Apparatus and method for analyzing crystal structure

Abstract

Provided are an apparatus and method for analyzing a crystal structure. The apparatus for analyzing a crystal structure may comprise: an electron backscatter diffraction (EBSD) data acquisition module for obtaining EBSD data for a solid material; an image generation module for generating a shape of the solid material as a first image comprising a plurality of pixels; a clustering module for clustering the plurality of pixels by using the EBSD data so that the first image comprises a plurality of clusters each representing a first index of a crystal with a first color; an image processing module for generating a second image by processing the first image so that a second index associated with the first index is displayed as a figure overlapping the plurality of clusters; and a rendering module for rendering the second image on a display area.

Description

Crystal structure analysis device and method

[0001] Cross-citation with related applications

[0002] This application claims the benefit of priority to Korean Patent Application No. 10-2023-0074914, filed June 12, 2023, the entire contents of which are incorporated herein by reference.

[0003] The disclosure relates to a device and method for analyzing a crystal structure.

[0004] EBSD (Electron Backscatter Diffraction) is a scanning electron microscope (SEM) that detects electrons (backscattered electrons) reflected when accelerated electrons are injected into a sample, allowing analysis of the material's orientation. In other words, EBSD can analyze the crystal structure of the examined area using the diffraction patterns measured from each crystal. For example, a computer system can control the position of the electron beam, record the patterns generated in the area of ​​the specimen where the electron beam resides through a camera, and automatically analyze the recorded patterns to derive crystallographic information for that area of ​​the specimen.

[0005] The task to be solved is to provide a crystal structure analysis device and method that can effectively analyze the crystal structure of a solid material from EBSD data for the solid material.

[0006] According to one embodiment, a crystal structure analysis device may include: an EBSD (Electron Backscatter Diffraction) data acquisition module for acquiring EBSD data for a solid material; an image generation module for generating a first image including a plurality of pixels representing a shape of the solid material; a clustering module for performing clustering on the plurality of pixels using the EBSD data so that the first image includes a plurality of clusters each representing a first indicator of a crystal in a first color; an image processing module for generating a second image by processing the first image so that a second indicator associated with the first indicator is displayed as a shape overlapping on the plurality of clusters; and a rendering module for rendering the second image on a display area.

[0007] In some embodiments, the first indicator is defined as a value of a sine square function for an acute angle between a first vector and a second vector, wherein the first vector comprises a one-way vector of the decision at a pixel location corresponding to the decision on the first image, and the second vector comprises a vector pointing from the center of the entire particle toward the pixel location in an outward direction.

[0008] In some embodiments, the first color may include at least one of an RGB color, an HSL color, an HSV color, a CMYK color, and a grayscale color.

[0009] In some embodiments, the display area includes a first display area and a second display area positioned adjacent to one side of the first display area, and the rendering module can render the second image on the first display area and render a first color bar that matches a value of the first indicator with the first color on the second display area.

[0010] In some embodiments, the first vector may be defined in a three-dimensional space defined by a first axis, a second axis, and a third axis that are perpendicular to each other, and the second indicator may be defined as a direction in which the first vector is projected onto a plane formed by the first axis and the second axis.

[0011] In some embodiments, the shape is an arrow-shaped shape, and the second indicator may be displayed so as to overlap on the plurality of clusters in the direction of the arrow head.

[0012] In some embodiments, the image processing module may process the first image to represent a third indicator associated with the second indicator as a second color within the shape.

[0013] In some embodiments, the third indicator may be defined as an angle formed by the first vector with a plane formed by the first axis and the second axis.

[0014] In some embodiments, the second color may include at least one of an RGB color, an HSL color, an HSV color, a CMYK color, and a grayscale color.

[0015] In some embodiments, the display area includes a first display area and a third display area positioned adjacent to one side of the first display area, and the rendering module can render the second image in the first display area and render a second color bar in the third display area that matches the value of the third indicator with the second color to display it.

[0016] In some embodiments, the first indicator is defined as a Degree of Alignment (DoA) value calculated at a pixel location corresponding to the decision on the first image, and the DoA value can be calculated according to the following mathematical formula:

[0017]

[0018] Here, L is the major axis vector of the crystal corresponding to the pixel position, S is the minor axis vector of the crystal corresponding to the pixel position, and C is the value of the cosine function for L and the vector pointing from the center of the entire particle to the pixel position in the outer direction.

[0019] In some embodiments, the first color may include at least one of an RGB color, an HSL color, an HSV color, a CMYK color, and a grayscale color.

