Virtual x-ray diffraction profile data creation device, virtual x-ray diffraction profile data creation method, program, and virtual x-ray diffraction profile data

Abstract

To create virtual X-ray diffraction profile data that enables detailed analysis of the crystalline characteristics of a target substance.SOLUTION: A virtual X-ray diffraction profile data creation device 1 of the present invention includes: a diffraction element derivation unit 116 that obtains, widths, shapes, and halo intensity of X-ray diffraction peaks, as virtual X-ray diffraction elements based on an X-ray diffraction pattern of a known target substance in which diffraction line positions (2θ) and X-ray intensity are represented in a bar graph; and a profile derivation unit 115 that obtains virtual profile data by applying, to the X-ray diffraction pattern, the virtual X-ray diffraction elements obtained by the diffraction element derivation unit 116, and determines this virtual profile data to be virtual X-ray diffraction profile data.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to a virtual X-ray diffraction profile data creation device, a virtual X-ray diffraction profile data creation method, a program, and virtual X-ray diffraction profile data. [Background technology]

[0002] Regarding the technology related to X-ray diffraction patterns used in the qualitative analysis of X-ray diffraction, Patent Document 1 discloses a method in which, when selecting strontium (Sr), aluminum (Al), lithium (Li) and oxygen (O), which are typical components of an inorganic luminescent material to be analyzed, compound information including these four elements is confirmed through inorganic crystal structure data (ICSD), a total of six random parameters are selected for background simulation, and a total of five random parameters are used for peak simulation. Then, a method is disclosed in which random noise data is added, and structural factors and thermal factors obtained from ICSD, multiplicity, Lorentz and polarization factors, absorption and preferred orientation are used as fixed variables, and at the same time, adjustable parameters such as peak profile (Caglioti and mixing parameters), background and white noise are used to obtain X-ray diffraction pattern data of a specific compound from ICSD crystal structure data by simulation.

[0003] The technique of Patent Document 1 is said to be capable of obtaining simulated X-ray diffraction pattern data that is very similar to the actual data. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2020-091872 A [Non-patent literature]

[0005] [Non-Patent Document 1] Kato et al., Development of Nd-saving magnets using Material DX, Materia, Vol. 60, No. 1 (2021) 57-59 Summary of the Invention [Problem to be solved by the invention]

[0006] However, in the technology of Patent Document 1, the simulated X-ray diffraction pattern data is constructed based on the peak and background. Therefore, it has not yet been possible to accurately simulate the X-ray diffraction profile. That is, in actual polycrystalline materials, the crystals that scatter X-rays mostly contain microcrystals or nanocrystals of, for example, μm to nm order, or amorphous components (halos). In contrast, the technology of Patent Document 1 does not take into account the crystallite size or lattice distortion in the simulation of the X-ray diffraction pattern, so there is a problem in that the width, shape, and intensity of the peak profile that appear in the X-ray diffraction of the above-mentioned actual material cannot be properly simulated.

[0007] On the other hand, standard peak search X-ray diffraction patterns (ICDD data) are generally used to analyze and identify unknown crystalline substances and crystalline materials measured using X-ray diffraction. In other words, unknown materials are identified and their crystal structures are analyzed by comparing the above-mentioned unknown measured X-ray diffraction profile with the standard peak search X-ray diffraction pattern. Here, the standard peak search X-ray diffraction pattern refers to a bar graph shown in a coordinate system consisting of the horizontal axis of 2θ value (diffraction angle) and the vertical axis of X-ray intensity, and exists as ICDD data.

[0008] However, in recent years, with the development of machine learning and the improvement in the processing power of information processing devices, a movement towards new research methods that utilize X-ray diffraction profile data to discover and investigate new substances has become apparent, as shown in Non-Patent Document 1.

[0009] X-ray diffraction profile data can be used as structural data that serves as explanatory variables, and there are efforts to derive it through machine learning that associates it with new material property data that serves as objective variables using analytical methods such as principal component analysis, and conversely, there are efforts to derive unknown structural data that can achieve material properties beyond human knowledge through machine learning. In this way, virtual X-ray diffraction profile data that contains a lot of information similar to actually measured X-ray diffraction profile data can be used in new material development methods, and there is a demand for the development of methods, creation devices, and creation programs for creating a large number of virtual X-ray diffraction profile data as big data.

[0010] The present invention has been made in consideration of the above-mentioned circumstances, and its purpose is to provide a virtual X-ray diffraction profile data creation device, a virtual X-ray diffraction profile data creation method, a program, and virtual X-ray diffraction profile data that have a large amount of information close to actually measured X-ray diffraction profile data, and that enable the creation of virtual X-ray diffraction profile data for crystalline substances and crystalline materials containing microcrystals and amorphous components, taking into account crystallite size and lattice distortion in particular. [Means for solving the problem]

[0011] As a result of intensive research to solve the above problems, the present inventors have found that the above object can be achieved by providing virtual profile data to an X-ray diffraction pattern of a known target substance, in which the position (2θ) of the diffraction line and the X-ray intensity are represented by a bar graph, with the width, shape and halo intensity of the X-ray diffraction peak as virtual X-ray diffraction elements.The present inventors have then completed the present invention.Specifically, the present invention provides the following.

