A method for fast realization of crystallographic orientation imaging in a transmission electron microscope

Abstract

The application discloses a method for quickly realizing crystallographic orientation imaging in a transmission electron microscope, and comprises the following steps: collecting 3-5 sample inclination under the first 8-10 diffraction ring conical scanning dark field images by a transmission electron microscope; carrying out drift correction on the dark field images under different sample inclinations, and then binarizing all the dark field images; building an incident electron beam conical scanning model, simulating electron diffraction patterns of any orientation under different sample inclinations, and constructing an electron diffraction pattern database; reconstructing the diffraction pattern of each pixel in the dark field image under the same sample inclination, and calibrating the orientation of all the pixels; and combining the data of multiple sample inclinations to complete the orientation calibration of all the pixels. The application realizes the quick characterization of grain orientation based on the transmission electron microscope conical scanning dark field imaging technology and the crystallographic orientation calibration algorithm, and is suitable for the crystallographic orientation characterization of crystal materials under the transmission electron microscope.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of material microcrystallography orientation characterization, and particularly relates to a method for quickly realizing crystallography orientation imaging in a transmission electron microscope. BACKGROUND

[0002] Materials are the cornerstone of social progress, and crystal materials play a crucial role in the field of materials today. For crystal materials, the orientation of the crystal grains has a crucial influence on the performance of the material. Therefore, it is necessary to characterize the grain orientation of the crystal material. Traditional two-dimensional crystallography orientation characterization methods, such as X-ray diffraction technology (XRD), electron backscatter diffraction technology (EBSD), etc., have gradually failed to meet the analysis needs of material researchers. In recent years, the development of nanomaterials has put forward higher resolution requirements for two-dimensional crystallography orientation characterization methods. For this reason, foreign scholars have developed precession electron diffraction technology (PED) in a transmission electron microscope, which can weaken the dynamic effect of electron diffraction, and its spatial resolution and angular resolution are about 2-3 nm and 1°, respectively (Microscopy and Microanalysis 5 (2021), 1102-1112). However, it takes 20-40 minutes to collect a 400x400 pixel orientation map using this technology (Zeitschrift Fur Kristallographie-Crystalline Materials 225 (2010), 103-109), and a nanobeam is used, which causes relatively large irradiation damage to the sample. Similarly, transmission Kikuchi diffraction technology (TKD) can also be used to calibrate the crystallographic orientation of nanomaterials (Journal of Microscopy 245 (2012), 245-251), and it takes about 40 minutes to collect a complete orientation map using this technology (Journal of Microscopy 267 (2017), 318-329). Compared with the EBSD technology, the TKD technology has a smaller area of the transmission electron beam interacting with the sample, so the sensitivity of the transmission Kikuchi pattern to crystal defects is reduced. However, when the density of crystal defects in the sample is relatively high, the obtained Kikuchi pattern is still relatively blurred, which is not conducive to calibration. In addition, the transmission Kikuchi pattern is also sensitive to the thickness of the sample, and only a suitable thickness can obtain a clear Kikuchi pattern.

[0003] In summary, the existing crystallographic orientation characterization technology can characterize the two-dimensional orientation of nanocrystalline grains, but the application range of the current two-dimensional crystallographic orientation characterization technology is still limited. Secondly, there is no crystallographic orientation characterization technology with a wide application range and high spatial resolution in China at present. Therefore, it is necessary to develop a characterization technology with a small irradiation dose and high spatial resolution, which can quickly characterize the crystallographic orientation and geometric morphology of nanomaterials, which will provide important technical support for the research of high-performance nanomaterials. SUMMARY

[0004] The purpose of the present application is to provide a system and method for quickly realizing two-dimensional crystallographic orientation imaging in a transmission electron microscope. In a transmission electron microscope equipped with an incident electron beam cone scanning controller, the method for realizing two-dimensional crystallographic orientation imaging of nanomaterials can quickly characterize the two-dimensional crystallographic orientation of nanomaterials with high spatial resolution, and can obtain the two-dimensional crystallographic orientation and morphology information of nanomaterials.

[0005] The present application is realized by the following technical solutions:

[0006] In one aspect, the present application provides a method for quickly realizing crystallographic orientation imaging in a transmission electron microscope, comprising the following steps: collecting 3-5 sample inclination under the first 8-10 diffraction ring cone scanning dark field images by transmission electron microscopy; after drift correction of the dark field images under different sample inclinations, binarizing all the dark field images; building an incident electron beam cone scanning model, simulating electron diffraction patterns of any orientation under different sample inclinations, and constructing an electron diffraction pattern database; reconstructing the diffraction pattern of each pixel in the dark field image under the same sample inclination and calibrating the orientation of all pixels; and combining the data of multiple sample inclinations to complete the orientation calibration of all pixels.

