Crystal structure analysis apparatus and method

Abstract

A crystal structure analysis apparatus and method are provided. The crystal structure analysis apparatus may include: an EBSD (Electron Backscatter Diffraction) data acquisition module for acquiring EBSD data for a solid material; an image generation module for generating the shape of the solid material as a first image containing a plurality of pixels; a clustering module for performing clustering on the plurality of pixels using the EBSD data such that the first image contains a plurality of clusters, each representing a first index of the crystal in a first color; an image processing module for generating a second image by processing the first image such 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 onto a display area.

Description

Technical Field

[0001] Cross-reference of related applications This application claims the benefit of priority based on Korean Patent Application No. 10-2023-0074914, filed on June 12, 2023, and all the contents disclosed in the document of the Korean Patent Application are incorporated herein by reference.

[0002] The disclosure relates to an apparatus and method for analyzing crystal structures.

Background Art

[0003] EBSD (Electron Backscatter Diffraction) is attached to a scanning electron microscope and can analyze the orientation of a material by detecting electrons (backscattered electrons) that are reflected when accelerated electrons are injected into a sample. That is, EBSD can analyze the crystal structure in the irradiation area using diffraction patterns measured from each crystal. For example, a computer system controls the position of an electron beam, a camera records a pattern generated in a test piece area where the electron beam stays, and the recorded pattern is automatically analyzed to calculate crystallographic information of the test piece area.

Summary of the Invention

Problems to be Solved by the Invention

[0004] One problem to be solved is to provide an apparatus and method for analyzing the crystal structure of a solid material effectively from EBSD data of the solid material.

Means for Solving the Problems

[0005] A crystal structure analyzer according to one embodiment may include: an EBSD (Electron Backscatter Diffraction) data acquisition module for acquiring EBSD data for a solid material; an image generation module for generating the shape of the solid material as a first image containing a plurality of pixels; a clustering module for performing clustering on the plurality of pixels using the EBSD data such that the first image contains a plurality of clusters, each representing a first index of the crystal in a first color; an image processing module for generating a second image by processing the first image such 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 onto a display area.

[0006] In some embodiments, the first index is defined as the value of a sine square function of an acute angle between a first vector and a second vector, wherein the first vector includes a unidirectional vector of the crystal at the pixel position corresponding to the crystal on the first image, and the second vector may include a vector pointing from the center of the whole particle outward toward the pixel position.

[0007] In some embodiments, the first color may include at least one of RGB, HSL, HSV, CMYK, and grayscale colors.

[0008] In some embodiments, the display area includes a first display area and a second display area arranged adjacent to one side of the first display area, and the rendering module can render the second image onto the first display area and render a first color bar onto the second display area, matching the values ​​of the first index with the first color.

[0009] 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 index may be defined as the direction in which the first vector is projected onto the plane formed by the first axis and the second axis.

[0010] In some embodiments, the figure is an arrow-shaped figure, and the second indicator may be displayed so as to overlap the plurality of clusters in the direction of the arrowhead.

[0011] In some embodiments, the image processing module can process the first image such that a third indicator associated with the second indicator is shown in a second color within the figure.

[0012] In some embodiments, the third index may be defined as the angle that the first vector makes with the plane formed by the first axis and the second axis.

[0013] In some embodiments, the second color may include at least one of RGB, HSL, HSV, CMYK, and grayscale colors.

[0014] 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 onto the first display area and render a second color bar onto the third display area, matching the values ​​of the third index with the second color.

[0015] In some embodiments, the first index is defined as a DoA (Degree of Alignment) value calculated at the pixel position corresponding to the crystal on the first image, and the DoA value may be calculated by the following formula:

number

[0016] 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 of L and a vector pointing from the center of the whole particle outwards toward the pixel position.

[0017] In some embodiments, the first color may include at least one of RGB, HSL, HSV, CMYK, and grayscale colors.

[0018] 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 onto the first display area and render a first color bar onto the third display area, matching the values ​​of the first index with the first color.