[0012] The present invention provides a diffraction element deriving unit that determines the width, shape and halo intensity of an X-ray diffraction peak as virtual X-ray diffraction elements based on an X-ray diffraction pattern of a known target substance, the X-ray diffraction pattern being represented by a bar graph showing the position (2θ) of a diffraction line and the X-ray intensity; a profile derivation unit that obtains virtual profile data by applying the virtual X-ray diffraction elements obtained by the diffraction element derivation unit to the X-ray diffraction pattern, and sets the virtual profile data as virtual X-ray diffraction profile data; The virtual X-ray diffraction profile data creation device is characterized by having:

[0013] According to the above configuration, virtual profile data is obtained by adding virtual X-ray diffraction elements to an X-ray diffraction pattern, and virtual X-ray diffraction profile data can be created that has a lot of information similar to actually measured X-ray diffraction profile data and is particularly suitable for crystalline materials containing microcrystals or nanocrystals, and crystalline materials containing amorphous components (halos).

[0014] The reason why virtual X-ray diffraction profile data is particularly suitable for analyzing crystalline materials containing microcrystals and nanocrystals, and crystalline materials containing amorphous components (halos) will be explained. Conventional X-ray diffraction pattern data is constructed based on the peaks and background of known target substances, and does not take into account crystallite size and lattice distortion, so there is a problem that the width, shape, and intensity of the peak profile appearing in the X-ray diffraction of real materials such as those described above cannot be properly simulated. On the other hand, virtual X-ray diffraction profile data is constructed by adding the width, shape, and intensity of the halo of the X-ray diffraction peak to the X-ray diffraction pattern of a known target substance, which shows the position (2θ) of the diffraction line and the X-ray intensity as a bar graph, so that it more accurately reflects the structure of crystalline materials containing microcrystals and nanocrystals, and crystalline materials containing amorphous components (halos). As a result, virtual X-ray diffraction profile data can be obtained as X-ray diffraction profile data with a lot of information close to that of actually measured X-ray diffraction profile data. Effect of the Invention

[0015] According to the present invention, it is possible to create virtual X-ray diffraction profile data that contains a wealth of information close to actually measured X-ray diffraction profile data, particularly for crystalline materials that contain microcrystals or nanocrystals, and for crystalline materials that contain amorphous components (halos). [Brief description of the drawings]

[0016] [Figure 1] FIG. 1 is an explanatory diagram showing the flow of information in the virtual X-ray diffraction profile data generating device of this embodiment. [Diagram 2] FIG. 2 is an explanatory diagram showing the relationship between the X-ray diffraction pattern and the virtual X-ray diffraction profile data. [Diagram 3] FIG. 3 is an explanatory diagram showing the relationship between the X-ray diffraction pattern and the virtual X-ray diffraction profile data. [Figure 4] FIG. 4 is an explanatory diagram showing the relationship between the X-ray diffraction pattern and the virtual X-ray diffraction profile data. [Diagram 5] FIG. 5 is an explanatory diagram showing the flow of information in the crystal analysis device. [Figure 6] FIG. 6 is an explanatory diagram of actually measured X-ray diffraction profile data. [Figure 7] FIG. 7 is an explanatory diagram showing the state in which the measured X-ray diffraction profile data is subjected to principal component analysis and plotted in a principal component space. [Figure 8] FIG. 8 is an explanatory diagram showing a state in which actually measured X-ray diffraction profile data (circle marks) and virtual X-ray diffraction profile data (square marks) are subjected to principal component analysis and plotted in a principal component space. [Figure 9] FIG. 9 is an explanatory diagram showing the characteristic values ​​of plotted points in the principal component space displayed with color leveling (black, mesh 2 level, white). [Figure 10] FIG. 10 is an explanatory diagram showing the characteristic values ​​of plotted points in the principal component space displayed with color leveling (black, mesh 2 level, white). [Figure 11] FIG. 11 is an explanatory diagram showing a group of newly discovered materials and a material development area in a principal component space. [Figure 12] FIG. 12 is an explanatory diagram showing the flow of information in the crystal characteristic analysis support device. [Figure 13] FIG. 13 is a flowchart of a virtual X-ray diffraction profile data creation routine. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0017] Hereinafter, an example of an embodiment of the present invention will be described in detail with reference to the drawings. (Virtual X-ray diffraction profile data creation device 1) As shown in FIG. 1, the virtual X-ray diffraction profile data creation device 1 is configured to obtain virtual profile data by adding virtual X-ray diffraction elements to an X-ray diffraction pattern, and to create this virtual profile data as virtual X-ray diffraction profile data.

[0018] As a specific example, the virtual X-ray diffraction profile data creation device 1 has a creation control unit 11 which is a computer that creates virtual X-ray diffraction profile data. The creation control unit 11 is connected to a storage unit 2 such as a hard disk so as to be able to communicate data. The storage unit 2 has a second storage area 21 that stores virtual X-ray diffraction profile data and a first storage area 22 that stores X-ray diffraction pattern data.

[0019] In this embodiment, the case where the X-ray diffraction pattern data and the virtual X-ray diffraction profile data are stored in the same storage unit 2 will be described, but the present invention is not limited to this and they may be stored in separate storage units 2. The storage unit 2 may be configured with a hard disk, or may be configured with a combination of a hard disk and a memory. In the case of a configuration in which a hard disk and a memory are combined, some of the data and indexes used by the database are cached in the memory as necessary, thereby making it possible to speed up access to the database. The storage unit 2 may be a data server connected to an information and communication network such as the Internet 5.