[0020] In some embodiments, the display area includes a first display area and a second display area positioned adjacent to one side of the first display area, and the rendering module can render the second image in the first display area and render a first color bar that matches the value of the first indicator with the first color in the third display area.

[0021] In some embodiments, the second indicator is defined as a major axis vector of a decision corresponding to the pixel location, the shape is an arrow-shaped shape, and the second indicator can be displayed to overlap on the plurality of clusters in the direction of the arrow head.

[0022] In one embodiment, a method for analyzing a crystal structure may include: obtaining EBSD data for a solid material; generating a first image including a plurality of pixels representing a shape of the solid material; performing clustering on the plurality of pixels using the EBSD data such that the first image includes a plurality of clusters each representing a first indicator of the crystal in a first color; processing the first image such that a second indicator associated with the first indicator is displayed as a shape overlapping the plurality of clusters to generate a second image; and rendering the second image on a display area.

[0023] In some embodiments, the first indicator is defined as a value of a sine square function for an acute angle between a first vector and a second vector, wherein the first vector comprises a one-way vector of the decision at a pixel location corresponding to the decision on the first image, and the second vector comprises a vector pointing from the center of the entire particle toward the pixel location in an outward direction.

[0024] In some embodiments, the first vector may be defined in a three-dimensional space defined by a first axis, a second axis, and a third axis that are perpendicular to each other, and the second indicator may be defined as a direction in which the first vector is projected onto a plane formed by the first axis and the second axis.

[0025] In some embodiments, the step of generating the second image may include the step of processing the first image to represent a third indicator associated with the second indicator in a second color within the shape to generate the second image.

[0026] In some embodiments, the first indicator is defined as a Degree of Alignment (DoA) value calculated at a pixel location corresponding to the decision on the first image, and the DoA value can be calculated according to the following mathematical formula:

[0027]

[0028] Here, L is the major axis vector of the crystal corresponding to the pixel position, S is the minor axis vector of the crystal corresponding to the pixel position, and C is the value of the cosine function for L and the vector pointing from the center of the entire particle to the pixel position in the outer direction.

[0029] In some embodiments, the second indicator is defined as a major axis vector of a decision corresponding to the pixel location, the shape is an arrow-shaped shape, and the second indicator can be displayed so as to overlap on the plurality of clusters in the direction of the arrow head.

[0030] In one embodiment, a computer-readable medium may be recorded with a program for causing a computer, comprising a processor executing a program or instructions stored in a memory or storage device, to perform the steps of: obtaining EBSD data for a solid material; generating a first image comprising a plurality of pixels representing a shape of the solid material; performing clustering on the plurality of pixels using the EBSD data such that the first image comprises a plurality of clusters each representing a first indicator of the crystal in a first color; processing the first image such that a second indicator associated with the first indicator is displayed as a shape overlapping the plurality of clusters to generate a second image; and rendering the second image on a display area.

[0031] According to embodiments, by extracting and visualizing information on the distribution of crystal orientations across all particles from data collected from an EBSD system, the crystal structure of a solid material can be effectively analyzed from EBSD data. Furthermore, since crystal orientations are visually represented by clusters, any desired crystal plane change is immediately reflected visually, allowing for rapid exploration of crystal orientation connectivity patterns in a typical computing environment.

[0032] FIG. 1 is a block diagram illustrating a crystal structure analysis device according to one embodiment.

[0033] FIGS. 2 to 4 are drawings for explaining an implementation example of a crystal structure analysis device according to one embodiment.

[0034] FIGS. 5 and 6 are drawings for explaining an implementation example of a crystal structure analysis device according to one embodiment.

[0035] Figure 7 is a flowchart illustrating a crystal structure analysis method according to one embodiment.

[0036] FIG. 8 is a drawing for explaining an implementation example of a crystal structure analysis device according to one embodiment.

[0037] FIGS. 9 to 13 are drawings for explaining implementation examples of a crystal structure analysis device according to one embodiment.

[0038] FIG. 14 is a diagram illustrating a computing device according to one embodiment.

[0039] Below, with reference to the attached drawings, embodiments of the present invention are described in detail so that those skilled in the art can easily implement the present invention. However, the present invention may be implemented in various different forms and is not limited to the embodiments described herein. In addition, in the drawings, parts irrelevant to the description are omitted for clarity of description, and similar parts are designated with similar reference numerals throughout the specification.

