Techniques for processing X-ray diffraction data

Abstract

A computer-implemented method for processing X-ray diffraction data is provided, wherein the X-ray diffraction data is provided by an X-ray detector configured to detect a diffracted X-ray beam of a sample to be studied. The method comprises: acquiring X-ray diffraction data from the X-ray detector while the sample is rotating relative to the incident X-ray beam; generating a 2D image frame from the acquired X-ray diffraction data, wherein the generated 2D image frame comprises 2D image data representing X-ray diffraction data at a specific rotational position of the sample, the X-ray diffraction data comprising sample-related X-ray data and background data; for the generated 2D image frame, distinguishing the sample-related X-ray diffraction data from the background data; mapping the distinguished sample-related X-ray diffraction data of the generated 2D image frame to a single 3D reciprocal space; and visualizing the 3D reciprocal space and the mapped X-ray diffraction data on a display screen. A device and an X-ray apparatus for implementing the above method are also provided.

Description

Technical Field

[0001] The present invention relates generally to the field of X-ray analysis. More particularly, the present invention relates to a method and apparatus for processing X-ray diffraction data. Background Art

[0002] X-ray analysis techniques such as X-ray diffraction have become increasingly popular because they employ non-destructive analysis of samples. For example, X-ray diffraction has become one of the fundamental experimental techniques for studying the properties of crystalline samples, polycrystalline samples or powder samples.

[0003] The general principle of X-ray diffraction of the sample to be studied is as follows. An X-ray source generates an X-ray beam (e.g., a monochromatic X-ray beam or a polychromatic X-ray beam). The generated X-ray beam is collimated and directed to the sample to be studied by a corresponding X-ray optical device. The incident beam on the sample is diffracted by the lattice of the sample. A diffraction beam is generated at an incident angle that satisfies the Bragg condition (i.e., at an angle at which coherent scattering is expected to occur from the lattice of the sample). The diffraction beam is detected by a planar, segmented, or curved two-dimensional X-ray detector (2D X-ray detector for short) and visualized using appropriate imaging techniques. The diffraction beam forms a pattern that characterizes the crystal structure characteristics of the sample to be studied. The pattern can be used to derive the structural properties of the sample, such as lattice structure, lattice symmetry, lattice distortion, the presence of intermediate layers, superlattice structure, twins, etc.

[0004] In order to obtain all the pattern information, the sample is rotated during the X-ray diffraction process, and the intensity of the diffracted beam is continuously measured by a 2D X-ray detector. The acquired intensity information is visualized using an appropriate imaging processing algorithm. In practice, the visualization of the pattern is performed by generating a series of continuous two-dimensional (2D) images while rotating the sample. By comparing the 2D images of the image sequence, the characteristics of the lattice structure can be derived. However, presenting the diffraction pattern in a series of 2D static images also has some disadvantages. The geometric structure of the instrument (especially in the form of the detector surface) distorts the position of the diffracted beam on the image, and when the crystal rotates through the Bragg diffraction conditions of the beam, the beam is usually presented on several continuous images. This makes it difficult to clearly observe the overall data and difficult to intuitively evaluate the crystallization quality. Artifact features, weak diffuse features or twins may be missed in data analysis. Moreover, the structural characteristics of the sample to be studied can only be studied after a sufficient number of 2D images have been obtained and compared with each other.

[0005] Therefore, there is a need for an improved X-ray detection technique that overcomes the above-mentioned problems known in standard detection techniques. In particular, there is a need for an X-ray detection technique that allows for more accurate and rapid determination of crystal structure properties of crystalline samples. Summary of the invention

[0006] In order to solve the above problems, a computer-implementable method for processing X-ray diffraction data is provided, wherein the X-ray diffraction data is provided by an X-ray detector, and the X-ray detector is configured to detect a diffracted X-ray beam of a sample to be studied. The method comprises the following steps: (a) acquiring X-ray diffraction data from the X-ray detector while the sample is rotated relative to the incident X-ray beam; (b) generating a two-dimensional (2D) image frame from the acquired X-ray diffraction data, wherein the generated 2D image frame includes 2D image data representing X-ray diffraction data of a specific rotational position of the sample, and the X-ray diffraction data includes sample-related X-ray data and background data; (c) for the generated 2D image frame, distinguishing the sample-related X-ray diffraction data from the background data; (d) mapping the distinguished sample-related X-ray diffraction data of the generated 2D image frame into a three-dimensional (3D) reciprocal space; and (e) visualizing the 3D reciprocal space and the mapped X-ray diffraction data on a display screen.

[0007] The 3D reciprocal space is momentum space (or K-space). The reciprocal lattice of the sample can be derived from the X-ray diffraction data (diffracted X-ray beam) mapped and visualized in the 3D reciprocal lattice.

[0008] In the following, the terms "sample-related X-ray diffraction data" and "crystallographically meaningful X-ray data" have the same meaning and can be used interchangeably. The diffracted X-ray beams of "sample-related X-ray diffraction data" and "crystallographically meaningful X-ray data" refer to X-ray satellite beams, (local) diffusely scattered X-rays and / or powder diffraction rays, but do not refer to unwanted background (e.g. caused by detector noise or Compton scattering). Optionally, depending on the experimental requirements, "sample-related X-ray diffraction data" and "crystallographically meaningful X-ray data" may also include artifacts (e.g. ice on the sample), X-ray scattering from device components (e.g. pinholes, beam blockers or high-pressure sensitive element pads).

[0009] While the rotational position of the sample changes, method steps (a) to (e) are continuously repeated. More specifically, X-ray diffraction data can be continuously acquired during the rotation of the sample. In addition, a series of 2D image frames can be generated based on the continuously acquired X-ray diffraction data. The generation of 2D image frames is performed so that each 2D image frame represents (sample-related) X-ray diffraction data obtained for a specific rotational position of the sample. According to one embodiment, X-ray diffraction data can be acquired at angular intervals of 0.1° or greater. Therefore, the continuously generated 2D image frames can have an angular resolution of 0.1° or greater. The angular width of the 2D image frame can be a user-selected parameter, which can be set according to the experimental angular resolution required to study the sample.