[0020] The creation control unit 11 in the virtual X-ray diffraction profile data creation device 1 has a diffraction element derivation unit 116 that determines the width, shape and halo intensity of the X-ray diffraction peak as virtual X-ray diffraction elements based on the X-ray diffraction pattern of a known target substance in which the position (2θ) of the diffraction line and the X-ray intensity are represented by a bar graph, and a profile derivation unit 115 that determines virtual profile data by applying the virtual X-ray diffraction elements determined by the diffraction element derivation unit 116 to the X-ray diffraction pattern, and treats this virtual profile data as virtual X-ray diffraction profile data.

[0021] Here, the "position of the diffraction line (2θ)" is the angle at which the X-rays diffracted by the atoms in the crystal reach the detector when the X-rays are irradiated to the crystal. This angle is determined by the wavelength of the X-rays and the lattice constant of the crystal. 2θ is also called the diffraction angle. "X-ray intensity" is the strength at which the X-rays reach the detector. This strength varies depending on the X-ray irradiation intensity, the thickness of the crystal, the structure of the crystal, etc. "Known target substance" is a substance whose composition and structure are already known. In the X-ray diffraction method, it is possible to estimate the composition and structure of an unknown substance by comparing it with the X-ray diffraction pattern of a known target substance. Known target substances can be collected by accessing the Crystal Structure Database (CCDC), Protein Data Bank (PDB), Molecular Structure Database (MMDB), etc.

[0022] An "X-ray diffraction pattern" is a representation of the intensity of X-rays diffracted by a crystal at each angle when X-rays are irradiated onto the crystal. Since X-ray diffraction patterns reflect the structure of a crystal, it is possible to estimate the structure of the crystal by analyzing the X-ray diffraction pattern. "X-ray diffraction peak width" refers to the width of a peak in an X-ray diffraction pattern, and the width of the peak is expressed as the half-width of the peak. The half-width of the peak is the width at the position of half the height of the peak. The width of the peak is affected by factors such as the size of the crystal, the shape of the crystal, the anisotropy of the crystal, and the thickness of the sample. Specifically, the smaller the size of the crystal, the wider the width of the peak. This is because the area where X-rays are diffracted is smaller in small crystals. The more irregular the shape of the crystal, the wider the width of the peak. This is because the direction in which X-rays are diffracted is non-uniform in crystals with irregular shapes. The greater the anisotropy of the crystal, the wider the width of the peak. This is because the strength of X-rays diffracted is non-uniform in anisotropic crystals. The thicker the sample, the broader the peak will be, since a thicker sample has a larger area over which the X-rays are diffracted. Thus, the width of the X-ray diffraction peak can be used to obtain information about the crystal size, crystal shape, crystal anisotropy, sample thickness, etc.

[0023] "Halo intensity" is the strength of the halo in the X-ray diffraction pattern. A halo is a diffraction pattern caused by crystal impurities or crystal growth anomalies. The intensity of the halo is affected by the amount of crystal impurities and the degree of crystal growth anomalies. In other words, the greater the amount of crystal impurities, the stronger the halo intensity. This is because the greater the impurities, the wider the area over which X-rays are diffracted. The greater the degree of crystal growth anomalies, the stronger the halo intensity. This is because the greater the growth anomalies, the more non-uniform the direction in which X-rays are diffracted becomes. In this way, the intensity of the halo can be used to obtain information such as the amount of crystal impurities and the degree of crystal growth anomalies.

[0024] "Virtual X-ray diffraction profile data" is data obtained by calculation that is similar to the diffraction profile data obtained when an actual X-ray diffraction experiment is performed. Using this data, the crystal structure of a substance, the positions of atoms, the bond lengths of atoms, the bond angles of atoms, etc. can be analyzed. This allows the crystallinity and crystal distortion to be analyzed, allowing the crystalline characteristics of the target substance to be analyzed in detail. For example, using virtual X-ray diffraction profile data, it is possible to determine whether the crystal structure of a substance belongs to a tetragonal, cubic, hexagonal, etc. crystal system. In addition, by analyzing the positions of atoms, the detailed shape of the crystal structure of the substance can be revealed. Furthermore, by analyzing the bond lengths and bond angles of atoms, the chemical properties of the crystal structure of the substance can be revealed.

[0025] According to the virtual X-ray diffraction profile data creation device 1 configured as described above, virtual profile data is obtained by adding virtual X-ray diffraction elements to an X-ray diffraction pattern, and this virtual profile data is used as virtual X-ray diffraction profile data, thereby making it possible to create virtual X-ray diffraction profile data that contains a lot of information close to actually measured X-ray diffraction profile data.

[0026] The virtual X-ray diffraction profile data creation device 1 also has a peak height derivation unit 114 that calculates each peak height as a virtual X-ray diffraction element using an intensity ratio based on the crystal system, space group, lattice constant, diffraction angle, and peak integrated intensity of the target substance, a peak width / shape derivation unit 113 that calculates the width and shape of the peak in each peak profile as a virtual X-ray diffraction element using the half-width curve, crystallite size, and lattice distortion of the target substance, and a profile synthesis unit 111 that synthesizes the virtual X-ray diffraction element calculated in the peak height derivation unit 114 and the virtual X-ray diffraction element calculated in the peak width / shape derivation unit 113 into virtual profile data as theoretical profile data.

