Photoelectron spectroscopy data analysis method and system, electronic equipment and storage medium

Abstract

The embodiment of the invention discloses a photoelectron spectroscopy data analysis method and system, electronic equipment and a storage medium, and relates to the technical field of material analysis. The method comprises the following steps: acquiring target photoelectron spectroscopy data of a target material, and generating first atlas data based on the target photoelectron spectroscopy data; performing charge correction on the first atlas data to obtain second atlas data, and determining a target peak based on a pre-established target database; fitting the second atlas data based on the attribute information of each target peak to obtain target atlas data matched with the target photoelectron spectroscopy data; and in response to an export instruction of the target map data, exporting the target map data to a target file. According to the scheme provided by the embodiment of the invention, the photoelectron spectroscopy data can be quickly and accurately analyzed.

Description

Technical Field

[0001] The present invention relates to the technical field of material analysis, and in particular to an analysis method, system, electronic equipment and storage medium for photoelectron energy spectrum data. Background Art

[0002] Photoelectron spectroscopy is a technology that uses the principle of the photoelectric effect to measure the kinetic energy, intensity and angular distribution of photoelectrons, and then studies the electronic structure of atoms, molecules, condensed phases, and especially solid surfaces. Typical photoelectron spectroscopy is X-ray photoelectron spectroscopy (XPS). X-ray photoelectron spectroscopy is an important means to characterize the surface composition and chemical state of materials. By measuring the binding energy of photoelectrons, the types of atoms on the surface of materials and their chemical bond states can be inferred. It has a wide range of applications in catalysts, semiconductors, new energy materials and other fields.

[0003] How to quickly and accurately analyze photoelectron energy spectrum data is a key research issue in the industry. Summary of the invention

[0004] The present invention provides a method, system, electronic equipment and storage medium for analyzing photoelectron energy spectrum data, so as to analyze the photoelectron energy spectrum data quickly and accurately.

[0005] According to one aspect of the present invention, a method for analyzing photoelectron spectrum data is provided, the method comprising:

[0006] Acquire target photoelectron spectrum data of a target material, and generate first spectrum data based on the target photoelectron spectrum data;

[0007] Performing charge correction on the first spectrum data to obtain second spectrum data, and determining a target peak based on a pre-established target database;

[0008] Fitting the second spectrum data based on the attribute information of each target peak to obtain target spectrum data matching the target photoelectron spectrum data;

[0009] In response to the export instruction of the target atlas data, the target atlas data is exported to a target file.

[0010] According to another aspect of the present invention, a system for analyzing photoelectron spectrum data is provided, the system comprising:

[0011] A photoelectron spectrum data acquisition module, used to acquire target photoelectron spectrum data of a target material, and generate first spectrum data based on the target photoelectron spectrum data;

[0012] A target peak determination module, used for performing charge correction on the first spectrum data to obtain second spectrum data, and determining the target peak based on a pre-established target database;

[0013] A target spectrum data determination module, used for fitting the second spectrum data based on the attribute information of each target peak to obtain target spectrum data matching the target photoelectron spectrum data;

[0014] An export module is used to export the target atlas data to a target file in response to an export instruction of the target atlas data.

[0015] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0016] at least one processor; and

[0017] a memory communicatively connected to the at least one processor; wherein,

[0018] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the method for analyzing photoelectron energy spectrum data described in any embodiment of the present invention.

[0019] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the method for analyzing photoelectron energy spectrum data described in any embodiment of the present invention when executed.

[0020] According to another aspect of the present invention, a computer program product is provided, comprising a computer program, wherein when the computer program is executed by a processor, the method for analyzing photoelectron energy spectrum data according to any embodiment of the present invention is implemented.

[0021] The technical solution of an embodiment of the present invention is to obtain target photoelectron spectrum data of a target material and generate first spectrum data based on the target photoelectron spectrum data; perform charge correction on the first spectrum data to obtain second spectrum data, and determine target peaks based on a pre-established target database; fit the second spectrum data based on the attribute information of each target peak to obtain target spectrum data that matches the target photoelectron spectrum data; and export the target spectrum data to a target file in response to an export instruction of the target spectrum data, so that the photoelectron spectrum data can be analyzed quickly and accurately.

