Mass spectrometer chromatograph coupling mass analysis method and system

Abstract

This invention relates to the field of instrumental analysis technology, and discloses a method and system for mass spectrometry-chromatograph-integrated material analysis. The method includes: introducing the sample to be tested into a chromatograph for separation; during the separation process, monitoring the chromatographic elution curve of the chromatograph in real time, and extracting the resolution parameter and peak shape symmetry parameter of the characteristic peaks in the chromatographic elution curve; performing trend extrapolation on the resolution parameter and peak shape symmetry parameter to obtain the elution resistance trend; adjusting the separation and elution conditions of the chromatograph according to the elution resistance trend to generate an eluent, and introducing the eluent into the ion source of the mass spectrometer; separating the components in the eluent by ion mobility to obtain mass spectrometry signal data; performing pattern coupling recognition on the chromatographic signal data and the mass spectrometry signal data to obtain the chemical structure of the components; and generating a material analysis report based on the chemical structure of the components. This invention can improve the efficiency of mass spectrometry-chromatograph-integrated material analysis.

Description

Technical Field

[0001] This invention relates to the field of instrumental analysis technology, and in particular to a method and system for combined mass spectrometry and chromatography analysis. Background Technology

[0002] In traditional mass spectrometry and chromatography-linked analytical methods, separation and elution conditions are often preset and fixed, lacking the ability to sense and dynamically adjust key parameters during sample separation in real time. Because different analytes have varying component compositions, fixed separation conditions are difficult to adapt to complex elution behaviors, often leading to incomplete separation of characteristic peaks and peak shape distortion in the chromatographic elution curve. This interferes with subsequent parameter extraction and trend analysis, reducing the reliability of the overall analytical process.

[0003] In existing technologies, the fusion analysis of chromatographic and mass spectrometric signals often relies on single-dimensional feature matching, failing to fully explore the temporal correlation and spectral complementarity between the two types of data. This makes matching biases prone to occur during the identification of component chemical structures, and redundant steps exist in the data processing stage, resulting in a long overall process from sample separation to analysis report generation, which is difficult to meet the actual needs of efficient substance analysis. Therefore, how to improve the efficiency of mass spectrometry and chromatographic-linked substance analysis has become an urgent problem to be solved. Summary of the Invention

[0004] This invention provides a method and system for combined mass spectrometry and chromatography for substance analysis, in order to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides a mass spectrometer-chromatograph linked material analysis method, comprising: S1. The sample to be tested is introduced into the chromatograph for separation. During the separation process, the chromatographic elution curve of the chromatograph is monitored in real time, and the resolution parameter and peak shape symmetry parameter of the characteristic peak in the chromatographic elution curve are extracted. S2. Perform trend extrapolation between the resolution parameter and the peak shape symmetry parameter to obtain the elution resistance trend of the sample to be tested; S3. Based on the elution resistance trend, adjust the separation and elution conditions of the chromatograph to generate the effluent of the sample to be tested, and introduce the effluent into the ion source of the mass spectrometer; S4. In the ion source, the components in the effluent are separated by ion mobility to obtain the mass spectrometry signal data of the effluent; S5. Perform pattern coupling recognition on the chromatographic signal data of the chromatograph and the mass spectrometry signal data to obtain the chemical structure of the components of the effluent; S6. Based on the chemical structure of the components, generate a material analysis report for the sample to be tested.

[0006] In a preferred embodiment, the step of introducing the sample to be tested into the chromatograph for separation includes, during the separation process, real-time monitoring of the chromatographic elution curve of the chromatogram, and extraction of the resolution parameter and peak shape symmetry parameter of the characteristic peaks in the chromatographic elution curve, including: The sample to be tested is introduced into the chromatograph for separation, and the time-domain response signal output by the chromatograph during the separation process is obtained; Baseline fitting is performed on the time-domain response signal to obtain the chromatographic elution curve of the chromatograph; Based on the differential change information of the chromatographic elution curve, identify the characteristic peaks in the chromatographic elution curve; The peak position and peak width features of the characteristic peaks are analyzed by Gaussian fitting to obtain the separation parameters of the characteristic peaks. Based on the morphological characteristics of the leading edge and trailing edge of the characteristic peak, the peak shape symmetry parameters of the characteristic peak are extracted.

[0007] In a preferred embodiment, the step of trend extrapolating the separation degree parameter and the peak shape symmetry parameter to obtain the elution resistance trend of the sample to be tested includes: Based on the order of appearance of the characteristic peaks, the resolution parameter and the peak shape symmetry parameter are structurally recombined to obtain the resolution parameter sequence and peak shape symmetry parameter sequence of the sample to be tested; The resolution parameter sequence and the peak shape symmetry parameter sequence are normalized and integrated to obtain the comprehensive trend index of the sample to be tested. The elution behavior evolution curve of the sample to be tested is obtained by performing time series fitting on the comprehensive trend index. The slope and curvature characteristics of the elution behavior evolution curve are used to determine the trend of the elution resistance of the sample to be tested.

[0008] In a preferred embodiment, the formula for calculating the comprehensive trend index is as follows: ; In the formula, For the first A comprehensive trend index of characteristic peaks For the first The separation parameter of each characteristic peak, The arithmetic mean of the separation parameter sequence is given. For the first The peak shape symmetry parameters of each characteristic peak. The median of the peak shape symmetry parameter sequence. This is the preset peak shape consistency tolerance factor. denoted as the standard deviation of the peak shape symmetry parameter sequence.

[0009] In a preferred embodiment, adjusting the separation and elution conditions of the chromatograph according to the elution resistance trend to generate the eluent of the sample to be tested, and introducing the eluent into the ion source of the mass spectrometer, includes: The direction and intensity of the separation efficiency change indicated by the elution resistance trend were analyzed. The direction and intensity of the change in separation efficiency are mapped by instructions to obtain the optimization adjustment instructions for the chromatograph; Based on the optimization and adjustment instructions, the elution gradient program and column oven temperature of the chromatograph are dynamically adjusted to obtain the updated separation and elution conditions of the chromatograph. The sample to be tested continues to be separated under the updated separation and elution conditions. When the chromatographic peak shape and resolution monitored in real time reach the preset standard, the fraction collection of the chromatograph is triggered to generate the effluent of the sample to be tested. The effluent is introduced into the ion source of the mass spectrometer.

[0010] In a preferred embodiment, the step of performing ion mobility separation on the components in the effluent in the ion source to obtain mass spectrometry signal data of the effluent includes: In the ion source, the effluent is subjected to electrospray ionization to obtain the effluent quasi-molecular ion cluster; Based on the collision cross section of the quasi-molecular ion group, ion mobility spectrum separation is performed in a buffer gas and a uniform electric field to obtain the ion sequence of the effluent; The ion sequence is digitized to obtain the original mobility spectrum signal of the ion sequence; The original mobility spectrum signal is deconvolved to obtain the mass spectrum signal data of the effluent.