[0027] Here, the term "crystal system" refers to the regularity of the atomic arrangement of a crystal. The term "space group" refers to the positional relationship of the atoms of a crystal. The term "lattice constant" refers to the length of the unit cell of a crystal. The term "diffraction angle" refers to the difference between the angle of incidence and the angle of scattering of the scattered X-rays when the X-rays collide with the atoms of a crystal and are scattered. The "intensity ratio based on peak integrated intensity" is one of the indices used to analyze the crystal structure of a crystal, and is the value obtained by dividing the peak integrated intensity by the peak width. The peak integrated intensity is a value that represents the intensity of the entire peak, and the peak width is a value that represents the half-width at both ends of the peak.

[0028] A "half-width curve" is a curve that represents the width of a peak in the X-ray diffraction pattern of a crystal. The width at half the height of the peak is called the half-width, and the half-width curve is plotted with the half-width on the horizontal axis and the height of the peak on the vertical axis. The shape of the half-width curve is affected by the crystallite size and lattice distortion of the crystal. "Crystallite size" is the size of the smallest unit part of a crystal particle that can be regarded as a single crystal. The crystallite size has a significant effect on the physical and chemical properties of a substance; for example, the smaller the crystallite size, the higher the strength and hardness of the substance, and the lower the reactivity of the substance. Also, the smaller the crystallite size, the larger the half-width.

[0029] "Lattice distortion" is a state in which the atomic arrangement in a crystal is not regular, that is, a state in which distortion occurs in the lattice structure of a crystal. Lattice distortion occurs when there are defects in a crystal or when an external force is applied. Lattice distortion has a significant effect on the physical and chemical properties of a substance. For example, the presence of lattice distortion can reduce the strength and hardness of a substance and increase its electrical resistance. Furthermore, when lattice distortion is present, the crystal structure becomes irregular and the diffraction of X-rays becomes disordered, widening the half-width of the X-ray diffraction peak. Furthermore, the greater the lattice distortion, the wider the half-width becomes.

[0030] A "peak profile" is a curve that represents the shape of a peak in the X-ray diffraction pattern of a crystal. The width and shape of the peak are affected by the crystallite size and lattice distortion of the crystal. "Peak width and shape of a peak profile" are quantities that characterize the shape of a peak in an X-ray diffraction pattern. The half-width of a peak is the width at half the height of the peak. The shape of a peak is represented by the gradient on the left and right sides of the peak. The width and shape of a peak are affected by the crystallite size and lattice distortion of the crystal.

[0031] The virtual X-ray diffraction profile data creation device 1 having the above configuration can eliminate the influence of lattice distortion in the virtual profile data and calculate the amount of lattice distortion by synthesizing the theoretical profile data and the virtual profile data, thereby creating virtual X-ray diffraction profile data that enables more accurate analysis of the crystal structure.

[0032] The peak width / shape derivation unit 113 has a Lorentzian profile calculation unit 1134 that performs calculation processing of the Lorentzian profile, a Gaussian profile calculation unit 1133 that performs calculation processing of the Gaussian profile, a pseudo-Voigt profile calculation unit 1132 that performs calculation processing of the pseudo-Voigt profile, and a selection unit 1131 that selects the Lorentzian profile calculation unit 1134 to calculate the crystallite size, selects the Gaussian profile calculation unit 1133 to calculate the lattice strain, and selects the pseudo-Voigt profile calculation unit 1132 when calculating the crystallite size and the lattice strain simultaneously. That is, the peak width / shape derivation unit 113 has a configuration that selectively uses the Lorentzian profile to calculate the crystallite size, the Gaussian profile to calculate the lattice strain, and the pseudo-Voigt profile when calculating the crystallite size and the lattice strain simultaneously.

[0033] Here, the "Lorentzian profile" is a profile used when the X-ray diffraction peak is sharp and narrow. The Gaussian profile is a profile used when the X-ray diffraction peak is round and wide. The pseudo-Voigt profile is a profile in which the Lorentzian and Gaussian profiles are superimposed. The Lorentzian is used to calculate the crystallite size. The Gaussian profile is used to calculate the lattice distortion. The pseudo-Voigt profile is used to calculate both the crystallite size and the lattice distortion simultaneously. This is because the shape of the X-ray diffraction peak can be more accurately expressed by superimposing the Lorentzian and Gaussian profiles.

[0034] According to the virtual X-ray diffraction profile data creation device 1 having the above-mentioned configuration, by using different profiles, it is possible to obtain more detailed theoretical profile data, and by combining this with the virtual profile data, it is possible to create more accurate virtual X-ray diffraction profile data.

[0035] The virtual X-ray diffraction profile data creation device 1 also has a theoretical profile derivation unit 112 that determines theoretical profile data by performing calculations using all of the profile function of the X-ray diffraction peak, the wavelength of the characteristic X-rays, the selection of the presence or absence of Kα2, the application of non-uniform strain, and the crystallite size, and a profile synthesis unit 111 that synthesizes the theoretical profile data determined by the theoretical profile derivation unit 112 into virtual profile data.