[0040] Throughout the specification and claims, whenever a part is referred to as "comprising" a component, this does not exclude other components, but rather includes other components, unless otherwise stated. Terms including ordinal numbers, such as "first," "second," etc., may be used to describe various components, but these components are not limited by these terms. These terms are used solely to distinguish one component from another.

[0041] Terms such as “part,” “unit,” and “module” described in the specification may mean a unit capable of processing at least one function or operation described in the specification, which may be implemented by hardware or a circuit, software, or a combination of hardware or a circuit and software.

[0042] FIG. 1 is a block diagram illustrating a crystal structure analysis device according to one embodiment.

[0043] Referring to FIG. 1, a crystal structure analysis device (10) according to one embodiment can analyze the crystal structure of a solid material. The crystal structure analysis device (10) can extract and visualize information on how crystal directions are distributed across all particles from data collected from an EBSD system. In some embodiments, the crystal structure analysis device (10) may be a server that services a web application, which is software that runs on a web browser. Accordingly, the crystal structure analysis device (10) can enable users to easily analyze the crystal structure of a solid material using only a web browser without having to install separate software on their computers. However, the scope of the present invention is not limited thereto, and the functions provided by the crystal structure analysis device (10) may be implemented as various arbitrary forms of software.

[0044] The crystal structure analysis device (10) may include an EBSD data acquisition module (110), an image generation module (120), a clustering module (130), an image processing module (140), and a rendering module (150).

[0045] The EBSD data acquisition module (110) can acquire EBSD data for a solid material. The EBSD data can include spatially linked crystallographic orientation and phase information, and the EBSD data acquisition module (10) can acquire data in various formats collected from an external EBSD system. For example, the EBSD data can be a file generated to follow the CSV (Comma Separated Values) format as two-dimensional data distinguished by a delimiter such as a comma. As another example, the EBSD data can be in the form of a compressed file composed of a collection of multiple CSV files. As yet another example, the EBSD data can be data that has undergone data cleaning in specific software (e.g., AZtecCrystal) that processes data collected using EBSD.

[0046] The image generation module (120) can generate a first image of the shape of a solid material that is the subject of crystal structure analysis. Here, the first image may be in the form of a pixel image including a plurality of pixels. For example, the image generation module (120) can generate the first image as a two-dimensional image that can be displayed on a display device electrically connected to the crystal structure analysis device (10).

[0047] The clustering module (130) may perform clustering on a plurality of pixels included in the first image using EBSD data acquired by the EBSD data acquisition module (110). In some embodiments, the clustering module (130) may adopt a density-based clustering algorithm to perform clustering. The clustering module (130) may adopt, for example, DBSCAN (Density-based spatial clustering of applications with noise). Unlike algorithms that perform clustering using the distance between clusters, the density-based clustering algorithm may operate by clustering areas where data points are closely clustered and thus have a high density. In particular, the clustering module (130) may use the EBSD data to cause the first image to include a plurality of clusters, each cluster representing a first indicator of the crystal in a first color.

[0048] For example, EBSD data may include data on crystal orientations of crystal grains. The data on crystal orientations may be a plurality of crystal orientation data collected for each crystal unit of a predetermined size that forms the solid material to be analyzed. Here, the crystal unit is not determined to have a specific size, but may be a unit having a predetermined size that can correspond to at least one included in the first image, taking into account the resolution according to the environment that the crystal structure analysis device according to the embodiments can display. The clustering module (130) may perform clustering on a plurality of pixels expressing the first image using a plurality of angle data.

[0049] The image processing module (140) can generate a second image representing the result of clustering performed by the clustering module (130). That is, the image processing module (140) can process the first image so that the first image generated by the image generation module (120) is displayed in different colors for each cluster, or can process the first image so that the second indicator associated with the first indicator is displayed in a shape overlapping multiple clusters and output the second image. In some embodiments, the color can include at least one of an RGB color, an HSL color, an HSV color, a CMYK color, and a grayscale color. An RGB color is a color expressed using red, green, and blue, and an HSL (or HSB) color can be a color expressed using hue, saturation, and lightness (or brightness). HSV color is a color expressed using Hue, Saturation, and Value, and CMYK color can be a color expressed using Cyan, Magenta, Yellow, and Black.

[0050] The rendering module (150) can render the second image generated by the image processing module (140) onto a display area provided on the display device. Accordingly, by expressing the second image in different colors for each pixel or cluster, or by expressing some indicator of the crystal as a shape overlapping the cluster, the user can visualize the crystal characteristics of the entire particle at a glance, thereby effectively analyzing the crystal structure from EBSD data collected in an unintuitive manner.

