulfonate surfactants were also found in the negative samples. A total of 38 sulfur / sulfonate surfactant compounds were ultimately identified. The results are shown in Table 3 below.

[0089] Table 338 sulfur / sulfonate surfactant compounds

[0090]

[0091]

[0092]

[0093] like Figure 6 As shown, this embodiment of the invention discloses an intelligent screening device for sulfur / sulfonate surfactants, comprising:

[0094] The scanning unit 601 is used to perform pretreatment and ultra-high performance liquid chromatography-high resolution mass spectrometry scanning on the sample to be tested to obtain the raw data of the sample to be tested.

[0095] The filtering unit 602 is used to convert the raw data into an mzXML format file, filter all secondary mass spectrometry peaks in the mzXML format file, and select the target secondary mass spectrometry peaks containing characteristic ions.

[0096] Extraction unit 603 is used to extract primary mass spectrometry data corresponding to the target secondary mass spectrometry peak from an mzXML format file. The primary mass spectrometry data includes the mass and peak intensity of all parent ions.

[0097] The calculation unit 604 is used to calculate the mass difference between two precursor ions. If the mass difference between the two precursor ions is within the range of sulfur isotope mass difference, the peak intensity ratio of the potential precursor ions is calculated.

[0098] Selecting unit 605 is used to select the lower-mass parent ion of the two parent ions as the quasi-molecular ion of the potential target compound if the peak intensity ratio is within a specified ratio range.

[0099] The generation unit 606 is used to generate a predicted molecular formula of the potential target compound according to the mass of the quasi-molecular ion of the potential target compound and the molecular formula distribution rules, and to retrieve matching structural information from the database based on the predicted molecular formula.

[0100] Simulation unit 607 is used to simulate fragmentation based on the matched structural information to obtain a simulated secondary mass spectrum;

[0101] The comparison unit 608 is used to compare the simulated secondary mass spectrum with the actual secondary mass spectrum of the quasi-molecular ion, and to determine the predicted structure of the potential target compound based on the comparison results.

[0102] The recognition unit 609 is used to identify potential target compounds as sulfate surfactants or sulfonate surfactants based on the actual secondary mass spectrum of the quasi-molecular ion.

[0103] Optionally, an acquisition unit (not shown) is also included, which is used to import the mass of the quasi-molecular ion of the potential target compound into the inclusion list of UPLC-HRMS before the comparison unit compares the simulated secondary mass spectrum with the actual secondary mass spectrum of the quasi-molecular ion, so as to acquire the actual secondary mass spectrum of the quasi-molecular ion of the potential target compound in PRM mode.

[0104] Optionally, the identification unit is specifically used to determine that the potential target compound is a sulfate surfactant when a preset first fragment ion and a preset second fragment ion are present simultaneously in the actual secondary mass spectrum of the quasi-molecular ion; and to determine that the potential target compound is a sulfonate surfactant when only the preset first fragment ion is present in the actual secondary mass spectrum of the quasi-molecular ion and the second fragment ion is not present.

[0105] Optionally, the first fragment ion refers to the fragment ion with m / z = 79.9567, and the second fragment ion refers to the fragment ion with m / z = 96.9588.

[0106] like Figure 7 As shown, an embodiment of the present invention discloses an electronic device, including a memory 701 storing executable program code and a processor 702 coupled to the memory 701;

[0107] The processor 702 calls the executable program code stored in the memory 701 to execute the intelligent screening method for sulfur / sulfonate surfactants described in the above embodiments.

[0108] This invention also discloses a computer-readable storage medium storing a computer program that causes a computer to execute the intelligent screening method for sulfur / sulfonate surfactants described in the above embodiments.

[0109] The purpose of the above embodiments is to reproduce and derive the technical solution of the present invention by way of example, and to fully describe the technical solution, purpose and effect of the present invention. The purpose is to enable the public to have a more thorough and comprehensive understanding of the disclosure of the present invention, and not to limit the scope of protection of the present invention.

[0110] The above embodiments are not an exhaustive list based on the present invention, and there may be many other embodiments not listed. Any substitutions and improvements made without departing from the concept of the present invention are within the protection scope of the present invention.

Claims

1. An intelligent screening method for sulfur / sulfonate surfactants, characterized in that, include: The sample to be tested is pretreated and scanned by ultra-high performance liquid chromatography and high resolution mass spectrometry to obtain the raw data of the sample. The raw data is converted into an mzXML format file. All secondary mass spectrometry peaks in the mzXML format file are filtered to select the target secondary mass spectrometry peaks containing characteristic ions. Extract the primary mass spectrometry data corresponding to the target secondary mass spectrometry peak from the mzXML format file. The primary mass spectrometry data includes the mass of all parent ions and the peak intensity. Calculate the mass difference between the two precursor ions. If the mass difference between the two precursor ions is within the range of the mass difference of sulfur isotopes, calculate the peak intensity ratio of the potential contents of these two precursor ions. If the peak intensity ratio is within the specified range, the parent ion with lower mass among the two parent ions will be selected as the quasi-molecular ion of the potential target compound. Based on the mass of the quasi-molecular ion of the potential target compound, the predicted molecular formula of the potential target compound is generated according to the molecular formula partitioning rules, and the matching structural information is retrieved from the database based on the predicted molecular formula. Based on the matched structural information, simulated fragmentation was performed to obtain a simulated second-order mass spectrum; The simulated secondary mass spectrum is compared with the actual secondary mass spectrum of the quasi-molecular ion, and the predicted structure of the potential target compound is determined based on the comparison results. Based on the actual secondary mass spectrum of the quasi-molecular ion, the potential target compound was identified as a sulfate surfactant or a sulfonate surfactant.