[0007] In some embodiments, the scanning dark field image comprises: collecting dark field images corresponding to diffraction spots in the first 8-10 diffraction rings under 3-5 sample inclinations using a cone scanning dark field imaging technology; such as the dark field images corresponding to the diffraction spots on the {111} ring to the {420} ring of a face-centered cubic crystal, the incident electron beam rotates around the principal axis every 2° or 1° on the same diffraction ring, that is, 180 or 360 dark field images are collected on each diffraction ring, and one complete data collection only takes 3-5 minutes.

[0008] In some embodiments, the drift correction of the dark field images under different sample tilt angles includes: correcting the drift of the bright field images under different sample tilt angles by using the feature point method, then correcting the drift of all bright field images under the same sample tilt angle, and indirectly correcting the drift of the dark field images based on the drift values of the bright field images; assuming that the drift values of 10 dark field images are approximately linear, every 10 dark field images are collected with a bright field image, then the drift values of the 10 dark field images between every two bright field images are calculated by interpolation method and applied to the dark field images. When binarizing all dark field images, a machine learning algorithm can be used to binarize all dark field images; specifically, a suitable machine learning model can be trained using a U-Net network and all dark field images are binarized.

[0009] In some embodiments, constructing the electron diffraction pattern database includes: simulating the diffraction pattern of any orientation according to the principle of incident electron beam cone scanning, reciprocal space and Ewald sphere, and recording the position of the diffraction spot. In a specific example, the Ewald sphere is established in the reciprocal space according to Bragg's law, where the deflection of the incident electron beam means the movement of the Ewald sphere center position, and the movement of the Ewald sphere center position is calculated according to the deflection of the incident electron beam in the real space; secondly, the reciprocal lattice of the material in the initial orientation (Euler angle is (0, 0, 0)) in the reciprocal space is calculated according to the crystal structure of the material in the real space, such as the lattice type of face-centered cubic crystal in the reciprocal space is body-centered cubic, and the corresponding reciprocal lattice is calculated according to the crystallographic orientation and the tilt angle of the sample; it is generally believed that the reciprocal lattice point intersecting with the Ewald sphere satisfies Bragg diffraction, so only the position of the reciprocal lattice point intersecting with the Ewald sphere and entering the objective aperture needs to be recorded; for example, a certain diffraction spot is in the 1st diffraction ring, and when the incident electron beam rotates 10° around the optical axis, the diffraction spot enters the objective aperture, so its position is (1, 10); the reciprocal lattice point intersecting with the Ewald sphere needs to be found again and the position of the reciprocal lattice point entering the objective aperture is recorded every time the incident electron beam is deflected, and the above process is repeated to simulate the diffraction pattern of the material with a specific crystal structure under any crystal orientation and any sample tilt angle considering the deflection of the incident electron beam.

[0010] In some embodiments, the orientation of all pixels under the same sample tilt angle is calibrated, including: extracting the intensity of the same pixel point in all images under the same sample tilt angle as the basis for crystallographic orientation calibration. The orientation of all pixels under the same sample tilt angle is calibrated, including: using the template matching method to calculate the correlation coefficient of the diffraction pattern and each diffraction pattern in the database, and considering that the orientation corresponding to the diffraction pattern with the highest correlation coefficient is the orientation corresponding to the pixel.

[0011] In some embodiments, the orientation calibration of all pixels in combination with the data of sample inclination includes: first calibrating the data of the first sample inclination, retaining the calibration results that meet the conditions, and the pixels without signal or unable to accurately determine the orientation will participate in the calibration of the second sample inclination; the calibration of the second sample inclination: for the pixels with signal but not meeting the conditions, the orientations with higher correlation coefficients screened out in the calibration of the first sample inclination are used as the database for the calibration of the second sample inclination, and the calibration results that meet the conditions are retained, and the pixels without signal or unable to accurately determine the orientation will participate in the calibration of the third sample inclination; the above process is repeated to complete the calibration of the third sample inclination. Or the data under different sample inclinations are coupled into a whole, and the coupled data are used as the basis for calibrating the orientation and matching the simulated database, and the orientation corresponding to the template with the highest correlation coefficient is considered as the calibration result.

[0012] In another aspect, the application provides a system for realizing two-dimensional crystallographic orientation imaging in a transmission electron microscope, comprising a memory and a processor, the memory stores a computer program, and the processor executes the computer program to realize the method for quickly realizing crystallographic orientation imaging in a transmission electron microscope according to any one of the above embodiments.