[0051] In some embodiments, the first index may be defined as the value of the sine square function for the acute angle between the first vector and the second vector. Here, the first vector may include a one-way vector of the crystal at a pixel location corresponding to the crystal on the first image, and the second vector may include a vector pointing from the center of the entire particle to the pixel location in an outward direction. Accordingly, the clustering module (130) may perform clustering so that each cluster included in the first image may represent the first index with a first color. At this time, the first color may be calculated for each pixel forming each cluster, and thus, one cluster may be represented with a gradient color. Here, the one-way vector of the crystal may be a vector corresponding to one of the lattice vectors of the crystal. In some embodiments, the lattice vector of the crystal may include the a-axis, the b-axis, and the c-axis, and the one-way vector of the crystal may include a vector corresponding to the c-axis of the crystal.

[0052] In some embodiments, the first color may include at least one of an RGB color, an HSL color, an HSV color, a CMYK color, and a grayscale color. An RGB color may be a color expressed using red, green, and blue, an HSL (or HSB) color may be a color expressed using hue, saturation, and lightness (or brightness), an HSV color may be a color expressed using hue, saturation, and value, and a CMYK color may be a color expressed using cyan, magenta, yellow, and black.

[0053] Meanwhile, the first vector is defined in a three-dimensional space defined by a first axis (e.g., x-axis), a second axis (e.g., y-axis), and a third axis (e.g., z-axis) that are perpendicular to each other, and the second indicator can be defined as a direction in which the first vector is projected onto a plane formed by the first and second axes. Accordingly, the image processing module (140) can process the first image to generate a second image so that the second indicator is displayed as a shape that overlaps each cluster included in the first image. In some embodiments, the shape may include an arrow-shaped shape, and the second indicator may be displayed so as to overlap on a plurality of clusters in the direction of the arrow head.

[0054] Additionally, the image processing module (140) may process the first image to display a third indicator associated with the second indicator in a second color within the shape. Here, the third indicator may be defined as the angle formed by the first vector with the plane formed by the first axis and the second axis.

[0055] In some embodiments, the second color may include at least one of an RGB color, an HSL color, an HSV color, a CMYK color, and a grayscale color. An RGB color is a color expressed using red, green, and blue, an HSL (or HSB) color may be a color expressed using hue, saturation, and lightness (or brightness), an HSV color may be a color expressed using hue, saturation, and value, and a CMYK color may be a color expressed using cyan, magenta, yellow, and black.

[0056] Accordingly, by extracting and visualizing information on how crystal orientations are distributed across all particles from data collected from the EBSD system, the crystal structure of a solid material can be effectively analyzed from EBSD data on the solid material. In addition, even when the user changes the desired crystal plane, the desired crystal orientation pattern can be easily explored based on the crystal plane. For example, a certain crystal orientation connection pattern that can be formed between adjacent clusters can be used as a meaningful analysis result, but analyzing such crystal orientation connection pattern from EBSD data provided as two-dimensional data requires a lot of computing resources and a considerable amount of work time. In contrast, according to the present embodiment, when the user changes the desired crystal plane while the crystal orientation is visually expressed by cluster, the result is immediately reflected visually, so that the connection pattern of crystal orientation can be explored quickly in a general computing environment.

[0057] FIGS. 2 to 4 are drawings for explaining an implementation example of a crystal structure analysis device according to one embodiment. FIG. 2 illustrates a second image (IMG1) expressed by a rendering module (150), and FIGS. 3 and 4 are drawings for explaining definitions of the first to third indices.

[0058] Referring to FIGS. 2 to 4 together, the second image (IMG1) represents the entire particle, with the center of the particle being displayed at its center. In FIG. 2, the center of the particle is represented as a circle with a black border, but the scope of the present invention is not limited thereto.

[0059] The first indicator is the first vector ( ) and the second vector ( ) can be defined as the value of the sine square function for the acute angle between the first vector ( ) is the crystal direction at a pixel location among the crystals expressed in the first image, for example, it can be a vector corresponding to one direction vector of the crystal, the c-axis. And the second vector ( ) may be a vector pointing from the center of the entire particle to the corresponding pixel position in the outer direction of the particle. Accordingly, for each pixel forming each cluster, a value corresponding to the first indicator (e.g., a real value between 0 and 1) may be displayed in a first color.