2. The intelligent screening method for sulfur / sulfonate surfactants as described in claim 1, characterized in that, Before comparing the simulated secondary mass spectrum with the actual secondary mass spectrum of the quasi-molecular ion, the method further includes: The mass of the quasi-molecular ion of the potential target compound is imported into the inclusion list of UPLC-HRMS to obtain the actual secondary mass spectrum of the quasi-molecular ion of the potential target compound in PRM mode.

3. The intelligent screening method for sulfur / sulfonate surfactants as described in claim 1, characterized in that, Based on the actual secondary mass spectrum of the quasi-molecular ion, potential target compounds were identified as sulfate surfactants or sulfonate surfactants, including: If the actual secondary mass spectrum of the quasi-molecular ion contains both the pre-defined first fragment ion and the second fragment ion, the potential target compound is determined to be a sulfate surfactant. If the actual secondary mass spectrum of the quasi-molecular ion only contains the preset first fragment ion and not the second fragment ion, the potential target compound is determined to be a sulfonate surfactant.

4. The intelligent screening method for sulfur / sulfonate surfactants as described in claim 3, characterized in that, The first fragment ion refers to the fragment ion with m / z = 79.9567, and the second fragment ion refers to the fragment ion with m / z = 96.9588.

5. An intelligent screening device for sulfur / sulfonate surfactants, characterized in that, include: The scanning unit is used for sample pretreatment and ultra-high performance liquid chromatography-high resolution mass spectrometry scanning to obtain the raw data of the sample. The filtering unit is used to convert the raw data into an mzXML format file, filter all secondary mass spectrometry peaks in the mzXML format file, and select the target secondary mass spectrometry peaks containing characteristic ions. The extraction unit is used to extract primary mass spectrometry data corresponding to the target secondary mass spectrometry peak from the mzXML format file. The primary mass spectrometry data includes the mass and peak intensity of all parent ions. The calculation unit is used to calculate the mass difference between two precursor ions. If the mass difference between the two precursor ions is within the range of sulfur isotope mass difference, the peak intensity ratio of the potential contents of these two precursor ions is calculated. The selection unit is used to select the lower-mass parent ion of the two parent ions as the quasi-molecular ion of the potential target compound if the peak intensity ratio is within a specified ratio range. The generation unit is used to generate a predicted molecular formula of the potential target compound according to the mass of the quasi-molecular ion and the molecular formula distribution rules, and to retrieve matching structural information from the database based on the predicted molecular formula. The simulation unit is used to simulate fragmentation based on the matched structural information to obtain a simulated secondary mass spectrum. The comparison unit is used to compare the simulated secondary mass spectrum with the actual secondary mass spectrum of the quasi-molecular ion, and to determine the predicted structure of the potential target compound based on the comparison results; The identification unit is used to identify potential target compounds as sulfate surfactants or sulfonate surfactants based on the actual secondary mass spectrum of the quasi-molecular ion.

6. The intelligent screening device for sulfur / sulfonate surfactants as described in claim 5, characterized in that, Also includes: The acquisition unit is used to import the mass of the quasi-molecular ion of the potential target compound into the inclusion list of UPLC-HRMS before the comparison unit compares the simulated secondary mass spectrum with the actual secondary mass spectrum of the quasi-molecular ion, so as to acquire the actual secondary mass spectrum of the quasi-molecular ion of the potential target compound in PRM mode.

7. The intelligent screening device for sulfur / sulfonate surfactants as described in claim 5, characterized in that, The identification unit is specifically used to determine that the potential target compound is a sulfate surfactant when a preset first fragment ion and a preset second fragment ion are present simultaneously in the actual secondary mass spectrum of the quasi-molecular ion; and to determine that the potential target compound is a sulfonate surfactant when only the preset first fragment ion is present in the actual secondary mass spectrum of the quasi-molecular ion and no second fragment ion is present.

8. The intelligent screening device for sulfur / sulfonate surfactants as described in claim 7, characterized in that, The first fragment ion refers to the fragment ion with m / z = 79.9567, and the second fragment ion refers to the fragment ion with m / z = 96.9588.

9. An electronic device, characterized in that, It includes a memory storing executable program code and a processor coupled to the memory; the processor calls the executable program code stored in the memory to execute the intelligent screening method for sulfur / sulfonate surfactants according to any one of claims 1 to 4.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, wherein the computer program causes a computer to perform the intelligent screening method for sulfur / sulfonate surfactants according to any one of claims 1 to 4.

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