[0019] In some embodiments, the second indicator is defined as the major axis vector of the crystal corresponding to the pixel position, the figure is an arrow-shaped figure, and the second indicator may be displayed so as to overlap the plurality of clusters in the direction of the arrowhead.

[0020] A crystal structure analysis method according to one embodiment may include the steps of: acquiring EBSD data for a solid material; generating the shape of the solid material as a first image containing a plurality of pixels; performing clustering on the plurality of pixels using the EBSD data such that the first image contains a plurality of clusters, each representing a first index of the crystal in a first color; generating a second image by processing the first image such that a second index associated with the first index is displayed as a figure overlapping the plurality of clusters; and rendering the second image onto a display area.

[0021] In some embodiments, the first index is defined as the value of the sine squared function for the acute angle between the first vector and the second vector, the first vector includes a one-direction vector of the crystal at a pixel position corresponding to the crystal on the first image, and the second vector can include a vector directed from the center of the whole particle toward the pixel position in the contour direction.

[0022] In some embodiments, the first vector is 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 index may be defined as the direction in which the first vector is projected onto a plane formed by the first axis and the second axis.

[0023] In some embodiments, the step of generating the second image may include a step of processing the first image to generate the second image such that a third index associated with the second index is indicated in a second color inside the figure.

[0024] In some embodiments, the first index is defined as a DoA (Degree of Alignment) value calculated at a pixel position corresponding to the crystal on the first image, and the DoA value may be calculated by the following formula:

Equation

[0025] Here, L is the long-axis vector of the crystal corresponding to the pixel position, S is the short-axis vector of the crystal corresponding to the pixel position, and C is the value of the cosine function for the vector from the center of the whole particle toward the pixel position in the contour direction with respect to L.

[0026] In some embodiments, the second indicator is defined as the major axis vector of the crystal corresponding to the pixel position, the figure is an arrow-shaped figure, and the second indicator may be displayed so as to overlap the plurality of clusters in the direction of the arrowhead.

[0027] A computer-readable medium according to one embodiment may contain a program that causes a computer, including a processor that executes a program or instructions stored in memory or a storage device, to perform the following steps: acquiring EBSD data for a solid material; generating the shape of the solid material as a first image including a plurality of pixels; using the EBSD data to perform clustering on the plurality of pixels such that the first image includes a plurality of clusters each showing a first index of the crystal in a first color; processing the first image to generate a second image such that a second index associated with the first index is displayed as a figure overlapping on the plurality of clusters; and rendering the second image onto a display area. [Effects of the Invention]

[0028] According to the example, by extracting and visualizing information about how the crystal orientation is distributed across the entire particle from the data collected by the EBSD system, the crystal structure of a solid material can be effectively analyzed from EBSD data. Furthermore, since the crystal orientation is visually represented for each cluster, and the user changes the desired crystal plane, the results are immediately reflected visually, allowing for the exploration of crystal orientation linkage patterns in a short time on a typical computing environment. [Brief explanation of the drawing]

[0029] [Figure 1] Figure 1 is a block diagram illustrating a crystal structure analyzer according to one embodiment. [Figure 2] Figure 2 is a diagram illustrating one example of a crystal structure analyzer according to one embodiment. [Figure 3] Figure 3 is a diagram illustrating one example of a crystal structure analyzer according to one embodiment. [Figure 4] Figure 4 is a diagram illustrating one example of a crystal structure analyzer according to one embodiment. [Figure 5] Figure 5 is a diagram illustrating one example of a crystal structure analyzer according to one embodiment. [Figure 6] Figure 6 is a diagram illustrating one example of a crystal structure analyzer according to one embodiment. [Figure 7] Figure 7 is a flowchart illustrating a crystal structure analysis method according to one embodiment. [Figure 8] Figure 8 is a diagram illustrating one example of a crystal structure analyzer according to one embodiment. [Figure 9] Figure 9 is a diagram illustrating an example of a crystal structure analyzer based on one embodiment. [Figure 10] Figure 10 is a diagram illustrating an example of a crystal structure analyzer based on one embodiment. [Figure 11] Figure 11 is a diagram illustrating an example of a crystal structure analyzer based on one embodiment. [Figure 12] Figure 12 is a diagram illustrating an example of a crystal structure analyzer based on one embodiment. [Figure 13] Figure 13 is a diagram illustrating an example of a crystal structure analyzer based on one embodiment. [Figure 14] Figure 14 is a diagram illustrating a computing device according to one embodiment. [Modes for carrying out the invention]