[0060] The second indicator is the first vector ( ) can be defined as the direction projected onto the plane formed by the first axis (e.g., x-axis) and the second axis (e.g., y-axis). Accordingly, the first vector ( ) can be displayed by overlapping a shape (e.g., an arrow) on the cluster that represents the direction projected onto the plane formed by the first axis (e.g., the x-axis) and the second axis (e.g., the y-axis).

[0061] The third indicator is the first vector ( ) can be defined as the angle formed by the plane formed by the first axis (e.g., the x-axis) and the second axis (e.g., the y-axis). Accordingly, the interior of the shape displayed by overlapping on each cluster can be displayed by using a second color corresponding to the angle value (e.g., a value expressed as -90 degrees to 90 degrees). Here, the closer the angle value (or the absolute value of the angle value) is to 0, the closer one axis of the crystal (e.g., the c-axis) can be to a shape lying on the screen of the display area where the second image (IMG1) is displayed, and the closer it is to 90 degrees or -90 degrees, the closer one axis of the crystal (e.g., the c-axis) can be to a shape perpendicular to the screen of the display area where the second image (IMG1) is displayed.

[0062] In this way, the first to third indices as described can be visually identified for the entire particle, thereby effectively analyzing the crystal structure from EBSD data collected in an unintuitive form.

[0063] Referring back to FIG. 1, in some embodiments, the first metric may be defined as a Degree of Alignment (DoA) value calculated at a pixel location corresponding to a decision on the first image. Here, the DoA value may be calculated according to the following mathematical formula:

[0064]

[0065] Here, L may be the major axis vector of the decision corresponding to the pixel position, S may be the minor axis vector of the decision corresponding to the pixel position, and C may be the value of a cosine function for L and a vector pointing from the center of the entire particle to the outer edge toward the pixel position. Accordingly, the clustering module (130) may perform clustering so that each cluster included in the first image may represent the first index with the first color.

[0066] In some embodiments, the first color may include at least one of an RGB color, an HSL color, an HSV color, a CMYK color, and a grayscale color. An RGB color may be a color expressed using red, green, and blue, an HSL (or HSB) color may be a color expressed using hue, saturation, and lightness (or brightness), an HSV color may be a color expressed using hue, saturation, and value, and a CMYK color may be a color expressed using cyan, magenta, yellow, and black.

[0067] Meanwhile, the second indicator may be defined as a major axis vector of a decision corresponding to a pixel position. Accordingly, the image processing module (140) may process the first image to generate a second image so that the second indicator is displayed as a shape that overlaps each cluster included in the first image. In some embodiments, the shape may include an arrow-shaped shape, and the second indicator may be displayed to overlap a plurality of clusters in the direction of the arrow head. Here, the direction of the arrow head may correspond to the direction in which the major axis vector is directed, and the length of the arrow may be determined as a value that has a correlation according to the length of the major axis.

[0068] Accordingly, by extracting and visualizing information on how crystal orientations are distributed across all particles from data collected from the EBSD system, the crystal structure of a solid material can be effectively analyzed from EBSD data on the solid material. In addition, even when the user changes the desired crystal plane, the desired crystal orientation pattern can be easily explored based on the crystal plane. For example, a certain crystal orientation connection pattern that can be formed between adjacent clusters can be used as a meaningful analysis result, but analyzing such crystal orientation connection pattern from EBSD data provided as two-dimensional data requires a lot of computing resources and a considerable amount of work time. In contrast, according to the present embodiment, when the user changes the desired crystal plane while the crystal orientation is visually expressed by cluster, the result is immediately reflected visually, so that the connection pattern of crystal orientation can be explored quickly in a general computing environment.

[0069] FIGS. 5 and 6 are drawings for explaining an implementation example of a crystal structure analysis device according to one embodiment. FIG. 5 illustrates a second image (IMG2) expressed by a rendering module (150), and FIG. 6 is a drawing for explaining the definitions of the first and second indices.

[0070] Referring to FIGS. 5 and 6 together, the second image (IMG1) represents the entire particle, with the center of the particle being displayed at its center. In FIG. 5, the center of the particle is represented as a circle with a black border, but the scope of the present invention is not limited thereto.

[0071] The first index may be defined as a DoA (Degree of Alignment) value calculated at a pixel location corresponding to a decision on the first image. Here, the DoA value may be calculated according to the following mathematical formula.