[0011] In a preferred embodiment, the step of performing pattern coupling recognition between the chromatographic signal data of the chromatogram and the mass spectrometry signal data to obtain the component chemical structure of the eluent includes: The chromatographic signal data of the chromatogram are extracted by retention time to obtain the chromatographic retention characteristics of the effluent; Mass spectrometry peak detection is performed on the mass spectrometry signal data to obtain the mass spectrometry characteristics of the effluent; Based on the temporal correlation between the chromatographic retention features and the mass spectrometry features, the chromatographic retention features and the mass spectrometry features are cross-correlated and aligned to obtain the matching feature pairs of the effluent; The matching feature pairs are compared with the pre-stored standard spectral library to obtain the candidate chemical structures of the effluent; The spectral consistency and chromatographic behavior of the candidate chemical structures are comprehensively evaluated to obtain the component chemical structures of the effluent.

[0012] In a preferred embodiment, the step of comprehensively evaluating the spectral consistency and chromatographic behavior of the candidate chemical structures to obtain the component chemical structures of the effluent includes: Based on a preset matching threshold, the candidate chemical structures are conditionally filtered to obtain preliminary candidate structures. The theoretical retention behavior of the candidate structures after the initial screening is compared and verified with the chromatographic retention characteristics to obtain the verified subset of structures in the effluent; The verification is performed by confidence fusion of structural subsets to obtain the component chemical structure of the effluent.

[0013] In a preferred embodiment, generating a material analysis report for the sample to be tested based on the chemical structure of the components includes: Based on a standard substance database, the chemical structure of the component is matched with a spectral library to obtain the identification information and physicochemical property parameters of the component's chemical structure. The relative content ratio of the eluent is determined based on the peak area in the chromatographic signal data; The identification information, the physicochemical property parameters, and the relative content ratio are comprehensively evaluated to obtain a summary of the component characteristics of the sample to be tested; The chemical structure of the components, the identification information, the relative content ratio, and the summary of the component characteristics are integrated into a material analysis report for the sample to be tested.

[0014] To address the above problems, the present invention also provides a mass spectrometer-chromatograph linked substance analysis system, the system comprising: The chromatographic parameter extraction module is used to introduce the sample to be tested into the chromatograph for separation. During the separation process, the chromatographic elution curve of the chromatograph is monitored in real time, and the resolution parameter and peak shape symmetry parameter of the characteristic peak in the chromatographic elution curve are extracted. The elution resistance trend deduction module is used to perform trend deduction between the resolution parameter and the peak shape symmetry parameter to obtain the elution resistance trend of the sample to be tested. The separation condition control module is used to adjust the separation and elution conditions of the chromatograph according to the elution resistance trend, so as to generate the effluent of the sample to be tested, and introduce the effluent into the ion source of the mass spectrometer; An ion mobility separation module is used to separate the components in the effluent by ion mobility in the ion source to obtain mass spectrometry signal data of the effluent. The pattern coupling recognition module is used to perform pattern coupling recognition between the chromatographic signal data of the chromatograph and the mass spectrometry signal data to obtain the chemical structure of the components of the effluent; The report generation module is used to generate a material analysis report for the sample to be tested based on the chemical structure of the components.

[0015] Compared with the prior art, the present invention has the following beneficial effects: 1. This invention achieves real-time monitoring of the elution curve during chromatographic separation, accurately extracting the resolution parameters and peak shape symmetry parameters of characteristic peaks. By trend extrapolation, the elution resistance trend is derived, allowing for dynamic adjustment of separation and elution conditions. This design enables adaptive optimization of the separation process, effectively improving the thoroughness of sample component separation and peak shape regularity, providing high-quality eluent for subsequent analysis, and ensuring the continuity and stability of the analytical process.

[0016] 2. This invention refines the separation of eluent components through ion mobility separation technology and deeply integrates chromatographic and mass spectrometric signal data using a pattern coupling recognition method, significantly improving the accuracy of component chemical structure identification. Simultaneously, based on standard database matching and peak area analysis, it efficiently integrates component identification, physicochemical properties, and relative content information to generate analysis reports. This not only simplifies the data processing workflow but also achieves a dual improvement in the efficiency and reliability of material analysis results, providing an efficient and feasible technical solution for material composition analysis. Attached Figure Description

[0017] Figure 1 This is a schematic flowchart of a mass spectrometer-chromatograph combined material analysis method according to an embodiment of the present invention; Figure 2 A functional module diagram of a mass spectrometer-chromatograph linked material analysis system provided in an embodiment of the present invention; The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0018] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0019] This application provides a mass spectrometer-chromatograph-integrated material analysis method. The executing entity of this mass spectrometer-chromatograph-integrated material analysis method includes, but is not limited to, at least one of the following electronic devices that can be configured to execute the method provided in this application embodiment: a server, a terminal, etc. In other words, the mass spectrometer-chromatograph-integrated material analysis method can be executed by software or hardware installed on a terminal device or a server device. The server includes, but is not limited to, a single server, a server cluster, a cloud server, or a cloud server cluster. The server can be an independent server or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDNs), and big data and artificial intelligence platforms.

[0020] Reference Figure 1 The diagram shown is a schematic flowchart of a mass spectrometer-chromatograph-linked substance analysis method according to an embodiment of the present invention. In this embodiment, the mass spectrometer-chromatograph-linked substance analysis method includes: S1. The sample to be tested is introduced into the chromatograph for separation. During the separation process, the chromatographic elution curve of the chromatograph is monitored in real time, and the resolution parameter and peak shape symmetry parameter of the characteristic peak in the chromatographic elution curve are extracted. In this embodiment of the invention, the step of introducing the sample to be tested into the chromatograph for separation includes, during the separation process, real-time monitoring of the chromatographic elution curve of the chromatogram, and extraction of the resolution parameter and peak shape symmetry parameter of the characteristic peaks in the chromatographic elution curve, including: The sample to be tested is introduced into the chromatograph for separation, and the time-domain response signal output by the chromatograph during the separation process is obtained; Baseline fitting is performed on the time-domain response signal to obtain the chromatographic elution curve of the chromatograph; Based on the differential change information of the chromatographic elution curve, identify the characteristic peaks in the chromatographic elution curve; The peak position and peak width features of the characteristic peaks are analyzed by Gaussian fitting to obtain the separation parameters of the characteristic peaks. Based on the morphological characteristics of the leading edge and trailing edge of the characteristic peak, the peak shape symmetry parameters of the characteristic peak are extracted.

[0021] A quantitative sample is precisely injected into the chromatographic column inlet of the chromatographic instrument using an injector. The column is filled with a pre-selected stationary phase, and the mobile phase continuously flows through the column at a constant flow rate, which is preset to 1.0 mL / min according to the column specifications. Different components in the sample interact with the stationary and mobile phases at different intensities, resulting in differences in the speed at which the mobile phase moves within the column, thereby achieving the gradual separation of components. During the separation process, the chromatographic instrument's detector captures the physical response signal generated when the component passes through the detection area in real time. This signal is collected and recorded at set time intervals, once every 0.1 seconds, forming a continuous data record that changes over time. This record is the time-domain response signal.

[0022] The stable time period in the time-domain response signal where no sample components appear is selected as the baseline reference interval. This time period is set to 10 minutes before sample injection. The mean value of all signal acquisition points in this interval is calculated. A smooth baseline straight line is formed by connecting the mean values. Then, each data point in the time-domain response signal is superimposed with the baseline value of the corresponding time point to correct the signal and eliminate the interference of background noise. The continuous curve formed by arranging the corrected signals in the order of acquisition time is the chromatographic elution curve.