[0010] The step of distinguishing can include segmenting the X-ray diffraction data of the 2D image frame into sample-related X-ray diffraction data and unwanted background data by an appropriate image processing algorithm. The sample-related X-ray diffraction data usually occupies several percentages of the 2D image frame and is composed of diffracted X-ray beams, satellite beams, local diffuse scattered X-rays and / or powder diffraction lines. The image processing algorithm used can be designed to segment (distinguish) different image features from the smooth background of the 2D image frame. To achieve this purpose, the image processing algorithm can apply feature detection according to the properties of the sample-related X-ray diffraction data to be segmented from the unwanted background. In addition, the image processing algorithm can perform background calculation or background evaluation (such as background fitting) based on the background data area found. Further, the image processing algorithm can subtract the calculated or evaluated background from the X-ray data. In order to carry out at least one of the above-mentioned feature detection and background calculation (assessment), the "Integration of macromolecular diffraction data" in the 11.2th chapter and 212-217 pages of "International Tables for Crystallography (2006)" volume F can be used, or the "Integration, scaling, space-group assignment and post refinement" in the 11.3th chapter and 218-225 pages of "International Tables for Crystallography (2006)" volume F is described in the special processing algorithm, and the teachings given are incorporated herein by reference. The sample-related X-ray diffraction data obtained are a small part of the original 2D image frame, and the data volume of the data is usually reduced by a factor of 20 or higher, allowing the effective operation of subsequent steps.

[0011] Once a 2D image frame is generated (and the sample-related X-ray diffraction data are distinguished from the background data), a mapping of the (sample-related) X-ray diffraction data of the corresponding 2D image frame into the 3D reciprocal space and a visualization of the mapped X-ray diffraction data in the 3D reciprocal space can be performed. This means that the mapping of the differentiated (segmented) 2D image data representing the acquired (sample-related) X-ray diffraction data (e.g. the diffracted X-ray beam) into the 3D reciprocal space and their visualization in the 3D reciprocal space is performed in a (near) real-time mode, that is, while the X-ray diffraction data acquisition is being performed. Therefore, according to the present invention, each newly generated 2D image frame is processed immediately after its generation in order to map the (sample-related) X-ray diffraction data of the 2D image frame into the 3D reciprocal space. Therefore, the present data processing technique is different from known data processing techniques in which a full sequence of 2D image frames within the full measurement range is first acquired and the full sequence of 2D image frames is post-processed for 3D visualization of the X-ray diffraction data.

[0012] In contrast to post-processing, near real-time processing of 2D image data requires fast data processing, which has become possible today through improvements in personal computer specifications (e.g., processor speed, multi-core parallel processing, and graphics processors optimized for 3D image visualization. In addition, appropriate image processing algorithms for distinguishing sample-related X-ray diffraction data as described above can be used to increase speed and data processing efficiency.

[0013] Each 2D image frame is generated by applying an appropriate image processing algorithm that is capable of converting X-ray diffraction data (raw detector data) into corresponding 2D image data. The 2D image data of the 2D image frame includes segmented 2D image data that distinguishes sample-related X-ray diffraction data from unwanted background data. The X-ray diffraction data may include at least intensity data measured by the corresponding 2D X-ray detector. The measured intensity data may include intensities associated with diffracted X-ray beams, satellite beams and / or diffusely scattered X-rays. The measured intensity data may also include unwanted background intensities (caused by incoherent Compton scattering and noise).

[0014] The intensity data obtained from the X-ray detector can be converted into corresponding 2D image data. Each 2D image data may include 2D image data corresponding to the intensity measured by the 2D X-ray detector for a specific rotational position of the sample. The 2D image data (of each image frame) can represent the measured intensity by an appropriate image parameter, which is proportional to the measured intensity value. At least one of brightness, color value and hue can be used as an image parameter. Therefore, those areas with high intensity (sample-related intensity) corresponding to diffracted X-ray beams (satellite beams or diffusely scattered X-rays) can be represented as bright and / or colored areas (i.e., 2D spots) in the 2D image frame. Similarly, frame areas with low intensity or suppressed intensity can represent background areas. These areas can be represented as dark areas or not considered at all.

[0015] Each generated 2D image frame can be rendered into a pixel image frame. Therefore, the 2D image frame can include 2D pixel image data, which represents the measured intensity by assigning at least one appropriate image parameter (e.g., color value, brightness) to each pixel of the pixel image frame. Therefore, in the pixel image frame, each 2D light spot representing a diffracted X-ray beam, a diffracted satellite beam, or a diffusely scattered X-ray can be represented by at least one pixel. The at least one pixel used to represent the 2D light spot can have a brightness, color value, hue, or other color parameter proportional to the measured intensity of the diffracted X-ray beam.

[0016] Most of the 2D image area (2D pixel image data) consists of unwanted background. (Crystallographically meaningful) X-ray diffraction data can occupy up to 5% of the 2D image area. Unwanted background areas (or 2D pixel image areas including unwanted background data) can be identified in the 2D image (by appropriate image processing algorithms as described above). Moreover, the identified image area (or 2D pixel image data) including the background can be eliminated (by image processing algorithms). Thus, pixels representing (sample-related) X-ray diffraction data in the 2D image frame can be distinguished from pixels representing background data in the 2D image frame. In addition, only the (sample-related) X-ray diffraction data that is distinguished (segmented) from the background is mapped into the 3D reciprocal space. By mapping only the crystallographically meaningful (sample-related) data in the 2D image, computational tasks are reduced and near real-time speeds can be achieved.

[0017] The mapping may include mapping crystallographically significant (i.e., sample-related) X-ray diffraction data that has been distinguished from (unwanted) background into a 3D reciprocal space. In this article, mapping crystallographically significant (sample-related) X-ray diffraction data refers to mapping 2D image data in a 2D image frame that represents diffracted X-ray beams, X-ray satellite beams, and diffusely scattered X-rays instead of background data into a 3D reciprocal space. Thus, by mapping crystallographically significant (sample-related) X-ray diffraction data, a 3D reciprocal space can be created that is not limited to specific diffraction features (e.g., Bragg peaks), but the 3D reciprocal space contains all the diffraction information obtained from the X-ray diffraction experiment (i.e., diffracted X-ray beams, X-ray satellite beams, and diffusely scattered X-rays that are distinguished by appropriate image processing algorithms). The mapping of all diffraction information into a 3D reciprocal space allows the user to better study the characteristics of the sample, which exceeds the study of the lattice structure alone. In particular, the presence of twins in the sample, disorder, lattice superstructure or quasicrystal behavior can be better observed from the overall diffraction data than from data showing only the main Bragg peak of the X-ray diffraction experiment. In addition, by mapping a fully crystallographically meaningful (sample-related) information image, artifacts (e.g. ice on the sample, X-ray scattering from device components such as pinholes, beam stops or high-voltage element pads) can also be better visible to the user and reveal the quality of or problems with the experiment.

