An ultraviolet photoelectron spectrometer energy calibration system and method

Abstract

The application discloses an ultraviolet photoelectron spectrum analyzer energy calibration system and method, and belongs to the field of photoelectron spectrum analysis calibration, and comprises the following steps: determining the energy window width parameter of an electron beam by the pixel position distribution of the energy distribution peak of the electron beam obtained by energy screening of the electron beam through an energy analyzer; performing ultraviolet photoelectron spectrum testing on a standard material sample based on the energy window width parameter, and correcting the zero energy point positioning parameter of the energy analyzer according to the deviation between the theoretical parameter and the test parameter of the Fermi level position of the standard material sample; and performing linear fitting correction on the energy axis position parameter of the energy analyzer according to the deviation between the theoretical parameter and the test parameter of the characteristic energy level of the standard material sample. A closed-loop optimization mechanism is formed, the step-by-step correction of the key parameters of the energy analyzer is realized, and the overall testing effect is improved.

Description

Technical Field

[0001] This application belongs to the field of photoelectron spectroscopy analysis and calibration, specifically relating to a method, system, device, and storage medium for calibrating the energy standard of an ultraviolet photoelectron spectroscopy analyzer. Background Technology

[0002] Ultraviolet photoelectron spectroscopy (UPS) analyzers are widely used in the study of electronic structure on material surfaces, and are of great value, especially in the energy level analysis of semiconductor devices, two-dimensional materials and catalytic materials.

[0003] Existing UPS energy calibration methods mostly employ image recognition and internal instrument parameter adjustments. Specifically, the system generates an electron beam using an electron source, which is then filtered by an energy analyzer to form an energy spectrum image. Subsequently, image processing algorithms are used to identify the pixel positions of the energy distribution peaks, and the zero-point position and energy axis scaling parameters of the energy analyzer are adjusted accordingly.

[0004] However, the above method suffers from insufficient energy calibration accuracy, which limits its application in high-resolution energy spectrum testing. Summary of the Invention

[0005] This application aims to provide a method, system, device, and storage medium for calibrating the energy scale of an ultraviolet photoelectron spectroscopy analyzer, which at least solves the problem of poor application performance in high-resolution scenarios caused by insufficient energy scale accuracy during UPS analysis.

[0006] In a first aspect, embodiments of this application disclose a method for calibrating the energy scale of an ultraviolet photoelectron spectroscopy analyzer, comprising: The pixel position distribution of the energy distribution peaks of the electron beam obtained by energy filtering of the electron beam using an energy analyzer is used to determine the energy window width parameter of the electron beam. Based on the energy window width parameter, ultraviolet photoelectron spectroscopy is performed on the standard material sample, and the zero energy point positioning parameter of the energy analyzer is corrected for position offset according to the deviation between the theoretical parameters of the Fermi level position of the standard material sample and the measured parameters of the Fermi level position of the standard material sample. Based on the deviation between the theoretical parameters of the characteristic energy levels of the standard material sample and the measured parameters of the characteristic energy levels of the standard material sample, the energy axis position parameters of the energy analyzer are linearly fitted and corrected.

[0007] Secondly, embodiments of this application also disclose an energy standard calibration system for an ultraviolet photoelectron spectroscopy analyzer, comprising: Energy window module, zero-point calibration module, and scale calibration module; The energy window module is used to determine the energy window width parameter of the electron beam by analyzing the pixel position distribution of the energy distribution peaks of the electron beam obtained by the energy analyzer through energy screening of the electron beam. The zero-point calibration module is used to perform ultraviolet photoelectron spectroscopy on a standard material sample based on the energy window width parameter, and to correct the position offset of the zero-energy point positioning parameter of the energy analyzer according to the deviation between the theoretical parameters of the Fermi level position of the standard material sample and the measured parameters of the Fermi level position of the standard material sample. The calibration module is used to perform linear fitting correction on the energy axis position parameters of the energy analyzer based on the deviation between the theoretical parameters of the characteristic energy levels of the standard material sample and the test parameters of the characteristic energy levels of the standard material sample obtained from the test.

[0008] Thirdly, embodiments of this application also disclose an electronic device, including a processor and a memory, wherein the memory stores a program or instructions that can run on the processor, and the program or instructions, when executed by the processor, implement the steps of the method described in the first aspect.

[0009] Fourthly, embodiments of this application also disclose a readable storage medium storing a program or instructions that, when executed by a processor, implement the steps of the method described in the first aspect.

[0010] In summary, in this embodiment, an energy analyzer is used to screen the electron beam's energy and obtain the pixel position distribution of its energy distribution peaks. This quantifies the energy window width parameter of the electron beam during imaging, serving as the basis for subsequent calibration. This establishes a mapping relationship between the electron beam energy distribution and image pixels, thereby improving the physical interpretation capability of the energy spectrum image and reducing initial deviations caused by improper window settings. Based on the energy window width parameter, ultraviolet photoelectron spectroscopy is performed on a standard material sample, and the obtained Fermi level position is compared with the theoretical Fermi level position of the standard material. This corrects the offset of the zero-energy point positioning parameter of the energy analyzer. By introducing a theoretical reference, the zero-point drift problem caused by image recognition errors or sample state fluctuations is reduced, enhancing the stability and physical consistency of zero-point positioning. Furthermore, by analyzing the deviation between the theoretical parameters and test parameters of the characteristic energy levels of the standard material sample, the energy axis position parameters of the energy analyzer are linearly fitted and corrected. This not only expands the calibration range to the entire energy axis but also improves the statistical consistency of the energy scale, achieving high calibration accuracy in both high and low energy regions. This overcomes the problem of local error accumulation caused by single-point calibration in existing technologies, enhancing its applicability and reliability in high-resolution energy spectrum testing and reducing energy level identification deviations caused by calibration errors. Therefore, based on the method of this application embodiment, by introducing the theoretical energy level parameters of the standard material sample as a calibration reference, a step-by-step calibration chain of "window width parameter—zero-point offset correction—energy axis linear fitting" is constructed. This ensures that the correction results of each stage become the input basis for the next stage, forming a closed-loop optimization mechanism. This achieves step-by-step correction of key parameters of the energy analyzer, thereby improving the overall testing effect. Attached Figure Description

[0011] In the attached diagram: Figure 1 This is a flowchart illustrating the steps of an energy standard calibration method for an ultraviolet photoelectron spectroscopy analyzer provided in an embodiment of this application. Figure 2 This is a flowchart of another method for calibrating the energy standard of an ultraviolet photoelectron spectroscopy analyzer provided in the embodiments of this application; Figure 3 These are grayscale images of a set of electron scattering peaks in the embodiments of this application; Figure 4 This is a comparative image of the scattering peak of an electron in an embodiment of this application; Figure 5 This is an electron energy spectrum data diagram of a standard material sample under ultraviolet light irradiation provided in the embodiments of this application; Figure 6 This is the process of determining the Fermi level position test parameters based on the Fermi step curve in the embodiments of this application; Figure 7 This is the process of adjusting the horizontal axis according to the secondary electron cutoff edge in the embodiments of this application; Figure 8 This is a block diagram of an energy standard calibration system for an ultraviolet photoelectron spectroscopy analyzer provided in an embodiment of this application; Figure 9 This is a block diagram of an electronic device provided in one embodiment of this application. Detailed Implementation

[0012] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0013] The terms "first," "second," etc., used in this application are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of this application can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first," "second," etc., are generally of the same class, without limiting the number of objects; for example, a first object can be one or more. Furthermore, "and / or" in this application indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects have an "or" relationship.

[0014] like Figure 1 The image shows a method for calibrating the energy scale of an ultraviolet photoelectron spectroscopy analyzer, as provided in an embodiment of this application.

[0015] The method may include the following steps: Step 101: Determine the energy window width parameter of the electron beam by analyzing the pixel position distribution of the energy distribution peaks of the electron beam obtained through energy screening using an energy analyzer.

[0016] In some embodiments of this application, to establish the mapping relationship between the energy distribution and image pixels required for subsequent calibration, the energy distribution characteristics of the electron beam need to be quantified first. Specifically, an energy analyzer is used to screen the energy of the electron beam, obtaining the pixel position distribution of the energy distribution peaks, and determining the energy window width parameter of the electron beam accordingly. An energy analyzer is a device used to select the energy of incident electrons; the peak positions in its output image reflect the spatial distribution characteristics of the electron energy. The energy window width parameter describes the energy range covered by the electron beam during imaging, and its value directly affects the accuracy of subsequent calibration. This effectively reduces energy calibration deviations caused by improper initial window settings and improves the physical interpretation capability of the energy spectrum image.