[0030] Hereinafter, embodiments of the present invention will be described in detail with reference to the attached drawings, so that they can be easily implemented by a person with ordinary skill in the art to which the present invention pertains. However, the present invention can be realized in various different forms and is not limited to the embodiments described herein. Furthermore, in order to clearly illustrate the present invention, unnecessary parts have been omitted from the drawings, and similar parts throughout the specification are denoted by similar reference numerals.

[0031] When a part of the specification and claims “includes” a component, unless otherwise stated, this means that it may further include other components rather than excluding them. Ordinal terms such as “first,” “second,” etc., can be used to describe a variety of components, but such components are not limited by such terms. Such terms are used solely for the purpose of distinguishing one component from another.

[0032] The terms "...part," "...device," and "module" as used in this specification mean a unit capable of performing at least one function or operation as described herein, which can be realized in hardware or circuitry, software, or a combination of hardware or circuitry and software.

[0033] Figure 1 is a block diagram illustrating a crystal structure analyzer according to one embodiment.

[0034] Referring to Figure 1, a crystal structure analyzer 10 according to one embodiment can analyze the crystal structure of a solid material. The crystal structure analyzer 10 can extract and visualize information about how the crystal orientation is distributed relative to the whole particle from the data collected from the EBSD system. In some embodiments, the crystal structure analyzer 10 may be a server serving a web application, which is software that runs in a web browser. This allows the crystal structure analyzer 10 to easily analyze the crystal structure of a solid material using only a web browser, without the need to install any other software on their computer. However, the scope of the present invention is not limited thereto, and the functions provided by the crystal structure analyzer 10 can be implemented as various forms of software.

[0035] The crystal structure analyzer 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.

[0036] The EBSD data acquisition module 110 can acquire EBSD data for solid materials. The EBSD data may include spatially linked crystallographic orientation and phase information, and the EBSD data acquisition module 110 can acquire data in various formats collected from external EBSD systems. For example, the EBSD data may be two-dimensional data distinguished by separators such as commas, and may be a file generated to conform to the CSV (Comma Separated Values) format. As another example, the EBSD data may be in the form of a compressed file consisting of a collection of multiple CSV files. As yet another example, the EBSD data may be data that has undergone data cleaning using specific software (e.g., AZtecCrystal) that processes data collected using EBSD.

[0037] The image generation module 120 can generate a first image representing the shape of the solid material to be subjected to crystal structure analysis. Here, the first image may be in the form of a pixel image containing multiple 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 analyzer 10.

[0038] The clustering module 130 can perform clustering on multiple pixels included in the first image using EBSD data acquired by the EBSD data acquisition module 110. In some embodiments, the clustering module 130 can employ a density-based clustering algorithm for clustering. For example, the clustering module 130 can employ DBSCAN (Density-based spatial clustering of applications with noise). Unlike algorithms that perform clustering using the distance between clusters, density-based clustering algorithms can operate by clustering areas where data points are closely clustered and have high density. In particular, the clustering module 130 may use EBSD data to create a first image that includes multiple clusters, and each cluster may represent the first index of the crystal in a first color.