[0023] The signal difference between two adjacent data points is calculated at 0.1-second intervals to obtain the differential change data of the curve. When the differential change data rises from zero and exceeds the preset signal change threshold (which is set to 3 times the standard deviation of the signal within the baseline reference interval), it is determined as the starting point of the peak. When the differential change data rises to the peak value and then gradually decreases until it returns to near zero and the differential change data of 5 consecutive data points are all below the above signal change threshold, it is determined as the ending point of the peak. The signal bulge formed between the starting point and the ending point is the characteristic peak in the chromatographic elution curve.

[0024] Determine the peak position of the characteristic peak, i.e., the time point corresponding to the maximum signal intensity of the characteristic peak. Using this peak position as the center, select all signal data points between the peak start point and the peak end point. By adjusting the amplitude, width, and other characteristics of the simulated curve, make the simulated Gaussian curve and the actual signal curve of the characteristic peak achieve the highest degree of overlap. The overlap criterion is that the absolute value of the error of the corresponding data points of the curve is less than 0.01. Based on the fitted Gaussian curve, measure the signal width of the characteristic peak at half the peak height, i.e., the half-peak width. Select two adjacent characteristic peaks and measure their half-peak widths respectively. Calculate the time difference between the peak positions of the two peaks. Divide this time difference by the average of the half-peak widths of the two peaks. The result is the separation parameter of the characteristic peak.

[0025] Using the peak position of the characteristic peak as the dividing point, the characteristic peak is divided into the peak front (from the peak start point to the peak position) and the peak back edge (from the peak position to the peak end point). The time length of the peak front rising from the start point to 80% of the peak height is measured, and the time length of the peak back edge falling from 80% of the peak height to the peak end point is measured. The ratio of these two time lengths is calculated, and this ratio is the peak shape symmetry parameter of the characteristic peak.

[0026] The beneficial effects are that, through standardized sample separation procedures, quantifiable baseline fitting methods, clear characteristic peak identification standards, and meticulous parameter extraction methods, the accuracy and consistency of time-domain response signal processing, chromatographic elution curve generation, characteristic peak identification, and related parameter extraction are ensured. The obtained resolution parameters and peak shape symmetry parameters can truly reflect the separation state of sample components, providing accurate and reliable basic data for subsequent elution resistance trend inference, and ensuring the scientific nature and reproducibility of the entire material analysis process.

[0027] S2. Perform trend extrapolation between the resolution parameter and the peak shape symmetry parameter to obtain the elution resistance trend of the sample to be tested; In this embodiment of the invention, the step of performing trend extrapolation between the resolution parameter and the peak shape symmetry parameter to obtain the elution resistance trend of the sample to be tested includes: Based on the order of appearance of the characteristic peaks, the resolution parameter and the peak shape symmetry parameter are structurally recombined to obtain the resolution parameter sequence and peak shape symmetry parameter sequence of the sample to be tested; The resolution parameter sequence and the peak shape symmetry parameter sequence are normalized and integrated to obtain the comprehensive trend index of the sample to be tested. The elution behavior evolution curve of the sample to be tested is obtained by performing time series fitting on the comprehensive trend index. The slope and curvature characteristics of the elution behavior evolution curve are used to determine the trend of the elution resistance of the sample to be tested.

[0028] The formula for calculating the comprehensive trend indicator is as follows: ; In the formula, For the first A comprehensive trend index of characteristic peaks For the first The separation parameter of each characteristic peak, The arithmetic mean of the separation parameter sequence is given. For the first The peak shape symmetry parameters of each characteristic peak. The median of the peak shape symmetry parameter sequence. This is the preset peak shape consistency tolerance factor. denoted as the standard deviation of the peak shape symmetry parameter sequence.

[0029] Following the chronological order in which the characteristic peaks in the chromatographic elution curve were identified, the identification time of each characteristic peak was checked one by one to ensure that the resolution parameter and peak shape symmetry parameter of each characteristic peak were bound together. Then, all the bound resolution parameters were arranged in strict accordance with the chronological order in which the characteristic peaks were identified to construct an ordered sequence of resolution parameters. At the same time, all the bound peak shape symmetry parameters were arranged in accordance with the chronological order that was completely consistent with the resolution parameter sequence to construct an ordered sequence of peak shape symmetry parameters. Parameters in the same position in the two sequences must correspond to the same characteristic peak, ensuring that there is no deviation in the correspondence between parameters and characteristic peaks.

[0030] To calculate the arithmetic mean of the separation parameter sequence, first sum all parameters in the sequence, then count the number of parameters in the sequence, and divide the sum by the number to obtain the arithmetic mean of the separation parameter sequence. Next, to calculate the median of the peak shape symmetry parameter sequence, arrange all parameters in ascending order of value. If the number of parameters in the sequence is odd, select the middle parameter after sorting as the median of the peak shape symmetry parameter sequence; if the number of parameters is even, select the two middle parameters after sorting, calculate the sum of these two parameters, divide by 2, and obtain the result as the median of the peak shape symmetry parameter sequence. Simultaneously, to calculate the standard deviation of the peak shape symmetry parameter sequence, first calculate the peak shape... The arithmetic mean of the peak shape symmetry parameter sequence is obtained by summing all parameters in the sequence and dividing the sum by the number of parameters in the sequence. Then, the arithmetic mean is subtracted from each peak shape symmetry parameter in the sequence to obtain the deviation value for each parameter. All deviation values ​​are squared, and the sum of all squared deviation values ​​is calculated. This sum is divided by the number of parameters in the sequence, and the square root of the result is taken. The final value is the standard deviation of the peak shape symmetry parameter sequence. The peak shape consistency tolerance factor is preset to 2. This value is obtained through statistical analysis of historical chromatographic analysis data of a large number of similar substances, which can effectively filter out the interference of abnormal peak shape data on subsequent calculations while allowing for normal differences in peak shape. The calculation of the... When considering the comprehensive trend index corresponding to the first characteristic peak, first use the first... The resolution parameter of the first characteristic peak is divided by the arithmetic mean of the resolution parameter sequence to obtain the resolution normalization result. Then the resolution parameter of the second characteristic peak is calculated. The difference between the peak shape symmetry parameter and the median of the peak shape symmetry parameter sequence is taken as the absolute value of the difference. Then, the product of the peak shape consistency tolerance factor and the standard deviation of the peak shape symmetry parameter sequence is calculated. The absolute difference is divided by this product to obtain the bias correction coefficient. The peak shape fit result is obtained by subtracting the bias correction coefficient from 1. Finally, the normalized separation result is multiplied by the peak shape fit result; the resulting product is the peak shape fit result. The comprehensive trend index corresponding to each characteristic peak.

[0031] A two-dimensional coordinate system is established with the time of occurrence of the characteristic peak as the horizontal axis and the comprehensive trend index corresponding to each characteristic peak as the vertical axis. The horizontal axis is marked with scales at fixed time intervals, and the vertical axis is marked with scales at fixed numerical intervals. The occurrence time of each characteristic peak is accurately mapped to the corresponding scale on the horizontal axis, and the comprehensive trend index corresponding to each characteristic peak is accurately mapped to the corresponding scale on the vertical axis. This ensures that the coordinate points formed by the time of occurrence of each characteristic peak and the comprehensive trend index accurately fall into the corresponding positions in the two-dimensional coordinate system. Using a linear connection method, all coordinate points in the coordinate system are smoothly connected sequentially according to the order of occurrence of the characteristic peaks. During the connection process, the line segments are kept continuous without breaks. The resulting continuous and complete curve is the elution behavior evolution curve of the sample to be tested.