[0018] The mapping of (sample-related) X-ray diffraction data represented by 2D image frames to 3D reciprocal space can be performed based on at least one of the following parameters: sample orientation, detector size, detector position relative to the sample, X-ray wavelength and Ewald sphere geometry. It is known that the appearance and position of the diffracted beams in the generated 2D image frames depend on the detector size, the distance from the detector to the sample and the angular position (orientation) of the sample relative to the incident X-ray beam, because when the sample is rotated, only the reciprocal lattice points intersecting the Ewald sphere can obtain diffracted X-ray beams. Therefore, by knowing the wavelength of the X-ray beam used for the X-ray diffraction experiment (which is inversely proportional to the radius of the Ewald sphere), the sample orientation (which can be deduced from the sample rotation position that continuously changes during data acquisition) and the geometry of the experiment (in particular the distance from the detector to the sample and the detector size), the 3D reciprocal lattice can be reconstructed on the basis of the X-ray diffraction data represented in the sequence of 2D image frames acquired from the crystal sample.

[0019] If the crystal symmetry (or crystallographic space group) of the sample is known, the mapping may further include: reconstructing a full X-ray diffraction data set for the sample in 3D reciprocal space based on the acquired X-ray diffraction data subset and the crystal symmetry. Further, the visualization step may include visualizing the reconstructed X-ray diffraction data on a display screen. In this case, the crystal symmetry (or crystallographic space group) may be used as an input parameter (entered by a user), and the mapping algorithm may calculate the X-ray diffraction data in the full angle range by using the acquired X-ray diffraction data subset for a partial angle range and the symmetry of the lattice. By reconstructing the full diffraction data set from the X-ray diffraction data subset, the X-ray diffraction data processing may be simplified and accelerated, because only a smaller X-ray diffraction data set within a partial angle range must be acquired and processed, while the X-ray diffraction data in the remaining angle range for which the X-ray diffraction data has not yet been acquired is mathematically generated by utilizing the symmetry of the lattice.

[0020] The 3D reciprocal space can be represented by a voxel grid (i.e., a voxel array). The voxel grid can have a predetermined resolution (e.g., 1024x1024x1024 voxels). The resolution of the voxel grid can be adjusted or preset accordingly (by the user) according to the experimental requirements. That is, the size of each voxel (and the corresponding number of voxels used to represent the 3D reciprocal space) should be preset so that each diffracted X-ray beam of the reciprocal lattice point representing the sample reciprocal lattice can be represented by at least one voxel. That is, the size of the voxel should be smaller than the size of the diffracted X-ray beam and / or the distance between adjacent diffracted X-ray beams, so as to provide a fully analytical 3D presentation of the acquired X-ray diffraction data. If the size of the voxel is selected to be smaller than the size of the diffracted X-ray beam, then a 3D rendering of the true shape and size of the diffracted X-ray beam can be obtained in the 3D reciprocal lattice. For typical small molecule samples, a voxel grid size of 512x512x512 will provide adequate resolution, while for protein or other macromolecular samples, a voxel grid size of 2048x2048x2048 will preferably show good resolution of the diffraction pattern. As personal computer specifications increase to provide support, the size of the voxel grid will be larger in the future.

[0021] If the 3D reciprocal lattice is divided into a voxel array (or voxel grid) as described above, the mapping may include mapping the distinguished (crystallographically significant or sample-related) X-ray diffraction data of the 2D image frame (that is, the pixel values ​​of the 2D pixel image that are proportional to the diffraction intensity measured by the 2D X-ray detector) to the corresponding voxels of the 3D reciprocal lattice. This can also be expressed as not mapping those pixels in each 2D image frame that have been distinguished as background (i.e., not containing crystallographically significant X-ray diffraction data, such as unwanted background). The mapping of the 2D pixel image to the 3D voxel image may be performed taking into account the sample orientation, detector geometry, position of the detector relative to the sample, and / or Ewald sphere geometry as described above. Therefore, only the pixel image data representing the crystallographically significant X-ray diffraction data (or sample-related X-ray diffraction data) in the 2D image frame is mapped to the corresponding voxels of the voxel grid to generate a 3D diffraction pattern that can clearly represent the full diffraction data.

[0022] The currently available specifications of personal computers cannot process data from fully used voxel grids in near real time. Let's take a voxel grid of 1024x1024x1024 size as an example. Each voxel used contains at least 2 bytes of data to represent the intensity of X-ray diffraction data. The total data size of the fully used voxel grid is therefore 2 gigabytes. By distinguishing the crystallographically meaningful (sample-related) X-ray diffraction data from the unwanted background in each 2D image frame, it is necessary to map only a small portion of the pixels (which can be 5%) to the voxels in the 3D grid. The voxel grid is thus sparsely filled with data (which can be 5% of the voxels containing data). Contrary to storing all voxel grids in computer memory, it is more efficient to store a list of filled voxels, which records their three-dimensional positions (4 bytes) in the grid and the intensity values ​​(2 bytes) of the X-ray diffraction data, which in this example produces about 300 megabytes of data. This significant reduction in the amount of data to be processed is important for realizing mapping and visualization processing in near real time.

[0023] The visualization step may include visualizing an empty 3D reciprocal space and continuously filling the empty 3D reciprocal space with mapped X-ray diffraction data. In this context, continuously filling may refer to adding mapped X-ray diffraction data (e.g., diffracted X-ray beams) obtained from a currently generated 2D image frame in the 3D reciprocal space, while previously mapped and visualized X-ray diffraction data extracted from previous 2D image frames remain visible in the 3D reciprocal space. Thus, as the sample rotates, the initially empty 3D space will be continuously filled with new X-ray diffraction data, making the complete reciprocal lattice structure of the sample increasingly visible.

[0024] According to one embodiment, (sample-related) X-ray diffraction data (e.g., diffraction beams, satellite beams) that appear redundantly in two or more 2D image frames and are mapped to the same position (voxel) in the 3D reciprocal space are highlighted for a short time during visualization. The highlighting may include the use of color pulses (e.g., white pulses) on those positions (voxels) in the 3D reciprocal space, where the overlapping redundant X-ray diffraction data are added to the 3D reciprocal space. This highlighting in the 3D reciprocal space signals to the user that "measurements of the sample are still in progress." In order to reduce the amount of data stored in the voxel grid, the redundant data mapped to the same position (voxel) are stored as a single average value calculated from the redundant measurements.

[0025] The mapped X-ray diffraction data can be visualized in the form of a 3D spot in the 3D reciprocal space. Each 3D spot can visualize the size, shape and / or intensity of the X-ray diffraction data (such as X-ray diffraction peaks, diffusely scattered X-rays or other scattering features or artifacts) represented by the 3D spot. For visualization purposes, each 3D spot can assume a color value, hue and / or brightness that is proportional to the intensity of the X-ray diffraction data represented by the 3D spot. If the 3D reciprocal space is represented by a voxel grid, then each 3D spot can be represented by at least one voxel. The number of voxels used to represent the 3D spot can depend on the size and shape of the 3D spot to be visualized and the grid resolution. In addition, at least one voxel representing the 3D spot can carry image information (such as color value, hue, brightness), which is proportional to the intensity of the X-ray diffraction data represented by the 3D spot.