[0039] For example, EBSD data may include data on the crystal orientation of crystal grains. The data on crystal orientation may be multiple crystal orientation data collected for each crystal unit of a predetermined size that forms the solid material being analyzed. Here, the crystal unit is not defined to a specific size, but may be assumed to be a unit having a predetermined size that can be associated with at least one of the crystal units included in the first image, taking into account the resolution that the crystal structure analyzer according to the example can display in the environment. The clustering module 130 can perform clustering on multiple pixels that represent the first image using multiple angle data.

[0040] The image processing module 140 can generate a second image showing the results of clustering performed by the clustering module 130. In other words, the image processing module 140 can process the first image generated by the image generation module 120 so that each cluster is displayed in a different color, or it can process the first image so that the second index associated with the first index on the crystal is displayed as a figure overlapping on multiple clusters, and output it as a second image. In some embodiments, the color may include at least one of RGB, HSL, HSV, CMYK, and grayscale colors. RGB colors are colors represented using red, green, and blue, and HSL (or HSB) colors may be colors represented using hue, saturation, and lightness or brightness. HSV colors are colors represented using Hue, Saturation, and Value, while CMYK colors may be colors represented using Cyan, Magenta, Yellow, and Black.

[0041] The rendering module 150 can render the second image generated by the image processing module 140 onto a display area provided in a display device. This allows the user to visualize the crystal properties of the entire particle at a glance, by representing each pixel or cluster with a different color, or by representing certain indicators of the crystal with shapes that overlap on the clusters. This enables effective analysis of crystal structures from EBSD data collected in an intuition-less format.

[0042] In some embodiments, the first index may be defined as the value of a sine squared function of the acute angle between the first vector and the second vector. Here, the first vector may include a unidirectional vector of the crystal at the pixel position corresponding to the crystal on the first image, and the second vector may include a vector pointing from the center of the whole particle toward the outer edge to the pixel position. This allows the clustering module 130 to perform clustering such that each cluster included in the first image can represent the first index with a first color. At this time, the first color can be calculated for each pixel making up each cluster, so that a cluster may be represented by a gradient color. Here, the unidirectional vector of the crystal may be a vector corresponding to one of the lattice vectors of the crystal. In some embodiments, the lattice vectors of the crystal may include the a-axis, b-axis and c-axis, and the unidirectional vector of the crystal may include a vector corresponding to the c-axis of the crystal.

[0043] In some embodiments, the first color may include at least one of RGB, HSL, HSV, CMYK, and grayscale colors. RGB colors are colors represented using red, green, and blue; HSL (or HSB) colors may be colors represented using hue, saturation, and lightness or brightness; HSV colors are colors represented using hue, saturation, and value; and CMYK colors may be colors represented using cyan, magenta, yellow, and black.

[0044] On the other hand, the first vector may be 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 index may be defined as the direction in which the first vector is projected onto the plane formed by the first and second axes. This allows the image processing module 140 to process the first image and generate a second image such that the second index is displayed as a figure that overlaps on each cluster contained in the first image. In some embodiments, the figure may include an arrow-shaped figure, and the second index may be displayed so as to overlap on multiple clusters in the direction of the arrowhead.

[0045] Furthermore, the image processing module 140 can process the first image so that the third index associated with the second index is shown in the second color inside the figure. Here, the third index may be defined as the angle that the first vector makes with the plane formed by the first axis and the second axis.

[0046] In some embodiments, the second color may include at least one of RGB, HSL, HSV, CMYK, and grayscale colors. RGB colors are colors represented using red, green, and blue; HSL (or HSB) colors may be colors represented using hue, saturation, and lightness or brightness; HSV colors are colors represented using hue, saturation, and value; and CMYK colors may be colors represented using cyan, magenta, yellow, and black.

[0047] This allows for the effective analysis of the crystal structure of solid materials from EBSD data by extracting and visualizing information about the distribution of crystal orientations relative to the overall particle size from the data collected by the EBSD system. Furthermore, even when the user modifies a desired crystal plane, the desired crystal orientation pattern can be easily explored based on that crystal plane. For example, any linkage pattern of crystal orientations that can be formed between adjacent clusters can be used as a meaningful analysis result, but analyzing such linkage patterns from EBSD data given as 2D data requires significant computing resources and considerable working time. In contrast, according to this embodiment, when the user modifies a desired crystal plane while the crystal orientation is visually represented for each cluster, the result is immediately reflected visually, allowing for the exploration of linkage patterns of crystal orientations in a short time on a typical computing environment.