[0032] The analysis interval is defined as the time range corresponding to all characteristic peaks, that is, the interval covered from the time point of the first characteristic peak to the time point of the last characteristic peak. The slope between two adjacent coordinate points within this interval is calculated. For two adjacent coordinate points, first determine the comprehensive trend index values ​​of the latter and former coordinate points, then subtract the former value from the latter to obtain the index difference. Next, determine the corresponding time values ​​for the two coordinate points, subtract the former time value from the latter to obtain the time difference. Finally, divide the index difference by the time difference to obtain the slope between the two adjacent coordinate points. Simultaneously, the curvature is determined by measuring the degree of bending of the line segment between two adjacent coordinate points, specifically quantified by the deviation distance between the two endpoints and the midpoint of the line segment. The ratio of distance to line segment length is the curvature value. The preset slope judgment benchmark is 0, and the curvature judgment benchmark is 0.1. The slope and curvature of all adjacent coordinate point line segments in the curve are statistically analyzed. When more than 80% of the adjacent coordinate point line segments have a slope value greater than 0 and a curvature value less than 0.1, the elution resistance trend is judged to be gradually decreasing. When more than 80% of the adjacent coordinate point line segments have a slope value less than 0 and a curvature value greater than 0.1, the elution resistance trend is judged to be gradually increasing. When the proportion of adjacent coordinate point line segments with a slope value greater than 0 in the curve does not exceed 80%, and the proportion of adjacent coordinate point line segments with a slope value less than 0 also does not exceed 80%, and the absolute value of the difference between the curvature value of all adjacent coordinate point line segments and 0.1 does not exceed 0.02, the elution resistance trend is judged to be stable.

[0033] The beneficial effects are as follows: through a clear and operable parameter sequence recombination method, a comprehensive trend index acquisition method based on detailed parameter statistical calculations and historical data support, a time series fitting process with clear steps, and trend judgment rules with clear quantitative standards, it not only achieves deep integration and accurate conversion of resolution parameters and peak shape symmetry parameters, but also ensures that the generation process of resolution parameter sequences, peak shape symmetry parameter sequences, comprehensive trend indicators, elution behavior evolution curves, and elution resistance trends has strong reproducibility. The results can truly and comprehensively reflect the elution change law of the test sample during the separation process, providing a logically coherent and data-reliable core basis for the precise adjustment of subsequent separation and elution conditions, further enhancing the scientificity and efficiency of the material analysis process, and effectively avoiding analytical errors caused by ambiguous processes or data deviations.

[0034] S3. Based on the elution resistance trend, adjust the separation and elution conditions of the chromatograph to generate the effluent of the sample to be tested, and introduce the effluent into the ion source of the mass spectrometer; In this embodiment of the invention, adjusting the separation and elution conditions of the chromatograph according to the elution resistance trend to generate the eluent of the sample to be tested, and introducing the eluent into the ion source of the mass spectrometer, includes: The direction and intensity of the separation efficiency change indicated by the elution resistance trend were analyzed. The direction and intensity of the change in separation efficiency are mapped by instructions to obtain the optimization adjustment instructions for the chromatograph; Based on the optimization and adjustment instructions, the elution gradient program and column oven temperature of the chromatograph are dynamically adjusted to obtain the updated separation and elution conditions of the chromatograph. The sample to be tested continues to be separated under the updated separation and elution conditions. When the chromatographic peak shape and resolution monitored in real time reach the preset standard, the fraction collection of the chromatograph is triggered to generate the effluent of the sample to be tested. The effluent is introduced into the ion source of the mass spectrometer.

[0035] Three types of elution resistance trends are identified: gradually decreasing, gradually increasing, and remaining stable. When the elution resistance trend is gradually decreasing, the corresponding direction of separation efficiency change is continuous improvement; when the elution resistance trend is gradually increasing, the corresponding direction of separation efficiency change is continuous decline; and when the elution resistance trend is remaining stable, the corresponding direction of separation efficiency change is no significant fluctuation. The intensity of separation efficiency change is divided according to the percentage of adjacent coordinate point line segments that meet the trend judgment conditions. A percentage of 80% or above indicates a strong change, a percentage between 50% and 80% indicates a medium change, and a percentage below 50% indicates a weak change. By matching the elution resistance trend type with the corresponding percentage range, the analysis of the direction and intensity of separation efficiency change is completed.

[0036] A fixed mapping rule is established between the direction and intensity of separation performance changes and optimization adjustment instructions. When the direction of separation performance change is continuously increasing and the intensity is strong, the mapped optimization adjustment instruction is to maintain the current elution gradient program slope and column oven temperature; when the direction of separation performance change is continuously increasing and the intensity is moderate, the mapped optimization adjustment instruction is to reduce the elution gradient program slope by 20% and keep the column oven temperature unchanged; when the direction of separation performance change is continuously increasing and the intensity is weak, the mapped optimization adjustment instruction is to reduce the elution gradient program slope by 10% and keep the column oven temperature unchanged; when the direction of separation performance change is continuously decreasing and the intensity is strong, the mapped... The optimization adjustment command is to increase the elution gradient slope by 30% and the column oven temperature by 3°C. When the separation efficiency changes in a continuously decreasing direction with moderate intensity, the mapped optimization adjustment command is to increase the elution gradient slope by 20% and the column oven temperature by 2°C. When the separation efficiency changes in a continuously decreasing direction with weak intensity, the mapped optimization adjustment command is to increase the elution gradient slope by 10% and the column oven temperature by 1°C. When the separation efficiency changes without significant fluctuations, the mapped optimization adjustment command is to maintain the current elution gradient program and column oven temperature. By completing the command mapping according to the above rules, the optimized adjustment command for the chromatograph is obtained.

[0037] The current elution gradient program of the chromatograph is obtained, including the initial value, final value, and rate of change of the organic phase ratio. Based on the gradient slope adjustment requirements in the optimization adjustment instructions, a new rate of change of the organic phase ratio is calculated. If the instruction is to increase the slope, the rate is increased proportionally based on the current rate; if the instruction is to decrease the slope, the rate is decreased proportionally based on the current rate, thus forming the updated elution gradient program. Simultaneously, the current column oven temperature of the chromatograph is obtained. Based on the temperature adjustment requirements in the optimization adjustment instructions, the corresponding increase is directly added or the temperature is kept unchanged to obtain the updated column oven temperature. The updated elution gradient program and the updated column oven temperature together constitute the updated separation and elution conditions of the chromatograph.

[0038] Under the updated separation and elution conditions, the chromatograph continues to separate the remaining sample. During the process, the chromatographic elution curve is monitored in real time, and the peak shape symmetry parameter and resolution parameter of the characteristic peak are extracted every 0.1 seconds. The preset acceptable range for the peak shape symmetry parameter is 0.8 to 1.2, and the acceptable standard for the resolution parameter is greater than 1.5. When the characteristic peaks extracted for three consecutive times all meet the requirements of peak shape symmetry parameter between 0.8 and 1.2 and resolution parameter greater than 1.5, it is determined that the real-time monitored chromatographic peak shape and resolution have reached the preset standard, triggering the fraction collection function of the chromatograph. The collection device collects the components that meet the standard according to the set collection volume, and the collected components are the elution liquid of the sample to be tested.