[0017] In a specific example, researchers irradiated a gold (Au) sample with an electron beam using an electron source and selected electron beam images with concentrated energy distribution peaks using an energy analyzer. Subsequently, they used image recognition software to extract the pixel location distribution range of the main peak in the image and calculated the energy window width parameter of the electron beam based on the instrument's preset pixel-to-energy conversion coefficient. After subsequent calibration using this parameter, the system exhibited higher energy calibration consistency in subsequent tests, and the positioning errors of each energy level feature in the image were effectively controlled.

[0018] Step 102: Based on the energy window width parameter, perform ultraviolet photoelectron spectroscopy on the standard material sample, and correct the zero energy point positioning parameter of the energy analyzer according to the deviation between the theoretical parameters of the Fermi level position of the standard material sample and the measured parameters of the Fermi level position of the standard material sample.

[0019] In some embodiments of this application, to correct the zero-energy point positioning parameters of the energy analyzer and make them more accurately reflect the physical zero-point position in the electron spectrum, it is necessary to perform ultraviolet photoelectron spectroscopy (UVP) testing on a standard material sample and compare the test results with theoretical values. Specifically, the system can perform UVP testing on the standard material sample based on the energy window width parameter obtained in the previous step and extract the Fermi level position test parameters of the sample. Subsequently, the test parameters are compared with the theoretical parameters of the Fermi level position of the standard material sample, the deviation between the two is calculated, and the position offset of the zero-energy point positioning parameters of the energy analyzer is corrected accordingly. The Fermi level refers to the highest energy state that an electron can occupy at absolute zero, and its position is usually represented as the step start point of the electron spectrum in a UPS image. By introducing the theoretical Fermi level position of the standard material sample as a reference, the zero-point positioning deviation caused by image recognition errors, changes in sample surface conditions, or instrument drift can be effectively reduced, thereby enhancing the stability and physical consistency of zero-point calibration.

[0020] In a specific example, researchers selected silver (Ag) as the standard material sample and conducted ultraviolet photoelectron spectroscopy (UVP) tests under predefined energy window width parameters. During the test, the system recorded the Fermi edge position of the silver sample and extracted its pixel position using an image processing algorithm. Subsequently, the system compared the obtained Fermi level position with the theoretical Fermi level position of the silver sample (4.26 eV), calculating a deviation of 0.12 eV. Based on this deviation, the system automatically adjusted the zero-energy point positioning parameter of the energy analyzer, shifting it 0.12 eV towards lower energies. After adjustment, the Fermi edge position in subsequent test images was more consistent with the theoretical value, and the zero-point positioning error of the spectrum was effectively controlled.

[0021] Step 103: Based on the deviation between the theoretical parameters of the characteristic energy levels of the standard material sample and the measured parameters of the characteristic energy levels of the standard material sample, perform linear fitting correction on the energy axis position parameters of the energy analyzer.

[0022] In some embodiments of this application, to improve the calibration consistency of the ultraviolet photoelectron spectroscopy analyzer across the entire energy range, it is necessary to perform linear fitting correction on the energy axis position parameters of the energy analyzer. Specifically, the system can establish a fitting model based on the deviation between the theoretical parameters of the characteristic energy levels of the standard material sample and the measured parameters of the characteristic energy levels, and adjust the energy axis position parameters accordingly. The characteristic energy level refers to the position of a stable peak in the ultraviolet photoelectron spectrum of the standard material sample; its theoretical value is usually derived from a standard database or literature, while the measured value is obtained by the instrument. Linear fitting is a mathematical method used to establish an optimal linear relationship between multiple data points. Its purpose is to correct the proportional and offset parameters of the energy axis by minimizing the overall deviation between the theoretical and measured values. This effectively expands the calibration range to the entire energy axis, reduces calibration errors caused by insufficient local calibration, and improves the overall accuracy and consistency of the energy spectrum.

[0023] In a specific example, the researchers chose silver as the standard material sample and, under conditions where zero-point calibration had been completed,... Ultraviolet photoelectron spectroscopy (UVP) was performed. The system identified multiple stable energy level peaks in the silver sample, such as the Fermi edge near 4.26 eV and other known energy level locations, and recorded their measured values. Subsequently, the system compared these measured values ​​with the theoretical energy level values ​​of the silver sample, obtaining multiple sets of deviation data. Then, a linear fit was performed using the least squares method, generating a correction curve, which was used to adjust the energy axis position parameters of the energy analyzer. After adjustment, the positioning error of each energy level in subsequent tests was significantly reduced, and the spectrum exhibited higher consistency and interpretability across the entire energy range.

[0024] In summary, in this embodiment, an energy analyzer is used to screen the electron beam's energy and obtain the pixel position distribution of its energy distribution peaks. This quantifies the energy window width parameter of the electron beam during imaging, serving as the basis for subsequent calibration. This establishes a mapping relationship between the electron beam energy distribution and image pixels, thereby improving the physical interpretation capability of the energy spectrum image and reducing initial deviations caused by improper window settings. Based on the energy window width parameter, ultraviolet photoelectron spectroscopy is performed on a standard material sample, and the obtained Fermi level position is compared with the theoretical Fermi level position of the standard material. This corrects the offset of the zero-energy point positioning parameter of the energy analyzer. By introducing a theoretical reference, the zero-point drift problem caused by image recognition errors or sample state fluctuations is reduced, enhancing the stability and physical consistency of zero-point positioning. Furthermore, by analyzing the deviation between the theoretical parameters and test parameters of the characteristic energy levels of the standard material sample, the energy axis position parameters of the energy analyzer are linearly fitted and corrected. This not only expands the calibration range to the entire energy axis but also improves the statistical consistency of the energy scale, achieving high calibration accuracy in both high and low energy regions. This overcomes the problem of local error accumulation caused by single-point calibration in existing technologies, enhancing its applicability and reliability in high-resolution energy spectrum testing and reducing energy level identification deviations caused by calibration errors. Therefore, based on the method of this application embodiment, by introducing the theoretical energy level parameters of the standard material sample as a calibration reference, a step-by-step calibration chain of "window width parameter—zero-point offset correction—energy axis linear fitting" is constructed. This ensures that the correction results of each stage become the input basis for the next stage, forming a closed-loop optimization mechanism. This achieves step-by-step correction of key parameters of the energy analyzer, thereby improving the overall testing effect.

[0025] Figure 2 This is another method for calibrating the energy scale of an ultraviolet photoelectron spectroscopy analyzer provided in the embodiments of this application.

[0026] The method may include the following steps: Step 201: Obtain multiple electron beams with energy distribution peak widths smaller than a preset width threshold.

[0027] In some embodiments of this application, to obtain electron beams with higher energy resolution for accurate extraction of subsequent energy window parameters, it is necessary to acquire multiple electron beams with energy distribution peak widths smaller than a preset width threshold. For example, a standard material sample can be irradiated with an electron gun, causing the energy distribution peak widths of the reflected electron beams to all be smaller than the preset width threshold, thus forming multiple scattering peaks of the electron beam. This process utilizes the monochromaticity of the electron beam to concentrate its output spectrum within a narrower wavelength range, thereby reducing the energy spread effect introduced during excitation. The energy distribution peak width refers to the full width at half maximum (FWHM) or full width at half maximum (FWHM) of the main peak in the energy spectrum image, and its value reflects the degree of energy concentration of the electron beam. By obtaining multiple electron beams that meet the distribution peak width requirements, higher selectivity and accuracy are provided for screening target electron beams and extracting pixel position distribution data. This effectively reduces the energy distribution ambiguity caused by excessively wide light source bandwidth, improving the stability and physical interpretability of subsequent energy window parameters.

[0028] In a specific example, researchers used an electron gun to excite and irradiate a silver sample. By adjusting the electron gun to ensure the monochromaticity of the emitted electron beam, the energy broadening of the reflected electron beam was controlled within a specific range (e.g., within ±0.4 eV; during the use of the electron source, if the energy transmission of the hemisphere and lens is fixed, different peak widths can be considered approximately the same). Under these conditions, the system recorded energy spectrum images of multiple electron beams and measured the energy distribution width of their main peaks. Three groups of electron beams had peak widths smaller than the preset 0.4 eV threshold. The system marked these electron beams as candidate targets for subsequent energy screening and pixel location distribution analysis. This allows the system to extract window parameters based on clearer energy spectrum images in subsequent steps, thereby improving the accuracy of the overall calibration chain.

[0029] Step 202: Determine the target electron beam from multiple electron beams through energy screening to obtain pixel position distribution data of the energy distribution peak of each target electron beam, and determine the energy window width parameter based on the pixel position distribution data corresponding to each target electron beam.

