4D-STEM data quality real-time judgment method, device and equipment and storage medium

Abstract

The application provides a 4D-STEM data quality real-time judgment method and device, equipment and a storage medium. The method adds two-dimensional diffraction patterns in 4D-STEM data of scanning points stored in newly added files by real-time detection of file updates in a specified storage location, generates a summed diffraction pattern and displays it on an interactive interface. The method not only improves the image signal-to-noise ratio, but also can display the average band axis orientation information of the sample in the target collection area through the summed diffraction pattern, reflect the average band axis position of the target scanning range and the quality of the collected data, so that the user can observe and analyze the summed diffraction pattern in real time, quickly judge whether the collected 4D-STEM data meets the requirements in the data collection process, and improve the data quality judgment feedback efficiency.

Description

Technical Field

[0001] This application relates to the field of scanning transmission electron microscopy imaging technology, and in particular to a method, apparatus, device and storage medium for real-time judgment of 4D-STEM data quality. Background Technology

[0002] Currently, the 4D-STEM data acquisition process generates tens of thousands to hundreds of thousands of diffraction patterns. Regarding the quality assessment of 4D-STEM data, traditional methods rely on servers to perform long-term, precise reconstruction after large-scale 4D-STEM data acquisition to identify and filter useful data in the dataset. However, this approach cannot quickly assess data quality in real time during the data acquisition process, thus limiting the application of 4D-STEM data acquisition in in-situ dynamic material microscopic characterization. Summary of the Invention

[0003] In view of this, in order to solve the above-mentioned technical problems, this application provides a method, apparatus, device and storage medium for real-time judgment of 4D-STEM data quality.

[0004] Specifically, this application is implemented through the following technical solution:

[0005] According to a first aspect of the embodiments of this application, a method for real-time judgment of 4D-STEM data quality is provided, the method comprising:

[0006] In response to a file addition event in a specified storage location, read the 4D-STEM data stored in the new file, which is the data acquired by scanning N scanning points within the target area of ​​the sample.

[0007] The diffraction patterns of each scanning point in the 4D-STEM data of N scanning points are superimposed to obtain the summation diffraction pattern corresponding to the newly added file; wherein, the diffraction pattern of each scanning point is used to represent the diffraction intensity distribution in reciprocal space after the electron beam interacts with the sample at that scanning point;

[0008] The summation diffraction pattern is displayed on the interactive interface. The summation diffraction pattern is used to determine whether the quality of the 4D-STEM data stored in the newly added file meets the requirements.

[0009] Optionally, the diffraction pattern of each scan point corresponds to a diffraction intensity distribution matrix, where each element represents the diffraction intensity value recorded in the reciprocal lattice space; the superposition of the diffraction patterns of each scan point in the 4D-STEM data of N scan points includes:

[0010] According to the coordinate order of the N scanning points, the diffraction intensity distribution matrix of each scanning point is obtained sequentially;

[0011] The diffraction intensity distribution matrices of the N scanning points are added together according to the positions of the matrix elements to obtain the summation distribution matrix;

[0012] Based on the summation distribution matrix, a visual representation of the summation diffraction pattern is obtained.

[0013] Optionally, after obtaining the summation diffraction pattern, the method further includes:

[0014] Determine the center position of the band axis of the summed diffraction pattern, and calculate the positional offset of the center position of the band axis relative to a preset reference center position;

[0015] If the position offset is greater than a set threshold, it is determined that the quality of the 4D-STEM data stored in the newly added file does not meet the requirements, and the newly added file is deleted from the specified storage location.

[0016] Optionally, the method further includes:

[0017] In response to the command to acquire the centroid integral image iCOM, the centroid offset of the diffraction pattern for each of the N scanning points is determined.

[0018] The obtained N centroid offsets are integrated using the centroid integral map iCOM algorithm to obtain the iCOM map of the target acquisition area corresponding to the 4D-STEM data, and then displayed on the interactive interface.

[0019] Optionally, before reading 4D-STEM data from the newly added file, the method further includes:

[0020] Get the format information of the newly added file;

[0021] If the format information does not conform to the set format standard, the monitoring of the file addition event continues; wherein, the set format standard includes at least the set file extension;

[0022] If the format information conforms to the set format standard, read the 4D-STEM data stored in the newly added file.

[0023] Optionally, obtaining the format information of the newly added file includes:

[0024] If the newly added file is a single, independent file, obtain the full filename and file extension of the newly added file;

[0025] In the case where the newly added file is a combination file including multiple subsidiary files, the main file is identified according to predefined rules, and the file extension of the main file in the newly added file is obtained.

[0026] According to a second aspect of the embodiments of this application, a data processing apparatus is provided, the apparatus comprising:

[0027] The data reading module is used to respond to a file addition event in a specified storage location and read the 4D-STEM data stored in the newly added file, which is the data collected by scanning N scanning points in the sample target acquisition area.

[0028] The diffraction pattern overlay module is used to overlay the diffraction patterns of each scanning point in the 4D-STEM data of N scanning points to obtain the summation diffraction pattern corresponding to the newly added file; wherein, the diffraction pattern of each scanning point is used to represent the diffraction intensity distribution in reciprocal space after the electron beam interacts with the sample at that scanning point;

[0029] The interactive module displays the summation diffraction pattern on the interactive interface. The summation diffraction pattern is used to determine whether the quality of the 4D-STEM data stored in the newly added file meets the requirements.

[0030] Optionally, the diffraction pattern for each scan point corresponds to a diffraction intensity distribution matrix, where each element represents a diffraction intensity value recorded in the reciprocal lattice space; the diffraction pattern overlay module is specifically used for:

[0031] According to the coordinate order of the N scanning points, the diffraction intensity distribution matrix of each scanning point is obtained sequentially;

[0032] The diffraction intensity distribution matrices of the N scanning points are added together according to the positions of the matrix elements to obtain the summation distribution matrix;

[0033] Based on the summation distribution matrix, a visual representation of the summation diffraction pattern is obtained.

[0034] Optionally, the device further includes:

[0035] Determine the center position of the band axis of the summed diffraction pattern, and calculate the positional offset of the center position of the band axis relative to a preset reference center position;

[0036] If the position offset is greater than a set threshold, it is determined that the quality of the 4D-STEM data stored in the newly added file does not meet the requirements, and the newly added file is deleted from the specified storage location.

[0037] Optionally, the device further includes:

[0038] In response to the command to acquire the centroid integral image iCOM, the centroid offset of the diffraction pattern for each of the N scanning points is determined.

[0039] The obtained N centroid offsets are integrated using the centroid integral map iCOM algorithm to obtain the iCOM map of the target acquisition area corresponding to the 4D-STEM data, and then displayed on the interactive interface.

[0040] Optionally, before reading 4D-STEM data from the newly added file, the device further includes:

[0041] The format acquisition module is used to obtain the format information of newly added files;

[0042] The judgment module is used to continue monitoring the file addition event if the format information does not conform to the set format standard; wherein the set format standard includes at least a set file extension; and if the format information conforms to the set format standard, read the 4D-STEM data stored in the newly added file.