[0026] The visualization step can be performed according to at least one pre-selected visualization parameter. The at least one pre-selected visualization parameter can indicate the intensity level of the X-ray diffraction data. If a predetermined intensity level is selected for the visualization step, only the mapped X-ray diffraction data with intensity levels lower than or higher than the pre-selected intensity level can be visualized in the 3D reciprocal space. For example, the at least one visualization parameter can indicate a pre-selected minimum intensity level and / or a pre-selected maximum intensity level. In this case, those mapped X-ray diffraction data indicating that the X-ray intensity is higher than the minimum intensity level, lower than the maximum intensity level, or between the maximum intensity level and the minimum intensity level can become visible in the 3D reciprocal space. In this case, the visualization step is designed to implement a high-pass filter, a low-pass filter, or a band-pass filter function.

[0027] At least one pre-selected visualization parameter may indicate a d-spacing resolution value of the X-ray diffraction data. The term "d-spacing" is used to represent the spacing between adjacent lattice planes in the sample crystal structure. If a predetermined d-spacing resolution value is selected for the visualization step, only those mapped X-ray diffraction data having a d-spacing resolution value lower or higher than the pre-selected d-spacing resolution value in the 3D reciprocal space are visualized. For example, at least one visualization parameter may indicate a pre-selected minimum d-spacing resolution value and / or a pre-selected maximum d-spacing resolution value. In this case, those mapped X-ray diffraction data indicating an X-ray d-spacing resolution value higher than a minimum value, lower than a maximum value, or between a minimum value and a maximum value may be made visible in the 3D reciprocal space. In this case, the visualization step is designed to implement a high-pass filter, a low-pass filter, or a band-pass filter function.

[0028] The 3D reciprocal space can be visualized in a graphical user interface in a manner that makes the space rotatable and / or scalable. By rotating the reciprocal space, the reciprocal lattice can be examined from different angles. Furthermore, by zooming in or out of the reciprocal space, the entirety or only a portion of the reciprocal lattice can be visualized.

[0029] In a possible embodiment, a portion of the 3D reciprocal space can be visualized on a graphical user interface by a defined plane that cuts through the space. Only those voxels that intersect the plane can be visualized in this embodiment. The user will be able to control the orientation of the plane and then slide the plane in a direction perpendicular to the plane to see which voxels are visualized. Control of the plane is achieved using an input unit connected to a computer for controlling the visualization.

[0030] In a possible embodiment, numerical or textual information may be displayed on a graphical user interface together with the 3D reciprocal space (in the form of an overlay) to provide the user with additional information about the displayed X-ray diffraction data. For example, hkl-indicators may be displayed next to voxels showing Bragg diffraction peaks, or (x, y, z) coordinates may be displayed to aid in understanding the lattice (and sample) orientation.

[0031] The acquiring step may include reading out X-ray diffraction data (intensity data) from the 2D X-ray detector. The acquiring step may also include buffering the read-out X-ray diffraction data in a memory.

[0032] According to another aspect, a computer program product is provided, which has a program code, which performs the above method when the computer program product is executed on a computer device. The program code of the computer program product is stored on a non-transitory recording medium. The recording medium may be a DVD, a CD, a solid-state memory or any other non-transitory recording medium.

[0033] According to another aspect, a device for processing X-ray diffraction data is provided, wherein the X-ray diffraction data is provided by an X-ray detector, which is configured to detect a diffracted X-ray beam of a sample to be studied. The device includes a processing unit (processor), which is configured to: acquire X-ray diffraction data from the X-ray detector when the sample rotates relative to the incident X-ray beam; generate a 2D image frame from the acquired X-ray diffraction data, wherein the 2D image frame includes 2D image data representing the X-ray diffraction data, and the X-ray diffraction data includes sample-related X-ray data and background data for a specific rotational position of the sample; for the generated 2D image frame, distinguish the sample-related X-ray diffraction data from the background data, and map the distinguished sample-related X-ray diffraction data of the 2D image frame to a 3D reciprocal space; and a visualization unit, which is configured to visualize the 3D reciprocal space together with the mapped X-ray diffraction data on a display screen.

[0034] The apparatus may further comprise an input unit configured to receive at least one pre-selected visualization parameter. The input unit may be a touch screen, a mouse, a keyboard or any other input unit.

[0035] According to another aspect of the present invention, an X-ray device for X-ray diffraction measurement is provided. The X-ray device comprises: an X-ray detector configured to detect a diffracted X-ray beam of a sample to be studied; the above-mentioned device for processing X-ray diffraction data acquired from the X-ray detector; and a display screen configured to display 3D reciprocal space and mapped X-ray diffraction data. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Other details, aspects and advantages of the present disclosure described herein will become apparent from the following drawings, in which:

[0037] Figure 1 is a schematic diagram of an X-ray device for X-ray diffraction measurement according to the present invention;

[0038] Figure 2 is a block diagram of an apparatus for processing X-ray diffraction data according to the present invention;

[0039] Figure 3 is a flow chart representing a computer-implemented method for processing X-ray diffraction data according to the present invention;

[0040] Figure 4a-4c is a schematic diagram illustrating the relationship between the reciprocal lattice of a sample to be investigated and the diffraction data acquired by a 2D detector; and

[0041] Figure 5a-5dVarious diffraction patterns obtained by the X-ray diffraction data processing technique according to the present invention are shown. DETAILED DESCRIPTION

[0042] In the following description, for the purpose of explanation rather than limitation, specific details are set forth in order to provide a thorough understanding of the present technology for processing X-ray diffraction data. It will be apparent to those skilled in the art that the disclosed method and apparatus for processing X-ray diffraction data and the disclosed X-ray device for X-ray diffraction measurement may deviate from the specific details described below within the scope of protection.

[0043] Reference is made below Figure 1 . Figure 1 A schematic diagram of an X-ray device 1000 according to the present invention is shown. The X-ray device 1000 is an X-ray diffractometer designed for performing an X-ray diffraction analysis on a crystalline sample 30.

[0044] The X-ray device 1000 includes an X-ray source 1010, which is configured to generate a monochromatic or polychromatic (white) X-ray beam. A conventional monochromatic or polychromatic X-ray source can be used as the X-ray source. The X-ray device 1000 also includes an X-ray optical device 1020, which is optically coupled to the X-ray source 1010 and is configured to collimate and direct the X-ray beam onto the sample 30 to be studied. Figure 1 In the diagram, the beam is denoted by reference numeral 10 .