[0036] Here, the "profile function" is a function that describes the shape of the X-ray diffraction peak. Examples of profile functions include the Lorentzian profile, Gaussian profile, and pseudo-Voigt profile mentioned above. The "wavelength of characteristic X-rays" is used to determine the lattice constant of a crystal in crystal structure analysis. Characteristic X-rays are X-rays emitted from atoms, and their wavelengths vary depending on the type of atom. In crystal structure analysis, the lattice constant of a crystal can be determined by measuring the wavelength of the characteristic X-rays. The "selection of the presence or absence of Kα2" is used to evaluate the lattice distortion of a crystal in crystal structure analysis. Kα1 and Kα2 are two types of wavelengths of characteristic X-rays. Kα1 has a shorter wavelength than Kα2, so it is more susceptible to lattice distortion than Kα2. Therefore, by selecting the presence or absence of Kα2, the lattice distortion of a crystal can be evaluated more accurately.

[0037] "Adding non-uniform strain" is used in crystal structure analysis to evaluate lattice strain in crystals. Non-uniform strain means that the crystal lattice is not uniform. By adding non-uniform strain, the peaks in the crystal's diffraction pattern are distorted, allowing for more accurate evaluation of lattice strain. "Crystallite diameter (also called crystallite size)" is the size of the crystal grain. In crystal structure analysis, the crystallite diameter can be determined from the width of the peak in the crystal's diffraction pattern. The smaller the crystallite diameter, the wider the width of the X-ray diffraction peak.

[0038] According to the virtual X-ray diffraction profile data creation device 1 having the above configuration, the shape of the X-ray diffraction peak in the theoretical profile data can be more accurately expressed by using the profile function of the X-ray diffraction peak, the wavelength of the characteristic X-ray, the selection of the presence or absence of Kα2, the application of non-uniform strain, and the crystallite size. As a result, by combining the theoretical profile data and the virtual profile data, it is possible to create more accurate virtual X-ray diffraction profile data.

[0039] (Example of virtual X-ray diffraction profile data) 2, 3 and 4 are specific examples of the virtual X-ray diffraction profile data created by the virtual X-ray diffraction profile data creation device 1.

[0040] The virtual X-ray diffraction profile data in Figures 2, 3, and 4 are created through the following processing steps. Specifically, intensity ratio data based on the crystal system, space group, lattice constant, diffraction angle, and peak integrated intensity of the target substance is used to set appropriate half-width curves, crystallite diameters, and lattice distortions, and calculate the heights of individual peaks. Appropriate values ​​are verified by randomly comparing with measured X-ray diffraction data of similar substances.

[0041] Next, a process is carried out to adjust the width and shape of the peak profile by setting the half-width curve, crystallite size, and lattice distortion. The Lorentzian profile is used to calculate the crystallite size, the Gaussian profile is used to calculate the lattice distortion, and if both are present, a pseudo-Voigt profile is used to create the final profile. The ratio of the Gaussian and Lorentzian profiles can be adjusted by comparing with the measured X-ray diffraction profile, and the symmetry of the peak can also be adjusted. It is also possible to add an amorphous halo to the Lorentzian profile.

[0042] Next, a calculation process is carried out using all of the X-ray diffraction conditions, including the setting of the profile function of the diffraction peaks mentioned above, the wavelength of the characteristic X-rays, the selection of the presence or absence of Kα2, the quantitative addition of non-uniform strain, and the crystallite size, to create the virtual X-ray diffraction profile data shown in Figures 2-3-4 below.

[0043] FIG. 2 is a graph of metal / Pt (target substance) in a coordinate system with the X-ray diffraction angle 2θ on the horizontal axis and the X-ray intensity on the vertical axis. The upper figure is a graph of virtual X-ray diffraction profile data when the crystallite diameter is 80 nm, 10 nm, 5 nm, and 2 nm, i.e., a virtual X-ray diffraction profile, and the lower figure is a bar graph of standard peak search X-ray diffraction pattern (ICDD data) which is an X-ray diffraction pattern. Note that ICDD is an abbreviation for International Centre for Diffraction Data. Even if Patent Document 1 is used, it is not possible to derive the difference in X-ray diffraction profile data depending on various crystallite diameters as shown in FIG. 2. Therefore, the graph in FIG. 2, which shows different virtual X-ray diffraction profile data depending on the crystallite diameter, is one of the results that clearly illustrates the features of the present invention.

[0044] Figure 3 shows the relationship between LiB positive electrode material and LiFePO in a coordinate system where the horizontal axis is the X-ray diffraction angle 2θ and the vertical axis is the X-ray intensity. 4 This is a graph for (target substance). The upper graph is a virtual X-ray diffraction profile, and the lower graph is a bar graph of the standard peak search X-ray diffraction pattern (ICDD data), which is an X-ray diffraction pattern.

[0045] Figure 4 shows the relationship between the LiB anode material and Li in a coordinate system where the horizontal axis is the X-ray diffraction angle 2θ and the vertical axis is the X-ray intensity. 4 Ti 5 O 12 This is a graph for (target substance). The upper graph is a virtual X-ray diffraction profile, and the lower graph is a bar graph of the standard peak search X-ray diffraction pattern (ICDD data), which is an X-ray diffraction pattern.