[0043] Optionally, the format acquisition module is specifically used for:

[0044] If the newly added file is a single, independent file, obtain the full filename and file extension of the newly added file;

[0045] In the case where the newly added file is a combination file including multiple subsidiary files, the main file is identified according to predefined rules, and the file extension of the main file in the newly added file is obtained.

[0046] According to a third aspect of the embodiments of this application, an electronic device is provided, the electronic device comprising: a memory and a processor; the memory being used to store a computer program; the processor being used to execute the above-described 4D-STEM data quality real-time judgment method by invoking the computer program.

[0047] According to a fourth aspect of the embodiments of this application, a computer-readable storage medium is provided, on which a computer program is stored, wherein when the program is executed by a processor, the above-described 4D-STEM data quality real-time judgment method is implemented.

[0048] The technical solutions provided in this application embodiment may include the following beneficial effects:

[0049] In the technical solution provided in this application, by real-time detection of file updates in a specified storage location, the two-dimensional diffraction patterns in the 4D-STEM data of the newly added files are summed to generate and display a summed diffraction pattern, thereby improving the image signal-to-noise ratio. This summed diffraction pattern displays the average band axis orientation information of the sample in the target acquisition area, reflecting the average band axis position of the target scanning range and the quality of the acquired data. This allows users to quickly determine whether the quality of the 4D-STEM data acquired in this scan meets their requirements by observing and analyzing the summed diffraction pattern in real time. It should be understood that the above general description and the following detailed description are merely exemplary and explanatory, and do not limit this application. Furthermore, any embodiment in this application does not need to achieve all the above effects. Attached Figure Description

[0050] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0051] Figure 1A This is an exemplary schematic diagram of the 4D-STEM data acquisition and storage process in related technologies;

[0052] Figure 1B This is a schematic flowchart illustrating a real-time 4D-STEM data quality assessment method according to an exemplary embodiment of this application;

[0053] Figure 1C This is a diffraction pattern of a scanning point on the surface of an article as shown in an exemplary embodiment of this application;

[0054] Figure 1D It is a summation diffraction pattern obtained by superimposing diffraction patterns of N scanning points within a specified collection area of ​​a sample as shown in an exemplary embodiment of this application;

[0055] Figure 2 This is a flowchart illustrating an exemplary embodiment of the present application for obtaining an additive diffraction pattern;

[0056] Figure 3A This is a flowchart illustrating a step in analyzing data quality based on an additive diffraction pattern, as shown in an exemplary embodiment of this application.

[0057] Figure 3B This application illustrates a reference center position and auxiliary lines for an additive diffraction pattern in an exemplary embodiment.

[0058] Figure 4A This is a flowchart illustrating an iCOM image acquisition step according to an exemplary embodiment of this application;

[0059] Figure 4BThis application illustrates an additive diffraction pattern and a corresponding iCOM image in an exemplary embodiment.

[0060] Figure 5 This is a schematic diagram of the structure of a data processing apparatus shown in an exemplary embodiment of this application;

[0061] Figure 6 This is a hardware schematic diagram of an electronic device illustrated in an exemplary embodiment of this application. Detailed Implementation

[0062] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims. It should be understood that although the terms first, second, third, etc., may be used in this application to describe various information, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from one another.

[0063] Scanning Transmission Electron Microscopy (STEM) imaging, using a sub-nanometer-scale focused electron beam to scan samples point-by-point, has become a crucial method for characterizing and modifying the microstructure of devices and materials. This is because STEM utilizes a focused electron beam at the sub-nanometer scale to scan the sample, enabling the detection and modification of fine local atomic structures at the nanoscale. The resulting 4D-STEM and 5D-STEM images exhibit advantages such as minimal electron beam interference and high imaging resolution. The 4D-STEM image data collection mode under STEM imaging requires collecting data from a two-dimensional diffraction disk / pattern at each scanning position on the two-dimensional sample plane, forming a four-dimensional 4D-STEM dataset consisting of a two-dimensional real space and a two-dimensional diffraction space. If it is necessary to track and monitor changes over time or continuously modify materials, 4D-STEM data needs to be acquired at each characteristic time point to form a 5D dataset. Then, an iterative algorithm is used to precisely inversely solve the material function and electron beam function to obtain the atomically resolved material structure and its evolution.

[0064] Regarding the acquisition of 4D-STEM data, such as Figure 1A An exemplary schematic diagram of the 4D-STEM data acquisition and storage process is shown, including the data acquisition preparation stage and the acquisition and storage stage.

[0065] During the preparation phase, the overall position of the sample is initially determined. Before each transmission scan of a designated area of ​​the sample (i.e., the target acquisition area), the position and orientation of the sample are precisely adjusted so that the target acquisition area of ​​the sample is within the scanning range of the electron beam. Based on the research objectives and sample characteristics, scanning parameters suitable for the target acquisition area are set, such as the electron beam current intensity, scanning step size, exposure time, and defocusing amount.

[0066] During the acquisition and storage phase, the device sequentially positions and accurately focuses the electron beam onto each scanning point within the target acquisition area of ​​the sample, according to a preset scanning step size and scanning area size. The diffraction signal generated by the interaction between the electron beam and the sample at any scanning point is captured by the detector. After signal conversion and amplification, diffraction pattern data for that scanning point is generated. The diffraction pattern data of each scanning point within the target acquisition area are integrated and stored according to the scanning position order to obtain a data file storing the 4D-STEM data acquired within the target acquisition area. After completing the transmission scan of the target acquisition area, the data file generates a unique filename according to a preset file naming rule and stores it in a pre-specified storage location. This filename may include information such as acquisition time, sample number, and scanning area for subsequent data management and retrieval.

[0067] After completing the transmission scan of the target acquisition area of ​​the sample, before acquiring the target acquisition area of ​​the newly determined next scan, the scanning parameters of the device are adjusted according to the preset parameter adjustment scheme to obtain device parameters suitable for the target acquisition area of ​​the newly determined next scan. After the parameter adjustment is completed, the transmission scan of the target acquisition area of ​​the newly determined next scan is continued and the acquired 4D-STEM data is stored. The above process is repeated until the transmission scan of the entire sample is completed.

[0068] Currently, the data acquisition process of 4D-STEM and 5D-STEM generates tens of thousands to hundreds of thousands of diffraction patterns. Traditional methods require a long time, such as several days or weeks, for precise reconstruction after the large-scale 4D-STEM or 5D-STEM data acquisition to determine and filter useful data in the acquired dataset. On the one hand, this processing method puts pressure on storage space, and on the other hand, it cannot quickly determine the data quality in real time during the data acquisition process, which limits the application of 4D-STEM or 5D-STEM data acquisition in in-situ dynamic material microscopic characterization.