[0048] Figures 2 to 4 illustrate one example of a crystal structure analyzer according to one embodiment. Figure 2 shows the second image IMG1 represented by the rendering module 150, and Figures 3 and 4 illustrate the definitions of the first to third indices.

[0049] Referring to Figures 2 to 4, the second image IMG1 may represent the entire particle, with the center of the particle displayed at its center. In Figure 2, the center of the particle is represented as a circle with a black frame, but the scope of the present invention is not limited to this.

[0050] The first indicator is the first vector.

number

number

number

number

[0051] The second indicator is the first vector

number

number

[0052] The third indicator is the first vector.

number

[0053] In this way, by visually grasping the first to third indicators described above for the entire particle, it becomes possible to effectively analyze the crystal structure from EBSD data collected in a non-intuitive form.

[0054] Referring again to Figure 1, in some embodiments, the first index may be defined as a DoA (Degree of Alignment) value calculated at the pixel position corresponding to the crystal on the first image. Here, the DoA value may be calculated by the following formula.

[0055]

number

[0056] Here, L may be the major axis vector of the crystal corresponding to the pixel position, S may be the minor axis vector of the crystal corresponding to the pixel position, and C may be the value of the cosine function of L and a vector that points from the center of the whole particle outward toward the pixel position. This allows the clustering module 130 to perform clustering such that each cluster included in the first image can represent the first index with the first color.

[0057] In some embodiments, the first color may include at least one of RGB, HSL, HSV, CMYK, and grayscale colors. RGB colors are colors represented using red, green, and blue; HSL (or HSB) colors may be colors represented using hue, saturation, and lightness or brightness; HSV colors are colors represented using hue, saturation, and value; and CMYK colors may be colors represented using cyan, magenta, yellow, and black.

[0058] On the other hand, the second index may be defined as the major axis vector of the crystal corresponding to the pixel position. This allows the image processing module 140 to process the first image and generate the second image so that the second index is displayed as a figure that overlaps on each cluster contained in the first image. In some embodiments, the figure may include an arrow shape, and the second index may be displayed so as to overlap on multiple clusters in the direction of the arrowhead. Here, the direction of the arrowhead may correspond to the direction in which the major axis vector is pointing, and the length of the arrow may be set to a value that is relevant to the length of the major axis.

[0059] This allows for the effective analysis of the crystal structure of solid materials from EBSD data by extracting and visualizing information about the distribution of crystal orientations relative to the overall particle size from the data collected by the EBSD system. Furthermore, even when the user modifies a desired crystal plane, the desired crystal orientation pattern can be easily explored based on that crystal plane. For example, any linkage pattern of crystal orientations that can be formed between adjacent clusters can be used as a meaningful analysis result, but analyzing such linkage patterns from EBSD data given as 2D data requires significant computing resources and considerable working time. In contrast, according to this embodiment, when the user modifies a desired crystal plane while the crystal orientation is visually represented for each cluster, the result is immediately reflected visually, allowing for the exploration of linkage patterns of crystal orientations in a short time on a typical computing environment.

[0060] Figures 5 and 6 illustrate an example of a crystal structure analyzer according to one embodiment. Figure 5 shows the second image IMG2 represented by the rendering module 150, and Figure 6 illustrates the definitions of the first and second indices.

[0061] Referring to Figures 5 and 6, the second image IMG2 may represent the entire particle, with the center of the particle displayed at its center. In Figure 5, the center of the particle is represented as a circle with a black frame, but the scope of the present invention is not limited to this.