[0022] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0024] Figure 1 is a flow chart of a method for analyzing photoelectron spectrum data provided according to Embodiment 1 of the present invention;

[0025] Figure 2 is a flow chart of a method for analyzing photoelectron spectrum data provided in accordance with the second embodiment of the present invention;

[0026] Figure 3 is a schematic diagram of the structure of a photoelectron spectrum data analysis system provided according to Embodiment 3 of the present invention;

[0027] Figure 4 It is a schematic diagram of the structure of an electronic device for implementing the method for analyzing photoelectron energy spectrum data according to an embodiment of the present invention. DETAILED DESCRIPTION

[0028] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0029] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention 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 interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order 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, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0030] Embodiment 1

[0031] Figure 1 This is a flow chart of a method for analyzing photoelectron spectrum data according to the first embodiment of the present invention. This embodiment is applicable to the case of analyzing photoelectron spectrum data. The method can be executed by a photoelectron spectrum data analysis system. The photoelectron spectrum data analysis system can be implemented in the form of hardware and / or software. The photoelectron spectrum data analysis system can be configured in electronic devices such as computers, servers or tablet computers. Figure 1 As shown, the method includes:

[0032] Step 110: Acquire target photoelectron spectrum data of a target material, and generate first spectrum data based on the target photoelectron spectrum data.

[0033] The target material may be any known polymer material, such as plastic, fiber or composite material, etc., which is not limited in this embodiment. In this embodiment, the photoelectron spectrum data of the target material may be the XPS data of the target material; illustratively, the XPS data of the target material may include binding energy, photoelectron peak, peak intensity, chemical shift, background signal and Auger electron peak, etc., which are not limited in this embodiment. .

[0034] Optionally, in this embodiment, the photoelectron spectrum data of the target material may be imported through a local file, or the photoelectron spectrum data of the target material generated by the test module may be directly acquired, which is not limited in this embodiment.

[0035] In an optional implementation of this embodiment, after obtaining the photoelectron spectrum data of the target material, first spectrum data can be further generated based on the obtained target photoelectron spectrum data. For example, the first spectrum data can be directly generated according to each binding energy, peak intensity or counting rate.

[0036] Optionally, in an optional implementation of the present embodiment, after acquiring the target photoelectron energy spectrum data of the target material, it may also include: detecting whether there are missing values ​​and / or outliers in the target photoelectron energy spectrum data; when it is determined that there are missing values ​​in the target photoelectron energy spectrum data, filling the missing values ​​based on an interpolation method; when it is determined that there are outliers in the target photoelectron energy spectrum data, deleting the outliers.

[0037] In an optional implementation of the present embodiment, after acquiring the target photoelectron energy spectrum data of the target material, it is possible to further detect whether there are missing values ​​or abnormal values ​​in the target photoelectron energy spectrum data; when it is determined that there are missing values ​​in the target photoelectron energy spectrum data, the missing values ​​can be supplemented based on an interpolation method; exemplarily, the missing values ​​can be supplemented based on linear interpolation, polynomial interpolation, spline interpolation, or nearest neighbor interpolation.

[0038] In another optional implementation of this embodiment, if it fails to find an outlier in the target photoelectron energy spectrum data, the outlier can be deleted, replaced or corrected to eliminate the impact of the outlier on subsequent photoelectron energy spectrum data analysis.

[0039] In another optional implementation of the present embodiment, after detecting the presence of missing values ​​or abnormal values ​​in the target photoelectron energy spectrum data, a prompt message may be generated. Exemplarily, the prompt message may be that there are abnormal values ​​in the target photoelectron energy spectrum data, or there are several abnormal values ​​in the target photoelectron energy spectrum data; it may also be that there are missing values ​​in the target photoelectron energy spectrum data, etc., which is not limited in the present embodiment; further, the user may process the abnormal values ​​or missing values ​​according to the prompt message, or ignore them and directly proceed to the next step of operation, which is not limited in the present embodiment.

[0040] Step 120: Perform charge correction on the first spectrum data to obtain second spectrum data, and determine the target peak based on a pre-established target database.

[0041] Optionally, in an optional implementation of the present embodiment, after obtaining first spectrum data corresponding to the target photoelectron energy spectrum data, the first spectrum data can be further subjected to nuclear power correction to obtain second spectrum data; further, the target peak can be determined based on a pre-established target database, wherein the number of target peaks can be one or more, and the specific number of target peaks is not limited in the present embodiment.