[0072]

[0073] Here, L is the major axis vector of the decision corresponding to the pixel position ( ), S is the short-axis vector of the decision corresponding to the pixel position, C is the vector pointing to the pixel position from the center of the entire particle to the outer direction with L ( ) can be the value of the cosine function for the DoA. DoA is the value when the long-shaped particle is oriented from the center to the outside, that is, the long axis direction is the vector ( ) is aligned with the direction of the vector ( ), and if the long-shaped particle is cultured vertically, i.e., the long axis direction is vector ( ) can be set to a value of 0 if it is perpendicular to the direction of the .

[0074] The second indicator is the major axis vector of the decision corresponding to the pixel position ( ) can be defined as. Accordingly, the direction of the arrow head displayed to overlap on the cluster is the major axis vector ( ) can correspond to the direction in which the arrow is facing, and the length of the arrow can be determined as a value that is related to the length of the major axis (for example, a value proportional to the length of the major axis).

[0075] In some embodiments, a third metric may be additionally calculated from the first metric. The third metric represents the DoA weighted by the area of ​​the decision, and may be referred to as "Area-weighted DoA," and may be calculated according to the following mathematical formula.

[0076]

[0077] Here, i is the index of the decision, and A i can represent the area of ​​the ith decision. This value can be a value that quantifies the overall geometric alignment of the primary particle within the given secondary particle by reflecting the area.

[0078] In this way, the first to third indices as described can be visually identified for the entire particle, thereby effectively analyzing the crystal structure from EBSD data collected in an unintuitive form.

[0079] Figure 7 is a flowchart illustrating a crystal structure analysis method according to one embodiment.

[0080] Referring to FIG. 7, a crystal structure analysis method according to an embodiment may include a step of obtaining EBSD data for a solid material (S701), a step of generating a first image including a plurality of pixels representing the shape of the solid material (S702), a step of performing clustering on the plurality of pixels using the EBSD data so that the first image includes a plurality of clusters each representing a first indicator of the crystal in a first color (S703), a step of processing the first image so that a second indicator associated with the first indicator is displayed as a shape overlapping on the plurality of clusters so as to generate a second image (S704), and a step of rendering the second image in a display area (S705).

[0081] For further details on the above method, reference may be made to the description given above with respect to FIGS. 1 to 6 and the description given below with respect to FIGS. 8 to 13, and therefore, redundant descriptions thereof will be omitted here.

[0082] FIG. 8 is a drawing for explaining an implementation example of a crystal structure analysis device according to one embodiment.

[0083] Referring to FIG. 8 and FIG. 2 together, the rendering module (150) can render the second image generated by the image processing module (140) to the display area (30) provided in the display device. Here, the display area (30) includes a first display area (31), a second display area (32), and a third display area (33), and the second display area (32) or the third display area (33) can be arranged adjacent to one side of the first display area (30). The rendering module (150) can render the second image to the first display area (31) and render a first color bar that matches the value of the first indicator with the first color to display it, to the second display area. Accordingly, convenience can be provided so that the user can visually compare the entire particles before and after clustering. In addition, the rendering module (150) can render the second image on the first display area (31) and render the second color bar that matches the value of the third indicator with the second color on the third display area. Meanwhile, referring to FIG. 8 and FIG. 5 together, the rendering module (150) can render the second image on the first display area (31) and render the first color bar that matches the value of the first indicator with the first color on the third display area.

[0084] This screen layout configuration allows for visualization of various indices of crystal structure across the entire particle, effectively enabling analysis of crystal structures from EBSD data collected in an unintuitive manner.

[0085] FIGS. 9 to 13 are drawings for explaining implementation examples of a crystal structure analysis device according to one embodiment.

[0086] Referring to FIGS. 9 to 13, the crystal structure analysis device according to one embodiment can output, in addition to the visual screen described above, an angle histogram as exemplarily illustrated in FIG. 9, a DoA histogram as exemplarily illustrated in FIG. 10, a DoA crystal histogram as exemplarily illustrated in FIG. 11, an aspect ratio histogram as exemplarily illustrated in FIG. 12, and a diameter histogram as exemplarily illustrated in FIG. 13.