[0046] (Application example 1 of virtual X-ray diffraction profile data) The virtual X-ray diffraction profile data generated as described above is used in one or more multivariate analyses, such as principal component analysis, factor analysis, cluster analysis, multiple regression analysis, discriminant analysis, and logistic regression analysis.

[0047] Here, "principal component analysis" is a method of extracting a small number of components called principal components from multivariate data and using these components to explain the majority of the data. With X-ray diffraction profile data, the structure of a crystal can be expressed concisely by performing principal component analysis using diffraction intensity as a variable. "Factor analysis" is a method of extracting latent variables called factors from multivariate data and using these factors to explain the majority of the data. With X-ray diffraction profile data, the properties of a crystal can be expressed concisely by performing factor analysis using diffraction intensity as a variable.

[0048] "Cluster analysis" is a method of dividing similar data into groups from multivariate data. For X-ray diffraction profile data, cluster analysis can be performed using diffraction intensity as a variable to group crystal structures. "Multiple regression analysis" is a method of predicting dependent variables from independent variables. For X-ray diffraction profile data, multiple regression analysis can be performed using diffraction intensity as an independent variable to predict crystal structures. "Discrimination analysis" is a method of analyzing the characteristics of grouped data and predicting which group new data will belong to. For X-ray diffraction profile data, discriminant analysis can be performed using diffraction intensity as a variable to identify or predict new crystal structures. "Logistic regression analysis" is a method of predicting categorical variables that can only take finite values. For X-ray diffraction profile data, logistic regression analysis can be performed using diffraction intensity as a variable to predict crystal differences and the probability of substance reactions.

[0049] These multivariate analysis methods are widely used to understand the structure and properties of crystals and to develop new crystals. Virtual X-ray diffraction profile data allows us to analyze and predict the properties, density, classification, etc. of crystal structures.

[0050] (Application example 1 of virtual X-ray diffraction profile data: Crystallography device 7) A crystal analysis device 7 that performs crystallinity analysis, crystal strain analysis, and multivariate analysis on virtual X-ray diffraction profile data will be described. As shown in FIG. 5, the crystal analysis device 7 has an analysis control unit 71 that analyzes virtual X-ray diffraction profile data. The analysis control unit 71 has a diffraction element selection unit 714 that selects whether to analyze crystallinity or crystal strain depending on which profile of the Lorentzian profile, Gaussian profile, and pseudo-Voigt profile the virtual X-ray diffraction element is calculated from, a crystallinity analysis unit 712 that is selected when the virtual X-ray diffraction element is calculated from the Lorentzian profile or the Gaussian profile, a crystal strain analysis unit 713 that is selected when the virtual X-ray diffraction element is calculated from the Lorentzian profile or the pseudo-Voigt profile, and a multivariate analysis unit 711 that performs multivariate analysis on the virtual X-ray diffraction profile data analyzed in the crystallinity analysis unit 712 and the crystal strain analysis unit 713.

[0051] The crystal analysis device 7 is capable of data communication with the user terminal 3 via the Internet 5. The user terminal 3 is an information processing device such as a general personal computer, laptop computer, smartphone, tablet terminal, etc. The crystal analysis device 7 reads out the virtual X-ray diffraction profile data to be analyzed from the storage unit 2 in response to an instruction from a user 4, such as a researcher or developer, who operates the user terminal 3, and selectively performs crystallinity analysis, crystal strain analysis, and multivariate analysis on the virtual X-ray diffraction profile data. As a result, the crystal analysis device 7 displays the analysis results of the crystallinity and crystal strain of the virtual X-ray diffraction profile data and the analysis results of the multivariate analysis on the user terminal 3 via the Internet 5, thereby enabling the user 4 to understand the crystal characteristics of the virtual X-ray diffraction profile data.

[0052] Data communication between crystal analysis apparatus 7 and user terminal 3 is not limited to Internet 5, but may use an information communication network such as a dedicated line or a LAN (Local Area Network), or may use Bluetooth (registered trademark), which is a wireless communication standard for short-distance communication. Data communication may also be via a dedicated line.

[0053] (Virtual X-ray diffraction profile data and the collaboration with the Crystallography Instrument 7) The analysis control unit 71 in the crystal analysis device 7 corresponds to a computer. Therefore, the virtual X-ray diffraction profile data is applied to a computer having a crystallinity analysis unit 712 that analyzes crystallinity and a crystal distortion analysis unit 713 that analyzes crystal distortion. The virtual X-ray diffraction profile data has virtual profile data in which the width, shape and halo intensity of the X-ray diffraction peak are added as virtual X-ray diffraction elements to an X-ray diffraction pattern of a known target substance, in which the position (2θ) of the diffraction line and the X-ray intensity are represented by a bar graph, and has a structure used in a process of analyzing the crystal characteristics of the target substance by having the crystallinity analysis unit 712 analyze the crystallinity of the target substance using the virtual X-ray diffraction elements and having the crystal distortion analysis unit 713 analyze the crystal distortion of the target substance using the virtual X-ray diffraction elements.

