Photoelectron spectroscopy analysis method and device, electronic equipment and storage medium

Abstract

The embodiment of the invention provides a photoelectron spectroscopy analysis method and device, electronic equipment and a storage medium, and belongs to the technical field of surface material detection. The method comprises the following steps: performing photoelectron spectroscopy detection on a target sample to obtain an initial photoelectron spectroscopy; performing energy spectrum data point selection according to the initial photoelectron spectroscopy to obtain a photoelectron spectroscopy data point sequence; updating a preset initial photoelectron spectroscopy model according to an expectation maximization algorithm and the photoelectron spectroscopy data point sequence to obtain a first photoelectron spectroscopy fitting model composed of all photoelectron peaks; obtaining a target quantum effect constraint of the target sample; updating all the first photoelectron peaks according to quantum effect constraints under centralization field approximation to obtain a second photoelectron spectrum fitting model; and performing accompanying peak correction fitting according to the accompanying peak energy proportion of the photoelectron peak in the second photoelectron spectrum to obtain a complete target photoelectron spectrum. According to the embodiment of the invention, the accuracy of photoelectron spectrum analysis can be improved.

Description

Technical Field

[0001] The present application relates to the technical field of surface material detection, and in particular to a photoelectron energy spectrum analysis method and device, electronic equipment, and storage medium. Background Art

[0002] X-ray photoelectron spectroscopy is a technique that uses X-rays to detect the sample surface, causing the sample surface to emit photoelectrons, thereby measuring the photoelectron spectrum. Photoelectron spectroscopy can characterize the physical and chemical properties of the sample.

[0003] At present, the specific parameters of the photoelectron peaks of the spectral lines in the measured photoelectron energy spectrum, such as the peak shape or peak area of ​​the photoelectron peak, are often not accurate enough. For example, due to the different scattering intensities of the photoelectrons emitted from the sample surface, the measured photoelectron energy spectrum often has errors, and the peak area of ​​the photoelectron energy spectrum does not conform to the quantum effect constraints of quantum mechanics.

[0004] Therefore, how to improve the authenticity and accuracy of photoelectron energy spectra has become a technical problem that needs to be solved urgently. Summary of the invention

[0005] The main purpose of the embodiments of the present application is to propose a photoelectron energy spectrum analysis method and device, electronic equipment, and storage medium, aiming to improve the authenticity and accuracy of the photoelectron energy spectrum and obtain a photoelectron energy spectrum that meets the constraints of quantum effects.

[0006] To achieve the above object, a first aspect of an embodiment of the present application provides a photoelectron spectroscopy analysis method, the method comprising: Performing photoelectron spectrum detection on the target sample to obtain an initial photoelectron spectrum; Selecting energy spectrum data points according to the initial photoelectron energy spectrum to obtain a photoelectron energy spectrum data point sequence; Performing a first model parameter update on a preset initial photoelectron energy spectrum fitting model according to a preset expectation maximization algorithm and the photoelectron energy spectrum data point sequence to obtain a first photoelectron energy spectrum fitting model; Acquiring target quantum effect constraints of the target sample; According to a preset centralized field approximate relationship and the target quantum effect constraint, updating the second model parameters of the first photoelectron energy spectrum fitting model to obtain a second photoelectron energy spectrum fitting model; The photoelectron energy spectrum data point sequence is subjected to energy spectrum fitting according to the second photoelectron energy spectrum fitting model to obtain a target photoelectron energy spectrum.

[0007] In some embodiments, the target quantum effect constraint includes a peak pairing constraint and a peak attribute ratio threshold; The method of updating the first photoelectron energy spectrum fitting model with a second model parameter according to the preset centralization field approximate relationship and the target quantum effect constraint to obtain a second photoelectron energy spectrum fitting model includes: Performing photoelectron peak fitting on the photoelectron spectrum data point sequence using the first photoelectron spectrum fitting model to obtain at least two target photoelectron peaks; Through the peak pairing constraint condition, a peak pairing test is performed on any two of the target photoelectron peaks to obtain a first target photoelectron peak and a second target photoelectron peak; Determining a peak attribute value ratio according to the attribute value of the first target photoelectron peak and the attribute value of the second target photoelectron peak; When the peak attribute value ratio is not equal to the peak attribute ratio threshold, model parameters of the first photoelectron energy spectrum fitting model are updated according to the centralized field approximate relationship to obtain the second photoelectron energy spectrum fitting model.

[0008] In some embodiments, the model parameters of the first photoelectron energy spectrum fitting model include an initial peak intensity parameter and an initial peak position parameter; the peak attribute value ratio includes a peak intensity ratio, the peak attribute ratio threshold includes a peak intensity ratio threshold, and the centralized field approximate relation includes a centralized field approximate splitting peak relation; When the peak attribute value ratio is not equal to the peak attribute ratio threshold, updating the model parameters of the first photoelectron energy spectrum fitting model according to the centralized field approximate relationship to obtain the second photoelectron energy spectrum fitting model includes: When the peak intensity ratio is not equal to the peak intensity ratio threshold, determining a first peak intensity constraint relational expression and a peak position constraint relational expression according to the centralized field approximate splitting peak relational expression; Determining a first peak intensity confinement factor according to the first peak intensity confinement relation, the total angular quantum number of the first target photoelectron peak, and the total angular quantum number of the second target photoelectron peak; Update the initial peak intensity parameter according to the first peak intensity constraint factor to obtain a first target peak intensity parameter; Determine a peak position constraint factor according to the peak position constraint relationship, the principal quantum number, angular quantum number and total angular quantum number of the first target photoelectron peak, and the principal quantum number, angular quantum number and total angular quantum number of the second target photoelectron peak; Update the initial peak position parameter according to the peak position constraint factor to obtain a target peak position parameter; The second photoelectron energy spectrum fitting model is determined according to the first target peak intensity parameter and the target peak position parameter.

[0009] In some embodiments, the model parameters of the first photoelectron energy spectrum fitting model include initial peak intensity parameters; the peak attribute value ratio also includes peak area ratio, the peak pairing constraint condition also includes satellite companion peak constraint condition, the peak attribute ratio threshold value also includes peak area ratio threshold value, and the centralized field approximate relationship formula also includes centralized field approximate satellite companion peak relationship formula; When the peak attribute value ratio is not equal to the peak attribute ratio threshold, updating the model parameters of the first photoelectron energy spectrum fitting model according to the centralized field approximate relationship to obtain the second photoelectron energy spectrum fitting model further includes: When the peak area ratio is not equal to the peak area ratio threshold, determining a second peak intensity constraint relational expression according to the central field approximate satellite companion peak relational expression; Determining a second peak intensity constraint factor according to the second peak intensity constraint relationship, the peak area of ​​the first target photoelectron peak, and the peak area of ​​the second target photoelectron peak; Update the initial peak intensity parameter according to the second peak intensity constraint factor to obtain a second target peak intensity parameter; The second photoelectron energy spectrum fitting model is determined according to the second target peak intensity parameter.