[0062] The first index may be defined as a DoA (Degree of Alignment) value calculated at the pixel position corresponding to the crystal on the first image. Here, the DoA value may be calculated by the following formula:

[0063]

number

[0064] Here, L is the major axis vector of the crystal corresponding to the pixel position.

number

number

number

number

[0065] The second indicator is the major axis vector of the crystal corresponding to the pixel position.

number

[0066] This means that the direction of the arrowheads displayed overlapping on the cluster is determined by the major axis vector.

number

[0067] In some embodiments, the first to third indices may be additionally calculated. The third indice represents DoA that takes the crystal area into consideration as a weighting, and may be called "Area weighted DoA," or it may be calculated by the following formula.

[0068]

number

[0069] Here, i is the index of the crystal, and A i This can represent the area of ​​the i-th crystal. This value may also be a numerical value that quantifies the overall morphological alignment of the primary particles within a given secondary particle, reflecting the area.

[0070] In this way, by visually grasping the first to third indicators described above for the entire particle, it becomes possible to effectively analyze the crystal structure from EBSD data collected in a non-intuitive form.

[0071] Figure 7 is a flowchart illustrating a crystal structure analysis method according to one embodiment.

[0072] Referring to Figure 7, a crystal structure analysis method according to one embodiment may include the steps of: S701 acquiring EBSD data for a solid material; S702 generating the shape of the solid material as a first image containing multiple pixels; S703 performing clustering on the multiple pixels using the EBSD data so that the first image contains multiple clusters, each representing a first index of the crystal in a first color; S704 processing the first image to generate a second image so that the second index associated with the first index is displayed as a figure overlapping on the multiple clusters; and S705 rendering the second image onto a display area.

[0073] For more detailed information regarding the aforementioned method, please refer to the explanations mentioned above in relation to Figures 1 to 6 and the explanations mentioned later in relation to Figures 8 to 13. Therefore, redundant explanations will be omitted here.

[0074] Figure 8 is a diagram illustrating one example of a crystal structure analyzer according to one embodiment.

[0075] Referring together to Figures 8 and 2, the rendering module 150 can render the second image generated by the image processing module 140 onto a display area 30 provided on a 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 may be arranged adjacent to one side of the first display area 31. The rendering module 150 can render the second image onto the first display area 31 and render a first color bar in the second display area, matching the value of the first index with the first color. This provides the user with the convenience of visually comparing the overall particles before and after clustering. The rendering module 150 can also render the second image onto the first display area 31 and render a second color bar in the third display area, matching the value of the third index with the second color. On the other hand, referring to Figures 8 and 5 together, the rendering module 150 can render the second image to the first display area 31 and render the first color bar, which matches the value of the first index with the first color, to the third display area.

[0076] This screen layout allows for a visual understanding of various indicators of the crystal relative to the entire particle, enabling effective analysis of crystal structure from EBSD data collected in a non-intuitive form.

[0077] Figures 9 to 13 illustrate an example of a crystal structure analyzer based on one embodiment.

[0078] Referring to Figures 9-13, the crystal structure analyzer according to one embodiment can output, in addition to the visual screen described above, an angle histogram shown as an example in Figure 9, a DoA histogram shown as an example in Figure 10, a DoA crystal histogram shown as an example in Figure 11, an aspect ratio histogram shown as an example in Figure 12, and a diameter histogram shown as an example in Figure 13.

[0079] The angle histogram in Figure 9 is the first vector

number

number

number

number

number

number

number

number

[0080] Figure 14 is a diagram illustrating a computing device according to one embodiment.

[0081] Referring to Figure 14, the crystal structure analysis apparatus and method according to the example can be realized using the computing device 50.

[0082] The computing device 50 may include at least one of a processor 510, memory 530, user interface input device 540, user interface output device 550, and storage device 560 that communicate via bus 520. The computing device 50 may also include a network interface 570 that is electrically connected to network 40. The network interface 570 can transmit or receive signals with other devices via network 40.