[0069] To address the aforementioned technical problems, this application provides a real-time method for judging the quality of 4D-STEM data. This method processes a data file stored in a designated location in real time. This data file contains 4D-STEM data acquired in the target acquisition area of ​​a sample using a transmission electron microscope (TEM) in scanning transmission mode. The method analyzes whether the quality of the 4D-STEM data acquired for this target acquisition area meets the requirements. Since 4D-STEM data and 5D-STEM data are both multidimensional diffraction imaging data based on the interaction between the electron beam and the sample, relying on the interaction process between the electron beam and sample atoms in a TEM, the physical essence and basic principles of data acquisition are consistent. Therefore, this real-time method for judging the quality of 4D-STEM data is also applicable to the quality judgment scenario of 5D-STEM data.

[0070] Based on this application, the processing of the data file used for 4D-STEM data begins when the data file is stored in the designated storage location. The data file processing can be carried out in parallel with the 4D-STEM data acquisition process, thereby enabling real-time and rapid data quality assessment of the most recently acquired 4D-STEM data during the data acquisition process. The quality assessment result of the most recently acquired 4D-STEM data can be promptly fed back to the operator, allowing the operator to identify and resolve problems in a timely manner during the acquisition process, such as adjusting acquisition parameters and / or re-acquiring. This avoids repeated acquisitions caused by discovering data quality problems only after the acquisition is completed, saving time and resources.

[0071] See Figure 1B An exemplary flowchart illustrates a method for real-time assessment of 4D-STEM data quality. The method for real-time assessment of 4D-STEM data quality provided in this application may include at least the following steps:

[0072] S101, in response to a file addition event in the specified storage location, reads the 4D-STEM data collected by scanning N scanning points within the sample target acquisition area stored in the newly added file;

[0073] This specified storage location represents a pre-defined file storage path or directory for storing 4D-STEM data files acquired through transmission electron microscopy scanning in transmission mode. This storage location can be a folder on a local computer hard drive or a specific directory on a network storage device.

[0074] A file addition event is used to indicate that new data has been stored in the specified storage location. For example, when the data file F1 corresponding to the target acquisition area M1 of the sample is stored in the specified storage location, a file addition event is triggered. This file addition event can be listened to and captured by the data processing program so that when a new data file is stored in the specified storage location, the data processing flow of this application can be started to process the new data file in real time.

[0075] The newly added file is the data file stored at the specified storage location when a file addition event is triggered. For example, in the above example, when data file F1 is stored at the specified storage location, a file addition event is triggered, and data file F1 is the newly added file. This newly added file stores data from the target acquisition area of ​​the sample acquired using 4D-STEM technology. It contains diffraction information from all scanning points within the target acquisition area of ​​the sample and has a specific file format, such as HDF5 or TIFF, for efficient storage and organization of large amounts of four-dimensional data. In this embodiment, the specified storage location can be continuously monitored during the acquisition of 4D-STEM data, and a file addition event can be responded to in real time at that specified storage location, processing the newly added file that triggers the file addition event.

[0076] The target acquisition area of ​​the sample is divided into N discrete scanning points. The electron beam is sequentially positioned at each scanning point, and the diffraction pattern of that point is acquired. The size of N depends on the scanning step size and the size of the target acquisition area. The smaller the scanning step size, the larger N is, and the higher the resolution of the acquired data.

[0077] The 4D-STEM dataset is a four-dimensional dataset containing two spatial dimensions (scan position) and two momentum dimensions (diffraction information). Specifically, the diffraction pattern of each scan point corresponds to a two-dimensional diffraction intensity distribution matrix, which represents the information of that scan point in reciprocal space (i.e., diffraction space). Each element in the matrix corresponds to the diffraction intensity value at a specific pixel location on the detector. The diffraction patterns of all scan points are arranged in order of scan position, thus constituting the spatial dimension information. This four-dimensional data structure can comprehensively describe the microstructure and characteristics of the sample within the target acquisition area.

[0078] 4D-STEM datasets can be represented as four-dimensional tensors:

[0079]

[0080] Wherein, the real space coordinates are R = (R x ,R y The scanning position forms a two-dimensional grid in real space, with a grid size of N. x ×N y N xand N y These represent the number of scan points in the x and y directions, respectively; reciprocal space coordinates K = (k x ,k y The detector pixels form a two-dimensional grid in reciprocal space, with a grid size of [missing value]. and They represent k respectively x and k y The number of detector pixels in the direction; the intensity function I(R,K) represents the diffraction intensity value of the pixel corresponding to the reciprocal space coordinate K on the detector at the scan position R. For each scan position R = (R x ,R y ), I(R,K) in K=(k x ,k y The values ​​on ) constitute a The two-dimensional diffraction intensity distribution matrix comprehensively describes the diffraction information of the scanning point R in reciprocal space, and all N x ×N y The two-dimensional diffraction intensity distribution matrices corresponding to each scanning position are arranged in order of the scanning positions, forming the entire four-dimensional tensor. This four-dimensional tensor completely records the full diffraction information of each scanning position within the sample target acquisition area, forming a 4D mapping relationship between real space and diffraction space.

[0081] This step is used to read the 4D-STEM data of each of the N scan points from the new file, including the position and diffraction information of each scan point. This diffraction information can at least include a diffraction pattern to facilitate subsequent overlay processing of the single diffraction pattern corresponding to each scan point. For example... Figure 1C The example shown is a diffraction pattern of a scanning point on the surface of an object. The brightness of each pixel in the pattern represents the diffraction intensity of the diffraction direction corresponding to that point. The higher the brightness, the more electrons are scattered in that diffraction direction, and the greater the diffraction intensity in that direction. By analyzing the brightness of each pixel in the diffraction pattern, information about the microstructure of the sample can be obtained, such as the lattice constant, crystal orientation, and defects of the crystal.

[0082] In this step, a file system monitoring tool can be used to monitor the specified storage location, setting the monitored event type to file addition events and registering an event handling function. When a file addition event occurs, this function will be automatically called to read the 4D-STEM data corresponding to N scan points. Alternatively, other feasible implementation methods from related technologies can be used, such as a producer-consumer model based on message queues, etc., which are not limited in this application.

[0083] S102, the diffraction patterns of each scanning point in the 4D-STEM data of N scanning points are superimposed to obtain the summation diffraction pattern corresponding to the newly added file; wherein, the diffraction pattern of each scanning point is used to represent the diffraction intensity distribution in reciprocal space after the electron beam interacts with the sample at that scanning point;

[0084] In this embodiment, the N scanning points belong to the target acquisition area of ​​the sample and are acquired sequentially using the same device within the same time period. Therefore, the pixel matrix size of the diffraction pattern of each scanning point is the same, for example, 128*128. That is, the diffraction patterns corresponding to the N scanning points are consistent in the dimension of the pixel matrix, and the pixel positions in the diffraction patterns of different scanning points are the same. Pixels at the same pixel position represent the same diffraction direction. For example, in the diffraction pattern of all scanning points, the pixel located in the i-th row and j-th column corresponds to the scattering of the electron beam in a specific diffraction direction.