[0087] The angle histogram in Fig. 9 is the first vector ( ) and the second vector ( ) shows a plot showing the value of the angle between the first vector ( ) and the second vector ( ) represents the probability for the angle between the two. The DoA histogram in Fig. 10 represents the count values ​​for the DoA values. The DoA decision histogram in Fig. 11 represents the first vector ( ) and the second vector ( ) is represented as a DoA decision. The aspect ratio histogram in Fig. 12 shows the count values ​​for the aspect ratio. The diameter histogram in Fig. 13 shows a plot calculated for the diameter of a circle having the same area as the decision. Through this analysis, the first vector ( ) and the second vector ( ) are related to a certain property, analysis can be performed by linking the distribution of the angular values ​​with the corresponding property, or the analysis can be utilized for parameterization of the product. For example, if the movement of particles in the radial direction and the direction of crystals are related, analysis can be performed by linking the movement of particles and the direction of crystals. In this regard, the visualized data or statistical distributions exemplified in FIGS. 9 to 13 can be utilized to provide convenience in quantitative analysis.

[0088] FIG. 14 is a diagram illustrating a computing device according to one embodiment.

[0089] Referring to FIG. 14, the crystal structure analysis device and method according to the embodiments can be implemented using a computing device (50).

[0090] The computing device (50) may include at least one of a processor (510), a memory (530), a user interface input device (540), a user interface output device (550), and a storage device (560) that communicate via a bus (520). The computing device (50) may also include a network interface (570) electrically connected to a network (40). The network interface (570) may transmit or receive signals to or from other entities via the network (40).

[0091] The processor (510) may be implemented in various types such as an MCU (Micro Controller Unit), an AP (Application Processor), a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), an NPU (Neural Processing Unit), etc., and may be any semiconductor device that executes instructions stored in a memory (530) or a storage device (560). The processor (510) may be configured to implement the functions and methods described above with respect to FIGS. 1 to 13.

[0092] The memory (530) and storage device (560) may include various types of volatile or non-volatile storage media. For example, the memory may include read-only memory (ROM) (531) and random access memory (RAM) (532). In the present embodiment, the memory (530) may be located inside or outside the processor (510), and the memory (530) may be connected to the processor (510) through various known means.

[0093] In some embodiments, at least some components or functions of the crystal structure analysis devices and methods according to the embodiments may be implemented as a program or software running on a computing device (50), and the program or software may be stored on a computer-readable medium.

[0094] In some embodiments, at least some components or functions of the crystal structure analysis devices and methods according to the embodiments may be implemented using hardware or circuitry of the computing device (50), or may be implemented as separate hardware or circuitry that can be electrically connected to the computing device (50).

[0095] According to the embodiments described thus far, by extracting and visualizing information on the distribution of crystal orientations across all particles from data collected from an EBSD system, the crystal structure of a solid material can be effectively analyzed from EBSD data. Furthermore, since crystal orientations are visually represented by clusters, any desired crystal plane change is immediately reflected visually, allowing for rapid exploration of crystal orientation connectivity patterns in a typical computing environment.

[0096] Although the embodiments of the present invention have been described in detail above, the scope of the present invention is not limited thereto, and various modifications and improvements made by a person of ordinary skill in the art to which the present invention pertains using the basic concept of the present invention defined in the following claims also fall within the scope of the present invention.

Claims

1. EBSD data acquisition module that acquires EBSD (Electron Backscatter Diffraction) data for solid materials; An image generation module for generating a shape of the solid material as a first image including a plurality of pixels; A clustering module that performs clustering on the plurality of pixels using the EBSD data so that the first image includes a plurality of clusters each representing a first indicator of the decision with a first color; An image processing module that processes the first image to generate a second image so that a second indicator associated with the first indicator is displayed as a shape overlapping on the plurality of clusters; and A rendering module that renders the second image to a display area. Crystal structure analysis device.

2. In paragraph 1, The above first indicator is defined as the value of the sine square function for the acute angle between the first vector and the second vector, The first vector includes a one-way vector of the decision at a pixel location corresponding to the decision on the first image, A crystal structure analysis device, wherein the second vector includes a vector pointing from the center of the entire particle to the outer edge toward the pixel position.

3. In paragraph 2, A crystal structure analysis device, wherein the first color includes at least one of RGB color, HSL color, HSV color, CMYK color, and grayscale color.

4. In paragraph 2, The display area includes a first display area and a second display area arranged adjacent to one side of the first display area, The above rendering module, Rendering the second image in the first display area, A crystal structure analysis device that renders a first color bar that matches the value of the first indicator and the first color to the second display area.

5. In paragraph 2, The above first vector is determined in a three-dimensional space defined by a first axis, a second axis, and a third axis that are perpendicular to each other, A crystal structure analysis device, wherein the second indicator is defined as a direction in which the first vector is projected onto a plane formed by the first axis and the second axis.

6. In paragraph 5, A crystal structure analysis device, wherein the above figure is an arrow-shaped figure, and the second indicator is displayed so as to overlap on the plurality of clusters in the direction of the arrow head.