[0054] The virtual X-ray diffraction profile data having the above configuration is configured by adding the width, shape and halo intensity of the X-ray diffraction peak to the X-ray diffraction pattern of a known target substance, which shows the position (2θ) of the diffraction line and the X-ray intensity as a bar graph, so that it is possible to more accurately express the X-ray diffraction profile of a microcrystalline material or a crystalline substance or material containing an amorphous component, taking into account the crystallite size and lattice distortion. As a result, by utilizing the virtual X-ray diffraction profile data, for example, even when a standard peak search X-ray diffraction pattern is used, the crystallinity and crystal distortion can be analyzed with the virtual X-ray diffraction element, allowing for detailed analysis of the crystalline characteristics of the target substance.

[0055] Moreover, the virtual X-ray diffraction profile data has a structure used for processing to analyze the crystal characteristics of the target substance by having the crystal distortion analysis unit 713 analyze the crystallinity of the target substance when a virtual X-ray diffraction element calculated by a Lorentzian profile is used, having the crystallinity analysis unit 712 analyze the crystal distortion of the target substance when a virtual X-ray diffraction element calculated by a Gaussian profile is used, and having the crystal distortion analysis unit 713 and the crystallinity analysis unit 712 analyze the crystallinity and crystal distortion of the target substance when a virtual X-ray diffraction element calculated by a pseudo-Voigt profile is used. This makes it possible to estimate and analyze the crystal characteristics of the virtual X-ray diffraction profile data with high accuracy by selectively using the crystal distortion analysis unit 713 and the crystallinity analysis unit 712 depending on the profile.

[0056] Furthermore, the virtual X-ray diffraction profile data has a structure that allows a computer to process any one of multivariate analyses such as principal component analysis, factor analysis, cluster analysis, multiple regression analysis, discriminant analysis, and logistic regression analysis, thereby making it possible to analyze and predict the characteristics, density, classification, etc. of a crystal structure using the virtual X-ray diffraction profile data.

[0057] In addition, a profile identification code indicating the type of each profile may be added to the virtual X-ray diffraction profile data so that the computer can determine whether the virtual X-ray diffraction element is calculated using the Lorentzian profile, the Gaussian profile, or the pseudo-Voigt profile. For example, the identification code of the Lorentzian profile is set to "P01", the identification code of the Gaussian profile is set to "P02", and the identification code of the pseudo-Voigt profile is set to "P03", and these are incorporated into the profile identification region of the virtual X-ray diffraction profile data.

[0058] According to the above configuration, when the computer performs analysis processing using virtual X-ray diffraction profile data, it is possible to determine the processing in the crystal distortion analysis unit 713 and the crystallinity analysis unit 712 by reading the profile identification code in the profile identification area and identifying in which profile the virtual X-ray diffraction element was obtained.

[0059] (Application example 2 of virtual X-ray diffraction profile data) We will explain how virtual X-ray diffraction profile data can be applied to the development of new materials with superior properties.

[0060] First, the X-ray diffraction profile of the compound under study is measured. For example, as shown in Figure 6, the X-ray diffraction profiles of compounds No. 1 to No. 12 are measured from 2θ of 5 to 145 deg with an interval of 0.01 deg, and 14,000-dimensional data are obtained for each compound No. 1 to No. 12.

[0061] Next, the measured X-ray diffraction profile data of compounds No. 1 to No. 12 are subjected to principal component analysis. The results of the principal component analysis are plotted as circle marks on a principal component space consisting of the first and second principal components, as shown in FIG. 7, and the characteristic values ​​of these plotted compounds No. 1 to No. 12 are leveled by color (black, mesh 2 level, white). The plot in FIG. 7 shows a gradation color bar 90 in four stages of gray scale, with the color changing from white on the lower side to black on the upper side in sequence. In this embodiment, in a basic experiment of purifying hydrocarbons (HC), which are air pollutants, the purification rate (%) of HC as a catalyst is set as a characteristic value of the material and is associated with the color of the gradation color bar 90. In addition to such catalytic properties, various material properties such as battery properties, mechanical properties, and thermal conductivity properties may be exemplified as the properties of the material.

[0062] Next, as shown in FIG. 8, the virtual X-ray diffraction profile data is subjected to principal component analysis and plotted in the principal component space with square marks. Then, as shown in FIG. 9, the material corresponding to the virtual X-ray diffraction profile data is determined as a new candidate material, and the result of evaluating the purification rate, which is its characteristic, is displayed in each plot with color leveling (black, mesh 2 level, white). It is not necessary to evaluate the characteristics of all the candidate materials. In addition to the principal component analysis, the virtual X-ray diffraction profile data may be subjected to multivariate analysis such as one or more of factor analysis, cluster analysis, multiple regression analysis, discriminant analysis, and logistic regression analysis.

[0063] After this, in addition to the existing compounds No. 1, 11, and 12 with good properties, a completely new material with good properties may be discovered from among the new candidate materials in the virtual X-ray diffraction profile data, as shown in Figure 10. In this case, as shown in Figure 11, a new region 91 indicated by a dashed dotted line, which is a group of materials in which a completely new material has been discovered, and a dotted new material development region 92, which indicates a range including existing materials with good properties, are identified.

