CN117574744A - Optimization processing method, device, equipment and medium based on mass spectrometer - Google Patents

Abstract

This application provides an optimization processing method, device, equipment and medium based on a mass spectrometer. The method includes: obtaining the field radius of the mass spectrometer to be optimized, and determining the computational domain of the mass spectrometer to be optimized based on the field radius; Use the control variable method to determine the grid unit parameters of the computational domain, and divide the computational domain according to the grid unit parameters; obtain the simulation equation of each grid unit in the computational domain and perform simulation Calculate to obtain the ion pass rate of the mass spectrometer to be optimized, and optimize the instrument parameters of the mass spectrometer to be optimized according to the ion pass rate. It solves the problems in the existing technology of weak grid controllability, long calculation time, and poor calculation accuracy and stability, and can better optimize the design of the mass spectrometer.

Description

An optimized processing method, device, equipment and medium based on mass spectrometer

Technical field

The present application relates to the field of data processing technology, and in particular to an optimized processing method, device, equipment and medium based on a mass spectrometer.

Background technique

Mass spectrometry technology is a method of ion analysis by measuring the mass-to-charge ratio of ions. It is usually used to analyze inorganic elements including isotopes, organic small molecules, or biological macromolecules. It is used in life sciences, materials science, environmental science, and pharmaceuticals. It plays a huge and irreplaceable role in the fields of development, food safety and petrochemical industry. Among them, the quadrupole mass spectrometer uses the different stabilization conditions of ions with different mass-to-charge ratios in the quadrupole field to separate ions. It has the advantages of simple structure, small size, light weight, cheap price and easy cleaning. It is currently the most widely used. One of the small mass spectrometers.

In the process of designing and optimizing a quadrupole mass spectrometer, it is necessary to conduct electric field analysis of the quadrupole field and prediction and simulation of ion motion trajectories based on grid cells. The existing technology usually uses an unstructured meshing method to divide the grid units in the quadrupole field. However, the grid obtained by this division method has weak controllability, and the number of grids often reaches tens of millions in precise calculations. , the calculation takes a long time, and the calculation accuracy and stability are relatively poor.

Contents of the invention

This application provides an optimization processing method, device, equipment and medium based on a mass spectrometer, which is used to solve the problems in the existing technology of weak grid controllability, long calculation time, and poor calculation accuracy and stability.

In a first aspect, this application provides an optimization processing method based on a mass spectrometer, which includes: obtaining the field radius of the mass spectrometer to be optimized, and determining the computational domain of the mass spectrometer to be optimized based on the field radius; using the control variable method , determine the grid unit parameters of the computational domain, and divide the computational domain according to the grid unit parameters; obtain the simulation equation of each grid unit in the computational domain and perform simulation calculations to obtain The ion pass rate of the mass spectrometer to be optimized is determined, and the instrument parameters of the mass spectrometer to be optimized are optimized according to the ion pass rate.

In a specific implementation, the use of the control variable method to determine the grid unit parameters of the computational domain includes: obtaining a plurality of first grid unit parameters, and for each of the first grid unit parameters, The calculation domain is divided according to the first grid unit parameters; the simulation equation of each grid unit is obtained and simulation calculation is performed to obtain the ion passage rate corresponding to each of the first grid unit parameters. ; Obtain the difference between the ion pass rate corresponding to each of the first grid unit parameters and the preset ion pass rate, and determine the minimum value among the plurality of difference values, and add the minimum value to the first grid unit parameter corresponding to the first grid unit parameter. A grid unit parameter is used as the grid unit parameter of the calculation domain.

In a specific implementation, the calculation domain includes a first partition and a second partition; wherein, the radius of the first partition is smaller than the field radius, and the outer ring radius of the second partition is larger than the field radius. , the inner ring radius of the second partition is the radius of the first partition; then the control variable method is used to determine the grid unit parameters of the calculation domain, and the calculation is performed according to the grid unit parameters. The domain division process includes: using the control variable method to determine the grid unit parameters of the first partition and the second partition respectively, and calculating the grid unit parameters of the first partition and the second partition respectively according to the grid unit parameters of the first partition and the second partition. The first partition and the second partition are divided and processed.

In a specific implementation, the instrument parameters of the mass spectrometer to be optimized include one or a combination of the following: electrode rod radius, electrode rod length, DC voltage amplitude, AC voltage amplitude, AC voltage frequency, ion Radius of incidence, and angle of incidence of ions.