7. In paragraph 5, A crystal structure analysis device, wherein the image processing module processes the first image to display a third indicator associated with the second indicator as a second color within the shape.

8. In paragraph 7, A crystal structure analysis device, wherein the third indicator is defined as the angle formed by the first vector and the plane formed by the first axis and the second axis.

9. In paragraph 7, A crystal structure analysis device, wherein the second color includes at least one of RGB color, HSL color, HSV color, CMYK color, and grayscale color.

10. In paragraph 7, The display area includes a first display area and a third display area arranged adjacent to one side of the first display area, The above rendering module, Rendering the second image in the first display area, A crystal structure analysis device that renders a second color bar that matches the value of the third indicator and the second color in the third display area.

11. In paragraph 1, The above first indicator is defined as a DoA (Degree of Alignment) value calculated at a pixel location corresponding to the decision on the first image, The above DoA value is calculated according to the following mathematical formula, crystal structure analysis device: Here, L is the major axis vector of the crystal corresponding to the pixel position, S is the minor axis vector of the crystal corresponding to the pixel position, and C is the value of the cosine function for L and the vector pointing from the center of the entire particle to the pixel position in the outer direction.

12. In paragraph 11, A crystal structure analysis device, wherein the first color includes at least one of RGB color, HSL color, HSV color, CMYK color, and grayscale color.

13. In paragraph 11, The display area includes a first display area and a second display area arranged adjacent to one side of the first display area, The above rendering module, Rendering the second image in the first display area, A crystal structure analysis device that renders a first color bar that matches the value of the first indicator and the first color in the third display area.

14. In paragraph 11, The second indicator is defined as a long axis vector of a decision corresponding to the pixel location, The above figure is an arrow-shaped figure, A crystal structure analysis device, wherein the second indicator is displayed so as to overlap on the plurality of clusters in the direction of the arrow head.

15. Step of obtaining EBSD data for solid materials; A step of generating a shape of the solid material as a first image including a plurality of pixels; A step of performing clustering on the plurality of pixels using the EBSD data such that the first image includes a plurality of clusters each representing a first indicator of the decision with a first color; A step of processing the first image to generate a second image so that a second indicator associated with the first indicator is displayed as a shape overlapping on the plurality of clusters; and comprising a step of rendering the second image to a display area; Methods for analyzing crystal structures.

16. In paragraph 15, The above first indicator is defined as the value of the sine square function for the acute angle between the first vector and the second vector, The first vector includes a one-way vector of the decision at a pixel location corresponding to the decision on the first image, A crystal structure analysis method, wherein the second vector includes a vector pointing from the center of the entire particle to the outer edge of the pixel position.

17. In paragraph 16, The above first vector is determined in a three-dimensional space defined by a first axis, a second axis, and a third axis that are perpendicular to each other, A crystal structure analysis method, wherein the second indicator is defined as a direction in which the first vector is projected onto a plane formed by the first axis and the second axis.

18. In paragraph 17, The step of generating the second image is: A method for analyzing a crystal structure, comprising the step of generating a second image by processing the first image to represent a third indicator associated with the second indicator in a second color within the shape.

19. In paragraph 18, The above first indicator is defined as a DoA (Degree of Alignment) value calculated at a pixel location corresponding to the decision on the first image, The above DoA value is calculated according to the following mathematical formula, crystal structure analysis method: Here, L is the major axis vector of the crystal corresponding to the pixel position, S is the minor axis vector of the crystal corresponding to the pixel position, and C is the value of the cosine function for L and the vector pointing from the center of the entire particle to the pixel position in the outer direction.

20. In paragraph 19, The second indicator is defined as a long axis vector of a decision corresponding to the pixel location, The above figure is an arrow-shaped figure, A crystal structure analysis method, wherein the second indicator is displayed so as to overlap on the plurality of clusters in the direction of the arrow head.

21. In a computer including a processor that executes programs or instructions stored in memory or storage devices, Step of obtaining EBSD data for solid materials; A step of generating a shape of the solid material as a first image including a plurality of pixels; A step of performing clustering on the plurality of pixels using the EBSD data such that the first image includes a plurality of clusters each representing a first indicator of the decision with a first color; A step of processing the first image to generate a second image so that a second indicator associated with the first indicator is displayed as a shape overlapping on the plurality of clusters; and A program for executing a step of rendering the above second image to the display area has been written. A computer-readable medium.

Images