[0010] In some embodiments, the initial photoelectron energy spectrum has an initial photoelectron peak; and selecting energy spectrum data points according to the initial photoelectron energy spectrum to obtain a photoelectron energy spectrum data point sequence includes: Dividing the energy spectrum data points according to the spectrum lines of the initial photoelectron energy spectrum to obtain at least two initial background data points and at least two initial non-background data points; wherein each of the initial background data points and each of the initial non-background data points has an energy value and an intensity value; Performing background energy spectrum curve fitting on at least two of the initial background data points according to a preset Gaussian random process function to obtain a background energy spectrum curve; According to the energy value and the intensity value of each of the initial background data points and the energy value of each of the initial non-background data points, performing a first intensity value update on the intensity value of each of the initial non-background data points to obtain a corresponding target non-background data point; According to the background energy spectrum curve, the intensity value of each of the initial background data points is updated with a second intensity value to obtain a corresponding target background data point; wherein the intensity value of the target background data point is less than the intensity value of the initial background data point; Data point integration is performed according to the target non-background data points and the target background data points to obtain the photoelectron energy spectrum data point sequence.

[0011] In some embodiments, performing a first intensity value update on the intensity value of each of the initial non-background data points according to the energy value and the intensity value of each of the initial background data points and the energy value of each of the initial non-background data points to obtain a corresponding target non-background data point includes: Calculate the background intensity according to the energy value and intensity value of each of the initial background data points and the energy value of each of the initial non-background data points to obtain a background intensity vector; The intensity value of each of the initial non-background data points is updated with a first intensity value according to the background intensity vector to obtain a target non-background data point.

[0012] In some embodiments, the dividing of the energy spectrum data points according to the spectrum lines of the initial photoelectron energy spectrum to obtain at least two initial background data points and at least two initial non-background data points includes: Selecting energy spectrum data points from the initial photoelectron energy spectrum to obtain a plurality of initial energy spectrum data points; Each of the initial energy spectrum data points is divided according to the trough of the spectrum line of the initial photoelectron energy spectrum to obtain at least two initial background data points and at least two initial non-background data points; wherein the initial background data point is located at the trough of the spectrum line.

[0013] To achieve the above-mentioned purpose, a second aspect of an embodiment of the present application provides a photoelectron spectrum analysis device, the device comprising: A photoelectron spectrum acquisition module is used to perform photoelectron spectrum detection on the target sample and obtain an initial photoelectron spectrum; A data point selection module, used for selecting energy spectrum data points according to the initial photoelectron energy spectrum to obtain a photoelectron energy spectrum data point sequence; A first model parameter updating module, used for updating a first model parameter of a preset initial photoelectron energy spectrum fitting model according to a preset expectation maximization algorithm and the photoelectron energy spectrum data point sequence to obtain a first photoelectron energy spectrum fitting model; A quantum effect constraint acquisition module, used to acquire a target quantum effect constraint of the target sample; A second model parameter updating module is used to update the second model parameters of the first photoelectron energy spectrum fitting model according to a preset centralized field approximate relationship and the target quantum effect constraint to obtain a second photoelectron energy spectrum fitting model; The energy spectrum fitting module is used to perform energy spectrum fitting on the photoelectron energy spectrum data point sequence according to the second photoelectron energy spectrum fitting model to obtain a target photoelectron energy spectrum.

[0014] To achieve the above objectives, a third aspect of an embodiment of the present application proposes an electronic device, which includes a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the method described in the first aspect is implemented.

[0015] To achieve the above-mentioned purpose, the fourth aspect of an embodiment of the present application proposes a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method described in the first aspect is implemented.

[0016] The photoelectron energy spectrum analysis method and device, electronic device, and storage medium proposed in the present application obtain a photoelectron energy spectrum data point sequence corresponding to an initial photoelectron energy spectrum, and update the initial photoelectron energy spectrum fitting model according to the expectation maximization algorithm and the photoelectron energy spectrum data point sequence to obtain a first photoelectron energy spectrum fitting model, and then obtain a target quantum effect constraint of the target sample; according to the centralized field approximation relationship and the target quantum effect constraint, the second model parameter of the first photoelectron energy spectrum fitting model is updated to obtain a second photoelectron energy spectrum fitting model, thereby ensuring that the target photoelectron energy spectrum fitted by the second photoelectron energy spectrum fitting model meets the target quantum effect constraint of the target sample, thereby improving the accuracy of photoelectron energy spectrum analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 is a flow chart of the photoelectron spectroscopy analysis method provided in an embodiment of the present application; Figure 2 yes Figure 1 Flowchart of step 102 in FIG. Figure 3 yes Figure 2 Flow chart of step 201 in; Figure 4 is a specific schematic diagram of the initial photoelectron energy spectrum provided in the embodiment of the present application; Figure 5 is a specific schematic diagram of an initial photoelectron energy spectrum provided by another embodiment of the present application; Figure 6 yes Figure 2 Flow chart of step 203 in; Figure 7 yes Figure 1 Flowchart of step 105 in; Figure 8 This is provided by an embodiment of the present application Figure 7 Flowchart of step 504 in; Fig. 9 Another embodiment of the present application provides Figure 7 Flowchart of step 504 in; Fig.10 is a schematic diagram of the structure of a photoelectron spectrum analysis device provided in an embodiment of the present application; Fig.11 It is a schematic diagram of the hardware structure of the electronic device provided in the embodiment of the present application. DETAILED DESCRIPTION

[0018] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0019] It should be noted that, although the functional modules are divided in the device schematic diagram and the logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than the module division in the device or the order in the flowchart. The terms "first", "second", etc. in the specification, claims and the above drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence.

[0020] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of this application and are not intended to limit this application.

[0021] First, some nouns involved in this application are analyzed: X-ray photoelectron spectroscopy (XPS): also known as Electron Spectroscopy for Chemical Analysis (ESCA), is a surface analysis technique. In X-ray photoelectron spectroscopy, the sample is irradiated with X-rays to stimulate the emission of electrons from atoms or molecules in the sample, so that photoelectrons are emitted from the sample surface. Electrons excited by photons are called photoelectrons, and these photoelectrons mainly come from the inner shell of atoms on the surface of the sample. The energy of the photoelectrons can be measured, and the photoelectron kinetic energy is used as the horizontal coordinate and the relative intensity of the photoelectrons is used as the vertical coordinate to obtain a photoelectron spectrum, thereby obtaining physical and chemical information of the sample, such as the chemical composition of the sample.

[0022] Central field approximation method: It is a method that regards each electron in an atom as moving in a potential field that is spherically symmetric with respect to the nucleus, and is used to calculate the energy of the electron.

[0023] Background signal: refers to other signals that exist in addition to the photoelectron signal of the sample during the XPS measurement process. These signals mainly come from the energy lost by the photoelectrons during the escape process, such as the energy lost due to inelastic collisions. These lost energies affect the measured value of the photoelectron binding energy and form background signals.

[0024] Split peak: refers to a pair of photoelectron peaks caused by the spin-orbit coupling of electrons. In photoelectron energy spectra (such as XPS), due to the spin-orbit coupling effect of electrons, energy levels with the same principal quantum number but different spin and orbital angular momentum undergo energy splitting, thus forming two or more peaks in the energy spectrum. These peaks are called split peaks.

[0025] Satellite peaks: refers to other spectral lines with lower energy produced by atoms or molecules being excited, in addition to the main spectral lines (also called main peaks) during spectral analysis. These satellite peaks are caused by the fact that when atoms or molecules transition from high energy levels to low energy levels, they are affected by various factors, such as multiple fission (splitting of energy levels), electron shock (electrons deviate from their original orbits due to external forces) and shock separation (electrons are completely stripped from atoms or molecules), resulting in the production of spectral lines with lower energy adjacent to the main peak.