In a second aspect, the present application provides an optimization processing device based on a mass spectrometer, including: an acquisition module for acquiring the field radius of the mass spectrometer to be optimized, and determining the computational domain of the mass spectrometer to be optimized based on the field radius. ; The processing module is used to use the control variable method to determine the grid unit parameters of the computational domain, and divide the computational domain according to the grid unit parameters; the processing module is also used to obtain the Calculate the simulation equation of each grid unit in the domain and perform simulation calculations to obtain the ion pass rate of the mass spectrometer to be optimized, and optimize the instrument parameters of the mass spectrometer to be optimized based on the ion pass rate.

In a specific implementation, the processing module is specifically configured to: obtain a plurality of first grid unit parameters, and for each first grid unit parameter, calculate the The calculation domain is divided; the simulation equation of each grid unit is obtained and simulation calculation is performed to obtain the ion passage rate corresponding to the parameters of each first grid unit; and the simulation equation of each first grid unit is obtained. The difference between the ion passage rate corresponding to the parameter and the preset ion passage rate is determined, and the minimum value among the plurality of differences is determined, and the first grid unit parameter corresponding to the minimum value is used as the calculation domain Grid unit parameters.

In a specific implementation, the calculation domain includes a first partition and a second partition; wherein, the radius of the first partition is smaller than the field radius, and the outer ring radius of the second partition is larger than the field radius. , the inner ring radius of the second partition is the radius of the first partition; then the processing module is specifically used to: use the control variable method to determine the grid unit parameters of the first partition and the second partition respectively. , and divide the first partition and the second partition according to the grid unit parameters of the first partition and the second partition respectively.

In a specific implementation, the instrument parameters of the mass spectrometer to be optimized include one or a combination of the following: electrode rod radius, electrode rod length, DC voltage amplitude, AC voltage amplitude, AC voltage frequency, ion Radius of incidence, and angle of incidence of ions.

In a third aspect, the present application provides an electronic device, including: a processor, a memory, and a communication interface; the memory is used to store executable instructions of the processor; wherein the processor is configured to execute the executable instructions via The instructions are executed to perform the mass spectrometer-based optimization processing method described in the first aspect.

In a fourth aspect, the present application provides a readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the mass spectrometer-based optimization processing method described in the first aspect is implemented.

This application provides an optimization processing method, device, equipment and medium based on a mass spectrometer. The method includes: obtaining the field radius of the mass spectrometer to be optimized, and determining the computational domain of the mass spectrometer to be optimized based on the field radius; using control Variable method, determine the grid unit parameters of the computational domain, and divide the computational domain according to the grid unit parameters; obtain the simulation equation of each grid unit in the computational domain and perform simulation calculations to obtain the to-be- Optimize the ion pass rate of the mass spectrometer, and optimize the instrument parameters of the mass spectrometer to be optimized based on the ion pass rate. Compared with the existing technology that uses unstructured meshing methods to divide the grid units in the quadrupole field, the mass spectrometer-based optimization processing method of this application provides a more efficient and reasonable meshing method. By optimizing the instrument parameters of the mass spectrometer by performing simulation calculations in the grid unit, it solves the problems in the existing technology of weak grid controllability, long calculation time, and poor calculation accuracy and stability, and can improve Optimize the design of the mass spectrometer.

Description of the drawings

In order to more clearly explain the embodiments of the present application or the technical solutions in the prior art, the following will briefly introduce the drawings that need to be used in the description of the embodiments or the prior art. Obviously, the drawings in the following description These are some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without exerting any creative effort.

Figure 1 is a schematic flow chart of Embodiment 1 of an optimization processing method based on a mass spectrometer provided by this application;

Figure 2 is a schematic diagram of the quadrupole field structure of a quadrupole mass spectrometer;

Figure 3 is a schematic flow chart of Embodiment 2 of an optimization processing method based on a mass spectrometer provided by this application;

Figure 4 is a schematic flow chart of Embodiment 3 of an optimized processing method based on a mass spectrometer provided by this application;

Figure 5 is a schematic diagram of the quadrupole field partition of a quadrupole mass spectrometer provided by this application;

Figure 6 is a schematic diagram of the quadrupole field partitioning of another quadrupole mass spectrometer provided by this application;

Figure 7 is a schematic structural diagram of an embodiment of an optimized processing device based on a mass spectrometer provided by this application;

Figure 8 is a schematic structural diagram of an electronic device provided by this application.