[0013] Compared with the prior art, the application has the following advantages and beneficial effects:

[0014] (1) High-quality conical scanning dark-field images can be obtained in a transmission electron microscope equipped with an incident electron beam conical scanning controller;

[0015] (2) Only 3-5 minutes are needed to collect complete data;

[0016] (3) Machine learning algorithms can be combined to better segment dark-field images;

[0017] (4) The crystallographic orientation map of a material can be obtained through high-quality conical scanning dark-field images;

[0018] (5) The incident electron beam is a parallel beam, which will not cause serious irradiation damage to light metals;

[0019] (6) A reasonable method is used to correct the drift of the sample, so that the obtained crystallographic orientation map is more accurate, and the spatial resolution can reach 1 nm;

[0020] (7) The 180° uncertainty in diffraction pattern calibration can be eliminated by combining dark-field images under multiple sample inclinations, and the dynamic effect can be avoided;

[0021] (8) The operation process is simple, and human intervention is less. BRIEF DESCRIPTION OF DRAWINGS

[0022] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings in the embodiments will be briefly introduced as follows. It should be understood that the following drawings only show some of the embodiments of the present application, and therefore should not be considered as limiting the scope. For those skilled in the art, other related drawings can also be obtained without creative labor on the basis of these drawings.

[0023] Figure 1 A flowchart of a method for quickly realizing crystallographic orientation imaging in a transmission electron microscope provided by some embodiments of the present application;

[0024] Figure 2 A schematic diagram of a diffraction pattern of a randomly selected pixel and a corresponding orientation after calibration in some embodiments of the present application, wherein (a) is a diffraction pattern reconstructed from a dark field image collected by an actual experiment, and (b) is a simulated diffraction pattern after calibration corresponding to the orientation.

[0025] Figure 3 A bright field image and an orientation map provided by some embodiments of the present application, wherein (a) is a bright field image when the sample inclination angle is equal to 0 degrees and the incident electron beam is not deflected, and the sample coordinate system and the grain number are shown in the figure, (b) is an orientation map obtained according to the calibration result, colored along the rolling direction (Z) of the sample, and (c) is a schematic diagram of the lattices of the five grains shown in the figure in three-dimensional space and the corresponding Euler angles. DETAILED DESCRIPTION

[0026] In order to make the purpose, technical solutions and advantages of the embodiments of the present application more clear, the technical solutions in the embodiments of the present application will be described clearly and completely in combination with the drawings in the embodiments of the present application. Obviously, the described embodiments are some of the embodiments of the present application, but not all the embodiments.

[0027] In the description of the present application, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer" and the like indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, or the orientation or positional relationship when the product of the present application is usually placed, and are only for the convenience of describing the present application and simplifying the description, and therefore cannot be understood as indicating or implying that the device or element must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as limiting the present application.

[0028] In addition, the terms "horizontal", "vertical" and the like in the description of the present application do not mean that the components must be absolutely horizontal or vertical, but can be slightly inclined. For example, "horizontal" only means that its direction is relatively more horizontal than "vertical", and does not mean that the structure must be completely horizontal, but can be slightly inclined.

[0029] In the description of the present application, it also needs to be explained that, unless explicitly defined and limited, if the terms "arrange", "install", "connect", "connect" appear, they should be understood broadly, for example, can be fixedly connected, can also be detachably connected, or integrally connected; can be mechanically connected, can also be electrically connected; can be directly connected, can also be indirectly connected through an intermediate medium, can be the communication inside two elements. For those skilled in the art, the specific meaning of the above terms in the present application can be understood according to the specific circumstances.

[0030] The terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or modules is not limited to the listed steps or modules, but can optionally include steps or modules not listed, or can optionally include other steps or modules inherent to the process, method, product or device.

[0031] In one aspect, referring to Figure 1 The embodiment of the present application provides a method for quickly realizing crystallographic orientation imaging in a transmission electron microscope, mainly comprising the following steps:

[0032] S1, collecting 3-5 sample inclination under the first 8-10 diffraction ring conical scanning dark field image. In S1, in some examples, the dark field image corresponding to the diffraction spot in the first 8-10 diffraction ring under 3-5 sample inclination can be collected by using the conical scanning dark field imaging technology, that is, the incident electron beam is deflected to make the diffraction beam pass through the center of the dark field image. Specifically, the dark field image corresponding to the diffraction spot on the 8 diffraction rings (such as face-centered cubic crystal {111} ring to {420} ring) under multiple sample inclinations is collected by using the conical scanning dark field imaging technology, the incident electron beam on the same diffraction ring rotates around the principal axis every 2° or 1°, that is, 180 or 360 dark field images are collected on each diffraction ring, and one complete data collection needs 3-5 minutes.