[0030] In some embodiments of this application, in order to select representative target electron beams from multiple electron beams for more accurate extraction of the energy window width parameter, energy screening of the electron beams and analysis of their image features are required. Specifically, the system performs energy screening operations on multiple electron beams to determine target electron beams that meet preset conditions and acquires pixel position distribution data of the energy distribution peaks of each target electron beam. Subsequently, the system calculates the energy window width parameter corresponding to each target electron beam based on these pixel position distribution data. Energy screening refers to selecting the part of the electron beam with a more concentrated energy distribution through an energy analyzer to exclude interfering beams with large energy diffusion. Pixel position distribution data refers to the pixel range covered by the main peak in the energy spectrum image, and its width reflects the degree of energy concentration of the electron beam. The energy window width parameter is used to describe the energy coverage range of the electron beam during the imaging process and is the basic input for subsequent calibration processes. This ensures that the selected electron beam has good energy resolution, improving the stability and physical consistency of the subsequent calibration chain.

[0031] In a specific example, after achieving monochromatic control of the electron beam, researchers obtained energy spectrum images of five electron beams. The system performed energy screening on these five beams, excluding two beams with energy distribution peak widths exceeding 0.2 eV, retaining three as target electron beams. Subsequently, the system extracted the main peak pixel position distribution data of these three target electron beams and, based on the instrument's pixel-to-energy conversion coefficient, calculated the corresponding energy window width parameters (i.e., the positions of the corresponding electron scattering peaks) to be 0.18 eV, 0.15 eV, and 0.17 eV, respectively. These parameters were recorded and used for subsequent zero-point calibration and energy axis fitting operations, thereby improving the overall accuracy of the energy scale.

[0032] Optionally, step 202 includes the following sub-steps: Sub-step 2021 involves irradiating the standard material sample with a first electron beam in each energy channel to obtain multiple second electron beams after reflection from the standard material sample, and determining the energy spectrum image of the standard material sample in each energy channel based on the multiple second electron beams.

[0033] In some embodiments of this application, to establish the response characteristics of standard material samples under different energy channels for subsequent energy distribution peak identification and pixel position mapping, it is necessary to sequentially irradiate the standard material samples under multiple energy channels and acquire their corresponding energy spectrum images. Specifically, the system controls the energy output of the electron beam to sequentially irradiate the standard material samples under multiple preset energy channels, thereby obtaining multiple second electron beams after reflection from the standard material samples. Each second electron beam also corresponds to an energy channel, and the ultraviolet photoelectron energy spectrum image of the sample based on each energy channel is recorded. An energy channel refers to the electron excitation conditions generated by the excitation source under different energy settings, and the interval can be set to a fixed step size according to experimental requirements. In this application, the energy channel refers to the kinetic energy possessed by electrons after escaping from the sample surface, the value of which is determined by the energy of the excitation photon minus the work function of the material. An energy spectrum image refers to the electron energy distribution map generated by the sample under a specific excitation energy, and its grayscale or pixel value reflects the distribution of electron density at different energy positions. In this way, the system can establish the image response sequence of the sample under different excitation energies, providing basic data support for subsequent pixel interval division and peak identification.

[0034] like Figure 3 As shown, in a specific example, the experimenters chose gold as the standard material sample and set the energy channel of the excitation electron source to E. k =19.4eV to E k =20.8 eV, with a step size of 0.2 eV. The system sequentially irradiated the gold sample through these eight energy channels and acquired its ultraviolet photoelectron spectroscopy image under each channel. Finally, the system obtained eight grayscale images characterizing the scattering peaks of electrons, labeled as follows: Figure 3 In the images 3-a to 3-h, each image corresponds to a specific excitation energy channel. These images are used in subsequent steps for pixel region segmentation and peak position identification, thereby establishing a mapping relationship between energy channels and image features and improving the accuracy of the overall calibration chain.

[0035] Sub-step 2022: Based on the specified target image region in the energy spectrum image, the target image region is divided into multiple pixel intervals according to pixels, and the gray value distribution data of the energy spectrum image is determined by integral statistics of the target image region divided into pixel intervals.

[0036] In some embodiments of this application, in order to extract the grayscale features of the electron energy distribution in the energy spectrum image for subsequent peak identification and energy channel mapping, it is necessary to perform grayscale segmentation and statistical processing on the target region in the image. Specifically, the system divides the target image region in the energy spectrum image into multiple pixel intervals according to the specified region, and determines the grayscale value distribution data of the image by performing integral statistics on the divided pixel intervals. The target image region refers to the region in the energy spectrum image that contains the main energy distribution information. Its location is usually preset by the system or specified by the user, and it is used to centrally reflect the energy response characteristics of the electron beam. A pixel interval refers to dividing the target region into segments with a fixed pixel width in the vertical or horizontal direction, and each interval contains a number of pixels. Integral statistics refers to accumulating or averaging the grayscale values ​​in each pixel interval to reflect the electron density distribution characteristics of that interval. In this way, the system can obtain a set of continuous grayscale value distribution data, providing a basic input for subsequent peak position identification and energy channel fitting.

[0037] In a specific example, the experimenters obtained E k =19.4eV to E k From eight energy spectrum images with a maximum energy density of 20.8 eV, the central region of each image was selected as the target image region. This region is defined as the "Region of Interest (ROI)" in image analysis, used to extract key energy distribution information. The system forms a column of pixels along the vertical direction for each ROI. Subsequently, the system integrates and statistically analyzes the grayscale values ​​of the pixels in each column, calculating the grayscale value distribution curve of the image with the vertical direction as the cumulative value. This curve reflects the trend of energy density variation at different pixel locations and is recorded as the grayscale value distribution data of the energy spectrum image. This data will be used in subsequent steps to identify the peak positions of the energy distribution peaks and establish a mapping relationship between them and the excitation energy channels.

[0038] Sub-step 2023 involves identifying the grayscale distribution data of the energy spectrum image to obtain the peak pixel position of the energy distribution peak of the energy channel corresponding to each energy spectrum image.

[0039] In some embodiments of this application, in order to extract the energy distribution peak positions of the corresponding energy channel for each energy spectrum image, so as to subsequently establish the mapping relationship between energy and pixels, it is necessary to perform identification processing on the obtained grayscale value distribution data. Specifically, the system can perform peak identification operation on the grayscale value distribution data of each energy spectrum image to extract the peak pixel positions of the energy distribution peaks. The peak pixel position refers to the pixel coordinates of the point with the maximum intensity in the grayscale value distribution curve, which usually reflects the main response position of the electron beam in that energy channel. The identification process can use a fitting algorithm to model the distribution curve to improve the accuracy and stability of peak positioning. In some embodiments of this application, the system can extract the center pixel position of the elastic scattering peak by performing Gaussian fitting on each group of images, and further use the least squares method to fit the mapping relationship between energy (E) and grayscale (P). According to the calibration coefficient obtained by fitting, the system can divide the pixel range of the energy channel, where the peak position is distributed between 68 and 755 pixels in multiple images, spanning 687 pixels. In this way, the system can obtain the peak pixel position of each energy spectrum image, providing key input for subsequent establishment of energy channel mapping and energy axis calibration.

[0040] In a specific example, after completing image acquisition and grayscale statistics, the researchers analyzed E... k =19.4eV to E k The system processes the grayscale distribution data of eight energy spectrum images with a voltage of 20.8 eV. The system then plots this data as... Figure 4 Eight curves are used for intuitive comparison, where the horizontal axis represents pixel location (unit: number of pixels) and the vertical axis represents the grayscale value of the energy channel (also known as intensity, unit: arb.unit). The system then performs Gaussian fitting on each curve to extract the center pixel location of the elastic scattering peak. For example, in E... k In the image corresponding to 19.4 eV, the peak position is identified as P=68 pixels, while in E... k In the image corresponding to 20.8 eV, the peak position is identified as P=755 pixels. The system compares these peak positions with the corresponding E... k The values ​​are calibrated, and the fitting coefficients are recorded for subsequent steps. Through this processing, the system completes the peak identification from image data to energy channels, providing accurate basic data for subsequent energy axis fitting and calibration.

[0041] Sub-step 2024: Establish the mapping relationship between the corresponding energy channel and the peak pixel position.

[0042] The mapping relationship establishes the quantitative relationship between peak pixel positions and energy channels through calibration coefficients.

[0043] In some embodiments of this application, to achieve a quantitative correspondence between the electron beam peak position and the excitation energy channel for subsequent energy axis calibration and image interpretation, a mapping relationship between the energy channel and the peak pixel position needs to be established. Specifically, the system uses a fitting algorithm to establish a mathematical mapping model between the peak pixel position and the corresponding excitation energy channel value of each energy spectrum image identified in the previous steps. This mapping relationship is expressed as a linear function through calibration coefficients, used to describe the quantitative relationship between the peak pixel position and the energy channel. The calibration coefficients refer to the scaling factor and offset factor obtained during the fitting process, usually obtained by least squares fitting. This relationship is not only used for energy axis calibration but also for converting pixel positions in image space into physical energy values, thereby improving the physical interpretation capability of the image. After performing this step, the system can obtain a set of stable mapping parameters, providing a foundation for subsequent energy scale correction and image analysis.