[0042] Optionally, in this embodiment, the first spectrum data is subjected to charge correction to obtain the second spectrum data, which may include: determining the carbon content of the target material, and determining the exogenous carbon peak based on the carbon content; comparing the binding energy of the exogenous carbon peak with the binding energy of the standard contamination carbon peak, and shifting the first spectrum data according to the comparison result to obtain the second spectrum data.

[0043] In an optional implementation of the present embodiment, when it is determined that the target material contains carbon elements, the carbon element with known binding energy can be used as a reference peak. In the present embodiment, it is called the standard contamination carbon peak, and its binding energy is usually set to 284.8 eV; further, the carbon peak can be compared with the standard carbon peak to obtain the offset between the carbon peak and the standard carbon peak; further, the first spectrum data can be offset corrected according to the offset to obtain second spectrum data.

[0044] Furthermore, the target peak can be determined based on a pre-established target database; in the present embodiment, each peak in the second spectrum data can be identified by automatic recognition, and further, each identified peak can be compared with the standard value in the pre-established target database, and by comparison, it can be determined which peak corresponds to a specific element.

[0045] Step 130: Fit the second spectrum data based on the attribute information of each target peak to obtain target spectrum data matching the target photoelectron energy spectrum data.

[0046] Optionally, in this embodiment, after each target peak is determined, the second spectrum data may be further fitted based on the property information of each target peak, so as to obtain target spectrum data matching the target electronic energy spectrum data.

[0047] The attribute information of the target peak may include: binding energy, full width at half maximum, and multi-peak area ratio, etc., which are not limited in this embodiment.

[0048] Optionally, in this embodiment, fitting the second spectrum data based on the attribute information of each target peak to obtain target spectrum data matching the target photoelectron energy spectrum data may include: performing background subtraction on the second spectrum data based on a background subtraction function to obtain first target spectrum data after background subtraction; inputting the first target spectrum data, binding energy, half-peak full width and multi-peak area ratio into the target fitting function to obtain target spectrum data matching the target photoelectron energy spectrum data.

[0049] The background subtraction function may be Shirley.

[0050] In this embodiment, after obtaining the second atlas data, the number of data points in the second atlas data can be determined, and the background array and the array after background subtraction can be initialized; wherein, the initial data of the initialized background array and the array after background subtraction are all 0; further, the background can be initially estimated, and the background value can be calculated through Shirley iteration, and the calculated background value can be returned to the background array; further, the array after background subtraction can be determined based on the second atlas data and the background array, that is, the first target atlas data in this embodiment is obtained.

[0051] Furthermore, the first target spectrum data obtained after background subtraction, the binding energy, half-maximum full width and multi-peak area ratio of each target peak determined in the above steps can be input into the target fitting function to obtain target spectrum data matching the target photoelectron energy spectrum data.

[0052] The target fitting function may be a Lorentzian Gaussian mixed function or other fitting functions, which are not limited in this embodiment.

[0053] In an optional implementation of the present embodiment, after obtaining the first target spectrum data after background subtraction, the first target spectrum data can be further input into the target fitting function, and the initial parameter guess and parameter range (peak center value, half-peak full width, area ratio, etc.) can be set: according to the data characteristics and the parameter limitations set in the system, set a reasonable initial parameter guess value and parameter value range; further, the curve_fit function can be called for fitting, and at the same time, the optimization algorithm can be used to start fitting the data; during the fitting process, it can be determined whether the stop condition is met. If the stop condition is met, proceed to the next step; otherwise, update the parameters and continue fitting; finally, return the optimal parameter value and the fitted data.

[0054] The advantage of this setting is that by setting the upper limit of the number of iterations of the background subtraction function, combined with factors such as data characteristics and noise level, the iteration strategy can be adaptively adjusted. At the same time, multiple iterations are performed based on the restored chi-square value after iterative fitting to continuously optimize the fitting parameters; the fitting strategy can be automatically adjusted according to the unique characteristics of the data, thereby significantly improving the accuracy and reliability of the fitting, successfully avoiding common problems such as overfitting or underfitting; the fitting results can be highly close to the actual data distribution, providing a strong guarantee for accurate data analysis.