[0033] S2, binarize all dark field images after drift correction of dark field images of different sample inclination angles. In S2, in some examples, interpolation method can be used to correct the drift of dark field images, and the drift of feature points is determined to correct the image; specifically, the drift of bright field images under different sample inclination angles is first corrected by using the feature point method, and then the drift of all bright field images under the same sample inclination angle is corrected; assuming that the drift values of 10 or less dark field images are approximately linear, every 10 dark field images are collected with a bright field image, and then the drift values of 10 dark field images between every two bright field images are calculated by interpolation method and applied to the dark field images. The drift of bright field images is corrected by using the feature point method, and the drift of feature points is determined to correct the image. In S2, in some specific examples, machine learning algorithm can be used to binarize all dark field images; specifically, a suitable machine learning model can be trained using U-Net network to binarize all dark field images.

[0034] S3, build an incident electron beam cone scanning model to simulate electron diffraction patterns of any orientation under different sample inclination angles, and construct an electron diffraction pattern database. In S3, more than 520,000 orientations of diffraction patterns are simulated and the positions of diffraction spots are recorded according to the principles of incident electron beam cone scanning, reciprocal space and Ewald sphere. In a specific example, an Ewald sphere is established in reciprocal space according to Bragg's law, wherein the deflection of the incident electron beam means the movement of the Ewald sphere center position, and the movement of the Ewald sphere center position is calculated according to the deflection of the incident electron beam in real space; secondly, the reciprocal lattice of the initial orientation (Euler angle (0, 0, 0)) of the material in real space is calculated according to the crystal structure of the material in real space, such as the lattice type of face-centered cubic crystal in reciprocal space is body-centered cubic, and the corresponding reciprocal lattice is calculated according to the crystallographic orientation and the inclination angle of the sample; it is generally considered that the reciprocal lattice points intersecting with the Ewald sphere satisfy Bragg diffraction, so only the positions of the reciprocal lattice points intersecting with the Ewald sphere and entering the objective aperture need to be recorded; for example, a certain diffraction spot is in the first diffraction ring, and when the incident electron beam rotates around the optical axis by 10°, the diffraction spot enters the objective aperture, so its position is (1, 10); the reciprocal lattice point intersecting with the Ewald sphere needs to be found again and the position of the reciprocal lattice point entering the objective aperture is recorded every time the incident electron beam is deflected, and the above process is repeated to simulate the diffraction patterns of materials with a specific crystal structure under any crystal orientation and any sample inclination angle considering the deflection of the incident electron beam.

[0035] S4, reconstructing the diffraction pattern of each pixel in the dark-field image at the same sample tilt and indexing the orientation of all the pixels with signal. In S4, the intensity of the same pixel in all the images at the same sample tilt is extracted as the basis for crystallographic indexing, and then the intensity values are represented in the form of a diffraction pattern. Indexing the orientation of all the pixels at the same sample tilt can specifically include: using a two-dimensional correlation coefficient function or a cosine similarity function to calculate the correlation coefficient of the diffraction pattern extracted from S4 and each diffraction pattern in the database, and considering that the orientation corresponding to the diffraction pattern with the highest correlation coefficient is the orientation corresponding to the pixel, and the pixel with a maximum correlation coefficient lower than a certain value is considered to have no corresponding orientation; specifically, using a two-dimensional correlation coefficient function or a cosine similarity function to calculate the correlation coefficient of the reconstructed diffraction data matrix and each matrix in the simulated database. Please refer to Figure 2 , which is the diffraction pattern of a randomly selected pixel and the conical scan diffraction pattern corresponding to the indexed orientation. The two-dimensional correlation coefficient function is as follows:

[0036]

[0037] In the formula, A and B are the experimental diffraction pattern matrix and the simulated database matrix respectively, and the size of the two matrices is consistent, m x n, and are the mean values of matrices A and B respectively.

[0038] The cosine similarity function is as follows:

[0039]

[0040] In the formula, C and D are the results of vectorization of matrices A and B respectively, and |C| and |D| are the modules of vectors C and D.