Detailed ways

In order to make the purpose, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments These are part of the embodiments of this application, but not all of them. Based on the embodiments in this application, all other embodiments made by those of ordinary skill in the art based on the inspiration of this embodiment fall within the scope of protection of this application.

The terms "first", "second", "third", "fourth", etc. (if present) in the description and claims of this application and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used for Describe a specific order or sequence. It is to be understood that the data so used are interchangeable under appropriate circumstances so that the embodiments of the application described herein can be practiced in sequences other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, e.g., a process, method, system, product, or apparatus that encompasses a series of steps or units and need not be limited to those explicitly listed. Those steps or elements may instead include other steps or elements not expressly listed or inherent to the process, method, product or apparatus.

Mass spectrometry technology is a method of ion analysis by measuring the mass-to-charge ratio of ions. It is usually used to analyze inorganic elements including isotopes, organic small molecules, or biological macromolecules. It is used in life sciences, materials science, environmental science, and pharmaceuticals. It plays a huge and irreplaceable role in the fields of development, food safety and petrochemical industry. Among them, the quadrupole mass spectrometer uses the different stabilization conditions of ions with different mass-to-charge ratios in the quadrupole field to separate ions. It has the advantages of simple structure, small size, light weight, cheap price and easy cleaning. It is currently the most widely used. One of the small mass spectrometers.

In the process of designing and optimizing a quadrupole mass spectrometer, it is necessary to conduct electric field analysis of the quadrupole field and prediction and simulation of ion motion trajectories based on grid cells. The existing technology usually uses an unstructured meshing method to divide the grid units in the quadrupole field. However, the grid obtained by this division method has weak controllability, and the number of grids often reaches tens of millions in precise calculations. , the calculation takes a long time, and the calculation accuracy and stability are relatively poor.

Based on the above technical problems, the technical conception process of this application is as follows: how to provide a more efficient and reasonable grid division method to solve the existing technical problems of weak grid controllability, long calculation time, and poor calculation accuracy and stability. issues to better optimize the design of mass spectrometers.

Below, the technical solution of the present application will be described in detail through specific embodiments. It should be noted that the following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments.

Figure 1 is a schematic flow chart of Embodiment 1 of an optimization processing method based on a mass spectrometer provided in this application. Referring to Figure 1, the mass spectrometer-based optimization processing method specifically includes the following steps:

Step S101: Obtain the field radius of the mass spectrometer to be optimized, and determine the computational domain of the mass spectrometer to be optimized based on the field radius.

In this embodiment, the field radius of the mass spectrometer to be optimized can be obtained. For example, based on the known geometric parameters and physical parameters of the quadrupole field, an unstructured rough grid can be used to calculate the electric field distribution of the quadrupole field and understand the electric field distribution characteristics of the quadrupole field.

Figure 2 is a schematic diagram of the quadrupole field structure of a quadrupole mass spectrometer. As shown in Figure 2, R1, R2, R3 and R4 are the four electrode rods of the mass spectrometer. Establish a three-dimensional coordinate system. R1, R2, R3 and R4 are respectively located on the coordinate axes with the field center as the origin. Electrodes R1 and R2 are located on the x-axis, electrodes R3 and R4 are located on the y-axis. The length direction of the electrode rod is the z-axis direction. . In the quadrupole field of the mass spectrometer to be optimized, the field radius is r ₀ .

The computational domain of the mass spectrometer to be optimized can be determined based on the field radius. The computational domain is the area where the electric field analysis of the quadrupole field of the mass spectrometer and the prediction and simulation of ion trajectories are performed, that is, the area that needs to be meshed. The calculation domain is determined according to the field radius of the quadrupole field, regardless of other parameters of the mass spectrometer, so that the optimization processing method based on the mass spectrometer of the present application is not limited to a specific quadrupole field. For example, the computational domain of the mass spectrometer to be optimized can be an area with a radius of 0.9r ₀ , as shown by the dotted line in Figure 2; it can also be an area with a radius of 1.1r ₀ , as shown by the dotted line in Figure 2 .