[0026] Artificial Intelligence (AI): is the study and development of theories, methods, techniques and application systems for simulating, extending and expanding human intelligence. Research in this field includes robotics, speech recognition, image recognition, natural language processing, etc.

[0027] Machine learning: is a branch of artificial intelligence that enables computer systems to automatically learn and improve their performance using data and algorithms. Specifically, machine learning models can be trained using sample data to make predictions or decisions.

[0028] The photoelectron energy spectrum analysis method and device, electronic device, and storage medium provided in the embodiments of the present application are specifically described through the following embodiments. First, the photoelectron energy spectrum analysis method in the embodiments of the present application is described.

[0029] The embodiments of the present application can acquire and process relevant data based on artificial intelligence technology. Artificial Intelligence (AI) 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 knowledge to obtain the best results.

[0030] The photoelectron energy spectrum analysis method provided in the embodiment of the present application can be applied in a terminal or in a server, and can also be software running in a terminal or a server.

[0031] The present application can be used in many general or special computer system environments or configurations, such as personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronic devices, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, etc.

[0032] Figure 1 is an optional flow chart of the photoelectron spectroscopy analysis method provided in an embodiment of the present application, Figure 1 The method may include but is not limited to steps 101 to 106.

[0033] Step 101, performing photoelectron spectrum detection on a target sample to obtain an initial photoelectron spectrum; Step 102, selecting energy spectrum data points according to the initial photoelectron energy spectrum to obtain a photoelectron energy spectrum data point sequence; Step 103, updating the first model parameters of the preset initial photoelectron energy spectrum fitting model according to the preset expectation maximization algorithm and the photoelectron energy spectrum data point sequence to obtain a first photoelectron energy spectrum fitting model; Step 104, obtaining target quantum effect constraints of the target sample; Step 105, updating the second model parameters of the first photoelectron energy spectrum fitting model according to the preset centralized field approximate relationship and the target quantum effect constraint to obtain a second photoelectron energy spectrum fitting model; Step 106 , performing energy spectrum fitting on the photoelectron energy spectrum data point sequence according to the second photoelectron energy spectrum fitting model to obtain a target photoelectron energy spectrum.

[0034] The beneficial effects of the embodiments of the present application include but are not limited to: after obtaining a photoelectron spectrum data point sequence corresponding to an initial photoelectron spectrum, and updating the initial photoelectron spectrum fitting model according to an expectation-maximization algorithm and the photoelectron spectrum data point sequence to obtain a first photoelectron spectrum fitting model, a target quantum effect constraint of the target sample is also obtained; according to a centralized field approximation relationship and a target quantum effect constraint, a second model parameter update is performed on the first photoelectron spectrum fitting model to obtain a second photoelectron spectrum fitting model, thereby ensuring that the target photoelectron spectrum fitted by the second photoelectron spectrum fitting model meets the target quantum effect constraint, thereby improving the reliability and authenticity of the photoelectron spectrum analysis method.

[0035] In some embodiments, step 101 may include: (1) pre-treating the target sample. Specifically, appropriate pre-treatment may be performed according to experimental requirements, such as polishing and cleaning the target sample. (2) The target sample is set in a vacuum system. The vacuum system has a sample slot for fixing the target sample; in the vacuum system, an X-ray light source, a photoelectron spectrometer and other equipment may also be installed. (3) Setting an X-ray source. Specifically, the X-ray source may be adjusted according to preset position information to ensure that the X-ray beam emitted by the X-ray source irradiates the sampling point on the surface of the target sample; or, the angle between the X-ray source and the target sample may be adjusted to ensure that the surface of the target sample and the X-ray emitted by the X-ray source are perpendicular to each other; the X-ray source may also be set according to a preset X-ray energy value to excite electrons on the surface of the target sample to generate photoelectrons. A monochromatic X-ray source may be used. (4) Initializing the instrument parameters of the photoelectron spectrometer. Specifically, the photoelectron spectrometer is used to collect data to generate a photoelectron spectrum. Prior to this, the instrument parameters of the photoelectron spectrometer, such as the energy resolution and the number of sampling points, need to be initialized. (5) The target sample is measured by an X-ray source and a photoelectron spectrometer to obtain an initial photoelectron energy spectrum. The initial measurement energy spectrum can be obtained by performing multiple measurements at different sampling points on the surface of the target sample, and then the average value of the multiple initial measurement energy spectra is calculated to obtain the initial photoelectron energy spectrum to improve the accuracy of the energy spectrum measurement. The initial photoelectron energy spectrum can also be obtained by other methods, not limited to this.

[0036] It should be noted that the target sample is a condensed matter, including solid and liquid substances. In some embodiments, the target sample can be a metal (iron, copper, etc.) or a semiconductor, such as a divalent copper sample. In another embodiment, the target photoelectron spectrum corresponding to the target sample can be the 2p orbital photoelectron spectrum of divalent copper.

[0037] It should be noted that the photoelectron energy spectrum (such as the initial photoelectron energy spectrum and the target photoelectron energy spectrum) has spectral lines, and the spectral lines have peaks and troughs. The photoelectron peak refers to the peak of the spectral line. The photoelectron peak has peak properties, such as peak position, peak width, peak shape, peak area (also called integrated intensity) and other properties. The abscissa of the photoelectron energy spectrum is the energy value, and the ordinate is the intensity value. Among them, the energy value is used to characterize the electron binding energy of the photoelectron, and the intensity value is used to characterize the relative intensity of the photoelectron, and the intensity value corresponds to the energy value one by one.

[0038] In step 102 of some embodiments, the photoelectron energy spectrum data point sequence includes a plurality of energy spectrum data points, and the energy spectrum data points are points on the spectrum line of the initial photoelectron energy spectrum. Specifically, the photoelectron energy spectrum data point sequence is a data point sequence obtained after deducting the background signal. In another embodiment, after obtaining the photoelectron energy spectrum background data point sequence, the photoelectron energy spectrum background data point sequence can be fitted according to a Gaussian random process to obtain a background curve of the entire spectrum (initial photoelectron energy spectrum).

[0039] In step 103 of some embodiments, the initial photoelectron energy spectrum fitting model is a machine learning model. In some embodiments, it should be noted that in the relevant technology, the photoelectron energy spectrum can be solved by the least square method, but the energy spectrum analysis efficiency of this method is low, it is easy to fall into the local optimal solution, and the authenticity of the photoelectron energy spectrum is low. In the embodiment of the present application, the initial photoelectron energy spectrum fitting model is updated by the expectation maximization algorithm to obtain the target photoelectron energy spectrum, which improves the efficiency of energy spectrum analysis and the authenticity of the target photoelectron energy spectrum.

[0040] In step 104 of some embodiments, the target quantum effect constraint is used to reflect whether the peak parameter ratio relationship between the two photoelectron peaks conforms to the theory of quantum mechanics. In one embodiment, for example, if the target sample is a metal titanium sample, the initial photoelectron energy spectrum is the 2p orbital photoelectron energy spectrum of ‌titanium (Ti), and the two photoelectron peaks in the initial photoelectron energy spectrum are a pair of splitting peaks, then based on the theory of quantum mechanics, the peak intensity ratio of the two photoelectron peaks should be 3:2. In another embodiment, if the two photoelectron peaks in the initial photoelectron energy spectrum of the metal titanium sample are a pair of satellite companion peaks, then based on the theory of quantum mechanics, the peak area ratio of the two photoelectron peaks should be 2:1.