[0045] The X-ray device 1000 further includes an X-ray detector 1030, which is configured to detect the diffracted X-ray beam (at Figure 1 The X-ray detector 1030 is designed as a two-dimensional (2D) detector consisting of a plane surface or several segmented plane surfaces or curved surfaces. The 2D X-ray detector 1030 is designed to measure the intensity of the diffracted X-ray beam 20 reaching the detector surface. For example, a 2D semiconductor-based detector can be used as the X-ray detector 1030. Figure 1 shown and combined in more detail Figures 4a to 4c As explained, the diffracted beam 20 at the detector surface is only expected to appear at an angle θ (or 2θ when the incident beam 20 is used as a measurement reference) that satisfies the Bragg condition. Therefore, by measuring the intensity and angle of the diffracted X-ray beam 20, the crystalline properties of the sample 30, such as its crystal structure (Bravais lattice), the presence of twins, superstructure, etc., can be derived.

[0046] In order to resolve the entire lattice structure of the sample 30 by X-ray diffraction, the sample 30 can be rotated relative to the incident beam 10. To this end, the X-ray device 1000 includes a goniometer 1040 configured to rotatably support the sample 30. The rotational freedom provided by the goniometer 1040 is Figure 1 Indicated by arrows 6 and 8 in FIG.

[0047] Furthermore, the X-ray device 1000 comprises a (central) control and operating unit 1050 , which comprises the data processing device 100 , the input unit 102 , the display screen 104 and the drive controller 106 .

[0048] The data processing device 100 is configured to process the X-ray diffraction data acquired by the detector 1030. Figure 2 and Figure 3 The operation of the apparatus 100 is described in more detail. The input unit 102 is configured to receive user commands (e.g., drive commands) or user input for controlling the X-ray device 1000. The display screen 104 is configured to display image data processed by the apparatus 100. In addition, the drive controller 106 is configured to control the drive units (e.g., the detector 1030, the goniometer 1040, and / or the X-ray source 1010) associated with the detector 1030, the goniometer 1040, and / or the X-ray source 1010. Figure 1 ), so as to move the detector 1030, the goniometer 1040 and / or the X-ray source 1010 to a desired position.

[0049] Figure 2 The apparatus 100 for processing X-ray diffraction data according to the present invention is shown in the form of a block diagram. The apparatus 100 may be Figure 1 The device 100 is part of the control and operating unit 1050. Alternatively, the device 100 can be implemented as a separate device or in a computer device that communicates with the X-ray device 1000.

[0050] The apparatus 100 includes a memory 110, a data processing unit 120 (referred to as processing unit 120), and a visualization unit 130. The apparatus 100 communicates with an X-ray detector 1030, an input unit 102, and a display screen 104 of the X-ray device 1000.

[0051] The memory 110 communicates with the processing unit 120. The memory 110 is designed to at least store or buffer the X-ray diffraction data received from the X-ray detector 1030. The memory 110 may also be configured to store or buffer two-dimensional (2D) image data and three-dimensional (3D) image data generated by the processing unit 120 from the raw X-ray diffraction data. In addition, the memory 110 may be configured to buffer input data received from the input unit 102. In order to perform the described storage function, the memory 110 may be implemented as a solid-state memory.

[0052] The processing unit 120 is designed to process the raw X-ray data (i.e., intensity data) provided by the X-ray detector 1030. To this end, the processing unit 120 implements a plurality of submodules, such as an acquisition unit 122, a two-dimensional (2D) image generation unit 124, and a mapping unit 126. Each of the units 122, 124, and 126 may be implemented as a programmable hardware module, a combined hardware and software module, or as a software module including computer code to perform certain functions when the processor of the processing unit 120 executes the code. At least one processor ( Figure 2 (not shown) can be implemented as a multi-core processor for parallel data processing. Figure 3 The functions of units 122, 124 and 126 are described in more detail.

[0053] The visualization unit 130 communicates with the processing unit 120 and the display screen 104. The visualization unit 130 may be implemented as a software module configured to present the processed data received from the processing unit 120 in a specific environment. For example, the visualization unit 130 may implement a graphical user interface designed to present the processed 3D image data. In addition, the graphical user interface may be configured to receive input data so as to change the rendering of the 3D image data while the 3D image data is presented on the display screen 104.

[0054] Combination Figure 3 , further describing a method for processing X-ray diffraction data according to the present invention. The X-ray diffraction data is obtained by a system configured to detect a sample to be studied (e.g. Figure 1 The diffracted X-ray beam of the sample 30) is detected by an X-ray detector (e.g. Figure 2 The method is provided by Figure 3 The device 100 is implemented and includes the following steps.

[0055] In a first step S10, X-ray diffraction data are (continuously) acquired from the X-ray detector 1030 by the acquisition unit 122 while the sample 30 to be studied is rotated. The acquisition step includes reading the X-ray detector 1030 by the acquisition unit 122. The reading of the detector can be performed at a predetermined angular interval. For example, the data reading of the detector can be performed at a rotation angle interval of 0.1° or higher. In addition, the acquisition unit 122 can buffer the read X-ray diffraction data in the memory 110. In addition, the acquisition unit 122 can retrieve the X-ray diffraction data buffered in the memory 110 and feed them to the 2D image generation unit 124 for subsequent data processing. The X-ray diffraction data acquired by the acquisition unit 122 includes at least intensity data (or simply intensity) measured by the X-ray detector 1030.

[0056] In the subsequent second step S20, a 2D image frame is generated by the 2D image generation unit 124 according to the acquired 2D X-ray diffraction data for a predetermined rotation position (or rotation angle or rotation angle interval) of the sample 30. Therefore, the 2D image frame includes 2D image data representing (the spatial distribution of) diffracted X-ray beams, satellite beams and / or diffusely scattered X-rays detected for a specific rotation position of the sample 30. In addition, the 2D image data may also include other experimental artifacts (e.g., diffraction from ice on crystals, scattering from hardware such as pinholes, beam stops or high-pressure sensitive element pads) and background data caused by incoherent Compton scattering or (detector) noise. Each detected diffracted beam, satellite beam and / or diffusely scattered X-ray is marked by a corresponding 2D spot in the 2D image frame. Each 2D spot can be represented by a hue, brightness value or other image parameters proportional to the measured intensity of the corresponding X-ray beam. Furthermore, the light spot of each generated 2D image frame may have a size and shape corresponding to the actual size and shape of the diffracted beam detected by the 2D detector 1030 .

[0057] If the 2D image frame is rendered as a pixel image (i.e., a pixel array), step S20 includes generating pixel image data of the 2D image frame, wherein each pixel of the 2D image frame includes image data (e.g., chromaticity, brightness value) proportional to the measured intensity. In other words, each pixel of the 2D image frame includes at least one image parameter value (e.g., brightness value and / or color value) proportional to the measured intensity. Therefore, each light spot used to represent the diffracted X-ray beam (satellite beam or diffusely scattered beam) can be represented by one or more pixels.