Step S102: Use the control variable method to determine the grid unit parameters of the computational domain, and divide the computational domain according to the grid unit parameters.

In this embodiment, the control variable method can be used to determine the grid unit parameters of the calculation domain. The grid unit parameters of the computational domain can be the grid unit size, including the size of the grid unit on the x, y, and z axes. For example, the grid unit parameter can be 0.06mm, or it can be a numerical range, such as 0.01~0.09mm.

For example, multiple grid unit parameters can be set, and the calculation domain can be divided according to each grid unit parameter. For example, set multiple grid unit parameters to 0.02mm, 0.04mm, 0.06mm and 0.08mm respectively. The calculation domain is divided according to these multiple grid unit parameters.

For each division method, obtain the simulation equation of each grid unit and perform simulation calculations to obtain the ion passage rate corresponding to each grid unit parameter. For example, when the grid unit parameter is 0.02mm, the ion pass rate is 95%; when the grid unit parameter is 0.04mm, the ion pass rate is 93%; when the grid unit parameter is 0.06mm, the ion pass rate is 92%; When the grid unit parameter is 0.08mm, the ion pass rate is 90%.

Obtain the difference between the ion pass rate corresponding to each grid unit parameter and the preset ion pass rate, determine the minimum value among the multiple differences, and determine the grid unit parameter corresponding to the minimum value as the network of the calculation domain. Cell parameters. As mentioned in the previous example, the preset ion pass rate is 96%. When the grid unit parameter is determined to be 0.02mm, the difference between the ion pass rate and the preset ion pass rate is the smallest. 0.02mm can be determined as the calculation domain. Grid unit parameters, and divide the computational domain according to the grid unit parameters.

Step S103: Obtain the simulation equation of each grid unit in the calculation domain and perform simulation calculations to obtain the ion pass rate of the mass spectrometer to be optimized, and optimize the instrument parameters of the mass spectrometer to be optimized based on the ion pass rate. deal with.

In this embodiment, after dividing the computational domain, the simulation equation of each grid unit in the computational domain can be obtained and simulated calculations can be performed to obtain the ion pass rate of the mass spectrometer to be optimized, and the ion pass rate can be calculated based on the ion pass rate. The instrument parameters of the mass spectrometer to be optimized are optimized. For example, the instrument parameters of the mass spectrometer to be optimized can be adjusted according to the difference between the ion pass rate of the mass spectrometer to be optimized and a preset ion pass rate to achieve optimization of the mass spectrometer.

Among them, the instrument parameters of the mass spectrometer to be optimized may include electrode rod radius, electrode rod length, DC voltage amplitude, AC voltage amplitude, AC voltage frequency, ion incident radius, and ion incident angle.

In this embodiment, the field radius of the mass spectrometer to be optimized is obtained, and based on the field radius, the computational domain of the mass spectrometer to be optimized is determined; the control variable method is used to determine the grid unit parameters of the computational domain, and based on the network The grid cell parameters are used to divide the computational domain; the simulation equations of each grid unit in the computational domain are obtained and simulation calculations are performed to obtain the ion pass rate of the mass spectrometer to be optimized, and the ion pass rate to be optimized is calculated based on the ion pass rate. Optimize the instrument parameters of the mass spectrometer for optimization processing. Compared with the existing technology that uses unstructured meshing methods to divide the grid units in the quadrupole field, the mass spectrometer-based optimization processing method of this application provides a more efficient and reasonable meshing method. By optimizing the instrument parameters of the mass spectrometer by performing simulation calculations in the grid unit, it solves the problems in the existing technology of weak grid controllability, long calculation time, and poor calculation accuracy and stability, and can improve Optimize the design of the mass spectrometer.

Figure 3 is a schematic flow chart of Embodiment 2 of a mass spectrometer-based optimization processing method provided by this application. Based on the embodiment shown in Figure 1, the above step S102 specifically includes the following steps:

Step S301: Obtain a plurality of first grid unit parameters, and for each first grid unit parameter, divide the computational domain according to the first grid unit parameter.

Step S302: Obtain the simulation equation of each grid unit and perform simulation calculation to obtain the ion passage rate corresponding to each first grid unit parameter.

Step S303: Obtain the difference between the ion pass rate corresponding to each first grid unit parameter and the preset ion pass rate, determine the minimum value among the multiple differences, and add the first grid unit corresponding to the minimum value to The parameters serve as the grid cell parameters of this computational domain.