[0044] In a specific example, after completing the peak pixel location identification, the researchers then... k =19.4eV to E k The eight energy channel values ​​of 20.8 eV and their corresponding peak pixel positions (pixels 68 to 755) are input into the system for fitting. The system uses the least squares method to establish a linear relationship model E = aP + b, where E represents the excitation energy channel value, P represents the peak pixel position, and a and b are calibration coefficients obtained from the fitting. After fitting, the system records this mapping relationship and uses it in subsequent steps to convert pixel positions in any image into corresponding energy values. This mapping relationship ensures the continuity and interpretability of the energy channels in image space, thus providing an accurate input basis for the linear fitting correction of the energy axis.

[0045] Step 203: Based on the energy window width parameter, perform ultraviolet photoelectron spectroscopy on the standard material sample, and correct the zero energy point positioning parameter of the energy analyzer according to the deviation between the theoretical parameters of the Fermi level position of the standard material sample and the measured parameters of the Fermi level position of the standard material sample.

[0046] The method shown in this step has been explained in step 102 and will not be repeated here.

[0047] Optionally, step 203 includes the following sub-steps: Sub-step 2031: Obtain the electron spectrum data of the standard material sample under ultraviolet light irradiation, and extract the ultraviolet photoelectron spectrum data in the target energy range from the ultraviolet photoelectron spectrum data according to the preset Fermi level intensity range.

[0048] In some embodiments of this application, in order to extract the electron spectral response characteristics of standard material samples under ultraviolet irradiation conditions for subsequent Fermi level position identification and calibration, it is necessary to acquire their ultraviolet photoelectron spectral data and extract data within the target energy range. Specifically, the system first acquires the electron spectral data of the standard material sample under ultraviolet irradiation, and then extracts the ultraviolet photoelectron spectral data within the target energy range from the complete spectral data according to a preset Fermi level intensity range. Ultraviolet photoelectron spectral data refers to the kinetic energy distribution information of electrons emitted from the sample surface under ultraviolet excitation conditions, typically expressed with electron kinetic energy as the horizontal axis and electron count rate as the vertical axis. The Fermi level intensity range refers to the energy range set around the Fermi level position, used to focus on analyzing the distribution characteristics of electrons near that level. In this way, the system can obtain energy resolution range data for subsequent fitting processing, thereby improving the accuracy and stability of Fermi level identification.

[0049] In a specific example, researchers selected gold as a standard material sample and collected its electron spectral data under ultraviolet light irradiation. The system plotted the complete spectral data as follows: Figure 5 The ultraviolet photoelectron spectroscopy curve shown is illustrated, where the horizontal axis represents electron kinetic energy (eV) and the vertical axis represents the number of electrons per second (counts / s). Subsequently, the system extracts the data segment within the target energy range of this curve based on a preset Fermi level intensity range, using it as input for subsequent fitting processing. This data segment comprehensively reflects the electron distribution characteristics of the sample near the Fermi level, providing fundamental data support for subsequent dual-tangent fitting and zero-point calibration.

[0050] Sub-step 2032 involves using the ultraviolet photoelectron spectroscopy data within the target energy range threshold as the energy resolution range for ultraviolet photoelectron spectroscopy testing, and fitting the Fermi step curve of the standard material sample within the energy resolution range using the double tangent method to obtain the first and second tangents of the Fermi step curve, respectively.

[0051] Wherein, the absolute value of the slope of each point of the Fermi step curve corresponding to the first tangent is less than a preset slope threshold, and the absolute value of the slope of each point of the Fermi step curve corresponding to the second tangent is greater than or equal to the slope threshold.

[0052] In some embodiments of this application, to accurately identify the Fermi level position of a standard material sample and achieve effective zero-point calibration of the energy analyzer, it is necessary to fit the Fermi step curve in the ultraviolet photoelectron spectroscopy data. Specifically, the system can first use the ultraviolet photoelectron spectroscopy data within the target energy range threshold as the energy resolution range, and perform a double-tangent fitting operation within this range. The double-tangent method is a method for identifying inflection points in a step-shaped curve. It constructs two tangents with different slopes to fit the low-slope and high-slope segments of the step curve, respectively. The first tangent corresponds to two regions in the curve where the absolute value of the slope is less than a preset slope threshold, and the second tangent corresponds to regions where the absolute value of the slope is greater than or equal to the threshold. The midpoint of the interval formed by the intersection of the three tangents is the midpoint of the Fermi step, used to represent the test position of the Fermi level. In this way, the system can obtain the structural characteristics of the Fermi step curve and provide an accurate positioning basis for subsequent zero-point offset correction.

[0053] In a specific example, such as Figure 6 As shown, the experimenters irradiated the cleaned gold sample with a deuterium lamp ultraviolet light source. The entire process was conducted in an experimental environment with the temperature controlled at 23±1℃ and the humidity below 40%, and ultraviolet photoelectron spectral data near the Fermi level (-1 to 1 eV) were collected. The system used this data segment as the energy resolution range and plotted it as follows. Figure 6 The Fermi step curve shown. Figure 6 In the diagram, the horizontal axis represents the binding energy (unit: eV), and the vertical axis represents the particle number (unit: kcps). The system uses a double-tangent method for fitting, obtaining a first tangent M and a second tangent N. M corresponds to the region where the absolute value of the slope is less than a preset threshold, and N corresponds to the region where the absolute value of the slope is greater than or equal to the threshold. The system marks the midpoint of the interval formed by the intersection of M and N as X, which is the final determined midpoint of the Fermi step. Through experimental optimization, selecting the energy resolution range within the intensity range of 20%–80% or 16%–84% ensures high data accuracy. This point is the test parameter for the Fermi level position, which will be compared with the theoretical value to calculate the offset.

[0054] Sub-step 2033: Determine the value of the midpoint of the interval formed by the intersection of the first tangent and the second tangent as the Fermi level position test parameter, and determine the deviation between the Fermi level position test parameter and the Fermi level position theoretical parameter.

[0055] In some embodiments of this application, in order to obtain the Fermi level position test parameters of the standard material sample and calculate the deviation between them and the theoretical value for subsequent zero-point calibration, further processing is required on the intersection of the tangents obtained in the previous step. Specifically, the system determines the value of the midpoint of the interval formed by the intersection of the first and second tangents as the Fermi level position test parameter, and compares this test parameter with the theoretical Fermi level position parameter of the standard material sample to calculate the deviation between the two. This deviation is used to quantify the difference between the test result and the theoretical reference, and serves as the basis for subsequent correction of the zero-point positioning parameters of the energy analyzer. The Fermi level position test parameter refers to the midpoint position obtained by fitting the Fermi step curve using the double tangent method, and its physical meaning is the turning point of the electron energy distribution at the Fermi level. In this way, the system can obtain a stable and traceable test value, and by comparing it with the theoretical value, establish offset data, providing key input for subsequent calibration processes.

[0056] In a specific example, the experimenters in Figure 6 In the Fermi step curve shown, the first tangent M and the second tangent N have been obtained using the double tangent method, and their intersection point X has been identified. The system further calculates the local interval formed by this intersection point and extracts the midpoint of this interval as the Fermi level position test parameter. The system compares this test parameter with the theoretical Fermi level value of gold material (typically 0.00 eV) and calculates the deviation Δ2, for example, Δ2 = +0.03 eV. This deviation is recorded and used in subsequent steps to correct the position offset of the energy analyzer zero-point positioning parameter. Simultaneously, the system includes this result in the calibration report to ensure data traceability and the integrity of the calibration process.

[0057] Sub-step 2034: Correct the position offset of the zero energy point positioning parameters of the energy analyzer based on the deviation.

[0058] In some embodiments of this application, to eliminate the systematic deviation of the ultraviolet photoelectron spectroscopy analyzer at the zero point of the energy scale and improve the physical accuracy of the overall energy spectrum, it is necessary to correct the position offset of the zero-energy point positioning parameter of the energy analyzer based on the deviation obtained in the previous step. For example, the system can use the deviation between the measured parameters of the Fermi level position of the standard material sample and its theoretical parameters as input, and adjust the zero-point positioning parameter of the energy analyzer accordingly so that it can accurately correspond to the physical position of the Fermi level in subsequent tests. The zero-energy point positioning parameter refers to the control variable inside the energy analyzer used to calibrate the starting point of the electron binding energy, and its value directly affects the horizontal axis positioning of the entire energy spectrum. Position offset correction refers to adjusting this parameter by addition or subtraction to compensate for the zero-point offset caused by instrument drift, environmental changes, or identification errors. In this way, the system can achieve dynamic calibration of the energy scale starting point, thereby reducing the energy level identification deviation caused by zero-point error and improving the accuracy of subsequent energy axis fitting.