[0058] In a subsequent step S30, the crystallographically meaningful (sample-related) X-ray diffraction data represented in the 2D image frame are distinguished (segmented) from other background data by the 2D image processing unit 124 (by using an appropriate image processing algorithm as described above). With the crystallographically meaningful (sample-related) X-ray diffraction data, the 2D image information of the 2D image frame represents the diffracted X-ray beam, X-ray satellite beams, diffusely scattered X-rays (and artifacts such as ice on the sample, X-ray scattering from instrument components (such as pinholes, beam stops or high-pressure sensitive element pads)), but does not represent those unwanted background (for example caused by detector noise or Compton scattering). If the 2D image is rendered as a pixel image, the distinguishing step includes selecting only those pixels that can represent the X-ray image data from the pixel array and eliminating the remaining pixels associated with the background.

[0059] In the next step S40, the differentiated (sample-related) X-ray diffraction data are mapped to a 3D space (3D reciprocal space or 3D momentum space). The 2D to 3D data mapping is performed by Figure 2The mapping unit 126 in FIG. 1 is executed and will be described below in conjunction with Figure 4a to Figure 4c Furthermore, in order to provide (near) real-time data processing and visualization, the mapping unit 126 is designed to perform data mapping of the 2D image data into the 3D space as soon as a 2D image frame is available (i.e., once the 2D image frame is generated by the 2D image generation unit 124 and handed over to the mapping unit 126).

[0060] In the following, the mapping algorithm performed by the mapping unit 126 is explained in more detail. The mapping unit 126 is designed to map, for each image frame, the crystallographically meaningful (sample-dependent) X-ray diffraction information derived from each 2D image frame to a corresponding position in the 3D reciprocal space by at least taking into account the rotational position of the sample. Figures 4a to 4c The 2D to 3D data mapping is discussed further.

[0061] Figure 4a A geometrical representation of the elastic scattering of an incident X-ray beam 10 on a sample 30 to be investigated using a so-called Ewald sphere configuration is shown. Figure 4a A 2D representation of the Ewald sphere is shown in . The Ewald sphere is thus represented by a circle 410 (actually it is a 3D sphere) whose radius r corresponds to the inverse of the wavelength λ of the incident X-ray beam 10. The origin O of the Ewald sphere 410 coincides with the position of the sample 30 to be investigated. Figure 4a The reciprocal lattice 30' of the sample 30 to be studied is also shown in FIG. Figure 4a In the 2D representation in , the reciprocal lattice 30' is represented as a 2D lattice (actually it is a 3D lattice). The origin O' of the reciprocal lattice is located on the Ewald sphere, and the incident beam 10 passes through the origin O of the Ewald sphere 410 and the origin O' of the reciprocal lattice 30'. Figure 4a Another circle 420 (actually it is also a sphere) is shown in FIG. 4 . The circle / sphere 420 has a radius r′=1 / D. The radius r′ represents the resolution limit of the sample 30 and D represents the threshold value of the d-spacing value, which should be determined by X-ray diffraction experiments.

[0062] from Figure 4a It becomes clearer from the geometric representation in that the Bragg condition for elastic scattering (where the wave vector of the incident X-ray beam 10 is must have a wave vector 20 with the diffracted beam The same amount, that is For , only the scattering vector q starting from the origin O' and ending at the surface of the Ewald sphere 410 can be satisfied. In other words, the Bragg condition is satisfied and diffraction occurs only at the reciprocal lattice points located on the Ewald sphere 410. Figure 4a As schematically shown in , only those reciprocal lattice points 32 ′ that are located within the confining sphere 420 and that hit the surface of the Ewald sphere 410 will induce a detectable diffraction spot at the position 1032 on the X-ray detector 1030 .

[0063] Figure 4b Shown with Figure 4a Same Ewald sphere structure. The only difference is that the radius r' of the limiting sphere 420 is changed, for example, the pre-set minimum d-spacing value (corresponding to the limiting circle / sphere 424) and / or the maximum d-spacing value (corresponding to the limiting circle / sphere 422) is changed. The d-spacing value can be set by the user using the input unit 102. Therefore, by pre-setting the minimum and / or maximum d-spacing value, only the X-ray diffraction data (spots) exceeding the minimum value (inner circle 424), below the maximum value (outer circle 422), or located within the minimum d-spacing value and the maximum d-spacing value (inside circles 422, 424) are visible.

[0064] It is apparent that for a particular sample orientation, only a few lattice points 32' are located on the Ewald sphere surface 410 and induce detectable diffraction spots at positions 1032 on the X-ray detector surface. By rotating the sample 30 relative to the incident X-ray beam 10, the reciprocal lattice 30' of the sample 30 is also rotated (see Figure 4c ). The rotation of the reciprocal lattice 30' is given by Figure 4a In addition, Figure 4c The reciprocal lattice 30' of the sample is shown relative to Figure 4a Therefore, by rotating the sample 30, a new reciprocal lattice 32' will appear on the surface of the Ewald sphere, thereby forming diffraction spots at different angular positions on the X-ray detector 1030. Figure 4a and Figure 4c A comparison of clearly shows that the rotation of the sample induces diffraction spots at different 2θ angles and, therefore, at different positions on the detector surface.

[0065] from Figure 4a-4cIt can be clearly seen that the Ewald sphere structure provides a clear relationship between the 3D reciprocal lattice of the sample 30 and the X-ray diffraction pattern (i.e., the angular distribution of the diffraction spot) acquired by the detector 1030 for different rotational positions of the sample. Therefore, by knowing the parameter wavelength λ of the X-ray beam (and the corresponding Ewald sphere radius r), the rotational position of the sample 30, the detector size and the position of the detector relative to the sample 30, the mapping algorithm can reconstruct the entire reciprocal lattice 30' of the sample 30 based on the 2D diffraction pattern obtained for different rotational positions of the sample 30. Or in other words, by considering the wavelength λ of the incident X-ray beam 10, the rotational position of the sample 30, the detector size and the (radial and angular) position of the detector relative to the sample 30, the X-ray diffraction spots of the X-ray detector 1030 detected and imaged in the corresponding 2D image frame can be mapped to the corresponding positions in the 3D space so that the 3D reciprocal lattice can be reconstructed. This mapping of 2D image data to 3D reciprocal space is Figure 4a and Figure 4b It is shown in Figure 4a and Figure 4b A cubic space element 34' (or voxel) at a reciprocal space point 32' is shown associated with an X-ray diffraction spot detected at a detector position 1032 (or pixel position 1032). A set of consecutive 2D diffraction patterns at different rotational positions of the sample 30 is sufficient to reconstruct the 3D reciprocal lattice of the sample 30.