[0055] Step 140: In response to the export instruction of the target atlas data, export the target atlas data to a target file.

[0056] In an optional implementation of the present embodiment, after obtaining the target atlas data, if an export instruction for the target atlas data is received, the target file (for example, the type of the target file) and the export path of the target atlas data can be set, and the target file can be exported according to the export path so that the target atlas data can be subsequently viewed or applied.

[0057] The technical solution of this embodiment is to obtain target photoelectron spectrum data of the target material and generate first spectrum data based on the target photoelectron spectrum data; perform charge correction on the first spectrum data to obtain second spectrum data, and determine the target peak based on a pre-established target database; fit the second spectrum data based on the attribute information of each target peak to obtain target spectrum data matching the target photoelectron spectrum data; and export the target spectrum data to a target file in response to an export instruction of the target spectrum data, so as to quickly and accurately analyze the photoelectron spectrum data.

[0058] Embodiment 2

[0059] Figure 2 1 is a flow chart of a method for analyzing photoelectron spectrum data according to Embodiment 2 of the present invention. This embodiment is a further refinement of the above technical solution. The technical solution in this embodiment can be combined with each optional solution in one or more of the above embodiments. Figure 2 As shown, the method includes:

[0060] Step 210: Obtain target photoelectron spectrum data of the target material.

[0061] Step 220, detecting whether the target photoelectron energy spectrum data contains missing values ​​and / or abnormal values; when it is determined that the target photoelectron energy spectrum data contains missing values, filling the missing values ​​based on an interpolation method; when it is determined that the target photoelectron energy spectrum data contains abnormal values, deleting the abnormal values.

[0062] Step 230: Generate first spectrum data based on the target photoelectron spectrum data.

[0063] Step 240: Perform charge correction on the first spectrum data to obtain second spectrum data, and determine the target peak based on a pre-established target database.

[0064] Optionally, in this embodiment, the target database can be established through the following steps: obtaining a historical photoelectron energy spectrum data analysis order set; the historical photoelectron energy spectrum data analysis order set includes: each photoelectron energy spectrum data, intermediate data obtained by analyzing each of the photoelectron energy spectra, and analysis result data of each of the photoelectron energy spectrum data; cleaning each data in the historical photoelectron energy spectrum data analysis order set, and decomposing the target photoelectron energy spectrum data into multiple target elements; generating a hash value matching each of the target elements, storing each of the hash values, and obtaining the target database.

[0065] In an optional implementation of the present embodiment, in the process of establishing a target database, relevant data can be obtained by summarizing and mining through in-depth analysis of historical analysis orders. For example, each photoelectron energy spectrum data, intermediate data obtained by analyzing each of the photoelectron energy spectra, and analysis result data of each of the photoelectron energy spectrum data can be obtained; further, the obtained chemical formula data can be cleaned and the chemical formula can be decomposed into various elements; further, each element, orbital, chemical formula decomposition result and binding energy can be used to generate a unique hash value for each element; further, the generated unique hash value and the cleaned data can be stored in the database for subsequent data analysis and use.

[0066] It should be noted that the overall architecture of the target database involved in this embodiment consists of three subsystems: search, calculation and recommendation. In the target database, the search system accurately selects the binding energy data suitable for the current analysis from the pre-established target database based on the search conditions during the fitting analysis and the element information contained in the spectrum file. This screening process optimizes the data query algorithm to ensure that the most matching binding energy data set is quickly found in massive data, laying the foundation for subsequent calculations and recommendations.

[0067] In this embodiment, for the selected binding energy data, a multi-dimensional analysis is performed on the fitting analysis conditions and the elements contained in the atlas file to generate a variety of fields for sorting to ensure the accuracy of the binding energy recommendation. Exemplarily, the calculation logic of each field is as follows:

[0068] (1) Absolute value of binding energy difference: The difference between the fitted analysis binding energy and the standard binding energy is calculated to reflect the degree of deviation between the analysis sample and the database data.

[0069] (2) Natural sorting of chemical states: Based on the Unicode encoding of chemical states, a natural sorting method is provided to facilitate subsequent priority sorting.