[0083] The processor 510 can be implemented in various forms such as an MCU (Micro Controller Unit), AP (Application Processor), CPU (Central Processing Unit), GPU (Graphic Processing Unit), or NPU (Neural Processing Unit), and can be any semiconductor device that executes instructions stored in the memory 530 or storage device 560. The processor 510 can be configured to implement the functions and methods described above in relation to Figures 1 to 13.

[0084] The memory 530 and storage device 560 can include various forms of volatile or non-volatile storage media. For example, the memory can include a ROM (read-only memory) 531 and a RAM (random access memory) 532. In this embodiment, the memory 530 can be located inside or outside the processor 510, and the memory 530 can be connected to the processor 510 via various already known means.

[0085] In some embodiments, at least some of the configurations or functions of the crystal structure analysis apparatus and method according to the embodiments can be implemented by a program or software executed on a computing device 50, and the program or software may be stored on a computer-readable medium.

[0086] In some embodiments, at least some of the configurations or functions of the crystal structure analysis apparatus and method according to the embodiments may be implemented using the hardware or circuits of the computing device 50, or by other hardware or circuits that can be electrically connected to the computing device 50.

[0087] As described above, by extracting and visualizing information about how the crystal orientation is distributed across the entire particle from the data collected by the EBSD system, the crystal structure of a solid material can be effectively analyzed from EBSD data. Furthermore, since the crystal orientation is visually represented for each cluster, and the user changes the desired crystal plane, the results are immediately reflected visually, allowing for the exploration of linked crystal orientation patterns in a short time on a typical computing environment.

[0088] Although embodiments of the present invention have been described in detail above, the scope of the present invention is not limited thereto. Various modifications and improvements made by persons with ordinary skill in the art to which the present invention pertains, utilizing the basic concepts of the present invention as defined in the following claims, also fall within the scope of the present invention. [Explanation of symbols]

[0089] 10...Crystal structure analyzer 110 ···EBSD data acquisition module 120 ···Image generation module 130 ···Clustering Module 140 ···Image Processing Module 150 ···Rendering Module 20 ···EBSD data 30 ···Display area 31 ···First display area 32 ···Second display area 33 ···Third display area 40 ···Network 50 ···Computing devices 510 ... Processor 520 ···Bus 530 ···Memory 531 ···ROM 532 ···RAM 540 ···User Interface Input Device 550 ···User Interface Output Device 560 ···Storage device 570 ···Network Interface

Claims

1. An EBSD data acquisition module that acquires EBSD (Electron Backscatter Diffraction) data for solid materials, An image generation module that generates the shape of the solid material as a first image containing multiple pixels, A clustering module that performs clustering on the plurality of pixels using the EBSD data such that the first image contains a plurality of clusters, each of which represents a first index of the crystal in a first color, An image processing module that processes the first image to generate a second image such that the second indicator associated with the first indicator is displayed as a figure that overlaps on the plurality of clusters, A crystal structure analyzer, comprising a rendering module for rendering the second image onto a display area.

2. The first index is defined as the value of the sine squared function for the acute angle between the first vector and the second vector, The first vector includes a unidirectional vector of the crystal at the pixel position corresponding to the crystal on the first image, The crystal structure analyzer according to claim 1, wherein the second vector includes a vector directed from the center of the whole particle toward the pixel position in the direction of the outer edge.

3. The crystal structure analyzer according to claim 2, wherein the first color includes at least one of RGB, HSL, HSV, CMYK, and grayscale colors.

4. The display area includes a first display area and a second display area arranged adjacent to one side of the first display area. The rendering module described above is The second image is rendered onto the first display area. The crystal structure analyzer according to claim 2, which renders a first color bar in the second display area, matching the value of the first index with the first color.

5. The first vector is defined in a three-dimensional space defined by a first axis, a second axis, and a third axis that are perpendicular to each other. The crystal structure analyzer according to claim 2, wherein the second index is defined as the direction in which the first vector is projected onto the plane formed by the first axis and the second axis.