In this embodiment, the control variable method can be used to determine the grid unit parameters of the calculation domain. The grid unit parameters of the computational domain can be the grid unit size, including the size of the grid unit on the x, y, and z axes. For example, the grid unit parameter can be 0.06mm, or it can be a numerical range, such as 0.01~0.09mm.

Specifically, a plurality of first grid unit parameters can be obtained, and for each first grid unit parameter, the calculation domain is divided according to the first grid unit parameter. For example, the plurality of first grid unit parameters are 0.02mm, 0.04mm, 0.06mm and 0.08mm respectively. The calculation domain is divided according to the plurality of first grid unit parameters respectively.

For each division method, obtain the simulation equation of each grid unit and perform simulation calculations to obtain the ion passage rate corresponding to each first grid unit parameter. For example, when the first grid unit parameter is 0.02mm, the ion pass rate is 95%; when the first grid unit parameter is 0.04mm, the ion pass rate is 93%; when the first grid unit parameter is 0.06mm, the ion pass rate is 93%. The pass rate is 92%; when the first grid unit parameter is 0.08mm, the ion pass rate is 90%.

Obtain the difference between the ion pass rate corresponding to each first grid unit parameter and the preset ion pass rate, determine the minimum value among the multiple differences, and determine the first grid unit parameter corresponding to the minimum value as Grid cell parameters of the computational domain. As mentioned in the previous example, the preset ion pass rate is 96%, then when the first grid unit parameter is determined to be 0.02mm, the difference between the ion pass rate and the preset ion pass rate is the smallest, and 0.02mm can be determined as the calculation The grid unit parameters of the domain, and the calculation domain is divided according to the grid unit parameters.

In this embodiment, the control variable method is used to determine the grid unit parameters of the calculation domain, and an efficient and reasonable grid division method can be determined, which further solves the problem of weak grid controllability, long calculation time and long calculation time in the existing technology. The accuracy and stability are also relatively poor, which can better optimize the design of the mass spectrometer.

Figure 4 is a schematic flow chart of Embodiment 3 of a mass spectrometer-based optimization processing method provided by the present application. Based on the above embodiments shown in Figures 1 to 3, see Figure 4 for details of the mass spectrometer-based optimization processing. Includes the following steps:

Step S401: Obtain the field radius of the mass spectrometer to be optimized, and determine the computational domain of the mass spectrometer to be optimized based on the field radius.

In this embodiment, the calculation domain includes a first partition and a second partition; wherein, the radius of the first partition is smaller than the field radius, the outer ring radius of the second partition is larger than the field radius, and the inner radius of the second partition is smaller than the field radius. The ring radius is the radius of the first partition.

In this embodiment, the calculation domain can be divided into a first partition Z1 and a second partition Z2. Figure 5 is a schematic diagram of the quadrupole field partition of a quadrupole mass spectrometer provided by this application. As shown in Figure 5, in the quadrupole field of the mass spectrometer to be optimized, the field radius is r ₀ . The radius R _in1 of the first zone Z1 may be 0.9r ₀ , the outer ring radius R _in2 of the second zone Z2 may be 1.1r ₀ , and the inner ring radius may be the radius 0.9r ₀ of the first zone Z1.

In this embodiment, the computing domain may also include a third partition Z3 and a second partition Z4. For example, the outer ring radius R _in3 of the third zone Z3 may be 2.41r ₀ , and the inner ring radius is the outer ring radius R _in2 of the second zone Z2. The outer ring radius of the fourth zone Z4 may be the outer ring radius of the quadrupole field, and the inner ring radius may be the outer ring radius R _in3 of the third zone Z3.

According to the degree of influence of the quadrupole field on ions, the first partition Z1 is a key calculation area in the quadrupole field and a key area for grid division; the second partition Z2 is a more important calculation area in the quadrupole field and is also The key area for meshing; the third partition Z3 is the transition area in the quadrupole field, which can be appropriately coarsened to reduce the number of meshes; the fourth partition Z4 is the edge area in the quadrupole field, which can be The mesh is coarsened and the number of meshes is reduced. In this way, the computational domain can be meshed more reasonably, improving calculation accuracy and stability while reducing the amount of calculations and time-consuming calculations.