[0059] In a specific example, after completing the double-tangent fitting of the Fermi step curve of the gold material, the researchers obtained the Fermi level position measurement parameter as +0.03 eV, while the theoretical value is 0.00 eV, with a deviation Δ = +0.03 eV. The system inputs this deviation into the calibration module and corrects the position offset of the zero-energy point positioning parameter of the energy analyzer, adjusting it by 0.03 eV towards the direction of energy reduction. After correction, the system re-acquires the energy spectrum image and verifies the Fermi edge position, finding that it is now aligned with the theoretical value, with the error controlled within ±0.005 eV. This correction process is automatically recorded by the system and a calibration report is generated, ensuring data traceability and meeting periodic maintenance requirements.

[0060] Step 204: Based on the deviation between the theoretical parameters of the characteristic energy levels of the standard material sample and the measured parameters of the characteristic energy levels of the standard material sample, perform linear fitting correction on the energy axis position parameters of the energy analyzer.

[0061] The method shown in this step has been explained in step 103 and will not be repeated here.

[0062] Optionally, step 204 includes the following sub-steps: Sub-step 2041: Obtain the test energy spectrum data of the standard material sample under ultraviolet irradiation, and extract the energy test positions of multiple characteristic peaks of the standard material sample from the test energy spectrum data to obtain the characteristic energy level test parameters of the standard material sample.

[0063] The test energy spectrum data includes the Fermi level test position and secondary electron cutoff test position of the standard material sample under ultraviolet light irradiation.

[0064] In some embodiments of this application, in order to establish the energy response characteristics of standard material samples under ultraviolet irradiation and provide multiple reference points for subsequent linear fitting of energy axes, it is necessary to acquire their test energy spectrum data and extract the energy test positions of multiple characteristic peaks from it. Specifically, the system can collect the electron energy spectrum data of standard material samples under ultraviolet irradiation and identify multiple characteristic peak positions, including the Fermi level test position and the secondary electron cutoff test position, to constitute characteristic energy level test parameters. The test energy spectrum data refers to the energy distribution curve of electrons emitted from the sample surface under ultraviolet excitation conditions, with the horizontal axis representing the binding energy and the vertical axis representing the particle count rate. The Fermi level test position is used to calibrate the zero-point reference of the energy spectrum, while the secondary electron cutoff test position is used to identify the lower limit boundary of the electron kinetic energy. In this way, the system can obtain multiple stable test points, providing necessary data support for subsequent energy deviation calculation and linear fitting.

[0065] In one specific example, researchers irradiated a gold sample with an ultraviolet light source and collected its electron spectral data near the Fermi level. The system then plotted this data as... Figure 7 The spectrum shown has the horizontal axis representing binding energy (eV) and the vertical axis representing particle number (cps). In the figure, the system identifies the Fermi level test position (tangent L) and the secondary electron cutoff test position (tangent K) based on the midpoint Y of the Fermi step, and determines the intersection point Z of the two as the location of the secondary electron cutoff edge. Subsequently, the system records the positions of multiple characteristic peaks in the tested energy spectrum data, such as the Fermi level test position E. cutoff and secondary electron cutoff test position E f This data was then used as a parameter for characteristic energy level testing. This process ensured the physical consistency of the test data and provided the foundational data for subsequently establishing the horizontal axis correction function.

[0066] Sub-step 2042 involves comparing the energy test position corresponding to each characteristic peak in the characteristic energy level test parameters with the theoretical energy position in the characteristic energy level test parameters to obtain the energy deviation value corresponding to each characteristic peak.

[0067] In some embodiments of this application, to quantify the energy difference between test data and theoretical reference for subsequent establishment of an energy axis correction function, it is necessary to compare the energy test position corresponding to each characteristic peak in the characteristic energy level test parameters with its theoretical position one-to-one. Specifically, the system can match the test positions of multiple extracted characteristic peaks with the theoretical energy level positions of standard material samples one by one, and calculate the energy deviation value corresponding to each peak. Characteristic peaks include Fermi level positions, secondary electron cutoff edge positions, and other stable energy level points, whose theoretical values ​​are usually derived from standard databases or reference spectra. The energy deviation value refers to the difference between the test position and the theoretical position, reflecting the calibration error of the instrument at that point. After performing this step, the system can obtain a set of deviation data for fitting, providing input for subsequent energy axis linear correction.

[0068] In a specific example, researchers used ultraviolet photoelectron spectroscopy to test gold materials and obtain their Fermi level position E. f and secondary electron cutoff test position E cutoff The system will E f With E cutoff These are respectively compared with the theoretical Fermi level energy level E. f0 Theoretical position of the second electron cutoff energy E cutoff0 By comparison, the Fermi level energy deviation value ΔE is obtained. f =+0.03eV, Secondary electron cutoff energy deviation ΔE cutoff = -0.05 eV, providing a data basis for subsequent fitting.

[0069] Sub-step 2043: Based on the one-to-one correspondence of characteristic peak values ​​and energy deviation values, determine the translation and scaling parameters of the energy axis of the energy analyzer under the linear fitting method, so as to obtain the linear proportional mapping function of the energy axis, so that the overall deviation between the energy test position and the energy theoretical position is minimized under the linear proportional mapping function.

[0070] In some embodiments of this application, to establish the mapping relationship between energy test locations and theoretical locations and to minimize the overall deviation, it is necessary to determine the energy axis translation and scaling parameters of the energy analyzer using a linear fitting method based on the obtained characteristic peak values ​​and energy deviation values. In this step, the system uses the test values ​​and theoretical values ​​of multiple feature points as fitting inputs, performs least squares fitting, and generates a linear proportional mapping function for the energy axis. The fitting objective is to minimize the overall deviation between all test points and the theoretical values ​​after mapping. In this way, the system can obtain a set of stable calibration coefficients for subsequent energy axis correction of the energy spectrum data.

[0071] In a specific example, the system will E f Ecutoff The test and theoretical positions of the other three characteristic peaks are input into the fitting module, which minimizes the objective function. Constraints are imposed, among which The measured energy value, E is the theoretical value. i The test locations correspond to the various characteristic peaks. After fitting, the system obtains a linear scaling function with a = 1.002 and b = -0.04 eV. This function is used for the horizontal axis correction of subsequent energy spectrum data, ensuring that the overall deviation is controlled within ±0.01 eV.

[0072] Sub-step 2044: Adjust the energy axis of the test energy spectrum data according to the linear scaling function to obtain the corrected test energy spectrum data.

[0073] In some embodiments of this application, to ensure that the tested energy spectrum data is consistent with the theoretical reference on the energy axis, it is necessary to adjust the energy axis of the tested data according to the linear scaling function obtained in the previous step. Specifically, the system can take the horizontal axis value of the original tested energy spectrum data as input, apply the linear scaling function for transformation, and generate corrected energy spectrum data. This adjustment process can be regarded as a recalibration of the horizontal axis, ensuring that all characteristic peaks are aligned with their theoretical positions after correction. After performing this step, the system can obtain a set of energy spectrum data with stronger physical consistency, improving the accuracy and comparability of subsequent analyses.

[0074] In a specific example, the system will use the horizontal axis energy value E from the original test data. raw Input fitting function E corrected =1.002E raw 0.04, and then perform a horizontal axis transformation on the entire energy spectrum curve. After correction, E f With E cutoff The data was aligned to theoretical values ​​of 0.00 eV and 5.00 eV respectively, and other characteristic peaks also fell within the theoretical error range. The system saved the corrected data as the calibration result and generated a calibration report, including the original data, fitted parameters, and corrected curves, to meet data traceability and instrument maintenance requirements.

[0075] In summary, in this embodiment, an energy analyzer is used to screen the electron beam's energy and obtain the pixel position distribution of its energy distribution peaks. This quantifies the energy window width parameter of the electron beam during imaging, serving as the basis for subsequent calibration. This establishes a mapping relationship between the electron beam energy distribution and image pixels, thereby improving the physical interpretation capability of the energy spectrum image and reducing initial deviations caused by improper window settings. Based on the energy window width parameter, ultraviolet photoelectron spectroscopy is performed on a standard material sample, and the obtained Fermi level position is compared with the theoretical Fermi level position of the standard material. This corrects the offset of the zero-energy point positioning parameter of the energy analyzer. By introducing a theoretical reference, the zero-point drift problem caused by image recognition errors or sample state fluctuations is reduced, enhancing the stability and physical consistency of zero-point positioning. Furthermore, by analyzing the deviation between the theoretical parameters and test parameters of the characteristic energy levels of the standard material sample, the energy axis position parameters of the energy analyzer are linearly fitted and corrected. This not only expands the calibration range to the entire energy axis but also improves the statistical consistency of the energy scale, achieving high calibration accuracy in both high and low energy regions. This overcomes the problem of local error accumulation caused by single-point calibration in existing technologies, enhancing its applicability and reliability in high-resolution energy spectrum testing and reducing energy level identification deviations caused by calibration errors. Therefore, based on the method of this application embodiment, by introducing the theoretical energy level parameters of the standard material sample as a calibration reference, a step-by-step calibration chain of "window width parameter—zero-point offset correction—energy axis linear fitting" is constructed. This ensures that the correction results of each stage become the input basis for the next stage, forming a closed-loop optimization mechanism. This achieves step-by-step correction of key parameters of the energy analyzer, thereby improving the overall testing effect.