[0041] In step 105 of some embodiments, it should be noted that in the related art, the spectral lines of the fitted photoelectron energy spectrum can be matched with the experimentally observed spectral lines, and the peak parameters (such as peak position and peak intensity) of the photoelectron peak of the spectral line can be adjusted to update the photoelectron energy spectrum. However, this method is easily affected by data noise and scattering intensity, resulting in a low degree of consistency between the photoelectron energy spectrum and the theory of quantum mechanics, or even violating the theory of quantum mechanics, such as the photoelectron peak of the spectral line of the photoelectron energy spectrum does not meet the constraint conditions of the splitting peak. In view of the above technical problems, the embodiment of the present application updates the first photoelectron energy spectrum fitting model through the centralized field approximate relationship and the target quantum effect constraint, and obtains the second photoelectron energy spectrum fitting model to ensure that the target photoelectron energy spectrum output by the second photoelectron energy spectrum fitting model meets the target quantum effect constraint, so that the target photoelectron energy spectrum that meets the target quantum effect constraint can be obtained, thereby improving the authenticity of the energy spectrum analysis results.

[0042] In step 106 of some embodiments, peak fitting can be performed on the photoelectron energy spectrum data point sequence using the second photoelectron energy spectrum fitting model to obtain multiple photoelectron peaks; then, energy spectrum fitting is performed on the multiple photoelectron peaks using the second photoelectron energy spectrum fitting model to obtain a target photoelectron energy spectrum.

[0043] It should be noted that the embodiment of the present application automatically performs spectrum fitting through the second photoelectron spectrum fitting model, and can analyze the photoelectron spectrum with high throughput, which can be applied to the scenario of large-scale photoelectron spectrum analysis in high-throughput laboratories / robotic laboratories. Among them, high-throughput analysis of the photoelectron spectrum refers to the detection and photoelectron spectrum analysis of a large number of samples.

[0044] See also Figure 2 In some embodiments, the initial photoelectron spectrum has an initial photoelectron peak. Step 102 may include but is not limited to steps 201 to 205: Step 201, dividing the energy spectrum data points according to the spectrum lines of the initial photoelectron energy spectrum to obtain at least two initial background data points and at least two initial non-background data points; wherein each initial background data point and each initial non-background data point has an energy value and an intensity value; Step 202, performing background energy spectrum curve fitting on at least two initial background data points according to a preset Gaussian random process function to obtain a background energy spectrum curve; Step 203, performing a first intensity value update on the intensity value of each initial non-background data point according to the energy value and intensity value of each initial background data point and the energy value of each initial non-background data point, to obtain a corresponding target non-background data point; Step 204, updating the intensity value of each initial background data point with a second intensity value according to the background energy spectrum curve to obtain a corresponding target background data point; wherein the intensity value of the target background data point is less than the intensity value of the initial background data point; Step 205 , integrating data points according to the target non-background data points and the target background data points to obtain a photoelectron energy spectrum data point sequence.

[0045] It should be noted that in the process of measuring the photoelectron spectrum of the target sample, there will be background signals. The background signal is an interference signal that will affect the accuracy of the photoelectron spectrum analysis. For example, the background signal will affect the intensity value of the spectrum line, resulting in a deviation between the intensity value and the actual photoelectron intensity value. In order to eliminate the influence of the background signal of the target sample on the photoelectron spectrum, the photoelectron spectrum needs to be corrected, that is, background stripping is performed.

[0046] The advantage of this embodiment is that the initial background data points and the initial non-background data points are obtained according to the initial photoelectron energy spectrum, and the intensity values ​​of the initial background data points and the initial non-background data points are updated respectively, thereby eliminating the influence of the background signal on the intensity value of the data point, realizing the background stripping of the initial background data points and the initial non-background data points, and obtaining more accurate target background data points and target non-background data points. Then, the photoelectron energy spectrum data point sequence is integrated, so that the target photoelectron energy spectrum can be obtained by performing energy spectrum fitting according to the photoelectron energy spectrum data point sequence, thereby improving the accuracy of the target photoelectron energy spectrum analysis.

[0047] In step 201 of some embodiments, the difference between the initial background data points and the initial non-background data points is that the initial background data points are located at the trough of the spectrum line, and the initial non-background data points are located at the peak of the spectrum line (ie, the photoelectron peak).

[0048] In step 202 of some embodiments, the initial background data points can be fitted by a Gaussian random process function to obtain a background energy spectrum curve. The background energy spectrum curve overlaps or approaches the part with the relatively lowest spectral line intensity value of the initial photoelectron energy spectrum. A suitable background energy spectrum curve fitting method can also be selected according to needs, which is not limited in the embodiments of the present application.

[0049] In step 203 of some embodiments, the intensity value of the target non-background data point is less than or equal to the intensity value of the initial non-background data point. Step 203 may also be to perform a difference calculation between the intensity value of the initial background data point and the intensity value of the corresponding data point on the background energy spectrum curve to obtain the corresponding target non-background data point. The corresponding data point on the background energy spectrum curve refers to a data point with the same energy value as the initial background data point.

[0050] In step 204 of some embodiments, the intensity value of each initial background data point may be subtracted from the corresponding data point on the background energy spectrum curve. For example, the initial background data point is a data point on the background energy spectrum curve, so the intensity value of each target background data point may be 0.

[0051] In step 205 of some embodiments, the photoelectron energy spectrum data point sequence includes all target non-background data points and target background data points. In some embodiments, the energy spectrum data points (including target background data points and target non-background data points) in the photoelectron energy spectrum data point sequence are sorted from small to large according to energy values.

[0052] See also Figure 3 In some embodiments, step 201 may include but is not limited to steps 301 to 302: Step 301, selecting energy spectrum data points from the initial photoelectron energy spectrum to obtain a plurality of initial energy spectrum data points; Step 302, dividing each initial energy spectrum data point according to the trough of the spectrum line of the initial photoelectron energy spectrum to obtain at least two initial background data points and at least two initial non-background data points; wherein the initial background data point is located at the trough of the spectrum line.

[0053] The advantage of this embodiment is that after obtaining the initial energy spectrum data points, each initial energy spectrum data point is divided according to the trough of the spectrum line of the initial photoelectron energy spectrum, thereby obtaining initial background data points and initial non-background data points, so as to facilitate the subsequent removal of background signals from the initial background data points and the initial non-background data points, respectively, to obtain more accurate target background data points and target non-background data points, thereby improving the accuracy of the target photoelectron energy spectrum analysis.

[0054] In step 301 of some embodiments, initial energy spectrum data points may be extracted according to a preset number of data points, or may be extracted according to special data points such as the apex of a photoelectron peak. Other suitable data point extraction methods may also be selected according to requirements, and the present application embodiment does not limit this.

[0055] like Figure 4 and Figure 5 As shown, in some embodiments, Figure 4 It is a specific schematic diagram of the initial photoelectron energy spectrum, which can be specifically the photoelectron energy spectrum of the 2p orbit of divalent copper. Among them, the horizontal axis X represents the energy value, specifically the electron binding energy of the photoelectron, and the unit is eV (electron volt). The vertical axis Y represents the intensity value, specifically the relative intensity of the photoelectron, and its unit is not limited and can be any unit. Figure 4 The original intensity spectrum line in the term "initially photoelectron energy spectrum" refers to the original spectrum line of the initial photoelectron energy spectrum; the Fourier transform intensity spectrum line refers to the Fourier transform intensity spectrum line obtained by smoothing the original intensity spectrum line through the Fourier transform algorithm, thereby improving the anti-interference ability of the photoelectron energy spectrum analysis method. The spectrum line of the initial photoelectron energy spectrum can be the original intensity spectrum line or the Fourier transform intensity spectrum line, without limitation. Figure 5 and Figure 4 Corresponding, in Figure 5 In the embodiment, the background energy spectrum curve is a curve obtained by Gaussian fitting based on the spectrum line of the initial photoelectron energy spectrum (the original intensity spectrum line is taken as an example in this embodiment). The background data point is the point of the overlapping part of the background energy spectrum curve and the spectrum line of the initial photoelectron energy spectrum.