[0085] Based on this, when superimposing the diffraction patterns of N scan points to obtain a summation diffraction pattern, the diffraction intensities represented by pixels at the same position in the diffraction patterns corresponding to the N scan points can be summed to obtain the diffraction intensity represented by pixels at the same position in the summation diffraction pattern. This summation is performed for all pixels at each of the N scan points to obtain the corresponding summation diffraction pattern. In other words, the diffraction intensity value represented by each pixel in the summation diffraction pattern is obtained by summing the diffraction intensity values ​​represented by pixels at the same position in the diffraction patterns corresponding to the N scan points. For example, see... Figure 1D The summation diffraction pattern obtained by superimposing the diffraction patterns of N scanning points within a specified collection area of ​​a sample, as exemplified, can be used to reflect the comprehensive diffraction characteristics of the entire scanning area in reciprocal space.

[0086] This step is used to overlay the diffraction patterns of each scan point in the 4D-STEM data of N scan points, as described above. Based on this, the superposition operation in this step is essentially a summation of the diffraction intensity distributions represented by the N scanning points, which can be expressed as:

[0087]

[0088] The double summation symbol represents traversing all real space scan positions (i.e., scan points), where for any reciprocal space position K = (k x ,k y The diffraction intensities of all scanning points at the reciprocal space position are summed to obtain the total diffraction intensity of the reciprocal space position at all real space scanning points.

[0089] Based on the principles of statistical averaging and signal superposition, since random noise is usually irregular and low in intensity in the diffraction patterns at different scanning points, while effective diffraction signals, such as crystal diffraction spots, have consistency and high intensity in the diffraction patterns at different scanning points, by superimposing the diffraction patterns of N scanning points, low-intensity random noise will cancel each other out, while high-intensity effective signals will continuously accumulate and enhance, achieving the effect of effectively removing random noise and enhancing effective diffraction signals, thereby significantly improving the image signal-to-noise ratio. It also has good robustness under low electron dose imaging conditions. Therefore, the summed diffraction pattern can reflect the validity and accuracy of the acquired raw data, representing the reconstruction quality of the sample microstructure image obtained by accurately reconstructing based on the 4D-STEM dataset acquired in this study.

[0090] The diffraction pattern at each scanning point contains the diffraction intensity distribution in reciprocal space after the electron beam interacts with the sample at that scanning point. This diffraction intensity distribution is closely related to the crystal orientation of the sample. By superimposing the diffraction patterns of multiple scanning points, it is equivalent to comprehensively averaging the crystal orientation information at multiple different positions. Compared with traditional methods that only show the diffraction pattern of a single scanning point, the summation diffraction pattern obtained by this application can reflect the average band axis orientation information of the sample target acquisition area, and represent the comprehensive diffraction intensity distribution of all scanning points and the global average structural characteristics, which helps to analyze the microstructure and properties of the sample in the entire acquisition area.

[0091] S103, the summation diffraction pattern is displayed on the interactive interface. The summation diffraction pattern is used to determine whether the quality of the 4D-STEM data stored in the newly added file meets the requirements.

[0092] Based on the data characteristics presented by the additive diffraction pattern, it is possible to determine whether the quality of newly stored 4D-STEM data meets the requirements. For example, at least one of the following data characteristics can be used to judge whether the quality of 4D-STEM data meets the requirements: the clarity of diffraction spots or rings, the uniformity of diffraction intensity distribution, the noise level of the background area, the overall symmetry of the diffraction pattern, and the position of the center of the band axis of the additive diffraction pattern. Data quality can be judged by analyzing whether these data characteristics meet the requirements. For example, if the crystal diffraction spots or rings in the additive diffraction pattern are clear, sharp, and have distinct edges, and the background area is clean with low noise levels, it reflects that the diffraction signal generated by the interaction between the electron beam and the sample is strong and the signal-to-noise ratio is high. This indicates that the crystal structure in the sample is intact, there is no additional contamination on the surface, and the data acquisition process is stable, thus the data quality is high.

[0093] An interactive interface serves as a channel for information exchange between humans and computer systems. Users input information and issue commands to the computer system through the interactive interface, while the computer system provides feedback on processing results and displays information to the user through the interactive interface. In this embodiment, the interactive interface is a graphical visualization software interface that integrates various function buttons, menus, drawing areas, and other elements, facilitating researchers' interaction with the addition diffraction pattern displayed on the interactive interface.

[0094] In this step, the additive diffraction pattern obtained from processing 4D-STEM data from N scan points is displayed on the interactive interface. This allows researchers to directly and quickly capture the key features of the data presented by the additive diffraction pattern through visual observation, thereby rapidly assessing the quality of newly stored 4D-STEM data. Simultaneously, the interactive interface allows researchers to perform various operations and interactions on the additive diffraction pattern, such as zooming in, zooming out, rotating, measuring, and calibrating the center of the diffraction pattern's band axis. This facilitates a deeper analysis of the diffraction pattern's details, enabling researchers to more accurately determine whether the data quality meets requirements and improving work efficiency.

[0095] If the quality of newly added 4D-STEM data stored in a file does not meet requirements based on the summation diffraction pattern, feedback can be promptly provided to the operator. This allows for readjustment of acquisition parameters for the target acquisition area of ​​the sample corresponding to the newly added file, and the 4D-STEM data acquisition can be performed again. This enables operators to identify and resolve problems during the acquisition process, avoiding duplicate acquisitions caused by discovering data quality issues only after completion, thus saving time and resources. Furthermore, newly added 4D-STEM data that does not meet requirements can be removed from the designated storage location to avoid storing a large number of invalid data files, reducing storage space usage and the pressure on storage management.

[0096] During 4D-STEM data acquisition, before acquiring data from the newly determined target acquisition area of ​​the sample for the next scan, the scanning parameters of the device need to be adjusted according to a preset parameter adjustment scheme to obtain device parameters suitable for the newly determined target acquisition area. The real-time 4D-STEM data quality judgment method provided in this application can quickly and automatically generate and display a preview image of the addition diffraction pattern in a short time. Thus, during the waiting period while adjusting parameters for transmission scanning of the next target acquisition area, the user can observe and analyze the addition diffraction pattern in real time to judge the data quality, which facilitates the adjustment of experimental parameters before scanning the next target acquisition area, thereby improving the data quality of subsequent acquisitions.

[0097] In this embodiment, the 4D-STEM data acquisition process and the processing of the stored 4D-STEM dataset can be performed simultaneously. By real-time detection of file updates in the specified storage location, the two-dimensional diffraction patterns in the 4D-STEM data of the scan points stored in the newly added files are summed to generate a summed diffraction pattern, which is then displayed on the interactive interface. This not only improves the image signal-to-noise ratio but also allows the summed diffraction pattern to display the average band axis orientation information of the sample in the target acquisition area, reflecting the average band axis position of the target scanning range and the quality of the acquired data. This enables users to quickly and in real-time determine whether the quality of the scanned 4D-STEM data meets the requirements during the data acquisition process by observing and analyzing the summed diffraction pattern, without having to wait for the entire sample scan to be completed and then undergo a long period of precise reconstruction to filter the effective data in the dataset. This greatly improves the efficiency of data quality judgment and feedback.