[0039] The eluent is delivered through a dedicated transfer line between the chromatograph and the mass spectrometer. The transfer line is kept at a constant temperature of 35°C throughout the process to prevent the components in the eluent from adsorbing or solidifying. The eluent flows through the transfer line at a constant flow rate of 0.2 mL / min and is finally stably introduced into the ion source of the mass spectrometer, ensuring that the eluent enters the ion source intact and without component loss.

[0040] The beneficial effects are that by establishing clear separation efficiency analysis rules, fixed instruction mapping logic, specific condition adjustment methods, and quantified peak shape and resolution judgment criteria, dynamic and precise control of separation and elution conditions is achieved, ensuring thorough separation of components and regular peak shapes in the generated effluent. At the same time, it ensures the stability and integrity of the effluent introduced into the mass spectrometer ion source, laying a high-quality foundation for subsequent ion mobility separation and mass spectrometry signal data acquisition, and improving the coherence and reliability of the entire material analysis process.

[0041] S4. In the ion source, the components in the effluent are separated by ion mobility to obtain the mass spectrometry signal data of the effluent; In this embodiment of the invention, the step of performing ion mobility separation on the components in the effluent in the ion source to obtain mass spectrometry signal data of the effluent includes: In the ion source, the effluent is subjected to electrospray ionization to obtain the effluent quasi-molecular ion cluster; Based on the collision cross section of the quasi-molecular ion group, ion mobility spectrum separation is performed in a buffer gas and a uniform electric field to obtain the ion sequence of the effluent; The ion sequence is digitized to obtain the original mobility spectrum signal of the ion sequence; The original mobility spectrum signal is deconvolved to obtain the mass spectrum signal data of the effluent.

[0042] The eluent enters the electrospray ionization source of the mass spectrometer at a constant flow rate of 0.2 mL / min. A dedicated quartz capillary is installed inside the ionization source, with the distance between the capillary outlet and the ionization region fixed at 1 mm. A high-voltage electric field of 3.5 kV is applied to the capillary, while 99.99% pure nitrogen is introduced as the nebulizer gas. The pressure of the nebulizer gas is set at 3 bar, and the temperature of the drying gas is strictly controlled at 350℃. Under the electrostatic attraction of the high-voltage electric field and the impact of the nebulizer gas, the eluent is dispersed and atomized into tiny droplets with a diameter of less than 1 micrometer. These tiny droplets rapidly evaporate the solvent under the continuous heating of the 350℃ drying gas. The molecules remaining in the droplets acquire charges due to being in the high-voltage electric field environment, eventually forming quasi-molecular ion clusters composed of charged molecules.

[0043] A 20cm long ion migration tube is filled with 99.999% pure helium as a buffer gas. The helium is continuously filled into the migration tube at a flow rate of 1mL / min to maintain a stable internal gas environment. A stable voltage is applied to both ends of the migration tube through a high-precision power supply to form a uniform electric field with a fixed intensity of 200V / cm. The entire migration tube is maintained at 40℃ by a thermostat. After the excimer ion cluster enters the tube through the inlet, it migrates towards the detector under the directional driving force of the uniform electric field. During the migration, each ion will have regular collisions with the buffer gas molecules. Ions with different structures have inherent differences in their collision cross sections. Ions with larger collision cross sections experience greater gas resistance during the collision and migrate slower. Ions with smaller collision cross sections experience less gas resistance and migrate faster. All ions flow out of the migration tube outlet in order of migration speed from fastest to slowest, forming an ordered ion sequence.

[0044] After the ion sequence flows out of the ion migration tube, it is immediately captured by an electron multiplier detector of model EM-100. The detector adsorbs ions through electrodes and converts the charge carried by the ions into a directly measurable electrical signal. The signal acquisition time interval is set to 0.001 seconds, and the intensity value of the electrical signal is continuously acquired at this fixed interval. The acquisition range is 0-10V. The specific time of each acquisition point and the corresponding electrical signal intensity value are recorded in the data storage unit, forming a continuous data set containing the correlation between time dimension information and signal intensity dimension information. This data set is the original mobility spectrum signal of the ion sequence.

[0045] When deconvolving the original mobility spectrum signal, the electrical signal intensity values ​​of 10 consecutive acquisition points at the beginning of signal acquisition are first selected. These 10 values ​​are added together and divided by 10. The result is used as the baseline intensity. This baseline intensity is then subtracted from the electrical signal intensity value of each acquisition point in the original mobility spectrum signal to complete baseline correction and eliminate background noise interference. Subsequently, the corrected signal is scanned point by point to identify consecutive acquisition points whose electrical signal intensity values ​​exceed three times the baseline intensity. These consecutive acquisition points are defined as an independent peak region, and the acquisition point with the largest electrical signal intensity value within the peak region is taken as the peak apex. Accurately record the acquisition time and electrical signal intensity value corresponding to the peak apex. At the same time, determine the starting acquisition point of the peak region, that is, the acquisition point where the electrical signal intensity first exceeds 3 times the baseline, and the ending acquisition point, that is, the acquisition point where the electrical signal intensity first falls below 3 times the baseline. Count the number of acquisition points between the peak starting acquisition point and the ending acquisition point. Calculate the peak width in combination with the signal acquisition time interval. Arrange all the identified peaks in the order of peak apex acquisition time to form structured data containing the acquisition time, signal intensity, peak width, and peak boundary acquisition point information of each peak. This structured data is the mass spectrometry signal data of the effluent.

[0046] The beneficial effects are as follows: by clarifying the specific structural parameters of the ion source and migration tube, refining key environmental conditions such as gas purity, flow rate, electric field strength, and temperature, and standardizing the equipment models, ranges, and intervals for signal acquisition, the baseline calculation, peak region identification, and data processing rules for deconvolution processing are clarified. This ensures that the generation process of quasi-molecular ion clusters, ion sequences, raw mobility spectrometry signals, and mass spectrometry signal data has a clear and operable basis and strong reproducibility. The obtained mass spectrometry signal data completely retains the ion migration characteristics and intensity information of the eluent components, providing high-precision and high-completeness basic data for subsequent pattern coupling identification of chromatographic and mass spectrometry signal data, thus ensuring the accuracy and reliability of component chemical structure identification from the source.

[0047] S5. Perform pattern coupling recognition on the chromatographic signal data of the chromatograph and the mass spectrometry signal data to obtain the chemical structure of the components of the effluent; In this embodiment of the invention, the step of performing pattern coupling recognition between the chromatographic signal data of the chromatogram and the mass spectrometry signal data to obtain the component chemical structure of the eluent includes: The chromatographic signal data of the chromatogram are extracted by retention time to obtain the chromatographic retention characteristics of the effluent; Mass spectrometry peak detection is performed on the mass spectrometry signal data to obtain the mass spectrometry characteristics of the effluent; Based on the temporal correlation between the chromatographic retention features and the mass spectrometry features, the chromatographic retention features and the mass spectrometry features are cross-correlated and aligned to obtain the matching feature pairs of the effluent; The matching feature pairs are compared with the pre-stored standard spectral library to obtain the candidate chemical structures of the effluent; The spectral consistency and chromatographic behavior of the candidate chemical structures are comprehensively evaluated to obtain the component chemical structures of the effluent.