[0070] (3) Element symbol correlation: The correlation of element characteristics is measured by calculating the similarity between the chemical state elements in the analysis sample and the database.

[0071] (4) Element number correlation: Based on the ratio of element numbers, the matching degree between the sample and the chemical state elements in the database is compared and analyzed.

[0072] (5) Fitting peak correlation binding energy: By calculating the matching degree with the added fitting peak, the matching accuracy with the target binding energy is improved.

[0073] (6) Graying out: Determine whether the analysis elements and binding energy ranges match the data in the database. Unmatched items will be grayed out and excluded from the recommendation list.

[0074] In this embodiment, the target database sorts the data according to the multi-dimensional correlation of binding energy and chemical state, and the priority from high to low is: graying out, fitting peak correlation binding energy, binding energy, element symbol correlation, element number correlation and chemical state natural sorting; at the same time, emphasis is placed on the binding energy matching degree, and the priority order is graying out, fitting peak correlation binding energy, binding energy, element symbol correlation, absolute value of binding energy difference, and chemical state natural sorting; in another optional implementation method of this embodiment, more emphasis is placed on chemical state information matching, and the priority order is graying out, fitting peak correlation binding energy, binding energy, element number correlation, element symbol correlation and chemical state natural sorting.

[0075] Optionally, in this embodiment, determining the target peak based on a pre-established target database may include: determining a target hash value for each element in the second atlas data, matching the target hash value with each hash value stored in the target database to obtain a reference hash value that matches the target hash value; determining a target binding energy corresponding to the reference hash value, and determining the target peak based on the target binding energy.

[0076] In an optional implementation of this embodiment, after obtaining the second atlas data, the target hash value of each element in the second atlas data can be further determined, and the target hash value can be matched with each hash value stored in the target database to obtain a reference hash value that matches the target hash value; further, the binding energy corresponding to the reference hash value can be determined, and the target binding energy can be determined as the binding energy of the target peak.

[0077] Step 250: Fit the second spectrum data based on the attribute information of each target peak to obtain target spectrum data matching the target photoelectron energy spectrum data.

[0078] Step 260: In response to the export instruction of the target atlas data, export the target atlas data to a target file.

[0079] Optionally, in this embodiment, in response to an export instruction of the target map data, exporting the target map data to a target file may include: determining target data related to the target map data; storing each target data in the target file, generating link data matching the target file; and displaying the target file in response to a click instruction of the link data.

[0080] The target data may include each spectrum of the target spectrum data, coordinate data corresponding to each spectrum, peak name, binding energy, half-peak full width and proportion, etc., which are not limited in this embodiment. The link data matching the target file may be a download link or a display interface link of the target file, etc., which are not limited in this embodiment.

[0081] In an optional implementation of the present embodiment, after obtaining the target map data, if an export instruction for the target map data is received, target data related to the target map data can be further determined; further, each target map data can be stored in a target file, and link data matching the target file can be generated; further, if a click instruction for the link data is received, the target file can be displayed or downloaded for local viewing.

[0082] The counting scheme of this embodiment obtains a historical photoelectron energy spectrum data analysis order set; the historical photoelectron energy spectrum data analysis order set includes: each photoelectron energy spectrum data, intermediate data obtained by analyzing each of the photoelectron energy spectra, and analysis result data of each of the photoelectron energy spectrum data; each data in the historical photoelectron energy spectrum data analysis order set is cleaned, and the target photoelectron energy spectrum data is decomposed into multiple target elements; a hash value matching each of the target elements is generated, and each of the hash values ​​is stored to obtain the target database, thereby providing a basis for fast and accurate analysis of the photoelectron energy spectrum data.

[0083] Embodiment 3

[0084] Figure 3 FIG. 1 is a schematic diagram of a photoelectron spectrum data analysis system according to Embodiment 3 of the present invention. Figure 3 As shown, the system includes: a photoelectron energy spectrum data acquisition module 310 , a target peak determination module 320 , a target spectrum data determination module 330 and an export module 340 .

[0085] The photoelectron spectrum data acquisition module 310 is used to acquire target photoelectron spectrum data of a target material and generate first spectrum data based on the target photoelectron spectrum data;

[0086] A target peak determination module 320, configured to perform charge correction on the first spectrum data to obtain second spectrum data, and determine a target peak based on a pre-established target database;

[0087] A target spectrum data determination module 330 is used to fit the second spectrum data based on the attribute information of each target peak to obtain target spectrum data matching the target photoelectron spectrum data;

[0088] The export module 340 is used to export the target atlas data to a target file in response to an export instruction of the target atlas data.