[0056] In step 302 of some embodiments, it should be noted that the initial background data point is not located at the photoelectron peak. The initial background data point may be a data point located at a trough of a spectrum line, or a data point with a relatively low intensity value.

[0057] In some embodiments, the spectrum line of the initial photoelectron spectrum has multiple spectrum data points. Specifically, the energy spectrum data point With energy value and intensity value . Where j represents the jth energy spectrum data point, On the spectrum line of the initial photoelectron energy spectrum, m independent background intervals are divided, and then all energy spectrum data points falling in the background intervals are determined as background data points. Thus, all energy spectrum data points on the spectrum line of the initial photoelectron energy spectrum are divided into two parts: Background data points ,as well as Non-background data points . Where k represents the kth background data point, l represents the lth non-background data point, ,satisfy .

[0058] See also Figure 6 In some embodiments, step 203 may include but is not limited to steps 401 to 402: Step 401, calculating the background intensity according to the energy value and intensity value of each initial background data point and the energy value of each initial non-background data point to obtain a background intensity vector; Step 402 , performing a first intensity value update on the intensity value of each initial non-background data point according to the background intensity vector to obtain a target non-background data point.

[0059] The advantage of this embodiment is that after the background intensity vector is calculated based on the energy value and intensity value of each initial background data point and the energy value of each initial non-background data point, the intensity value of each initial non-background data point is updated with a first intensity value through the background intensity vector, thereby obtaining the target non-background data point, thereby improving the accuracy of the target non-background data point.

[0060] In step 401 of some embodiments, according to Initial background data points The energy value of the initial background energy value vector is determined by , ;according to The intensity values ​​of the initial background data points determine the initial background intensity value vector , ;according to Initial non-background data points The energy value of the initial non-background energy value vector is determined by , ;according to The intensity values ​​of the initial non-background data points determine the initial non-background intensity value vector , , that is, dividing the data into two complementary sets.

[0061] Initial non-background energy value vector The corresponding background intensity vector As shown in formula (1): , formula (1); in, It is a hyperparameter, and its default setting is 0.01; represents the identity matrix, Represents the Gaussian kernel function. The definition of the Gaussian kernel function is shown in formula (2): , formula (2); in, represents the two input variables of the Gaussian kernel function, express The square of the second norm of For generation optimization variables, it can be set to a fixed value of 0.01.

[0062] In step 402 of some embodiments, the intensity value of each initial non-background data point may be subtracted from the corresponding vector element in the background intensity vector to obtain the target non-background data point.

[0063] In some embodiments, the initial non-background intensity value vector may be determined based on the intensity value of each initial non-background data point. Afterwards, according to the initial non-background intensity value vector and the background intensity vector Perform difference calculation to obtain the second background strength value vector of the target interval In addition, (see step 203), the intensity value of each initial background data point is updated with a second intensity value according to the preset standard intensity data to obtain the corresponding target background data point, which can be the initial background intensity value vector All elements of are replaced with standard intensity data to obtain the target interval-background intensity value vector Thus, we get two new data point sets: target background data point set and the target non-background data point set Then, (see step 204), data points are integrated according to the target non-background data points and the target background data points to obtain a photoelectron spectrum data point sequence, which can be obtained by splicing the target background data point set and the target non-background data point set into a photoelectron spectrum data point sequence containing n data pairs. .

[0064] See also Figure 7 In some embodiments, the target quantum effect constraint includes a peak pair constraint and a peak attribute ratio threshold. Step 105 may include but is not limited to steps 501 to 504: Step 501, performing photoelectron peak fitting on a photoelectron spectrum data point sequence using a first photoelectron spectrum fitting model to obtain at least two target photoelectron peaks; Step 502, performing a peak pairing test on any two target photoelectron peaks through a peak pairing constraint condition to obtain a first target photoelectron peak and a second target photoelectron peak; Step 503, determining a peak attribute value ratio according to the attribute value of the first target photoelectron peak and the attribute value of the second target photoelectron peak; Step 504 , when the peak attribute value ratio is not equal to the peak attribute ratio threshold, the model parameters of the first photoelectron energy spectrum fitting model are updated according to the centralized field approximate relationship to obtain a second photoelectron energy spectrum fitting model.

[0065] The advantage of this embodiment is that after obtaining at least two target photoelectron peaks, the first target photoelectron peak and the second target photoelectron peak are obtained through peak pairing constraints, thereby determining the peak attribute value ratio, and then when the peak attribute value ratio is not equal to the peak attribute ratio threshold, the model parameters of the first photoelectron energy spectrum fitting model are updated according to the centralized field approximation relationship to ensure that the target photoelectron energy spectrum fitted by the second photoelectron energy spectrum fitting model meets the target quantum effect constraint, thereby improving the reliability and authenticity of the photoelectron energy spectrum analysis method.

[0066] It should be noted that the peak pairing constraint is used to characterize the peak attribute ratio relationship between two photoelectron peaks, and the peak attribute ratio threshold is used to characterize the peak attribute ratio value that conforms to the theory of quantum mechanics.

[0067] In step 501 of some embodiments, the photoelectron energy spectrum fitting model (such as the initial photoelectron energy spectrum fitting model, the first photoelectron energy spectrum fitting model, and the second photoelectron energy spectrum fitting model) has a photoelectron peak fitting function and an energy spectrum fitting function. The photoelectron peak fitting function of the first photoelectron energy spectrum fitting model can be used to perform photoelectron peak fitting on the photoelectron energy spectrum data point sequence to obtain at least two target photoelectron peaks. Then, the energy spectrum fitting function can be used to perform energy spectrum fitting on the target photoelectron peak to obtain the corresponding photoelectron energy spectrum.

[0068] In some embodiments, the photoelectron peak fitting function is shown in formula (3), and the energy spectrum fitting function is shown in formula (4): , formula (3); , formula (4); in Indicates Photoelectron peaks; Representation function The independent variable x can be set to the energy value of any energy spectrum data point according to the requirements, such as the energy value of the initial background data point Or the energy value of the initial non-background data point ; Represents the photoelectron peak , that is, the model parameters of the photoelectron spectrum fitting model, where i represents the i-th photoelectron peak, ; Represents the total number of photoelectron peaks; corresponding to the i-th photoelectron peak, represents the first peak intensity parameter, represents the second peak intensity parameter, represents the peak position parameter, represents the first peak shape parameter, represents the second peak shape parameter; Represents the photoelectron spectrum output by the photoelectron spectrum fitting model (such as the initial photoelectron spectrum and the target photoelectron spectrum).

[0069] In some embodiments, performing the first model parameter update according to a preset expectation maximization algorithm refers to defining an iterative update strategy of the model parameters based on the expectation maximization algorithm, that is, given the first ( ) step model parameters are obtained by iterative method ( ) step model parameters. Specifically include: Starting from 0, when When , the model parameters are initial values , ,when When , the model parameters are updated according to formula (5) to formula (9).