[0066] It is worth noting that the above-mentioned mapping algorithm based on Ewald sphere reconstruction maps only the crystallographically meaningful (sample-related) X-ray diffraction information that can be deduced from the 2D image frames into the 3D reciprocal space, while ignoring the background data, thereby obtaining a complete three-dimensional diffraction pattern in the 3D reciprocal space.

[0067] According to one variation, the 3D reciprocal space is rendered as a 3D raster graphic, wherein the reciprocal space is divided into a voxel grid. In other words, the 3D reciprocal space is divided into a 3D array of volume cells (i.e., voxels). The size of the voxels of the voxel grid (and the corresponding number of voxels) may be adjustable and may be selected so that the position, size, and shape of the diffracted X-ray beam are adequately resolved in the 3D reciprocal lattice presentation. It has been found that a voxel grid of 1024x1024x1024 voxels for representing the 3D reciprocal space is sufficient for most experimental needs. If the 3D reciprocal space is represented by a voxel grid, the mapping comprises mapping the 2D pixel image data of a 2D image frame (i.e., crystallographically meaningful / sample-related X-ray diffraction data) into corresponding voxels of the 3D voxel space. The mapping of 2D detector pixels to 3D voxels follows the combination of Figure 4a and Figure 4c The mapping algorithm explained. Returns Figure 3. After the mapping step S40 is performed, the mapped X-ray diffraction data of the 2D image frame is visualized in the 3D reciprocal space by the visualization unit 130. The visualization includes representing the mapped (sample-related) X-ray diffraction data (i.e., mapped diffraction beams, satellite beams and / or diffusely scattered X-rays) as 3D spots in the 3D reciprocal space. If the 3D reciprocal space is rendered as a raster graphic, each 3D spot is represented by at least one voxel. The number of voxels required to represent the 3D spot depends on the size and shape of the spot to be visualized in the 3D space. In turn, the size and shape of the 3D spot corresponds to the actual size and shape of the diffraction beam measured by the X-ray detector. Therefore, according to the data processing technology of the present invention, not only the position of the spot is mapped to the 3D space (i.e., the position where the X-ray beam is expected to appear in the reciprocal space), but also the shape and size are mapped. In addition, the mapping and visualization of the diffracted X-ray beam are performed in real time (i.e., as soon as a new 2D image frame with a diffracted X-ray beam appears).

[0068] Depending on the sample to be investigated, the mapping and visualization of the entire X-ray diffraction information can induce a dense diffraction pattern in the 3D reciprocal space, making individual diffraction spots almost difficult to distinguish from each other or from the background. In order to further improve the visualization, the visualization unit can provide a selection tool to the user (for example, a graphical user interface generated by the visualization unit 130), in which the user can define which mapped X-ray diffraction data should be visualized in the 3D reciprocal space. According to a variant, the user can define an intensity range for the mapped X-ray diffraction data that should preferably be visualized in the 3D reciprocal space by means of the selection tool. For example, the user can define a minimum intensity level (or a minimum intensity threshold) so that the visualization unit 130 can only visualize the mapped X-ray diffraction data associated with an intensity above the minimum intensity level (implemented with a so-called high-pass filter). It is also conceivable that the user defines a maximum intensity level (or a maximum intensity threshold) so that the visualization unit 130 can suppress the visualization of those mapped X-ray diffraction data that show an intensity above the maximum intensity level (implemented with a low-pass filter). It is also conceivable that the user defines a minimum intensity level and an upper intensity level so that the visualization unit 130 can only display those mapped X-ray diffraction data that show an intensity between the lower and upper intensity levels (implemented as a so-called bandpass filter). By setting the corresponding intensity levels (thresholds), different characteristics of the mapped 3D diffraction pattern can be visualized and studied. For example, the background and diffuse scattering parts of the mapping are reduced so that the 3D light spots representing the Bragg peaks are more clearly visible. It is also conceivable that the high-intensity Bragg peaks are suppressed so that the diffuse scattering parts are better visible.

[0069] Redundant information in the measured X-ray diffraction data is also visualized (and temporarily highlighted for the user's attention) so that a 3D reciprocal space view is built from all the measured information during the experiment. In normal operation, the redundant data will overlap. In the event that the measurement device is not operating correctly or the software calibration of the instrument's geometry is not accurate enough, the user will be able to see that the redundant data does not overlap and the 3D reciprocal space will show distorted, amplified or separated features in the diffracted beam.

[0070] In addition, 3D reciprocal space can be visualized in other projections. For example, X-ray diffraction data can be displayed on a graphical display in stereographic or centric plane projections, which can also help users to make an intuitive crystallographic interpretation of the data.

[0071] Obviously, the above method steps S10-S50 are repeated while rotating the sample, so that a complete 3D X-ray diffraction pattern (including artifacts but without background) can be generated and made visible.

[0072] Reference now Figure 5a-5d . Figure 5a-5d Images of 3D diffraction patterns obtained for different samples by the above-mentioned X-ray data processing technique are shown. Figure 5a-5d The image in shows a local bright spot corresponding to a diffraction peak in 3D reciprocal space. As mentioned in the background section above, a diffraction peak in 3D reciprocal space appears when the Bragg condition is met. Figure 5a-5d The light spots in the diffraction pattern follow specific patterns with specific symmetries. These patterns represent the reciprocal lattices of the sample under investigation. The reciprocal lattice is a lattice in reciprocal space. In turn, each reciprocal lattice can be associated with the real lattice structure of the sample (the Bravais lattice) by Fourier transformation. Therefore, the crystallographic properties of the sample, such as lattice structure, lattice symmetry, crystallization quality (crystallinity, presence of twins, interlayers), etc., can be easily inferred from the visualized diffraction pattern.

[0073] Furthermore, the X-ray data processing technique of the present invention allows visualization of less prominent features in addition to the main diffracted beam, such as diffusely scattered X-rays between the main spots (see e.g. Figure 4a ); bimodal structure (see e.g. Figure 5d ), which may indicate the presence of twins; superspots and lattice modulation (see e.g. Figure 5b ), which may indicate the presence of substructure in the sample; or multiple weaker satellite peaks (e.g. Figure 5c ) Therefore, using the technology of the present invention, all diffraction information can be obtained at a glance.