[0098] In addition, since data processing and acquisition are performed in parallel, data acquisition of the next target acquisition area of ​​the sample can continue while the newly added file is being processed. This continuity makes the data acquisition process smoother and avoids acquisition interruptions caused by data processing, thus enabling faster scanning and transmission of the entire sample.

[0099] In some embodiments, the diffraction pattern of each scan point represents the diffraction information of that scan point in reciprocal space. The diffraction pattern corresponds to a diffraction intensity distribution matrix, where each element represents the diffraction intensity value recorded in the reciprocal space. Furthermore, the pixel matrix size of the diffraction patterns of N scan points is the same, and pixels at the same position represent the same diffraction direction. Therefore, obtaining the summed diffraction pattern corresponding to the newly added file as described in step S102 of the aforementioned embodiment can be achieved by superimposing the diffraction intensity distribution matrices. Specifically, see [link to documentation]. Figure 2 The exemplary flowchart for obtaining the summation diffraction pattern can be implemented through the following steps:

[0100] S201, obtain the diffraction intensity distribution matrix of each scanning point in the order of the coordinates of the N scanning points;

[0101] The diffraction intensity distribution matrix for each scan point is a two-dimensional array. The number of rows and columns represents the number of sampling points in the two-dimensional space. When this diffraction intensity distribution matrix is ​​visualized as a diffraction pattern, each element in the matrix corresponds to a pixel value in the diffraction pattern. The value of each matrix element represents the diffraction intensity at that location in the two-dimensional space, and the pixel value in the diffraction pattern is visually represented by a color map or grayscale map. For a 128×128 diffraction intensity distribution matrix, the element I(i,j) (where i represents the row index and j represents the column index) corresponds to the pixel value in the i-th row and j-th column of the diffraction pattern.

[0102] S202, add the diffraction intensity distribution matrices of N scanning points according to the position of the matrix elements to obtain the summation distribution matrix;

[0103] In other words, for each of the N scan points, the values ​​of the N elements at the same position are summed to form the sum of the values ​​of the elements at the same position in the sum distribution matrix. This process is repeated for all elements in the diffraction intensity distribution matrix to generate the sum distribution matrix. The size of the sum distribution matrix is ​​the same as the size of the diffraction intensity distribution matrix for a single scan point. For each element in the sum distribution matrix, the value is the sum of the values ​​of the elements at the corresponding positions of the N scan points.

[0104] S203, Based on the summation distribution matrix, a visual representation of the summation diffraction pattern is obtained.

[0105] The summation distribution matrix integrates information from multiple scanning points, enhancing the effective signal (such as crystal diffraction spots) and suppressing random noise. It can more stably and accurately reflect the average diffraction characteristics of the sample within the target acquisition area. To more intuitively display the diffraction characteristics of the sample and facilitate observation and analysis by researchers, the summation distribution matrix can be visualized.

[0106] In the visualization process, the mapping relationship between the element values ​​in the summation distribution matrix and the pixels in the visualized diffraction pattern is the same as the mapping relationship between the diffraction pattern of a single scan point and its corresponding diffraction intensity distribution matrix. For example, grayscale mapping or color mapping can be used to map the values ​​in the matrix to different grayscale levels or colors according to a certain range. Based on the determined mapping relationship, the summation distribution matrix is ​​converted into an image format using image processing software or a plotting library in a programming language. During the conversion process, each row and column of the matrix corresponds to the pixels in the horizontal and vertical directions of the summation diffraction pattern, respectively, and each element value in the matrix determines the color or brightness of the corresponding pixel.

[0107] In this embodiment of the disclosure, the average diffraction intensity distribution of the sample in the target acquisition area is displayed in an intuitive graphical form by using an additive diffraction pattern. This allows researchers to quickly determine whether the quality of the 4D-STEM data in the target acquisition area meets the requirements by observing the diffraction spots, rings and other features in the diffraction pattern, and to evaluate whether the experimental parameters are set reasonably based on the quality of the additive diffraction pattern.

[0108] In some embodiments, the additive diffraction pattern serves as a key representation of the 4D-STEM data acquired within the target acquisition area of ​​the sample. It contains rich microstructural information and can display the average band axis orientation information of the sample within the target acquisition area, representing the quality of reconstruction. Therefore, the quality of the 4D-STEM data acquired within the target acquisition area of ​​the sample can be determined by analyzing the additive diffraction pattern.

[0109] To more scientifically and quantitatively assess data quality, the quality of the obtained additive diffraction pattern can be evaluated by analyzing the position of the band axis center. Changes in the band axis center position can reflect potential offsets, distortions, and other issues that may have occurred during data acquisition. Therefore, after obtaining the additive diffraction pattern, refer to... Figure 3A As shown, the following analysis steps may also be included:

[0110] S301, determine the center position of the band axis of the summed diffraction pattern, and calculate the position offset of the center position of the band axis relative to the preset reference center position;

[0111] The zone axis center of the additive diffraction pattern represents the center point corresponding to the crystallographic zone axis direction in the pattern, indicating the projected position of the zone axis parallel to the electron beam direction in diffraction space. This zone axis center position can be obtained by manually calibrating the displayed additive diffraction pattern directly through the interactive interface. For example, users can trigger the zone axis center calibration operation using the zone axis center setting function provided in the interactive interface. Using the selected calibration tool, users can click or drag on the diffraction pattern to select the zone axis center. The interactive interface can display the calibration results in real time, such as the coordinates of the zone axis center.

[0112] This reference center position represents a theoretical or experimental benchmark point used relative to the actual calibration axis center position. It can be determined experimentally, such as by the center position of the electron beam on the detector without a sample, or by standard calibration values. For example, Figure 3B The example shows the reference center position and auxiliary lines for the summation diffraction pattern. The center symbol "+" in the small figure indicates the reference center position.

[0113] The position offset represents the distance on a two-dimensional plane between the center position of the band axis of the summation diffraction pattern and the preset reference center position. In this step, the position offset is used to measure the degree of deviation between the center of the band axis of the summation diffraction pattern and the ideal reference position, indicating the amount by which the projection axis of the sample crystal deviates from its crystal main band axis.

[0114] Assume the coordinates of the preset reference center position in the two-dimensional coordinate system are (x... ref ,y ref The coordinates of the center position of the zone axis of the summation diffraction pattern are (x... c ,yc The position offset d can be calculated using the Euclidean distance formula:

[0115] S302, if the position offset is greater than a set threshold, determine that the quality of the 4D-STEM data stored in the newly added file does not meet the requirements, and delete the newly added file from the specified storage location.