[0070] , formula (5); , formula (6); , formula (7); , formula (8); , formula (9); in, , , The definition of is shown in formula (10) to formula (12): , formula (10); , formula (11); , formula (12); in, Represents the experimental data after removing the background signal, that is, the intensity value of the photoelectron spectrum data point sequence It should be noted that the parameters other than the model parameters in the above formulas (5) to (12) (such as , , etc.) are all intermediate parameters or preset parameters, which can be initialized and set according to the requirements, and the embodiments of the present application do not make specific limitations on this.

[0071] With the first ) step model parameters , we can use formula (5) to formula (9) to get the first ( +1) Step Model Parameters , and then into formula (3) to get the first ( +1) Step Substituting the peak function of the photoelectron into formula (4) yields +1) step theoretical photoelectron spectroscopy spectrum.

[0072] It should be noted that the splitting peak refers to a pair of photoelectron peaks caused by the spin-orbit coupling of electrons. The satellite peak refers to the photoelectron peak caused by multiple excited states due to the final state effect, which may include multiple splitting, electron shock and shock separation; among them, the final state effect refers to the energy change and influence caused by the photoelectron escaping from the nucleus and escaping from the surface during the photoemission process.

[0073] In step 502 of some embodiments, the peak pairing constraint condition includes at least one of a splitting peak constraint condition and a satellite companion peak constraint condition, and the peak attribute ratio threshold value includes at least one of a peak intensity ratio threshold value and a peak area ratio threshold value. In one embodiment, step 502 includes: performing a splitting peak pairing test on any two target photoelectron peaks through the splitting peak constraint condition to obtain a first target splitting peak and a second target splitting peak. Among them, the splitting peak constraint condition is used to characterize that the elements to which the two target photoelectron peaks belong are the same elements of the same valence state, and have the same principal quantum number and angular quantum number. In another embodiment, step 502 also includes: performing a satellite companion peak pairing test on any two target photoelectron peaks through the satellite companion peak constraint condition to obtain a first target satellite companion peak and a second target satellite companion peak. Among them, the satellite companion peak constraint condition is used to characterize that the elements to which the two target photoelectron peaks belong are the same elements of the same valence state, and have the same principal quantum number and total angular quantum number. It should be noted that the principal quantum number, angular quantum number and total angular quantum number of any target photoelectron peak can be obtained from a preset photoelectron peak database. The element to which any target photoelectron peak belongs and the initial value of its element valence state can be determined by table lookup method.

[0074] In step 503 of some embodiments, the attribute value includes peak intensity and peak area, and the peak attribute value ratio includes peak intensity ratio and peak area ratio. In one embodiment, after obtaining the first target splitting peak and the second target splitting peak, step 503 includes: determining the peak intensity ratio according to the peak intensity of the first target splitting peak and the peak intensity of the second target splitting peak. In another embodiment, after obtaining the first target satellite companion peak and the second target satellite companion peak, step 503 also includes: determining the peak area ratio according to the peak area of ​​the first target satellite companion peak and the peak area of ​​the second target satellite companion peak.

[0075] In step 504 of some embodiments, the centralized field approximation relationship includes at least one of a centralized field approximation splitting peak relationship and a centralized field approximation satellite companion peak relationship. In one embodiment, after determining the peak intensity ratio, step 504 includes: when the peak intensity ratio is not equal to the peak intensity ratio threshold, updating the model parameters of the first photoelectron energy spectrum fitting model according to the centralized field approximation splitting peak relationship to obtain the second photoelectron energy spectrum fitting model. In another embodiment, after determining the peak area ratio, step 504 also includes: when the peak area ratio is not equal to the peak area ratio threshold, updating the model parameters of the first photoelectron energy spectrum fitting model according to the centralized field approximation satellite companion peak relationship to obtain the second photoelectron energy spectrum fitting model. Alternatively, the model parameters of the second photoelectron energy spectrum fitting model may also be updated according to the centralized field approximation satellite companion peak relationship to obtain an updated second photoelectron energy spectrum fitting model.

[0076] See also Figure 8In some embodiments, the model parameters of the first photoelectron energy spectrum fitting model include an initial peak intensity parameter and an initial peak position parameter; the peak attribute value ratio includes a peak intensity ratio, the peak attribute ratio threshold includes a peak intensity ratio threshold, and the centralized field approximate relationship includes a centralized field approximate splitting peak relationship. Step 504 may include but is not limited to steps 601 to 606: Step 601, when the peak intensity ratio is not equal to the peak intensity ratio threshold, determine a first peak intensity constraint relational expression and a peak position constraint relational expression according to a centralized field approximate splitting peak relational expression; Step 602, determining a first peak intensity confinement factor according to a first peak intensity confinement relation, a total angular quantum number of a first target photoelectron peak, and a total angular quantum number of a second target photoelectron peak; Step 603, updating the initial peak intensity parameter according to the first peak intensity constraint factor to obtain a first target peak intensity parameter; Step 604, determining a peak position constraint factor according to the peak position constraint relationship, the principal quantum number, angular quantum number and total angular quantum number of the first target photoelectron peak, and the principal quantum number, angular quantum number and total angular quantum number of the second target photoelectron peak; Step 605, updating the initial peak position parameters according to the peak position constraint factor to obtain the target peak position parameters; Step 606: Determine a second photoelectron energy spectrum fitting model according to the first target peak intensity parameter and the target peak position parameter.

[0077] The advantage of this embodiment is that the first peak intensity constraint relationship and the peak position constraint relationship are determined by the centralized field approximation splitting peak relationship, and the initial peak intensity parameter is updated according to the first peak intensity constraint factor, the peak position constraint factor is determined according to the peak position constraint relationship, and then the initial peak intensity parameter is updated according to the first peak intensity constraint factor to obtain the first target peak intensity parameter, and the initial peak position parameter is updated according to the peak position constraint factor to obtain the target peak position parameter, thereby ensuring that the target photoelectron energy spectrum output by the second photoelectron energy spectrum fitting model meets the relevant constraints of the splitting peak, that is, the peak intensity ratio of any pair of splitting peaks in the target photoelectron energy spectrum is equal to the peak intensity ratio threshold, thereby improving the authenticity of the energy spectrum analysis results.

[0078] It should be noted that the initial peak intensity parameter refers to the first peak intensity parameter of formula (4): The initial peak position parameter refers to the peak position parameter of formula (3) .

[0079] In step 601 of some embodiments, the centralized field approximate splitting peak relationship includes a first peak intensity constraint relationship and a peak position constraint relationship.

[0080] In step 602 of some embodiments, the first peak intensity constraint factor is defined as shown in formula (13): , formula (13); in, represents the first peak strength constraint factor, represents the total angular quantum number of the first target photoelectron peak, represents the total angular quantum number of the second target photoelectron peak; formula (13) is also the strong confinement relation of the first peak.