Step S402: Use the control variable method to determine the grid unit parameters of the first partition and the second partition respectively, and perform the calculation on the first partition and the second partition according to the grid unit parameters of the first partition and the second partition respectively. Division processing.

In this embodiment, the control variable method can be used to determine the grid unit parameters of the first partition and the grid unit parameters of the second partition. The grid unit parameter can be the grid unit size, including the size of the grid unit on the x, y, and z axes. For example, the grid unit parameter can be 0.06mm, or it can be a numerical range, such as 0.01~0.09mm. The control variable method can also be used to determine the grid unit parameters of the third partition and the grid unit parameters of the fourth partition respectively. When determining the grid unit parameters using the control variable method for each partition, the grid unit parameters of other partitions remain unchanged.

For example, the grid unit parameters of the first partition, the second partition, the third partition and the fourth partition may be as shown in Table 1.

Table 1 Grid unit parameter table

In this embodiment, the first partition, the second partition, the third partition and the fourth partition can be divided according to the grid unit parameters of the first partition, the second partition, the third partition and the fourth partition respectively.

For example, when performing structured meshing, in order to facilitate the control of the grid unit size in each partition and improve the mesh quality, the coin method can also be used to perform structured meshing in the circular area of the first partition. The second partition, the third partition and the fourth partition are then cut into 4 equal parts using the x=0, y=0 lines, finally forming a structured grid division area on the xy plane. Figure 6 is a schematic diagram of the quadrupole field partitioning of another quadrupole mass spectrometer provided by this application. As shown in Figure 6, the side length L _in0 of the central square of the first partition can be 1.15r ₀ .

In this embodiment, a variable control method can also be used to adjust the partition parameters of the first partition, the second partition, the third partition, and the fourth partition. The partition parameters can be the radii of the first partition and the second partition. Specifically, multiple partition parameters can be set while setting multiple grid unit parameters, and the calculation domain can be divided according to the combination of each partition parameter and the grid unit parameter. For example, for the first partition, multiple partition parameters are set: 0.7r ₀ , 0.9r ₀ , r ₀ and 1.1r ₀ , corresponding to multiple grid unit parameters of 0.02mm, 0.04mm, 0.06mm and 0.08mm respectively. The computational domain is divided according to the combination of these multiple partition parameters and grid unit parameters.

For each partitioning method, obtain the simulation equation of each grid unit and perform simulation calculations to obtain the ion passage rate corresponding to each combination of partition parameters and grid unit parameters. Obtain the difference between the ion pass rate corresponding to each combination and the preset ion pass rate, determine the minimum value among the multiple differences, and determine the partition parameters and grid unit parameters corresponding to the minimum value as the first partition Partition parameters and grid cell parameters.

Step S403: Obtain the simulation equation of each grid unit in the calculation domain and perform simulation calculations to obtain the ion pass rate of the mass spectrometer to be optimized, and optimize the instrument parameters of the mass spectrometer to be optimized based on the ion pass rate. deal with.

In this embodiment, after dividing the computational domain, the simulation equation of each grid unit in the computational domain can be obtained and simulated calculations can be performed to obtain the ion pass rate of the mass spectrometer to be optimized, and the ion pass rate can be calculated based on the ion pass rate. The instrument parameters of the mass spectrometer to be optimized are optimized. For example, the instrument parameters of the mass spectrometer to be optimized can be adjusted according to the difference between the ion pass rate of the mass spectrometer to be optimized and a preset ion pass rate to achieve optimization of the mass spectrometer.

Among them, the instrument parameters of the mass spectrometer to be optimized may include electrode rod radius, electrode rod length, DC voltage amplitude, AC voltage amplitude, AC voltage frequency, ion incident radius, and ion incident angle.

In this embodiment, the calculation domain includes the first partition and the second partition. The control variable method is used to determine the grid unit parameters of the first partition and the second partition respectively. The unit parameters divide the first partition and the second partition. The computational domain can be meshed by partition according to the degree of influence of the quadrupole field on ions, which can mesh the computational domain more reasonably, improve calculation accuracy and stability, and reduce the amount of calculation and time-consuming calculation. .

The following are device embodiments of the present application, which can be used to execute method embodiments of the present application. For details not disclosed in the device embodiments of this application, please refer to the method embodiments of this application.