[0076] refer to Figure 8 It illustrates an energy standard calibration system 30 for an ultraviolet photoelectron spectroscopy analyzer provided in an embodiment of this application, comprising: Energy window module 301, zero-point calibration module 302, and scale calibration module 303; The energy window module 301 is used to determine the pixel position distribution of the energy distribution peak of the electron beam obtained by energy screening of the electron beam through the energy analyzer, and to determine the energy window width parameter of the electron beam. The zero-point calibration module 302 is used to perform ultraviolet photoelectron spectroscopy tests on a standard material sample based on the energy window width parameter, and to correct the position offset of the zero energy point positioning parameter of the energy analyzer according to the deviation between the theoretical parameters of the Fermi level position of the standard material sample and the measured parameters of the Fermi level position of the standard material sample. The calibration module 303 is used to perform linear fitting correction on the energy axis position parameters of the energy analyzer based on the deviation between the theoretical parameters of the characteristic energy levels of the standard material sample and the test parameters of the characteristic energy levels of the standard material sample obtained from the test.

[0077] In summary, in this embodiment, the energy window module utilizes an energy analyzer to screen the electron beam's energy and obtain the pixel position distribution of its energy distribution peaks, thereby determining the electron beam's energy window width parameter. This provides a quantitative basis for subsequent calibration modules and establishes a mapping relationship between the electron beam energy distribution and image pixels, effectively reducing initial energy deviations caused by improper window settings and providing stable input for subsequent calibration processes. Furthermore, upon receiving the energy window width parameter, the zero-point calibration module performs ultraviolet photoelectron spectroscopy testing on a standard material sample and compares the obtained Fermi level position with the theoretical value, thereby correcting the positional offset of the energy analyzer's zero-energy point positioning parameter. By introducing a theoretical reference, This method reduces zero-point drift caused by image recognition errors or sample state fluctuations, enhancing the stability and physical consistency of zero-point positioning. It also provides a more accurate starting reference point for the calibration module. Furthermore, the calibration module uses the deviation between the theoretical parameters and test parameters of the characteristic energy levels of the standard material sample to perform linear fitting correction on the energy axis position parameters of the energy analyzer. This not only expands the calibration range to the entire energy axis but also improves the statistical consistency of the energy scale, thereby achieving high calibration accuracy in both high and low energy regions. This overcomes the problem of local error accumulation caused by single-point calibration in existing technologies, enhancing its applicability and reliability in high-resolution energy spectrum testing and reducing energy level identification deviation caused by calibration errors. Therefore, the method based on the embodiments of this application constructs a step-by-step calibration process of "energy window extraction - zero-point offset correction - energy axis linear fitting", which enables data linkage between modules and forms a closed-loop optimization mechanism. This not only improves the energy scale accuracy and calibration efficiency of the UPS analyzer, but also enhances its applicability and reliability in high-resolution energy spectrum testing, reduces energy level identification deviation caused by scale errors, and thus improves the overall testing effect.

[0078] Optionally, the UV photoelectron spectroscopy analyzer energy standard calibration system 30 also includes a standard sample module, which contains standard material samples with known surface energy levels.

[0079] In some embodiments of this application, the ultraviolet photoelectron spectroscopy analyzer energy calibration system 30 further includes a standard sample module. This standard sample module contains standard material samples with known surface energy levels, which serve as theoretical references during the calibration process. The standard sample module, zero-point calibration module 302, and scale calibration module 303 form a data linkage relationship, providing a stable physical benchmark for subsequent energy deviation identification and calibration parameter fitting.

[0080] Standard material samples refer to material samples with known surface electronic structures and stable energy level positions. Their surface energy level parameters can be used to compare with test results, thereby calculating energy deviations and performing calibration operations. The preferred standard material sample is high-purity gold foil, with dimensions suitable for experimental use (e.g., 10 mm × 10 mm × 0.3 mm), and high purity (e.g., the purity of the gold element standard material sample is not less than 99.99%). The introduction of this standard sample enables the system to obtain stable Fermi level positions and secondary electron cutoff edge positions during ultraviolet photoelectron spectroscopy (UVP) testing, thereby improving the accuracy of zero-point calibration and scale fitting. Because the sample surface state is controllable and energy level parameters are traceable, the standard sample module effectively reduces calibration errors caused by sample uncertainties or environmental fluctuations, enhancing the reliability and data consistency of the entire system in high-resolution energy dispersive spectroscopy testing.

[0081] Optionally, the UV photoelectron spectroscopy energy standard calibration system 30 also includes a vacuum chamber for placing standard material samples and an argon ion gun for cleaning the standard material samples placed in the vacuum chamber.

[0082] In some embodiments of this application, the ultraviolet photoelectron spectroscopy analyzer energy standard calibration system 30 further includes a vacuum chamber for placing standard material samples and an argon ion gun for cleaning the standard material samples placed in the vacuum chamber. The vacuum chamber provides a low-pressure environment to avoid interference from air molecules in the electron spectroscopy test, while the argon ion gun performs ion bombardment cleaning on the surface of the standard material samples to remove oxide layers and adsorbed contaminants, ensuring the stability of the sample surface. The vacuum chamber and the standard sample module form a physically enclosed structure, and the argon ion gun communicates with the interior of the chamber via an interface, allowing for directional cleaning after sample loading. The standard material sample is preferably high-purity gold foil, which needs to be placed in the vacuum chamber and evacuated to 5 × 10⁻⁶ before cleaning. -7 Pa, and high-purity argon gas is introduced to maintain a pressure of 1.2 × 10⁻⁶. -³ Pa. The filament current of the argon ion gun can be set to 2.5 A, the anolyte discharge current to 35 mA, and the sputtering time to 40 minutes. This cleaning process effectively removes the oxide layer and organic residues from the sample surface, resulting in a stable and repeatable surface energy level response in ultraviolet photoelectron spectroscopy (UVP) testing. The introduction of this structure not only improves the surface cleanliness and energy level stability of standard material samples but also significantly reduces testing errors caused by surface contamination. This enhances the accuracy and reliability of the zero-point calibration module 302 and the scale calibration module 303 during calibration tasks, providing a more controllable physical basis for the entire energy calibration process.

[0083] Optionally, the energy analyzer performs ultraviolet photoelectron spectroscopy by emitting ultraviolet light from a helium iodide or deuterium lamp.

[0084] In some embodiments of this application, the energy analyzer in the ultraviolet photoelectron spectroscopy (UES) energy calibration system 30 can optionally perform UES photoelectron spectroscopy testing by emitting helium iodide ultraviolet light to achieve highly sensitive excitation and energy distribution acquisition of the electronic structure on the surface of a standard material sample. Helium iodide ultraviolet light is a short-wavelength, high-energy light source with a photon energy of approximately 21.2 eV, suitable for exciting electron transitions on the sample surface and generating measurable photoelectron signals. This light source forms an irradiation path with the standard sample module, works with the energy window module 301 to complete the energy screening of the electron beam, and forms data linkage with the zero-point calibration module 302 and the scale calibration module 303. Due to the high monochromaticity and stability of helium iodide ultraviolet light, it can effectively improve the resolution and signal-to-noise ratio of electron energy distribution in UES photoelectron spectroscopy testing, thereby enhancing the accuracy of identifying the Fermi level position and the secondary electron cutoff edge. This light source can be used to generate an elastic scattering peak energy range covering 19.4 eV to 20.8 eV, and in conjunction with an industrial camera for image acquisition, it ultimately achieves precise localization of the elastic scattering peak and linear fitting of the energy axis. The introduction of this structure helps improve the physical consistency and data stability of the overall calibration chain, enhancing the system's applicability in high-resolution energy dispersive spectroscopy (EDS) testing.

[0085] Optionally, the energy window module 301 includes: The electron beam control submodule is used to acquire multiple electron beams whose energy distribution peak width is less than a preset width threshold. The energy window submodule is used to determine the target electron beam among multiple electron beams by energy screening, to obtain the pixel position distribution data of the energy distribution peak of each target electron beam, and to determine the energy window width parameter based on the pixel position distribution data corresponding to each target electron beam.