[0081] See also Fig. 9 In some embodiments, the model parameters of the first photoelectron energy spectrum fitting model include initial peak intensity parameters; the peak attribute value ratio also includes peak area ratio, the peak pairing constraint condition also includes satellite companion peak constraint condition, the peak attribute ratio threshold also includes peak area ratio threshold, and the centralized field approximate relationship also includes centralized field approximate satellite companion peak relationship. Step 504 may also include but is not limited to steps 701 to 704: Step 701, when the peak area ratio is not equal to the peak area ratio threshold, determine a second peak intensity constraint relationship according to the central field approximate satellite companion peak relationship; Step 702, determining a second peak intensity constraint factor according to the second peak intensity constraint relationship, the peak area of ​​the first target photoelectron peak, and the peak area of ​​the second target photoelectron peak; Step 703, updating the initial peak intensity parameter according to the second peak intensity constraint factor to obtain a second target peak intensity parameter; Step 704: Determine a second photoelectron energy spectrum fitting model according to the second target peak intensity parameter.

[0082] The advantage of this embodiment is that the second peak intensity constraint factor is determined according to the second peak intensity constraint relationship, the peak area of ​​the first target photoelectron peak, and the peak area of ​​the second target photoelectron peak, and then the second target peak intensity parameter is determined according to the second peak intensity constraint factor, thereby ensuring that the target photoelectron energy spectrum output by the second photoelectron energy spectrum fitting model meets the relevant constraints of the satellite companion peaks, that is, ensuring that the peak area ratio of any pair of satellite companion peaks in the target photoelectron energy spectrum is equal to the peak area ratio threshold, thereby improving the authenticity of the energy spectrum analysis results.

[0083] In step 702 of some embodiments, the first target photoelectron peak includes a first target satellite companion peak and a second target satellite companion peak, which are a pair of satellite companion peaks. The second target photoelectron peak includes a third target satellite companion peak and a fourth target satellite companion peak, which are a pair of satellite companion peaks. The second peak intensity constraint factor can be determined based on the second peak intensity constraint relationship, the peak area of ​​the first target photoelectron peak, and the peak area of ​​the second target photoelectron peak. The definition of the second peak intensity constraint factor is shown in formula (14): , formula (14); in, represents the second peak strength constraint factor, represents the peak area of ​​the first target satellite companion peak, represents the peak area of ​​the second target satellite companion peak, represents the peak area of ​​the third target satellite companion peak, represents the peak area of ​​the fourth target satellite companion peak; formula (14) is also the second peak strength constraint relation.

[0084] See also Fig.10 The present application also provides a photoelectron spectrum analysis device, which can implement the above-mentioned photoelectron spectrum analysis method, and the device includes: The photoelectron spectrum acquisition module 801 is used to perform photoelectron spectrum detection on the target sample and obtain an initial photoelectron spectrum; A data point selection module 802 is used to select energy spectrum data points according to the initial photoelectron energy spectrum to obtain a photoelectron energy spectrum data point sequence; A first model parameter updating module 803 is used to update the first model parameters of the preset initial photoelectron energy spectrum fitting model according to a preset expectation maximization algorithm and a photoelectron energy spectrum data point sequence to obtain a first photoelectron energy spectrum fitting model; A quantum effect constraint acquisition module 804 is used to acquire a target quantum effect constraint of a target sample; A second model parameter updating module 805 is used to update the second model parameters of the first photoelectron energy spectrum fitting model according to a preset centralized field approximate relationship and a target quantum effect constraint to obtain a second photoelectron energy spectrum fitting model; The energy spectrum fitting module 806 is used to perform energy spectrum fitting on the photoelectron energy spectrum data point sequence according to the second photoelectron energy spectrum fitting model to obtain a target photoelectron energy spectrum.

[0085] The specific implementation of the photoelectron spectrum analysis device is basically the same as the specific embodiment of the above-mentioned photoelectron spectrum analysis method, and will not be repeated here.

[0086] The embodiment of the present application also provides an electronic device, the electronic device includes a memory and a processor, the memory stores a computer program, and the processor implements the above-mentioned photoelectron spectrum analysis method when executing the computer program. The electronic device may include any intelligent terminal such as a tablet computer and a car computer.

[0087] See also Fig.11 , Fig.11 The hardware structure of an electronic device of another embodiment is illustrated, and the electronic device includes: The processor 901 may be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of the present application; The memory 902 can be implemented in the form of a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 902 can store an operating system and other application programs. When the technical solution provided in the embodiment of this specification is implemented by software or firmware, the relevant program code is stored in the memory 902, and the processor 901 is used to call and execute the photoelectron spectrum analysis method of the embodiment of this application; Input / output interface 903, used to implement information input and output; Communication interface 904, used to realize communication interaction between the device and other devices, which can be realized through wired mode (such as USB, network cable, etc.) or wireless mode (such as mobile network, WIFI, Bluetooth, etc.); A bus 905 that transmits information between various components of the device (e.g., the processor 901, the memory 902, the input / output interface 903, and the communication interface 904); The processor 901 , the memory 902 , the input / output interface 903 and the communication interface 904 are connected to each other in communication within the device via a bus 905 .

[0088] An embodiment of the present application further provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the above-mentioned photoelectron energy spectrum analysis method is implemented.

[0089] The memory, as a non-transient computer-readable storage medium, can be used to store non-transient software programs and non-transient computer executable programs. In addition, the memory may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory may optionally include a memory remotely disposed relative to the processor, and these remote memories may be connected to the processor via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0090] The embodiments described in the embodiments of the present application are intended to more clearly illustrate the technical solutions of the embodiments of the present application and do not constitute a limitation on the technical solutions provided in the embodiments of the present application. Those skilled in the art will appreciate that with the evolution of technology and the emergence of new application scenarios, the technical solutions provided in the embodiments of the present application are also applicable to similar technical problems.

[0091] Those skilled in the art will appreciate that the technical solutions shown in the figures do not constitute a limitation on the embodiments of the present application, and may include more or fewer steps than shown in the figures, or a combination of certain steps, or different steps.

[0092] The device embodiments described above are merely illustrative, and the units described as separate components may or may not be physically separated, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0093] Those skilled in the art will appreciate that all or some of the steps in the methods disclosed above, and the functional modules / units in the systems and devices may be implemented as software, firmware, hardware, or a suitable combination thereof.

[0094] The terms "first", "second", "third", "fourth", etc. (if any) in the specification of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0095] It should be understood that in the present application, "at least one (item)" means one or more, and "plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that three relationships may exist. For example, "A and / or B" can mean: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally indicates that the objects associated before and after are in an "or" relationship. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple.

[0096] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the above units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. The mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0097] The units described above as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0098] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0099] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including multiple instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk and other media that can store programs.

[0100] The preferred embodiments of the present invention are described above with reference to the accompanying drawings, but the scope of the rights of the present invention is not limited thereto. Any modification, equivalent substitution and improvement made by a person skilled in the art without departing from the scope and essence of the present invention should be within the scope of the rights of the present invention.

Claims

1. A photoelectron spectroscopy analysis method, characterized in that: The method comprises: Performing photoelectron spectrum detection on the target sample to obtain an initial photoelectron spectrum; Selecting energy spectrum data points according to the initial photoelectron energy spectrum to obtain a photoelectron energy spectrum data point sequence; Performing a first model parameter update on a preset initial photoelectron energy spectrum fitting model according to a preset expectation maximization algorithm and the photoelectron energy spectrum data point sequence to obtain a first photoelectron energy spectrum fitting model; Acquiring target quantum effect constraints of the target sample; According to a preset centralized field approximate relationship and the target quantum effect constraint, updating the second model parameters of the first photoelectron energy spectrum fitting model to obtain a second photoelectron energy spectrum fitting model; The photoelectron energy spectrum data point sequence is subjected to energy spectrum fitting according to the second photoelectron energy spectrum fitting model to obtain a target photoelectron energy spectrum.