FIG. 7 is a schematic structural diagram of an embodiment of a mass spectrometer-based optimization processing device provided by this application; as shown in FIG. 7 , the mass spectrometer-based optimization processing device 70 includes: an acquisition module 71 and a processing module 72 . Among them, the acquisition module 71 is used to obtain the field radius of the mass spectrometer to be optimized, and determine the computational domain of the mass spectrometer to be optimized based on the field radius; the processing module 72 is used to determine the grid unit of the computational domain using the control variable method. parameters, and divide the calculation domain according to the grid unit parameters; the processing module 72 is also used to obtain the simulation equation of each grid unit in the calculation domain and perform simulation calculations to obtain the ions of the mass spectrometer to be optimized. pass rate, and optimize the instrument parameters of the mass spectrometer to be optimized based on the ion pass rate.

The mass spectrometer-based optimization processing device provided by the embodiments of the present application can execute the technical solutions shown in the above method embodiments. Its implementation principles and beneficial effects are similar and will not be described again here.

In a possible implementation, the processing module 72 is specifically configured to obtain a plurality of first grid unit parameters, and for each first grid unit parameter, divide the computational domain according to the first grid unit parameter. ; Obtain the simulation equation of each grid unit and perform simulation calculations to obtain the ion pass rate corresponding to each first grid unit parameter; Obtain the ion pass rate corresponding to each first grid unit parameter and the preset The difference between the ion passage rates is determined, and the minimum value among the multiple differences is determined, and the first grid cell parameter corresponding to the minimum value is used as the grid cell parameter of the calculation domain.

The mass spectrometer-based optimization processing device provided by the embodiments of the present application can execute the technical solutions shown in the above method embodiments. Its implementation principles and beneficial effects are similar and will not be described again here.

In a possible implementation, the calculation domain includes a first partition and a second partition; wherein, the radius of the first partition is smaller than the field radius, the outer ring radius of the second partition is larger than the field radius, and the second partition The inner ring radius of the partition is the radius of the first partition; then the processing module 72 is specifically configured to use the control variable method to determine the grid unit parameters of the first partition and the second partition respectively, and according to the first partition and the second partition respectively. The grid unit parameters of the second partition divide the first partition and the second partition.

In a possible implementation, the instrument parameters of the mass spectrometer to be optimized include one or a combination of the following: electrode rod radius, electrode rod length, DC voltage amplitude, AC voltage amplitude, AC voltage frequency, ion Radius of incidence, and angle of incidence of ions.

The mass spectrometer-based optimization processing device provided by the embodiments of the present application can execute the technical solutions shown in the above method embodiments. Its implementation principles and beneficial effects are similar and will not be described again here.

Figure 8 is a schematic structural diagram of an electronic device provided by this application. As shown in Figure 8, the electronic device 80 includes: a processor 81, a memory 82, and a communication interface 83; the memory 82 is used to store executable instructions of the processor 81; the processor 81 is configured to execute the executable instructions. Implement the technical solution in any of the foregoing method embodiments.

Optionally, the memory 82 can be independent or integrated with the processor 81 .

Optionally, when the memory 82 is a device independent of the processor 81, the electronic device 80 may also include a bus 84 for connecting the above devices.

The electronic device is used to execute the technical solutions in any of the foregoing method embodiments. Its implementation principles and technical effects are similar and will not be described again here.

Embodiments of the present application also provide a readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the technical solution provided by any of the foregoing embodiments is implemented.

Persons of ordinary skill in the art can understand that all or part of the steps to implement the above method embodiments can be completed by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, the steps including the above-mentioned method embodiments are executed; and the aforementioned storage media include: ROM, RAM, magnetic disks, optical disks and other media that can store program codes.

Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present application, but not to limit it; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: The technical solutions described in the foregoing embodiments can still be modified, or some or all of the technical features can be equivalently replaced; and these modifications or substitutions do not deviate from the essence of the corresponding technical solutions from the technical solutions of the embodiments of the present application. scope.