[0086] Optionally, the energy window submodule includes: The electron reflection energy spectrum unit uses a first electron beam in each energy channel to irradiate a standard material sample to obtain multiple second electron beams after reflection from the standard material sample, and determines the energy spectrum image of the standard material sample in each energy channel based on the multiple second electron beams. The integration unit is used to divide the target image region in the energy spectrum image into multiple pixel intervals according to the specified target image region, and to determine the gray value distribution data of the energy spectrum image by integrating the target image region divided into pixel intervals. The recognition unit is used to identify the gray value distribution data of the energy spectrum image in order to obtain the peak pixel position of the energy distribution peak of the energy channel corresponding to each energy spectrum image. The mapping unit is used to establish the mapping relationship between the corresponding energy channel and the peak pixel position; the mapping relationship establishes the quantitative relationship between the peak pixel position and the energy channel through the calibration coefficient.

[0087] Optionally, the zero-point calibration module 302 includes: The ultraviolet photoelectron spectroscopy submodule is used to acquire the electron spectrum data of standard material samples under ultraviolet light irradiation, and extract the ultraviolet photoelectron spectroscopy data in the target energy range from the ultraviolet photoelectron spectroscopy data according to the preset Fermi level intensity range. The tangent fitting submodule is used to take the ultraviolet photoelectron spectroscopy data within the target energy range threshold as the energy resolution range of ultraviolet photoelectron spectroscopy testing, and to fit the Fermi step curve of the standard material sample within the energy resolution range using the double tangent method to obtain the first tangent and the second tangent of the Fermi step curve respectively; the absolute value of the slope of each point of the Fermi step curve corresponding to the first tangent is less than the preset slope threshold, and the absolute value of the slope of each point of the Fermi step curve corresponding to the second tangent is greater than or equal to the slope threshold. The deviation determination submodule is used to determine the value of the midpoint of the interval formed by the intersection of the first tangent and the second tangent as the Fermi level position test parameter, and to determine the deviation between the Fermi level position test parameter and the Fermi level position theoretical parameter. The zero-point adjustment submodule is used to correct the position offset of the zero-energy point positioning parameters of the energy analyzer based on the deviation.

[0088] Optionally, the scale calibration module 303 includes: The feature submodule is used to acquire the test energy spectrum data of the standard material sample under ultraviolet irradiation, and extract the energy test positions of multiple characteristic peaks of the standard material sample from the test energy spectrum data to obtain the characteristic energy level test parameters of the standard material sample; the test energy spectrum data includes the Fermi level test position and the secondary electron cutoff test position of the standard material sample under ultraviolet irradiation. The deviation submodule is used to compare the energy test position corresponding to each characteristic peak in the characteristic energy level test parameters with the theoretical energy position in the characteristic energy level test parameters to obtain the energy deviation value corresponding to each characteristic peak. The linear fitting submodule is used to determine the translation and scaling parameters of the energy axis of the energy analyzer under the linear fitting method based on the one-to-one corresponding characteristic peak and energy deviation value, so as to obtain the linear scaling function of the energy axis, so that the overall deviation between the energy test position and the energy theoretical position is minimized under the linear scaling function. The energy axis adjustment submodule is used to adjust the energy axis of the test energy spectrum data according to the linear scaling function to obtain the corrected test energy spectrum data.

[0089] In summary, in this embodiment, the energy window module utilizes an energy analyzer to screen the electron beam's energy and obtain the pixel position distribution of its energy distribution peaks, thereby determining the electron beam's energy window width parameter. This provides a quantitative basis for subsequent calibration modules and establishes a mapping relationship between the electron beam energy distribution and image pixels, effectively reducing initial energy deviations caused by improper window settings and providing stable input for subsequent calibration processes. Furthermore, upon receiving the energy window width parameter, the zero-point calibration module performs ultraviolet photoelectron spectroscopy testing on a standard material sample and compares the obtained Fermi level position with the theoretical value, thereby correcting the positional offset of the energy analyzer's zero-energy point positioning parameter. By introducing a theoretical reference, This method reduces zero-point drift caused by image recognition errors or sample state fluctuations, enhancing the stability and physical consistency of zero-point positioning. It also provides a more accurate starting reference point for the calibration module. Furthermore, the calibration module uses the deviation between the theoretical parameters and test parameters of the characteristic energy levels of the standard material sample to perform linear fitting correction on the energy axis position parameters of the energy analyzer. This not only expands the calibration range to the entire energy axis but also improves the statistical consistency of the energy scale, thereby achieving high calibration accuracy in both high and low energy regions. This overcomes the problem of local error accumulation caused by single-point calibration in existing technologies, enhancing its applicability and reliability in high-resolution energy spectrum testing and reducing energy level identification deviation caused by calibration errors. Therefore, the method based on the embodiments of this application constructs a step-by-step calibration process of "energy window extraction - zero-point offset correction - energy axis linear fitting", which enables data linkage between modules and forms a closed-loop optimization mechanism. This not only improves the energy scale accuracy and calibration efficiency of the UPS analyzer, but also enhances its applicability and reliability in high-resolution energy spectrum testing, reduces energy level identification deviation caused by scale errors, and thus improves the overall testing effect.

[0090] Reference Figure 9The electronic device 500 may include one or more of the following components: processing component 502, memory 504, power supply component 506, multimedia component 508, audio component 510, input / output (I / O) interface 512, sensor component 514, and communication component 516.

[0091] Processing component 502 typically controls the overall operation of electronic device 500, such as operations associated with display, telephone calls, data communication, camera operation, and recording. Processing component 502 may include one or more processors 520 to execute instructions to perform all or part of the steps of the methods described above. Furthermore, processing component 502 may include one or more modules to facilitate interaction between processing component 502 and other components. For example, processing component 502 may include a multimedia module to facilitate interaction between multimedia component 508 and processing component 502.

[0092] Memory 504 is used to store various types of data to support the operation of electronic device 500. Examples of this data include instructions for any application or method operating on electronic device 500, contact data, phonebook data, messages, pictures, multimedia, etc. Memory 504 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0093] Power supply component 506 provides power to various components of electronic device 500. Power supply component 506 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to electronic device 500.

[0094] Multimedia component 508 includes an interface that provides an output interface between electronic device 500 and user. In some embodiments, the interface may include a liquid crystal display (LCD) and a touch panel (TP). If the interface includes a touch panel, the interface may be implemented as a touchscreen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel. The touch sensors may not only sense the boundaries of touch or swipe actions but also detect the duration and pressure associated with the touch or swipe operation. In some embodiments, multimedia component 508 includes a front-facing camera and / or a rear-facing camera. When electronic device 500 is in an operating mode, such as shooting mode or multimedia mode, the front-facing camera and / or rear-facing camera may receive external multimedia data. Each front-facing camera and rear-facing camera may be a fixed optical lens system or have focal length and optical zoom capabilities.

[0095] Audio component 510 is used to output and / or input audio signals. For example, audio component 510 includes a microphone (MIC) used to receive external audio signals when electronic device 500 is in an operating mode, such as call mode, recording mode, and voice recognition mode. The received audio signals may be further stored in memory 504 or transmitted via communication component 516. In some embodiments, audio component 510 also includes a speaker for outputting audio signals.

[0096] Input / output (I / O) interface 512 provides an interface between processing component 502 and peripheral interface modules, such as keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to, home buttons, volume buttons, power buttons, and lock buttons.

[0097] Sensor assembly 514 includes one or more sensors for providing state assessments of various aspects of electronic device 500. For example, sensor assembly 514 may detect the on / off state of electronic device 500, the relative positioning of components such as the display and keypad of electronic device 500, changes in position of electronic device 500 or a component of electronic device 500, the presence or absence of user contact with electronic device 500, orientation or acceleration / deceleration of electronic device 500, and temperature changes of electronic device 500. Sensor assembly 514 may include a proximity sensor configured to detect the presence of nearby objects without any physical contact. Sensor assembly 514 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, sensor assembly 514 may also include an accelerometer, gyroscope, magnetometer, pressure sensor, or temperature sensor.

[0098] Communication component 516 facilitates wired or wireless communication between electronic device 500 and other devices. Electronic device 500 can access wireless networks based on communication standards, such as WiFi, carrier networks (such as 2G, 3G, 4G, or 5G), or combinations thereof. In one exemplary embodiment, communication component 516 receives broadcast signals or broadcast-related information from an external broadcast management system via a broadcast channel. In one exemplary embodiment, communication component 516 also includes a near-field communication (NFC) module to facilitate short-range communication. For example, the NFC module may be implemented based on radio frequency identification (RFID) technology, Infrared Data Association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.

[0099] In an exemplary embodiment, the electronic device 500 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to implement the methods provided in the embodiments of this application.

[0100] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory 504 including instructions, which can be executed by a processor 520 of an electronic device 500 to perform the above-described method. For example, the non-transitory storage medium may be a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device, etc.

[0101] In an exemplary embodiment, the electronic device 500 may also be provided as a server, including a processing component 502, which further includes one or more processors, and memory resources represented by memory 504 for storing instructions, such as applications, that can be executed by the processing component 502. The applications stored in memory 504 may include one or more modules, each corresponding to a set of instructions. Furthermore, the processing component 502 is configured to execute instructions to perform the methods provided in the embodiments of this application.