[0089] The scheme of this embodiment is to acquire the target photoelectron spectrum data of the target material through the photoelectron spectrum data acquisition module, and generate the first spectrum data based on the target photoelectron spectrum data; to perform charge correction on the first spectrum data through the target peak determination module 320 to obtain the second spectrum data, and determine the target peak based on the pre-established target database; to fit the second spectrum data based on the attribute information of each target peak through the target spectrum data determination module to obtain the target spectrum data matching the target photoelectron spectrum data; to export the target spectrum data to the target file through the export module in response to the export instruction of the target spectrum data, so as to quickly and accurately analyze the photoelectron spectrum data.

[0090] In an optional implementation of this embodiment, the photoelectron spectrum data analysis system further includes: a data verification module, used to detect whether there are missing values ​​and / or abnormal values ​​in the target photoelectron spectrum data;

[0091] When it is determined that there are missing values ​​in the target photoelectron energy spectrum data, filling the missing values ​​based on an interpolation method;

[0092] When it is determined that an abnormal value exists in the target photoelectron energy spectrum data, the abnormal value is deleted.

[0093] In an optional implementation of this embodiment, the target peak determination module 320 is specifically used to determine the carbon content of the target material, and determine the exogenous carbon peak based on the carbon content;

[0094] The binding energy of the exogenous carbon peak is compared with the binding energy of the standard contamination carbon peak, and the first spectrum data is shifted according to the comparison result to obtain the second spectrum data.

[0095] In an optional implementation of this embodiment, the target database is established through the following steps:

[0096] Acquire a historical photoelectron energy spectrum data analysis order set; the historical photoelectron energy spectrum data analysis order set includes: each photoelectron energy spectrum data, intermediate data obtained by analyzing each photoelectron energy spectrum, and analysis result data of each photoelectron energy spectrum data;

[0097] Cleaning each data in the historical photoelectron energy spectrum data analysis order set, and decomposing the target photoelectron energy spectrum data into multiple target elements;

[0098] Generate a hash value matching each of the target elements, store each of the hash values, and obtain the target database.

[0099] In an optional implementation of this embodiment, the target peak determination module 320 is further specifically used to determine a target hash value for each element in the second atlas data, and match the target hash value with each hash value stored in the target database to obtain a reference hash value matching the target hash value;

[0100] A target binding energy corresponding to the reference hash value is determined, and the target peak is determined according to the target binding energy.

[0101] In an optional implementation of this embodiment, the attribute information includes: binding energy, full width at half maximum, and multi-peak area ratio;

[0102] Correspondingly, the target atlas data determination module 330 is specifically configured to perform background subtraction on the second atlas data based on the background subtraction function to obtain first target atlas data after background subtraction;

[0103] The first target spectrum data, binding energy, half-maximum full width and multi-peak area ratio are input into a target fitting function to obtain target spectrum data matching the target photoelectron energy spectrum data.

[0104] In an optional implementation of this embodiment, the export module 340 is specifically used to determine target data related to the target atlas data;

[0105] Storing each of the target data in a target file, and generating link data matching the target file;

[0106] In response to a click instruction of the link data, the target file is displayed.

[0107] The photoelectron energy spectrum data analysis system provided in the embodiment of the present invention can execute the photoelectron energy spectrum data analysis method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0108] Embodiment 4

[0109] Figure 4 A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0110] like Figure 4 As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0111] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0112] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The processor 11 executes the various methods and processes described above, such as a method for analyzing photoelectron spectrum data, the method comprising: obtaining target photoelectron spectrum data of a target material, and generating first spectrum data based on the target photoelectron spectrum data; performing charge correction on the first spectrum data to obtain second spectrum data, and determining a target peak based on a pre-established target database; fitting the second spectrum data based on the attribute information of each target peak to obtain target spectrum data matching the target photoelectron spectrum data; and exporting the target spectrum data to a target file in response to an export instruction for the target spectrum data.