6. The crystal structure analyzer according to claim 5, wherein the figure is an arrow-shaped figure, and the second indicator is displayed so as to overlap the plurality of clusters in the direction of the arrowhead.

7. The crystal structure analyzer according to claim 5, wherein the image processing module processes the first image so that a third index associated with the second index is shown in the second color inside the figure.

8. The crystal structure analyzer according to claim 7, wherein the third index is defined as the angle that the first vector makes with the plane formed by the first axis and the second axis.

9. The crystal structure analyzer according to claim 7, wherein the second color includes at least one of RGB, HSL, HSV, CMYK, and grayscale colors.

10. The display area includes a first display area and a third display area arranged adjacent to one side of the first display area. The rendering module described above is The second image is rendered onto the first display area. The crystal structure analyzer according to claim 7, which renders a second color bar in the third display area, matching the value of the third indicator with the second color.

11. The first index is defined as a DoA (Degree of Alignment) value calculated at the pixel position corresponding to the crystal on the first image, The DoA value is calculated by the following formula, according to the crystal structure analyzer described in claim 1: [Math 1] 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 of L and a vector pointing from the center of the whole particle outwards toward the pixel position.

12. The crystal structure analyzer according to claim 11, wherein the first color includes at least one of RGB color, HSL color, HSV color, CMYK color, and grayscale color.

13. The display area includes a first display area and a second display area arranged adjacent to one side of the first display area. The rendering module described above is The second image is rendered onto the first display area. The crystal structure analyzer according to claim 11, which renders a first color bar in the third display area, matching the value of the first index with the first color.

14. The second index is defined as the major axis vector of the crystal corresponding to the pixel position, The aforementioned figure is an arrow-shaped figure, The crystal structure analyzer according to claim 11, wherein the second indicator is displayed so as to overlap the plurality of clusters in the direction of the arrowhead.

15. The step of obtaining EBSD data for solid materials, The steps include generating the shape of the solid material as a first image containing multiple pixels, The steps include: performing clustering on the plurality of pixels using the EBSD data such that the first image contains a plurality of clusters, each representing a first index of the crystal in a first color; A step of generating a second image by processing the first image so that the second indicator associated with the first indicator is displayed as a figure that overlaps on the plurality of clusters, A method for analyzing a crystal structure, comprising the step of rendering the second image onto a display area.

16. The first index is defined as the value of the sine squared function for the acute angle between the first vector and the second vector, The first vector includes a unidirectional vector of the crystal at the pixel position corresponding to the crystal on the first image, The crystal structure analysis method according to claim 15, wherein the second vector includes a vector directed from the center of the whole particle toward the pixel position in the direction toward the outer edge.

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

18. The step of generating the second image is: The crystal structure analysis method according to claim 17, further comprising the step of processing the first image to generate the second image, such that a third index associated with the second index is shown in a second color within the figure.

19. The first index is defined as a DoA (Degree of Alignment) value calculated at the pixel position corresponding to the crystal on the first image, The DoA value is calculated by the following formula in the crystal structure analysis method according to claim 18: [Math 2] 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 of L and a vector pointing from the center of the whole particle outwards toward the pixel position.

20. The second index is defined as the major axis vector of the crystal corresponding to the pixel position, The aforementioned figure is an arrow-shaped figure, The crystal structure analysis method according to claim 19, wherein the second indicator is displayed so as to overlap the plurality of clusters in the direction of the arrowhead.

21. A computer including a processor that executes programs or instructions stored in memory or storage devices, The step of obtaining EBSD data for solid materials, The steps include generating the shape of the solid material as a first image containing multiple pixels, The steps include: performing clustering on the plurality of pixels using the EBSD data such that the first image contains a plurality of clusters, each representing a first index of the crystal in a first color; A step of generating a second image by processing the first image so that the second indicator associated with the first indicator is displayed as a figure that overlaps on the plurality of clusters, A computer-readable medium containing a program for performing the step of rendering the second image onto a display area.

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