[0041] S5, combine the orientation data of different sample tilt angles, and complete the orientation calibration of all pixels. Some grains do not have Bragg diffraction or have Bragg diffraction with relatively low intensity at a single sample tilt angle, which is not enough to calibrate the correct orientation. Therefore, the data at the first sample tilt angle are calibrated first, and the calibration results that meet the conditions are retained. The pixels without signals or unable to accurately determine the orientation will participate in the calibration of the second sample tilt angle. The second sample tilt angle calibration: for the pixels with signals but not meeting the conditions, the orientations with relatively high correlation coefficients screened out during the calibration of the first sample tilt angle are used as the database for the calibration of the second sample tilt angle, and the calibration results that meet the conditions are retained. The pixels without signals or unable to accurately determine the orientation will participate in the calibration of the third sample tilt angle. The above process is repeated to complete the calibration of the third sample tilt angle. Alternatively, the data at different sample tilt angles are coupled into a whole, and the coupled data are used as the basis for calibrating the orientation and matching the simulated database, and the orientation corresponding to the template with the highest correlation coefficient is considered as the calibration result. The data at multiple sample tilt angles are combined to ensure that the orientations of all grains in the same region can be correctly calibrated, and the 180° uncertainty of the crystal orientation can also be eliminated.

[0042] In another aspect, an embodiment of the present application provides a system for quickly realizing crystallographic orientation imaging in a transmission electron microscope, comprising a memory and a processor, the memory storing a computer program, and the processor executing the computer program to realize the method for quickly realizing crystallographic orientation imaging in a transmission electron microscope according to any one of the above embodiments.

[0043] The embodiment also provides a computer storage medium storing a computer program, and the computer program is loaded by a processing module to realize the method for quickly realizing crystallographic orientation imaging in a transmission electron microscope according to any one of the above embodiments.

[0044] The above is only a preferred embodiment of the present application, and does not limit the present application in any way. Any simple modification or equivalent change to the above embodiment according to the technical essence of the present application falls within the protection scope of the present application.

Claims

1. A method for rapidly achieving crystallographic orientation imaging in a transmission electron microscope, characterized in that: The following steps are involved: Conical scanning dark field images of the first 8 to 10 diffraction rings at 3 to 5 sample tilt angles were collected using a transmission electron microscope; After drift correction of dark field images at different sample inclination angles, all dark field images are binarized; Build an incident electron beam cone scanning model to simulate electron diffraction patterns of arbitrary orientations at different sample inclination angles and construct an electron diffraction pattern database; Reconstruct the diffraction pattern of each pixel in the dark field image at the same sample tilt angle and calibrate the orientation of all pixels with signals; Combined with the sample inclination data, the orientation calibration of all pixels is completed; Refer to the principles of incident electron beam conical scanning, reciprocal space and Ewald sphere to simulate the diffraction pattern of arbitrary orientation and record the position of the diffraction spot; Reconstructing the diffraction pattern for each pixel in the dark field image involves extracting the intensity of the same pixel in all images at the same sample tilt angle as the basis for crystallographic orientation calibration. Calibrating the orientation of all pixels at the same sample tilt angle involves calculating the correlation coefficient between the diffraction pattern and each diffraction pattern in the database using a template matching method, and assuming that the orientation corresponding to the diffraction pattern with the highest correlation coefficient is the orientation corresponding to the pixel. The method of completing the orientation calibration of all pixels in combination with the sample tilt data includes: first calibrating the tilt data of the first sample, retaining the calibration results that meet the conditions, and pixels with no signal or whose orientation cannot be accurately determined will participate in the calibration of the second sample tilt; calibration of the second sample tilt: for pixels with signals but not meeting the conditions, the orientation with a relatively high correlation coefficient screened out during the first sample tilt calibration is used as the database for the second sample tilt calibration, and retaining the calibration results that meet the conditions, and pixels with no signal or whose orientation cannot be accurately determined will participate in the calibration of the third sample tilt; repeating the above process to complete the calibration of the third sample tilt; Alternatively, the data at different sample inclination angles are coupled into a whole, and the coupled data are used as the basis for calibrating the orientation to match it with the simulated database, and the orientation corresponding to the template with the highest correlation coefficient is considered to be the calibration result.

2. The method for rapidly achieving crystallographic orientation imaging in a transmission electron microscope according to claim 1, characterized in that: The scanning dark field image includes: using the cone scanning dark field imaging technology to collect dark field images corresponding to the diffraction spots in the first 8 to 10 diffraction rings at 3 to 5 sample inclination angles.

3. The method for rapidly achieving crystallographic orientation imaging in a transmission electron microscope according to claim 1, characterized in that: The drift correction of dark field images at different sample inclination angles includes: correcting the drift of bright field images at different sample inclination angles using a feature point method, then correcting the drift of all bright field images at the same sample inclination angle, and indirectly correcting the drift of the dark field image based on the drift value of the bright field image.

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