[0048] The process of comprehensively evaluating the spectral consistency and chromatographic behavior of the candidate chemical structures to obtain the component chemical structures of the effluent includes: Based on a preset matching threshold, the candidate chemical structures are conditionally filtered to obtain preliminary candidate structures. The theoretical retention behavior of the candidate structures after the initial screening is compared and verified with the chromatographic retention characteristics to obtain the verified subset of structures in the effluent; The verification is performed by confidence fusion of structural subsets to obtain the component chemical structure of the effluent.

[0049] The chromatographic signal data recorded by the chromatograph is scanned point by point in chronological order. Based on the previously set peak identification standard, that is, the signal intensity of consecutive acquisition points exceeds 3 times the baseline and is sustained for no less than 3 acquisition points, all labeled characteristic peaks are identified. The specific value is determined by reading the acquisition timestamp corresponding to the peak of each characteristic peak. This value is the retention time of the component corresponding to the characteristic peak. At the same time, the specific value of the peak intensity corresponding to each retention time is recorded. All combinations of retention times and corresponding peak intensities are sorted and arranged in order of retention time from early to late to form structured information containing a one-to-one correspondence between retention time and corresponding peak intensity. This structured information is the chromatographic retention characteristics of the eluent.

[0050] The mass spectrometry signal data is analyzed line by line in chronological order of data recording, identifying the peak regions. The acquisition point with the highest signal intensity in each peak region is defined as the peak apex, and the acquisition time corresponding to the peak apex is defined as the migration time. The specific migration time, signal intensity, and peak width of each peak are recorded. The peak width is calculated by subtracting the acquisition time of the peak start point from the acquisition time of the peak end point. The migration time, signal intensity, and peak width of all peaks are arranged in chronological order from earliest to latest, forming structured data containing the correspondence between migration time, signal intensity, and peak width. This structured data is the mass spectrometry characteristic of the effluent.

[0051] Based on the transmission delay characteristics of chromatographic and mass spectrometric signals, a time-matching window for time-series association is set to ±0.1 seconds. Taking each retention time in the chromatographic retention feature as a reference point, target mass spectrometric peaks falling within the ±0.1-second range of the migration time data of the mass spectrometric feature are searched. If only one target mass spectrometric peak exists within the range corresponding to a certain retention time, the retention time and its corresponding peak intensity are directly bound to the migration time, signal intensity, and peak width of the target mass spectrometric peak. If multiple target mass spectrometric peaks exist within the range, the signal intensity value of each target mass spectrometric peak is divided by the peak intensity value of the corresponding chromatographic peak to obtain multiple ratios. The absolute value of the difference between all ratios and 1 is compared, and the target mass spectrometric peak with the smallest absolute value of the difference (i.e., the ratio closest to 1) is selected for binding. If no target mass spectrometric peak exists within the range, the chromatographic retention feature fragment corresponding to that retention time is not included in the matching for the time being. Finally, multiple one-to-one corresponding combinations of chromatographic retention feature fragments and mass spectrometric feature fragments are formed, and these combinations are the matching feature pairs of the eluent.

[0052] The pre-stored standard spectral library is constructed by integrating authoritative chemical databases and contains a massive amount of standard chromatographic retention features and standard mass spectrometry features corresponding to known chemical structures. The standard chromatographic retention features include standard retention time and standard peak intensity ratio, while the standard mass spectrometry features include standard migration time, standard signal intensity, and standard peak width. Each matching feature pair's indicators are compared with the corresponding standard features of known chemical structures in the standard spectral library. First, the absolute difference between the actual retention time and the standard retention time of the matching feature pair is calculated. Then, this absolute difference is divided by the standard retention time to obtain the retention time ratio. The matching feature pair is then calculated... The absolute difference between the peak intensity ratio and the standard peak intensity ratio is calculated. The absolute difference between the actual migration time and the standard migration time of the matched feature pair is calculated and divided by the standard migration time to obtain the migration time ratio. The absolute difference between the actual signal intensity and the standard signal intensity of the matched feature pair is calculated and divided by the standard signal intensity to obtain the signal intensity ratio. The absolute difference between the actual peak width and the standard peak width of the matched feature pair is calculated and divided by the standard peak width to obtain the peak width ratio. The values ​​of these five indicators are added together and divided by 5 to obtain the similarity score. Known chemical structures with a similarity score ≥ 80% are retained. These chemical structures are the candidate chemical structures of the effluent.

[0053] Based on historical verification data from a large number of similar substance analyses, the preset similarity threshold is set at 85%. The similarity score of each structure is checked one by one according to the storage order of the candidate chemical structures. Candidate chemical structures with a score greater than or equal to 85% are completely retained, while candidate chemical structures with a score lower than 85% are directly eliminated. The remaining candidate chemical structures after screening are the candidate structures after the initial screening.

[0054] The theoretical retention time of each candidate chemical structure after initial screening is retrieved under the same chromatographic conditions as the current analysis. These same conditions specifically refer to the same column type, mobile phase composition ratio, and column temperature settings. The actual retention time corresponding to the chromatographic retention characteristic is subtracted from the retrieved theoretical retention time, and the absolute value of the result is taken as the absolute difference between the two. Considering the time acquisition accuracy of the chromatograph, the allowable range for this difference is set to ≤0.05 seconds. If the absolute difference between the theoretical retention time and the corresponding actual retention time of all candidates after initial screening is ≤0.05 seconds, then the structure is deemed to have passed the verification. All verified structures are then integrated and arranged in alphabetical order of their chemical structure names to form a subset of verified structures in the effluent.

[0055] To verify the calculation of confidence scores for each structure in the structural subset, the similarity score of the structure was first converted to a percentage value, and then calculated according to a set weight. The scoring method was to multiply the percentage similarity score by 0.7 and add the retention time matching score by 0.3. The retention time matching score rule was that a difference of less than 0.02 seconds between the theoretical and actual retention times was 100 points, and a difference of more than 0.02 seconds but less than 0.05 seconds was 80 points. The two scores were added together to obtain the total confidence score for each structure. The structures were sorted in descending order of total confidence scores, and the structure with the highest total score was selected as the final component chemical structure of the effluent. If multiple structures had the same total score, the degree of matching of the mass spectrometry peak widths was further compared. The absolute difference of the peak width was obtained by subtracting the standard peak width from the actual peak width of each structure with the same total score. The absolute difference of the peak widths was compared among all structures with the same total score, and the structure with the smallest difference was selected as the component chemical structure of the effluent.

[0056] The beneficial effects are that by clarifying the scanning standards, analysis methods, matching window setting basis, standard spectrum library sources, comparison and calculation steps for various indicators, threshold and difference range setting basis, and confidence score calculation rules, a series of quantifiable and operable detailed processes are completely avoided, thus eliminating the problems of operational ambiguity and insufficient disclosure. This ensures that the entire process, from chromatographic feature retention and mass spectrometry feature extraction to the formation of matching feature pairs, and then to the screening, verification, and final determination of the chemical structure of the components, is highly reproducible. It effectively eliminates interfering structures and error data, significantly improving the accuracy, reliability, and authority of component chemical structure identification, and providing solid and accurate core data support for the generation of subsequent material analysis reports.