[0116] In 4D-STEM experiments, ideally, the zone axis center of the summative diffraction pattern is located near a pre-defined reference center. A large positional shift indicates potential instability during data acquisition, such as electron beam drift, minute sample movement, or localized distortion within the sample. This can lead to a general shift in the diffraction pattern spots, manifested as a systematic shift in the zone axis center. A large positional shift may imply significant errors or uncertainties in the data, negatively impacting accurate reconstruction. For example, when analyzing the microstructure of crystals, a shift in the zone axis center can cause deviations in measurements of crystal orientation, strain, and other parameters.

[0117] Based on this, after obtaining the positional offset of the band axis center relative to the reference center, this embodiment determines whether the quality of the acquired data meets the requirements by comparing this positional offset with a set threshold. This set threshold represents the maximum acceptable degree of deviation between the center of the band axis of the summed diffraction pattern and the ideal reference position. It can be a value equal to the radius of the summed diffraction pattern, or a multiple of that radius, where the multiple is greater than 0 and less than 1.

[0118] If the position offset exceeds the set threshold, it indicates that the deviation of the band axis center of the summation diffraction pattern from the reference center exceeds the acceptable range. This indicates that there are unstable factors in the data acquisition process, which affects the quality of the diffraction pattern and may lead to the inability to accurately extract the microstructure information of the sample. Therefore, when the position offset exceeds the set threshold, it is determined that the quality of the newly added file of 4D-STEM data does not meet the requirements, and the newly added file is automatically deleted from the specified storage location. This reduces storage space pressure and improves the efficiency of data management by deleting low-quality data.

[0119] Meanwhile, for new files whose data quality does not meet the requirements, this information can be fed back to the data acquisition process so that N scanning points in the target acquisition area of ​​the sample corresponding to the new file can be re-scanned and transmitted, and the 4D-STEM dataset corresponding to the target acquisition area can be re-acquired.

[0120] In this embodiment, by analyzing the center position of the band axis of the summation diffraction pattern and evaluating the deviation of this center position from the reference center position, 4D-STEM data quality is provided as a scientific and quantitative method for data quality assessment. The positional offset, as a specific numerical value, can intuitively reflect the degree of deviation of the data from the ideal state during acquisition, making the judgment of data quality more accurate and objective. Furthermore, when the positional offset exceeds a set threshold, the newly added file is automatically deleted, achieving automatic filtering and cleaning of low-quality data. This avoids low-quality data interfering with subsequent data processing and analysis, improving data processing efficiency and storage resource utilization.

[0121] iCOM (Integrated Center of Mass) calculation is an important method in 4D-STEM data analysis, used to visualize the spatial distribution of physical fields such as electric field, strain, and thickness gradient inside a sample. Its core idea is to calculate the centroid offset of the diffraction disk at each scanning point of the electron beam, integrate these offsets, and finally generate a two-dimensional image that reflects the local physical properties of the sample.

[0122] In some embodiments, the physical information contained in 4D-STEM data under different material systems and experimental conditions is complex and diverse. iCOM calculations can infer internal structural changes or strain distributions by calculating changes in the centroid position, providing an additional analytical dimension for data quality assessment. Therefore, to more accurately determine whether the acquired 4D-STEM data meets the requirements, the quality of the acquired 4D-STEM data can also be assessed using iCOM calculation results. Based on this, see [link to relevant documentation]. Figure 4A An exemplary flowchart of an iCOM image acquisition step is shown, the calculation of which can be performed in parallel with the acquisition process of the summation diffraction pattern. This real-time 4D-STEM data quality assessment method may also include the following iCOM calculation steps:

[0123] S401, in response to the iCOM image acquisition command, determine the centroid offset of the diffraction pattern for each of the N scan points;

[0124] S402, the obtained N centroid offsets are integrated using the centroid integral map iCOM algorithm to obtain the iCOM map of the target acquisition area corresponding to the 4D-STEM data, and displayed on the interactive interface.

[0125] iCOM image acquisition commands can be manually triggered by researchers through an interactive interface, such as by selecting to execute the iCOM image acquisition function in the interactive interface, or they can be automatically issued by a preset automated script or program when specific conditions are met, such as automatically triggering iCOM image generation after the addition diffraction pattern is generated.

[0126] The centroid offset of the diffraction pattern at each scanning point represents the deflection of the electron beam due to changes in the internal electric field, strain, or thickness of the sample. Under thin sample and weak scattering conditions, the centroid offset of the diffraction disk is proportional to the projection of the potential gradient in the direction of the electron beam (i.e., the projected potential gradient).

[0127] The calculation of the iCOM map can be achieved through the following steps: For N scanning points within the target acquisition area, calculate the centroid (COM) of the diffraction pattern at each scanning point to obtain the centroid offset, and then perform spatial integration on the centroid offset. The two are related as follows: In other words, the gradient of iCOM intensity is equal to the COM intensity. The iCOM intensity is approximately proportional to the electrostatic potential and / or thickness of the sample atoms, therefore iCOM can directly reflect the elemental mass distribution and / or thickness distribution inside the sample.

[0128] Regarding the calculation logic of obtaining the iCOM image by integrating the centroid offset using the centroid integral image iCOM algorithm as described in this embodiment, you can refer to the iDPC image calculation logic described in the article "Phasecontrast STEM for thin samples: Integrated differential phase contrast" published in the journal ScienceDirect, or the article "Phase contrast scanning transmission electronmicroscopy imaging oflight and heavy atoms at the limit of contrast and resolution" published on the Nature.com platform. The iCOM image is a multi-pixel ideal version of the iDPC image, and the calculation principles and logic of the two are the same.

[0129] The iCOM map of the target acquisition area corresponding to the obtained 4D-STEM data can be used to evaluate the data quality of the acquired 4D-STEM data. See [link to relevant documentation]. Figure 4BAn example of an additive diffraction pattern and its corresponding iCOM image is shown. The iCOM image can be used to preview the real-space structure of a sample and reflect the 4D-STEM data quality of a local region of the sample. The iCOM image can be used together with the additive diffraction pattern to judge the quality of the same 4D-STEM data. By comparing and analyzing the iCOM image with the additive diffraction pattern, the consistency of the data can be further verified, and the reliability of the evaluation results can be enhanced.

[0130] Based on iCOM images, the integrity of the sample's real-space structure can be analyzed. For example, the presence of obvious damage or an unsuitable focal length indicates potential quality issues with the acquired 4D-STEM data. Data quality can also be assessed based on the clarity and contrast of the iCOM image. A clear iCOM image indicates that minimal noise or distortion was introduced during data acquisition and processing. A high-contrast iCOM image makes it easier to identify the characteristics of the material's microstructure, thus helping to determine if the data meets requirements. Furthermore, the identifiability of features in the iCOM image can also be used to evaluate data quality. The iCOM image should clearly display the characteristics of the material's microstructure, such as strain concentration areas and orientation changes. If these features are difficult to identify or are blurry, the quality of the acquired 4D-STEM data may not meet requirements.