[0113] In some embodiments, the method for analyzing photoelectron spectral data may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the method for analyzing photoelectron spectral data described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform the method for analyzing photoelectron spectral data in any other appropriate manner (e.g., by means of firmware).

[0114] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0115] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0116] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0117] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0118] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0119] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0120] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0121] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for analyzing photoelectron spectrum data, characterized in that: include: Acquire target photoelectron spectrum data of a target material, and generate first spectrum data based on the target photoelectron spectrum data; Performing charge correction on the first spectrum data to obtain second spectrum data, and determining a target peak based on a pre-established target database; Fitting the second spectrum data based on the attribute information of each target peak to obtain target spectrum data matching the target photoelectron spectrum data; In response to the export instruction of the target atlas data, the target atlas data is exported to a target file.

2. The method for analyzing photoelectron spectrum data according to claim 1, characterized in that: After obtaining the target photoelectron spectrum data of the target material, it also includes: Detecting whether there are missing values ​​and / or abnormal values ​​in the target photoelectron energy spectrum data; When it is determined that there are missing values ​​in the target photoelectron energy spectrum data, filling the missing values ​​based on an interpolation method; When it is determined that an abnormal value exists in the target photoelectron energy spectrum data, the abnormal value is deleted.

3. The method for analyzing photoelectron spectrum data according to claim 1, characterized in that: The step of performing charge correction on the first spectrum data to obtain second spectrum data includes: Determining the carbon content of the target material, and determining an exogenous carbon peak based on the carbon content; The binding energy of the exogenous carbon peak is compared with the binding energy of the standard contamination carbon peak, and the first spectrum data is shifted according to the comparison result to obtain the second spectrum data.

4. The method for analyzing photoelectron spectrum data according to claim 1, characterized in that: The target database is established by the following steps: Acquire a historical photoelectron energy spectrum data analysis order set; the historical photoelectron energy spectrum data analysis order set includes: each photoelectron energy spectrum data, intermediate data obtained by analyzing each photoelectron energy spectrum, and analysis result data of each photoelectron energy spectrum data; Cleaning each data in the historical photoelectron energy spectrum data analysis order set, and decomposing the target photoelectron energy spectrum data into multiple target elements; Generate a hash value matching each of the target elements, store each of the hash values, and obtain the target database.

5. The method for analyzing photoelectron spectrum data according to claim 4, characterized in that: Determining the target peak based on a pre-established target database comprises: Determine a target hash value for each element in the second atlas data, match the target hash value with each hash value stored in the target database, and obtain a reference hash value that matches the target hash value; A target binding energy corresponding to the reference hash value is determined, and the target peak is determined according to the target binding energy.

6. The method for analyzing photoelectron spectrum data according to claim 1, characterized in that: The attribute information includes: binding energy, full width at half maximum and multi-peak area ratio; Correspondingly, fitting the second spectrum data based on the attribute information of each target peak to obtain target spectrum data matching the target photoelectron spectrum data includes: Performing background subtraction on the second atlas data based on a background subtraction function to obtain first target atlas data after background subtraction; The first target spectrum data, binding energy, half-maximum full width and multi-peak area ratio are input into a target fitting function to obtain target spectrum data matching the target photoelectron energy spectrum data.

7. The method for analyzing photoelectron spectrum data according to claim 1, characterized in that: The step of exporting the target atlas data to a target file in response to the export instruction of the target atlas data comprises: Determining target data related to the target atlas data; Storing each of the target data in a target file, and generating link data matching the target file; In response to a click instruction of the link data, the target file is displayed.

8. A photoelectron spectrum data analysis system, characterized in that: include: A photoelectron spectrum data acquisition module, used to acquire target photoelectron spectrum data of a target material, and generate first spectrum data based on the target photoelectron spectrum data; A target peak determination module, used for performing charge correction on the first spectrum data to obtain second spectrum data, and determining the target peak based on a pre-established target database; A target spectrum data determination module, used for fitting the second spectrum data based on the attribute information of each target peak to obtain target spectrum data matching the target photoelectron spectrum data; An export module is used to export the target atlas data to a target file in response to an export instruction of the target atlas data.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can perform the method for analyzing photoelectron energy spectrum data according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the method for analyzing photoelectron energy spectrum data according to any one of claims 1 to 7 when executed.

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