[0057] S6. Based on the chemical structure of the components, generate a material analysis report for the sample to be tested.

[0058] In this embodiment of the invention, generating a material analysis report for the sample to be tested based on the chemical structure of the components includes: Based on a standard substance database, the chemical structure of the component is matched with a spectral library to obtain the identification information and physicochemical property parameters of the component's chemical structure. The relative content ratio of the eluent is determined based on the peak area in the chromatographic signal data; The identification information, the physicochemical property parameters, and the relative content ratio are comprehensively evaluated to obtain a summary of the component characteristics of the sample to be tested; The chemical structure of the components, the identification information, the relative content ratio, and the summary of the component characteristics are integrated into a material analysis report for the sample to be tested.

[0059] The Standard Material Database is a comprehensive database of chemical substances certified by national authoritative institutions. It contains complete information on various known chemical substances. The determined chemical structure of a component is entered into the database retrieval system. By comparing the types, quantities, connection methods, and molecular skeleton structures of functional groups in the chemical structure, the corresponding target substance entry is accurately matched. The chemical name, CAS registry number, and molecular formula are extracted from the information marked in the entry as the identification information of the component's chemical structure. At the same time, experimentally verified numerical data such as melting point, boiling point, solubility, density, and polarity are extracted. These data are the physicochemical property parameters of the component's chemical structure.

[0060] The trapezoidal method was used to calculate the peak area of ​​each characteristic peak in the chromatographic signal data. Based on the baseline of the characteristic peak, the region under the peak curve was divided into several adjacent trapezoids from the peak start point to the peak end point. The upper and lower bases of each trapezoid were the signal intensity values ​​of the adjacent acquisition points, and the height was the acquisition time interval. The area of ​​each trapezoid was calculated and accumulated to obtain the peak area of ​​a single characteristic peak. The peak areas of all characteristic peaks were added together to obtain the total peak area. The peak area of ​​each characteristic peak was divided by the total peak area, and the result was rounded to four decimal places. This value is the relative content ratio of the corresponding component in the eluent.

[0061] The extracted identification information is uniquely verified to ensure that the chemical name, CAS registration number, molecular formula and component chemical structure are completely consistent without deviation. Each value in the physicochemical property parameters is checked to see if it is within the standard range of the type of substance, such as melting point between -200℃ and 800℃ and solubility between 0g / L and 1000g / L. At the same time, the specific value of each relative content ratio and the corresponding component are clarified. Following the logical order of "identification information - core physicochemical properties - relative content", a concise overview containing basic material information, key physicochemical properties and content ratio is formed. This overview is the component characteristic summary of the sample to be tested.

[0062] Construct a material analysis report framework according to the preset report template. The report begins by clearly indicating basic information such as sample number, analysis date, and analytical equipment model. Then, it includes structural diagrams of the chemical structures of the components, complete identification information, a list of physicochemical properties and their corresponding values, and the relative content ratio of each component. Finally, it includes an integrated summary of the component characteristics. All information is presented by chapter, with clear and unambiguous chapter titles and accurate data labeling, ultimately forming a material analysis report of the sample to be tested that is structurally complete and information-rich.

[0063] The beneficial effects are that by relying on authoritative standard databases to ensure information accuracy, by adopting clear peak area calculation methods to ensure accurate relative content ratios, and by conducting comprehensive evaluation and report integration according to standardized logic, the process of acquiring and integrating identification information, physicochemical property parameters, relative content ratios, and component characteristic summaries is highly reproducible. The generated material analysis reports are complete, reliable, and logically clear, providing users with comprehensive and accurate analysis results of the components of the samples to be tested, meeting the practical application needs of material composition research, quality testing, and other applications.

[0064] like Figure 2 The diagram shown is a functional block diagram of a mass spectrometer-chromatograph linked material analysis system provided in an embodiment of the present invention.

[0065] The mass spectrometer-chromatograph integrated material analysis system 100 described in this invention can be installed in an electronic device. Depending on the functions implemented, the mass spectrometer-chromatograph integrated material analysis system 100 may include a chromatographic parameter extraction module 101, an elution resistance trend prediction module 102, a separation condition control module 103, an ion mobility separation module 104, a mode coupling recognition module 105, and a report generation module 106. The modules described in this invention can also be referred to as units, which are a series of computer program segments that can be executed by the processor of an electronic device and perform a fixed function, stored in the memory of the electronic device.

[0066] In this embodiment, the functions of each module / unit are as follows: The chromatographic parameter extraction module 101 is used to introduce the sample to be tested into the chromatograph for separation. During the separation process, the chromatographic elution curve of the chromatograph is monitored in real time, and the resolution parameter and peak shape symmetry parameter of the characteristic peak in the chromatographic elution curve are extracted. The elution resistance trend deduction module 102 is used to perform trend deduction between the resolution parameter and the peak shape symmetry parameter to obtain the elution resistance trend of the sample to be tested. The separation condition control module 103 is used to adjust the separation and elution conditions of the chromatograph according to the elution resistance trend, so as to generate the effluent of the sample to be tested, and introduce the effluent into the ion source of the mass spectrometer. The ion mobility separation module 104 is used to separate the components in the effluent by ion mobility in the ion source to obtain the mass spectrometry signal data of the effluent. The pattern coupling recognition module 105 is used to perform pattern coupling recognition between the chromatographic signal data of the chromatograph and the mass spectrometry signal data to obtain the chemical structure of the components of the effluent. The report generation module 106 is used to generate a material analysis report of the sample to be tested based on the chemical structure of the components.

[0067] In the several embodiments provided by this invention, it should be understood that the disclosed methods and systems can be implemented in other ways. For example, the system embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and other division methods may be used in actual implementation.

[0068] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0069] Furthermore, the functional modules in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in the form of hardware plus software functional modules.

[0070] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0071] This application embodiment can acquire and process relevant data based on artificial intelligence technology. Artificial intelligence is the theory, method, technology, and application system that uses digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to obtain optimal results.

[0072] 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 it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for combined mass spectrometry and chromatography for substance analysis, characterized in that, The method includes: S1. The sample to be tested is introduced into the chromatograph for separation. During the separation process, the chromatographic elution curve of the chromatograph is monitored in real time, and the resolution parameter and peak shape symmetry parameter of the characteristic peak in the chromatographic elution curve are extracted. S2. Perform trend extrapolation between the resolution parameter and the peak shape symmetry parameter to obtain the elution resistance trend of the sample to be tested; S3. Based on the elution resistance trend, adjust the separation and elution conditions of the chromatograph to generate the effluent of the sample to be tested, and introduce the effluent into the ion source of the mass spectrometer; S4. In the ion source, the components in the effluent are separated by ion mobility to obtain the mass spectrometry signal data of the effluent; S5. Perform pattern coupling recognition on the chromatographic signal data of the chromatograph and the mass spectrometry signal data to obtain the chemical structure of the components of the effluent; S6. Based on the chemical structure of the components, generate a material analysis report for the sample to be tested.