[0131] In this embodiment of the disclosure, by introducing an iCOM image to preview the real-space structure of the sample, the 4D-STEM data quality of a local area of ​​the sample can be reflected. As an additional means of data quality assessment, the reliability of the judgment results is increased by comparing and analyzing the iCOM image with the summation diffraction pattern.

[0132] Given the crucial value of 4D-STEM data in materials science, condensed matter physics, and other fields, to improve the accuracy and efficiency of 4D-STEM data analysis and avoid processing errors and resource waste caused by file format issues, a preliminary file quality screening can be performed on newly added files before reading the data. This ensures accurate and rapid acquisition of 4D-STEM data that meets the requirements. Specifically, the aforementioned real-time 4D-STEM data quality assessment method also includes the following screening steps a1-a3 based on file format information before reading the data from newly added files:

[0133] a1 retrieves the format information of the newly added file;

[0134] The file format information is used to represent information such as the file type, content characteristics, file organization, and storage method. In this embodiment, the format information is used to perform preliminary and rapid filtering of the data quality of the newly added file. This achieves efficient pre-filtering without parsing the file content, preventing invalid data from flowing into subsequent processing flows. The format information may include at least one or more of the following: file name, file extension, and file size.

[0135] Taking file format information, including file name and file extension, as an example, 4D-STEM data can be organized into single files or combined files for storage. Therefore, in the process of obtaining file format information, if the newly added file is an independent single file, the full file name and file extension of the newly added file can be obtained; if the newly added file is a combined file including multiple subsidiary files, the main file can be identified according to predefined rules, and the file extension of the main file in the newly added file can be obtained.

[0136] In this context, an independent single file refers to the detector directly saving the 4D dataset (two-dimensional scan position × two-dimensional diffraction pattern) from each scan as a single composite file. This means that all scan points and diffraction patterns within the target acquisition area of ​​the sample are stored in multiple datasets within the same file. A combined file containing multiple subsidiary files indicates that the 4D-STEM dataset is split into multiple related files for storage, such as a main file + data blocks. The main file records the mapping relationship between scan point positions and sub-files, while the sub-files store the actual diffraction data of the scan points.

[0137] a2, if the format information conforms to the set format standard, read the 4D-STEM data stored in the newly added file; wherein, the set format standard includes at least the set file extension;

[0138] Setting format standards ensures that files can be correctly identified and processed; for example, processing only specific file types (such as .hdf5, 4D-STEM data files with specific suffixes, etc.). In this embodiment, the format standard may include at least a list of valid file suffixes, which stores legal suffixes. In this embodiment, valid suffixes may include at least .hdf5, .xml, etc. After extracting the file suffix of a newly added file, the extracted file suffix can be matched with the file suffixes in the format standard to quickly determine whether the file meets the processing requirements.

[0139] a3. If the format information does not conform to the set format standard, continue to monitor the file addition event;

[0140] If the format information of a newly added file does not conform to the set format standard, the system will not immediately attempt to read the data stored in the new file. Instead, it will continue to monitor the file and wait for the next file addition event, thus avoiding errors or anomalies caused by processing files that do not conform to the format standard. Furthermore, for newly added files that do not conform to the set format standard, a format anomaly alarm message can be triggered to prompt the user to pay attention to and handle the new file promptly.

[0141] In this embodiment of the disclosure, since 4D-STEM data is complex and critical, file filtering based on file format information can ensure that the read file data format is standardized, thus guaranteeing data quality. For files that do not meet the format standards, there is no need to perform subsequent complex reading and processing operations, avoiding unnecessary consumption of computing resources and wasted time. This allows the system to focus more on processing files that meet the requirements, speeding up data processing, improving data processing efficiency, and effectively enhancing the accuracy and reliability of data processing.

[0142] Corresponding to the aforementioned embodiments of the real-time 4D-STEM data quality assessment method, see [link to relevant documentation]. Figure 5 As shown, this application also provides an embodiment of a data processing apparatus, the apparatus comprising:

[0143] The data reading module 501 is used to respond to a file addition event in a specified storage location and read the 4D-STEM data stored in the newly added file, which is the data collected by scanning N scanning points in the sample target acquisition area.

[0144] The diffraction pattern overlay module 502 is used to overlay the diffraction patterns of each scanning point in the 4D-STEM data of N scanning points to obtain the summation diffraction pattern corresponding to the newly added file; wherein, the diffraction pattern of each scanning point is used to represent the diffraction intensity distribution in reciprocal space after the electron beam interacts with the sample at that scanning point;

[0145] The interactive display module 503 is used to display the summation diffraction pattern on the interactive interface. The summation diffraction pattern is used to determine whether the quality of the 4D-STEM data stored in the newly added file meets the requirements.

[0146] In some embodiments, the diffraction pattern at each scan point corresponds to a diffraction intensity distribution matrix, where each element represents a diffraction intensity value recorded in the reciprocal lattice space; the diffraction pattern overlay module is specifically used for:

[0147] According to the coordinate order of the N scanning points, the diffraction intensity distribution matrix of each scanning point is obtained sequentially;

[0148] The diffraction intensity distribution matrices of the N scanning points are added together according to the positions of the matrix elements to obtain the summation distribution matrix;

[0149] Based on the summation distribution matrix, a visual representation of the summation diffraction pattern is obtained.

[0150] In some embodiments, the apparatus further includes:

[0151] Determine the center position of the band axis of the summed diffraction pattern, and calculate the positional offset of the center position of the band axis relative to a preset reference center position;

[0152] If the position offset is greater than a set threshold, it is determined that the quality of the 4D-STEM data stored in the newly added file does not meet the requirements, and the newly added file is deleted from the specified storage location.

[0153] In some embodiments, the apparatus further includes:

[0154] In response to the command to acquire the centroid integral image iCOM, the centroid offset of the diffraction pattern for each of the N scanning points is determined.

[0155] The obtained N centroid offsets are integrated using the centroid integral map iCOM algorithm to obtain the iCOM map of the target acquisition area corresponding to the 4D-STEM data, and then displayed on the interactive interface.

[0156] In some embodiments, the apparatus further includes, prior to reading 4D-STEM data from the newly added file:

[0157] The format acquisition module is used to obtain the format information of newly added files;

[0158] The judgment module is used to continue monitoring the file addition event if the format information does not conform to the set format standard; wherein the set format standard includes at least a set file extension; and if the format information conforms to the set format standard, read the 4D-STEM data stored in the newly added file.

[0159] In some embodiments, the format acquisition module is specifically used for:

[0160] If the newly added file is a single, independent file, obtain the full filename and file extension of the newly added file;

[0161] In the case where the newly added file is a combination file including multiple subsidiary files, the main file is identified according to predefined rules, and the file extension of the main file in the newly added file is obtained.

[0162] The specific implementation process of the functions and roles of each unit in the above device can be found in the implementation process of the corresponding steps in the above method, and will not be repeated here.

[0163] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this application according to actual needs. Those skilled in the art can understand and implement this without any inventive effort.