Claims (10)

1. An optimization processing method based on mass spectrometer, characterized by including: Obtain the field radius of the mass spectrometer to be optimized, and determine the computational domain of the mass spectrometer to be optimized based on the field radius; Using the control variable method, determine the grid unit parameters of the computational domain, and divide the computational domain according to the grid unit parameters; Obtain the simulation equation of each grid unit in the calculation domain and perform simulation calculations to obtain the ion pass rate of the mass spectrometer to be optimized, and perform instrument parameters of the mass spectrometer to be optimized based on the ion pass rate. Optimization processing. 2. The mass spectrometer-based optimization processing method according to claim 1, characterized in that the use of a control variable method to determine the grid unit parameters of the computational domain includes: Obtain a plurality of first grid unit parameters, and for each first grid unit parameter, divide the computing domain according to the first grid unit parameter; Obtain the simulation equation of each grid unit and perform simulation calculations to obtain the ion passage rate corresponding to each first grid unit parameter; Obtain the difference between the ion pass rate corresponding to each of the first grid unit parameters and the preset ion pass rate, determine the minimum value among the plurality of difference values, and add the first value corresponding to the minimum value to The grid cell parameters are used as the grid cell parameters of the computational domain. 3. The mass spectrometer-based optimization processing method according to claim 1 or 2, characterized in that the calculation domain includes a first partition and a second partition; wherein the radius of the first partition is smaller than the field radius. , the outer ring radius of the second partition is greater than the field radius, and the inner ring radius of the second partition is the radius of the first partition; Then, using the control variable method to determine the grid unit parameters of the calculation domain, and dividing the calculation domain according to the grid unit parameters includes: using the control variable method to determine the first partitions respectively. and the grid unit parameters of the second partition, and divide the first partition and the second partition according to the grid unit parameters of the first partition and the second partition respectively. 4. The mass spectrometer-based optimization processing method according to claim 1 or 2, characterized in that the instrument parameters of the mass spectrometer to be optimized include a combination of one or more of the following: Electrode rod radius, electrode rod length, DC voltage amplitude, AC voltage amplitude, AC voltage frequency, ion incident radius, and ion incident angle. 5. An optimized processing device based on a mass spectrometer, characterized in that it includes: An acquisition module, used to obtain the field radius of the mass spectrometer to be optimized, and determine the computational domain of the mass spectrometer to be optimized based on the field radius; A processing module, configured to use the control variable method to determine the grid unit parameters of the computational domain, and divide the computational domain according to the grid unit parameters; The processing module is also used to obtain the simulation equation of each grid unit in the calculation domain and perform simulation calculations to obtain the ion pass rate of the mass spectrometer to be optimized, and calculate the ion pass rate according to the ion pass rate. The instrument parameters of the mass spectrometer to be optimized are optimized. 6. The optimized processing device based on mass spectrometer according to claim 5, characterized in that the processing module is specifically used for: Obtain a plurality of first grid unit parameters, and for each first grid unit parameter, divide the computing domain according to the first grid unit parameter; Obtain the simulation equation of each grid unit and perform simulation calculations to obtain the ion passage rate corresponding to each first grid unit parameter; Obtain the difference between the ion pass rate corresponding to each of the first grid unit parameters and the preset ion pass rate, determine the minimum value among the plurality of difference values, and add the first value corresponding to the minimum value to The grid cell parameters are used as the grid cell parameters of the computational domain. 7. The mass spectrometer-based optimization processing device according to claim 5 or 6, characterized in that the calculation domain includes a first partition and a second partition; wherein the radius of the first partition is smaller than the field radius. , the outer ring radius of the second partition is greater than the field radius, and the inner ring radius of the second partition is the radius of the first partition; then the processing module is specifically used for: Using the control variable method, the grid unit parameters of the first partition and the second partition are determined respectively, and the first partition and the second partition are performed according to the grid unit parameters of the first partition and the second partition respectively. Division processing. 8. The mass spectrometer-based optimization processing device according to claim 5 or 6, characterized in that the instrument parameters of the mass spectrometer to be optimized include a combination of one or more of the following: Electrode rod radius, electrode rod length, DC voltage amplitude, AC voltage amplitude, AC voltage frequency, ion incident radius, and ion incident angle. 9. An electronic device, characterized in that it includes: Processor, memory, communication interface; The memory is used to store executable instructions of the processor; Wherein, the processor is configured to execute the mass spectrometer-based optimization processing method according to any one of claims 1 to 4 via executing the executable instructions. 10. A readable storage medium with a computer program stored thereon, characterized in that when the computer program is executed by a processor, the mass spectrometer-based optimization processing method according to any one of claims 1 to 4 is implemented.