2. The mass spectrometer-chromatograph combined material analysis method as described in claim 1, characterized in that, The step involves introducing the sample to be tested into a chromatograph for separation. During the separation process, the chromatographic elution curve of the chromatograph is monitored in real time, and the resolution parameters and peak shape symmetry parameters of the characteristic peaks in the chromatographic elution curve are extracted, including: The sample to be tested is introduced into the chromatograph for separation, and the time-domain response signal output by the chromatograph during the separation process is obtained; Baseline fitting is performed on the time-domain response signal to obtain the chromatographic elution curve of the chromatograph; Based on the differential change information of the chromatographic elution curve, identify the characteristic peaks in the chromatographic elution curve; The peak position and peak width features of the characteristic peaks are analyzed by Gaussian fitting to obtain the separation parameters of the characteristic peaks. Based on the morphological characteristics of the leading edge and trailing edge of the characteristic peak, the peak shape symmetry parameters of the characteristic peak are extracted.

3. The mass spectrometer-chromatograph combined material analysis method as described in claim 1, characterized in that, The step of performing trend extrapolation between the resolution parameter and the peak shape symmetry parameter to obtain the elution resistance trend of the sample to be tested includes: Based on the order of appearance of the characteristic peaks, the resolution parameter and the peak shape symmetry parameter are structurally recombined to obtain the resolution parameter sequence and peak shape symmetry parameter sequence of the sample to be tested; The resolution parameter sequence and the peak shape symmetry parameter sequence are normalized and integrated to obtain the comprehensive trend index of the sample to be tested. The elution behavior evolution curve of the sample to be tested is obtained by performing time series fitting on the comprehensive trend index. The slope and curvature characteristics of the elution behavior evolution curve are used to determine the trend of the elution resistance of the sample to be tested.

4. The mass spectrometer-chromatograph combined material analysis method as described in claim 3, characterized in that, The formula for calculating the comprehensive trend indicator is as follows: ； In the formula, For the first A comprehensive trend index of characteristic peaks, For the first The separation parameter of each characteristic peak, The arithmetic mean of the separation parameter sequence is given. For the first The peak shape symmetry parameters of each characteristic peak. The median of the peak shape symmetry parameter sequence. This is the preset peak shape consistency tolerance factor. denoted as the standard deviation of the peak shape symmetry parameter sequence.

5. The mass spectrometer-chromatograph combined material analysis method as described in claim 1, characterized in that, The step of adjusting the separation and elution conditions of the chromatograph according to the elution resistance trend to generate the eluent of the sample to be tested, and introducing the eluent into the ion source of the mass spectrometer, includes: The direction and intensity of the separation efficiency change indicated by the elution resistance trend were analyzed. The direction and intensity of the change in separation efficiency are mapped by instructions to obtain the optimization adjustment instructions for the chromatograph; Based on the optimization and adjustment instructions, the elution gradient program and column oven temperature of the chromatograph are dynamically adjusted to obtain the updated separation and elution conditions of the chromatograph. The sample to be tested continues to be separated under the updated separation and elution conditions. When the chromatographic peak shape and resolution monitored in real time reach the preset standard, the fraction collection of the chromatograph is triggered to generate the effluent of the sample to be tested. The effluent is introduced into the ion source of the mass spectrometer.

6. The mass spectrometer-chromatograph combined material analysis method as described in claim 1, characterized in that, The step of separating the components in the eluent by ion mobility in the ion source to obtain mass spectrometry signal data of the eluent includes: In the ion source, the effluent is subjected to electrospray ionization to obtain the effluent quasi-molecular ion cluster; Based on the collision cross section of the quasi-molecular ion group, ion mobility spectrum separation is performed in a buffer gas and a uniform electric field to obtain the ion sequence of the effluent; The ion sequence is digitized to obtain the original mobility spectrum signal of the ion sequence; The original mobility spectrum signal is deconvolved to obtain the mass spectrum signal data of the effluent.

7. The mass spectrometer-chromatograph combined material analysis method as described in claim 1, characterized in that, The step of performing pattern coupling recognition between the chromatographic signal data and the mass spectrometry signal data of the chromatogram to obtain the component chemical structure of the eluent includes: The chromatographic signal data of the chromatogram are extracted by retention time to obtain the chromatographic retention characteristics of the effluent; Mass spectrometry peak detection is performed on the mass spectrometry signal data to obtain the mass spectrometry characteristics of the effluent; Based on the temporal correlation between the chromatographic retention features and the mass spectrometry features, the chromatographic retention features and the mass spectrometry features are cross-correlated and aligned to obtain the matching feature pairs of the effluent; The matching feature pairs are compared with the pre-stored standard spectral library to obtain the candidate chemical structures of the effluent; The spectral consistency and chromatographic behavior of the candidate chemical structures are comprehensively evaluated to obtain the component chemical structures of the effluent.

8. The mass spectrometer-chromatograph combined material analysis method as described in claim 7, characterized in that, The process of comprehensively evaluating the spectral consistency and chromatographic behavior of the candidate chemical structures to obtain the component chemical structures of the effluent includes: Based on a preset matching threshold, the candidate chemical structures are conditionally filtered to obtain preliminary candidate structures. The theoretical retention behavior of the candidate structures after the initial screening is compared and verified with the chromatographic retention characteristics to obtain the verified subset of structures in the effluent; The verification is performed by confidence fusion of structural subsets to obtain the component chemical structure of the effluent.

9. The mass spectrometer-chromatograph combined material analysis method as described in claim 1, characterized in that, The step of generating a material analysis report for the sample to be tested based on the chemical structure of the components includes: Based on a standard substance database, the chemical structure of the component is matched with a spectral library to obtain the identification information and physicochemical property parameters of the component's chemical structure. The relative content ratio of the eluent is determined based on the peak area in the chromatographic signal data; The identification information, the physicochemical property parameters, and the relative content ratio are comprehensively evaluated to obtain a summary of the component characteristics of the sample to be tested; The chemical structure of the components, the identification information, the relative content ratio, and the summary of the component characteristics are integrated into a material analysis report for the sample to be tested.

10. A mass spectrometer-chromatograph linked material analysis system, characterized in that, The system for implementing the mass spectrometer-chromatograph linked material analysis method according to claim 1 comprises: The chromatographic parameter extraction module is used to introduce the sample to be tested into the chromatograph for separation. During the separation process, the chromatographic elution curve of the chromatograph is monitored in real time, and the resolution parameter and peak shape symmetry parameter of the characteristic peak in the chromatographic elution curve are extracted. The elution resistance trend deduction module is used to perform trend deduction between the resolution parameter and the peak shape symmetry parameter to obtain the elution resistance trend of the sample to be tested. The separation condition control module is used to adjust the separation and elution conditions of the chromatograph according to the elution resistance trend, so as to generate the effluent of the sample to be tested, and introduce the effluent into the ion source of the mass spectrometer; An ion mobility separation module is used to separate the components in the effluent by ion mobility in the ion source to obtain mass spectrometry signal data of the effluent. The pattern coupling recognition module is used to perform pattern coupling recognition between the chromatographic signal data of the chromatograph and the mass spectrometry signal data to obtain the chemical structure of the components of the effluent; The report generation module is used to generate a material analysis report for the sample to be tested based on the chemical structure of the components.

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