2. The photoelectron spectroscopy analysis method according to claim 1, characterized in that: The target quantum effect constraints include peak pairing constraints and peak attribute ratio thresholds; The method of updating the first photoelectron energy spectrum fitting model with a second model parameter according to the preset centralization field approximate relationship and the target quantum effect constraint to obtain a second photoelectron energy spectrum fitting model includes: Performing photoelectron peak fitting on the photoelectron spectrum data point sequence using the first photoelectron spectrum fitting model to obtain at least two target photoelectron peaks; Through the peak pairing constraint condition, a peak pairing test is performed on any two of the target photoelectron peaks to obtain a first target photoelectron peak and a second target photoelectron peak; Determining a peak attribute value ratio according to the attribute value of the first target photoelectron peak and the attribute value of the second target photoelectron peak; When the peak attribute value ratio is not equal to the peak attribute ratio threshold, model parameters of the first photoelectron energy spectrum fitting model are updated according to the centralized field approximate relationship to obtain the second photoelectron energy spectrum fitting model.

3. The photoelectron spectroscopy analysis method according to claim 2, characterized in that: The model parameters of the first photoelectron energy spectrum fitting model include an initial peak intensity parameter and an initial peak position parameter; the peak attribute value ratio includes a peak intensity ratio, the peak attribute ratio threshold includes a peak intensity ratio threshold, and the centralized field approximate relation includes a centralized field approximate splitting peak relation; When the peak attribute value ratio is not equal to the peak attribute ratio threshold, updating the model parameters of the first photoelectron energy spectrum fitting model according to the centralized field approximate relationship to obtain the second photoelectron energy spectrum fitting model includes: When the peak intensity ratio is not equal to the peak intensity ratio threshold, determining a first peak intensity constraint relational expression and a peak position constraint relational expression according to the centralized field approximate splitting peak relational expression; Determining a first peak intensity confinement factor according to the first peak intensity confinement relation, the total angular quantum number of the first target photoelectron peak, and the total angular quantum number of the second target photoelectron peak; Update the initial peak intensity parameter according to the first peak intensity constraint factor to obtain a first target peak intensity parameter; Determine a peak position constraint factor according to the peak position constraint relationship, the principal quantum number, angular quantum number and total angular quantum number of the first target photoelectron peak, and the principal quantum number, angular quantum number and total angular quantum number of the second target photoelectron peak; Update the initial peak position parameter according to the peak position constraint factor to obtain a target peak position parameter; The second photoelectron energy spectrum fitting model is determined according to the first target peak intensity parameter and the target peak position parameter.

4. The photoelectron spectroscopy analysis method according to claim 2, characterized in that: The model parameters of the first photoelectron energy spectrum fitting model include initial peak intensity parameters; the peak attribute value ratio also includes peak area ratio, the peak pairing constraint condition also includes satellite companion peak constraint condition, the peak attribute ratio threshold also includes peak area ratio threshold, and the centralized field approximate relational expression also includes centralized field approximate satellite companion peak relational expression; When the peak attribute value ratio is not equal to the peak attribute ratio threshold, updating the model parameters of the first photoelectron energy spectrum fitting model according to the centralized field approximate relationship to obtain the second photoelectron energy spectrum fitting model further includes: When the peak area ratio is not equal to the peak area ratio threshold, determining a second peak intensity constraint relational expression according to the central field approximate satellite companion peak relational expression; Determining a second peak intensity constraint factor according to the second peak intensity constraint relationship, the peak area of ​​the first target photoelectron peak, and the peak area of ​​the second target photoelectron peak; Update the initial peak intensity parameter according to the second peak intensity constraint factor to obtain a second target peak intensity parameter; The second photoelectron energy spectrum fitting model is determined according to the second target peak intensity parameter.

5. The photoelectron spectroscopy analysis method according to any one of claims 1 to 4, characterized in that: The initial photoelectron energy spectrum has an initial photoelectron peak; the selecting of energy spectrum data points according to the initial photoelectron energy spectrum to obtain a photoelectron energy spectrum data point sequence includes: Dividing the energy spectrum data points according to the spectrum lines of the initial photoelectron energy spectrum to obtain at least two initial background data points and at least two initial non-background data points; wherein each of the initial background data points and each of the initial non-background data points has an energy value and an intensity value; Performing background energy spectrum curve fitting on at least two of the initial background data points according to a preset Gaussian random process function to obtain a background energy spectrum curve; According to the energy value and the intensity value of each of the initial background data points and the energy value of each of the initial non-background data points, performing a first intensity value update on the intensity value of each of the initial non-background data points to obtain a corresponding target non-background data point; According to the background energy spectrum curve, the intensity value of each of the initial background data points is updated with a second intensity value to obtain a corresponding target background data point; wherein the intensity value of the target background data point is less than the intensity value of the initial background data point; Data point integration is performed according to the target non-background data points and the target background data points to obtain the photoelectron energy spectrum data point sequence.

6. The photoelectron spectroscopy analysis method according to claim 5, characterized in that: The step of updating the intensity value of each of the initial non-background data points by a first intensity value according to the energy value and intensity value of each of the initial background data points and the energy value of each of the initial non-background data points to obtain a corresponding target non-background data point comprises: Calculate the background intensity according to the energy value and intensity value of each of the initial background data points and the energy value of each of the initial non-background data points to obtain a background intensity vector; The intensity value of each of the initial non-background data points is updated with a first intensity value according to the background intensity vector to obtain a target non-background data point.

7. The photoelectron spectroscopy analysis method according to claim 5, characterized in that: The dividing of the energy spectrum data points according to the spectrum lines of the initial photoelectron energy spectrum to obtain at least two initial background data points and at least two initial non-background data points includes: Selecting energy spectrum data points from the initial photoelectron energy spectrum to obtain a plurality of initial energy spectrum data points; Each of the initial energy spectrum data points is divided according to the trough of the spectrum line of the initial photoelectron energy spectrum to obtain at least two initial background data points and at least two initial non-background data points; wherein the initial background data point is located at the trough of the spectrum line.

8. A photoelectron spectrum analysis device, characterized in that: The device comprises: A photoelectron spectrum acquisition module is used to perform photoelectron spectrum detection on the target sample and obtain an initial photoelectron spectrum; A data point selection module, used for selecting energy spectrum data points according to the initial photoelectron energy spectrum to obtain a photoelectron energy spectrum data point sequence; A first model parameter updating module, used for updating a first model parameter of a preset initial photoelectron energy spectrum fitting model according to a preset expectation maximization algorithm and the photoelectron energy spectrum data point sequence to obtain a first photoelectron energy spectrum fitting model; A quantum effect constraint acquisition module, used to acquire a target quantum effect constraint of the target sample; A second model parameter updating module is used to update the second model parameters of the first photoelectron energy spectrum fitting model according to a preset centralized field approximate relationship and the target quantum effect constraint to obtain a second photoelectron energy spectrum fitting model; The energy spectrum fitting module is used to perform energy spectrum fitting on the photoelectron energy spectrum data point sequence according to the second photoelectron energy spectrum fitting model to obtain a target photoelectron energy spectrum.

9. An electronic device, characterized in that: The electronic device comprises a memory and a processor, the memory stores a computer program, and the processor implements the photoelectron energy spectrum analysis method according to any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the photoelectron spectroscopy analysis method according to any one of claims 1 to 7 is implemented.

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