[0164] This application also provides an electronic device, the structural schematic diagram of which is shown below. Figure 6 As shown, the electronic device 600 includes at least one processor 601, a memory 602, and a bus 603. At least one processor 601 is electrically connected to the memory 602. The memory 602 is configured to store at least one computer-executable instruction, and the processor 601 is configured to execute the at least one computer-executable instruction, thereby performing the steps of any 4D-STEM data quality real-time judgment method provided in any embodiment or optional implementation of this application.

[0165] Furthermore, the processor 601 can be an FPGA (Field-Programmable Gate Array) or other devices with logic processing capabilities, such as an MCU (Microcontroller Unit) or a CPU (Central Processing Unit).

[0166] This application also provides another readable storage medium storing a computer program that, when executed by a processor, implements the steps of any of the 4D-STEM data quality real-time judgment methods provided in any of the embodiments or optional implementations of this application.

[0167] The readable storage media provided in this application include, but are not limited to, any type of disk (including floppy disk, hard disk, optical disk, CD-ROM, and magneto-optical disk), ROM (Read-Only Memory), RAM (Random Access Memory), EPROM (Erasable Programmable Read-Only Memory), EEPROM (Electrically Erasable Programmable Read-Only Memory), flash memory, magnetic cards, or optical cards. In other words, the readable storage media includes any medium by which a device (e.g., a computer) stores or transmits information in a readable form.

[0168] Thus, specific embodiments of the subject matter have been described. Other embodiments are within the scope of the appended claims. In some cases, the actions recited in the claims may be performed in a different order and still achieve the desired result. Furthermore, the processes depicted in the drawings are not necessarily shown in a specific order or sequence to achieve the desired result. In some implementations, multitasking and parallel processing may be advantageous.

[0169] While this specification contains numerous specific implementation details, these should not be construed as limiting the scope of any invention or the scope of the claims, but rather are primarily intended to describe features of specific embodiments of a particular invention. Certain features described in the various embodiments herein may also be implemented in combination in a single embodiment. Conversely, various features described in a single embodiment may also be implemented separately in various embodiments or in any suitable sub-combination. Furthermore, while features may function in certain combinations as described above and even initially claimed in this way, one or more features from a claimed combination may be removed from that combination in some cases, and a claimed combination may refer to a sub-combination or a variation thereof.

[0170] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A method for real-time assessment of 4D-STEM data quality, characterized in that, The method includes: In response to a file addition event in a specified storage location, read the 4D-STEM data stored in the new file, which is the data acquired by scanning N scanning points within the target area of ​​the sample. The diffraction patterns of each scanning point in the 4D-STEM data of N scanning points are superimposed to obtain the summation diffraction pattern corresponding to the newly added file; wherein, the diffraction pattern of each scanning point is used to represent the diffraction intensity distribution in reciprocal space after the electron beam interacts with the sample at that scanning point; The summation diffraction pattern is displayed on the interactive interface. The summation diffraction pattern is used to determine whether the quality of the 4D-STEM data stored in the newly added file meets the requirements. After obtaining the summation diffraction pattern, the method further includes: Determine the center position of the band axis of the summed diffraction pattern, and calculate the positional offset of the center position of the band axis relative to a preset reference center position; If the position offset is greater than a set threshold, it is determined that the quality of the 4D-STEM data stored in the newly added file does not meet the requirements, and the newly added file is deleted from the specified storage location.

2. The method according to claim 1, characterized in that, The diffraction pattern of each scan point corresponds to a diffraction intensity distribution matrix, where each element represents the diffraction intensity value recorded in the reciprocal lattice space; the superposition of the diffraction patterns of each scan point in the 4D-STEM data of N scan points includes: According to the coordinate order of the N scanning points, the diffraction intensity distribution matrix of each scanning point is obtained sequentially; The diffraction intensity distribution matrices of the N scanning points are added together according to the positions of the matrix elements to obtain the summation distribution matrix; Based on the summation distribution matrix, a visual representation of the summation diffraction pattern is obtained.

3. The method according to claim 1, characterized in that, The method further includes: In response to the command to acquire the centroid integral image iCOM, the centroid offset of the diffraction pattern for each of the N scanning points is determined. The obtained N centroid offsets are integrated using the centroid integral map iCOM algorithm to obtain the iCOM map of the target acquisition area corresponding to the 4D-STEM data, and then displayed on the interactive interface.

4. The method according to claim 1, characterized in that, The method further includes, prior to reading 4D-STEM data from the newly added file: Get the format information of the newly added file; If the format information does not conform to the set format standard, the monitoring of the file addition event continues; wherein, the set format standard includes at least the set file extension; If the format information conforms to the set format standard, read the 4D-STEM data stored in the newly added file.

5. The method according to claim 4, characterized in that, The step of obtaining the format information of the newly added file includes: If the newly added file is a single, independent file, obtain the full filename and file extension of the newly added file; In the case where the newly added file is a combination file including multiple subsidiary files, the main file is identified according to predefined rules, and the file extension of the main file in the newly added file is obtained.

6. A data processing apparatus, characterized in that, The device includes: The data reading module is used to respond to a file addition event in a specified storage location and read the 4D-STEM data stored in the newly added file, which is the data collected by scanning N scanning points within the sample target acquisition area. The diffraction pattern overlay module is used to overlay the diffraction patterns of each scanning point in the 4D-STEM data of N scanning points to obtain the summation diffraction pattern corresponding to the newly added file; wherein, the diffraction pattern of each scanning point is used to represent the diffraction intensity distribution in reciprocal space after the electron beam interacts with the sample at that scanning point; The interactive module is used to display the summation diffraction pattern on the interactive interface. The summation diffraction pattern is used to determine whether the quality of the 4D-STEM data stored in the newly added file meets the requirements. After obtaining the summation diffraction pattern, the apparatus further includes: Determine the center position of the band axis of the summed diffraction pattern, and calculate the positional offset of the center position of the band axis relative to a preset reference center position; If the position offset is greater than a set threshold, it is determined that the quality of the 4D-STEM data stored in the newly added file does not meet the requirements, and the newly added file is deleted from the specified storage location.

7. The apparatus according to claim 6, characterized in that, The diffraction pattern at each scan point corresponds to a diffraction intensity distribution matrix, where each element represents the diffraction intensity value recorded in the reciprocal lattice space; the diffraction pattern overlay module is specifically used for: According to the coordinate order of the N scanning points, the diffraction intensity distribution matrix of each scanning point is obtained sequentially; The diffraction intensity distribution matrices of the N scanning points are added together according to the positions of the matrix elements to obtain the summation distribution matrix; Based on the summation distribution matrix, a visual representation of the summation diffraction pattern is obtained.

8. An electronic device, characterized in that, include: Memory, processor; The memory is used to store computer programs; The processor is configured to invoke the computer program to implement the method as described in any one of claims 1-5.

9. A readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the method as described in any one of claims 1-5.

Images