[0074] The above techniques can be applied to study powder or multi-particle samples through X-ray diffraction. Compared with single crystal samples, the 2D image frames obtained from these samples will contain more meaningful X-ray diffraction data because the diffraction takes the form of lines rather than isolated peaks. Therefore, more pixels from the 2D image frame will be mapped into the 3D reciprocal lattice, resulting in more densely packed voxels in the grid. In order to better visualize the data in this case, the d-spacing resolution value should be applied as a bandpass filter. In this case, the mapped X-ray diffraction data representing the X-ray d-spacing resolution value between the minimum and maximum values ​​can be visible in the 3D reciprocal space. In this filtered visualization, the user will be able to observe directional features in the data (for example, from fiber diffraction or oriented powder). From this visualization, the user can also generate pole figures, which are spherical polar plane projections that can represent the orientation distribution and texture analysis of the crystal lattice plane.

[0075] Compared to the evaluation or imaging techniques known in the prior art, the described technique has the following advantages. First, the overall diffraction information of the sample is illustrated / mapped into a single 3D space. There is no need to record a sequence of image frames and there is no need to compare different image frames of the sequence with each other. In addition, mapping the image data into a 3D reciprocal space eliminates the geometric distortions that occur due to measurements on a 2D detector. The 3D reciprocal space view provides the user with crystallographically meaningful and intuitive information. Therefore, compared to conventional X-ray imaging techniques, the crystallographic properties of the sample can be evaluated faster and the risk of missing important features (e.g., the presence of twins in the sample, superstructures, intermediate layers) is significantly reduced. In addition, mapping and imaging are performed in real time. This gives the user the opportunity to stop the X-ray diffraction analysis once sufficient information is received to estimate the sample quality. There is no need to wait until the entire sequence of image frames is obtained.

Claims

1. A method for processing X-ray diffraction data provided by an X-ray detector configured to detect a diffracted X-ray beam of a sample to be investigated, the method comprising the following steps: (a) acquiring X-ray diffraction data from the X-ray detector while the sample is rotated relative to an incident X-ray beam; (b) generating a 2D image frame from the acquired X-ray diffraction data, wherein the generated 2D image frame includes 2D image data, the 2D image data represents X-ray diffraction data for a specific rotational position of the sample, and the X-ray diffraction data includes sample-related X-ray diffraction data and background data; (c) for the generated 2D image frame, distinguishing the sample-related X-ray diffraction data from the background data; (d) mapping the differentiated sample-dependent X-ray diffraction data of the generated 2D image frames into a single 3D reciprocal space; and (e) visualizing the 3D reciprocal space and the mapped X-ray diffraction data together on a display screen; Therein, method steps (a) to (e) are continuously repeated while the rotational position of the sample changes.

2. The method according to claim 1, wherein: The acquired X-ray diffraction data comprises intensity data measured by the X-ray detector, and wherein method step (b) comprises converting the measured intensity data into corresponding 2D pixel image data.

3. The method according to claim 1, wherein: The distinguishing step includes distinguishing pixels of the 2D image frame representing sample-related X-ray diffraction data from pixels of the 2D image frame representing background data.

4. The method according to claim 3, wherein: The mapping step includes mapping 2D pixels representing the sample-related X-ray diffraction data into the 3D reciprocal space.

5. The method according to claim 1, wherein: The generated mapping of the X-ray diffraction data of the 2D image frame to the 3D reciprocal space is performed based on at least one of the following parameters: sample orientation, detector size, detector position relative to the sample, X-ray wavelength, and Ewald sphere geometry.

6. The method according to claim 1, wherein: The mapping step comprises reconstructing the X-ray diffraction data of the sample to be studied in the 3D reciprocal space based on a subset of the obtained X-ray diffraction data and known crystal symmetry; and wherein the visualization step comprises visualizing the reconstructed X-ray diffraction data on the display screen.

7. The method according to claim 1, wherein: The 3D reciprocal space is represented by a voxel grid, and wherein the mapping step comprises mapping the differentiated X-ray diffraction data of the 2D image frame onto corresponding voxels of the 3D reciprocal space.

8. The method according to claim 7, wherein: The mapped X-ray diffraction data representing the diffracted X-ray beam is visualized by at least one voxel in the 3D reciprocal space.

9. The method according to claim 1, wherein: The visualization step includes visualizing an empty 3D reciprocal space and continuously filling the empty 3D reciprocal space with the mapped X-ray diffraction data derived from the continuously generated 2D image frames.

10. The method according to claim 7, wherein: X-ray diffraction data that appear redundantly in two or more 2D image frames and are mapped to the same voxel position in the 3D reciprocal space are highlighted for a short time during the above-mentioned visualization step.

11. The method according to claim 1, wherein: The visualization of the mapped X-ray diffraction data is performed according to at least one pre-selected visualization parameter.

12. The method according to claim 11, wherein: The at least one pre-selected visualization parameter indicates a minimum intensity level and / or a maximum intensity level to be visualized, and wherein X-ray diffraction data representing X-ray intensities above the minimum intensity level, below the maximum intensity level, or mapped between the minimum intensity level and the maximum intensity level are visualized in the 3D reciprocal space.

13. The method according to claim 11, wherein: The at least one pre-selected visualization parameter indicates a minimum d-spacing value and / or a maximum d-spacing value to be visualized, and wherein mapped X-ray diffraction data representing d-spacing values ​​above a minimum value, below a maximum value, or between a minimum value and a maximum value are visualized in the 3D reciprocal space.

14. The method according to claim 1, wherein: The 3D reciprocal space visualized on the display screen is rotatable and / or scalable. 15 . A computer program product having a program code which, when the computer program product is run on a computer device, executes the method according to claim 1 .

16. An apparatus for processing X-ray diffraction data provided by an X-ray detector configured to detect diffracted X-rays of a sample to be investigated, the apparatus comprising: A processor configured to: (a) acquiring X-ray diffraction data from an X-ray detector while the sample is rotated relative to an incident X-ray beam; (b) generating a 2D image frame from the acquired X-ray diffraction data, wherein the 2D image frame includes 2D image data, the 2D image data represents X-ray diffraction data for a specific rotational position of the sample, and the X-ray diffraction data includes sample-related X-ray diffraction data and background data; (c) for the generated 2D image frame, distinguishing the sample-related X-ray diffraction data from the background data; (d) mapping the distinguished sample-dependent X-ray diffraction data of the 2D image frames into a single 3D reciprocal space; and (e) visualizing the 3D reciprocal space and the mapped X-ray diffraction data together on a display screen; Therein, method steps (a) to (e) are continuously repeated while the rotational position of the sample changes. 17 . The apparatus according to claim 16 , further comprising an input unit configured to receive at least one pre-selected visualization parameter.

18. An X-ray device for X-ray diffraction measurement, comprising: an X-ray detector configured to detect a diffracted X-ray beam of the sample to be investigated; The apparatus according to claim 16 or 17, which is used to process X-ray diffraction data acquired from the X-ray detector; and A display screen configured to display 3D reciprocal space and processed X-ray diffraction data.

Images