[0102] Electronic device 500 may also include a power supply component 506 configured to perform power management of electronic device 500, a wired or wireless communication component 516 configured to connect electronic device 500 to a network, and an input / output (I / O) interface 512. Electronic device 500 may operate on an operating system stored in memory 504, such as Windows Server™, Mac OS X™, Unix™, Linux™, FreeBSD™, or similar.

[0103] It should be noted that, for the sake of simplicity, the method embodiments of this application are all described as a series of actions. However, those skilled in the art should understand that the embodiments of this application are not limited to the described order of actions, because according to the embodiments of this application, some steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also understand that the embodiments described in the specification are all preferred embodiments, and the actions involved are not necessarily essential to the embodiments of this application.

[0104] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the application disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this application are indicated by the claims made herein.

[0105] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the claimed rights.

Claims

1. A method for calibrating the energy standard of an ultraviolet photoelectron spectroscopy analyzer, characterized in that, include: The pixel position distribution of the energy distribution peaks of the electron beam obtained by energy filtering of the electron beam using an energy analyzer is used to determine the energy window width parameter of the electron beam. Based on the energy window width parameter, ultraviolet photoelectron spectroscopy is performed on the standard material sample, and the zero energy point positioning parameter of the energy analyzer is corrected for position offset according to the deviation between the theoretical parameters of the Fermi level position of the standard material sample and the measured parameters of the Fermi level position of the standard material sample. Based on the deviation between the theoretical parameters of the characteristic energy levels of the standard material sample and the test parameters of the characteristic energy levels of the standard material sample obtained by testing, the energy axis position parameters of the energy analyzer are linearly fitted and corrected. The step of linearly fitting and correcting the energy axis position parameters of the energy analyzer based on the deviation between the theoretical parameters of the characteristic energy levels of the standard material sample and the measured parameters of the characteristic energy levels of the standard material sample includes: The test energy spectrum data of the standard material sample under ultraviolet light irradiation is obtained, and the energy test positions of multiple characteristic peaks of the standard material sample are extracted from the test energy spectrum data to obtain the characteristic energy level test parameters of the standard material sample; the test energy spectrum data includes the Fermi level test position and the secondary electron cutoff test position of the standard material sample under ultraviolet light irradiation. The energy test position corresponding to each characteristic peak in the characteristic energy level test parameters is compared one-to-one with the theoretical energy position in the characteristic energy level test parameters to obtain the energy deviation value corresponding to each characteristic peak. Based on the one-to-one correspondence of the characteristic peak value and the energy deviation value, the translation and scaling parameters of the energy axis of the energy analyzer are determined using the linear fitting method to obtain the linear scaling mapping function of the energy axis, so that the overall deviation between the energy test position and the energy theoretical position is minimized under the linear scaling mapping function. The energy axis of the test energy spectrum data is adjusted according to the linear scaling function to obtain the corrected test energy spectrum data.

2. The method for calibrating the energy scale of an ultraviolet photoelectron spectroscopy analyzer as described in claim 1, characterized in that, The pixel position distribution of the energy distribution peaks of the electron beam obtained by energy screening of the electron beam through an energy analyzer, and the determination of the energy window width parameter of the electron beam, include: Acquire multiple electron beams with energy distribution peak widths smaller than a preset width threshold; The target electron beam is determined among the multiple electron beams by energy screening to obtain pixel position distribution data of the energy distribution peak of each target electron beam, and the energy window width parameter is determined according to the pixel position distribution data corresponding to each target electron beam.

3. The method for calibrating the energy scale of an ultraviolet photoelectron spectroscopy analyzer as described in claim 2, characterized in that, The step of determining the target electron beam among multiple electron beams through energy screening to obtain pixel position distribution data of the energy distribution peak of each target electron beam, and determining the energy window width parameter based on the pixel position distribution data corresponding to each target electron beam, includes: The standard material sample is irradiated with a first electron beam in each energy channel to obtain multiple second electron beams after reflection from the standard material sample, and the energy spectrum image of the standard material sample in each energy channel is determined based on the multiple second electron beams. Based on the specified target image region in the energy spectrum image, the target image region is divided into multiple pixel intervals according to pixels, and the gray value distribution data of the energy spectrum image is determined by integral statistics of the target image region divided into the pixel intervals. The grayscale value distribution data of the energy spectrum image is identified to obtain the peak pixel position of the energy distribution peak of the energy channel corresponding to each energy spectrum image; Establish a mapping relationship between the corresponding energy channel and the peak pixel position; the mapping relationship establishes a quantitative relationship between the peak pixel position and the energy channel through a calibration coefficient.

4. The method for calibrating the energy scale of an ultraviolet photoelectron spectroscopy analyzer as described in claim 1, characterized in that, The process involves performing ultraviolet photoelectron spectroscopy (UVP) on a standard material sample based on the energy window width parameter, and correcting the zero-energy point positioning parameters of the energy analyzer according to the deviation between the theoretical parameters of the Fermi level position of the standard material sample and the measured parameters of the Fermi level position of the standard material sample. This includes: Obtain the electron spectrum data of the standard material sample under ultraviolet light irradiation, and extract the ultraviolet photoelectron spectrum data in the target energy range from the ultraviolet photoelectron spectrum data according to the preset Fermi level intensity range; The ultraviolet photoelectron spectroscopy data within the target energy range threshold is used as the energy resolution range for ultraviolet photoelectron spectroscopy testing. The Fermi step curve of the standard material sample within the energy resolution range is fitted using the double tangent method to obtain a first tangent and a second tangent to the Fermi step curve. The absolute value of the slope of each point of the Fermi step curve corresponding to the first tangent is less than a preset slope threshold, and the absolute value of the slope of each point of the Fermi step curve corresponding to the second tangent is greater than or equal to the slope threshold. The value of the midpoint of the interval formed by the intersection of the first tangent and the second tangent is determined as the Fermi level position test parameter, and the deviation between the Fermi level position test parameter and the Fermi level position theoretical parameter is determined. The zero-energy point positioning parameters of the energy analyzer are corrected for position offset based on the deviation.

5. A calibration system for an energy standard of an ultraviolet photoelectron spectroscopy analyzer, characterized in that, include: Energy window module, zero-point calibration module, and scale calibration module; The energy window module is used to determine the energy window width parameter of the electron beam by analyzing the pixel position distribution of the energy distribution peaks of the electron beam obtained by the energy analyzer through energy screening of the electron beam. The zero-point calibration module is used to perform ultraviolet photoelectron spectroscopy on a standard material sample based on the energy window width parameter, and to correct the position offset of the zero-energy point positioning parameter of the energy analyzer according to the deviation between the theoretical parameters of the Fermi level position of the standard material sample and the measured parameters of the Fermi level position of the standard material sample. The calibration module is used to perform linear fitting correction on the energy axis position parameters of the energy analyzer based on the deviation between the theoretical parameters of the characteristic energy levels of the standard material sample and the test parameters of the characteristic energy levels of the standard material sample obtained by testing. The calibration module is specifically used to acquire the test energy spectrum data of the standard material sample under ultraviolet irradiation, extract the energy test positions of multiple characteristic peaks of the standard material sample from the test energy spectrum data to obtain the characteristic energy level test parameters of the standard material sample, and compare the energy test position corresponding to each characteristic peak in the characteristic energy level test parameters with the theoretical energy position in the characteristic energy level test parameters to obtain the energy deviation value corresponding to each characteristic peak. Based on the one-to-one correspondence of the characteristic peaks and the energy deviation values, the translation and scaling parameters of the energy axis of the energy analyzer are determined using a linear fitting method to obtain a linear proportional mapping function for the energy axis, so that the overall deviation between the energy test position and the theoretical energy position is minimized under the linear proportional mapping function. The energy axis of the test energy spectrum data is adjusted according to the linear proportional mapping function to obtain the corrected test energy spectrum data. The test energy spectrum data includes the Fermi level test position and the secondary electron cutoff test position of the standard material sample under ultraviolet irradiation.

6. The ultraviolet photoelectron spectroscopy analyzer energy standard calibration system as described in claim 5, characterized in that, It also includes a standard sample module, which contains standard material samples with known surface energy levels.

7. The ultraviolet photoelectron spectroscopy analyzer energy standard calibration system as described in claim 6, characterized in that, It also includes a vacuum chamber for placing the standard material sample, and an argon ion gun for cleaning the standard material sample placed in the vacuum chamber.

8. A computer-readable storage medium, characterized in that, A computer program is stored on the computer-readable storage medium, which, when executed by a processor, implements the ultraviolet photoelectron spectroscopy energy standard calibration method as described in any one of claims 1 to 4.

9. An electronic device, characterized in that, It includes a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the steps of the ultraviolet photoelectron spectroscopy analyzer energy scale calibration method as described in any one of claims 1 to 4.

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