[0064] By discovering a new region 91 and a new material development region 92 using the virtual X-ray diffraction profile data according to the above procedure, a completely new material or a development region for the next new material (regions 91 and 92 indicated by dotted and dashed lines) is clarified. That is, according to the above procedure, by performing principal component analysis on the X-ray diffraction profile data, each material can be plotted in an axis space as a feature quantity, and by providing a guide (such as color coding) indicating the characteristics in the plot data, materials with better characteristics can be identified. In addition, by plotting the virtual X-ray diffraction profile data provided by the present invention on the above principal component space, candidates for new materials with better characteristics can be found. That is, when a characteristic evaluation is performed on the plot points obtained by principal component analysis of the virtual X-ray diffraction profile data, the material regions with better characteristics (new region 91 and new material development region 92) become clearer, and new materials can be discovered, and the regions 91 and 92 for the development of the next new material are also clarified.

[0065] In this manner, when a new group of materials or new development areas 91 and 92 with excellent properties beyond human knowledge are discovered, it becomes possible to use a machine learning model to determine whether the virtual X-ray diffraction profile data of the test subject is a compound present in the new development areas 91 or 92.

[0066] Specifically, the results of principal component analysis of a plurality of actually measured X-ray diffraction profiles of compounds No. 1 to No. 12, etc., and virtual X-ray diffraction profile data created by the present invention from known compound data (ICDD, etc.) are plotted with characteristic values ​​in a principal component space consisting of a first principal component and a second principal component, and the areas of a group of plots having characteristic values ​​equal to or greater than a predetermined value (new material groups or development areas 91 and 92) are associated with the virtual X-ray diffraction profile data and used as training data for the machine learning model. Then, when training of the machine learning model using the training data is completed, a judgment using the feature amounts in the virtual X-ray diffraction profile data is performed using the machine learning model.

[0067] As a result, when new virtual X-ray diffraction profile data to be newly inspected is input, it becomes possible to use the already machine-learned model to determine whether or not the new virtual X-ray diffraction profile data exists in the new material group or development area 91 or 92. Furthermore, if the amount of data used for the machine learning model is increased and training is continued, it becomes possible to realize determination with higher accuracy, and at the same time, it is possible to further expand the new material group and development area.

[0068] (Application example 3 of virtual X-ray diffraction profile data) The virtual X-ray diffraction profile data can be used, by converting the coordinate system graph data into text, as a database for a language model of natural language processing that supports the analysis of crystal properties, or in a crystal property analysis support device 8 that supports analysis and interpretation by the user 4.

[0069] Specifically, as shown in FIG. 12, the crystal property analysis support device 8 has a virtual X-ray diffraction profile database 822 in which virtual X-ray diffraction profile data is stored in a normalized state in a unified data format so that it can be adapted to the learning of a language model for natural language processing, and a support information generation unit 811 that generates support information to support the analysis of crystal properties based on the virtual X-ray diffraction profile database 822 by combining one or more types of natural language processing and utilizing a language model that has been trained and adjusted to be specialized for the analysis of crystal properties, depending on the content of the prompt.

[0070] The virtual X-ray diffraction profile database 822 is stored in a storage unit 82, and the support information generating unit 811 is provided in a support control unit 81 which is a computer. The storage unit 82 may be configured with a hard disk, or may be configured with a combination of a hard disk and a memory, or may be a data server connected to an information communication network such as the Internet 5.

[0071] When an analysis support system is constructed by connecting the crystal property analysis support device 8 configured as described above, the crystal analysis device 7, one or more user terminals 3, and various web pages and databases in a manner enabling data communication via the Internet 5 or the like, the virtual X-ray diffraction profile database 822 is updated with the latest data, and the user 4 can analyze the analysis results of the crystal analysis device 7 and develop new materials while receiving conversational support from the crystal property analysis support device 8.

[0072] (Virtual X-ray diffraction profile data creation program) 1, the profile synthesis unit 111, theoretical profile derivation unit 112, peak width / shape derivation unit 113, peak height derivation unit 114, profile derivation unit 115, and diffraction element derivation unit 116 may be configured as either hardware or software. When each of the units 111 to 116 is configured as software, the creation control unit 11 is made to execute a program for obtaining virtual profile data by adding virtual X-ray diffraction elements to an X-ray diffraction pattern, and creating this virtual profile data as virtual X-ray diffraction profile data.

[0073] 13, a specific example is shown. The virtual X-ray diffraction profile data creation program causes the computer, which is the creation control unit 11 of the virtual X-ray diffraction profile data creation device 1, to execute a diffraction element derivation processing step (S1) for determining the width, shape and halo intensity of the X-ray diffraction peak as virtual X-ray diffraction elements based on the X-ray diffraction pattern of a known target material in which the position (2θ) of the diffraction line and the X-ray intensity are represented by a bar graph, and a profile derivation processing step (S2) for determining virtual profile data by applying the virtual X-ray diffraction elements determined in the diffraction element derivation processing step (S1) to the X-ray diffraction pattern, and for making the virtual profile data into virtual X-ray diffraction profile data. According to the above program, by analyzing the crystallinity and crystal distortion with the virtual X-ray diffraction elements, virtual X-ray diffraction profile data that can analyze the crystal characteristics of the target material in detail can be created.

[0074] Furthermore, the virtual X-ray diffraction profile data creation program causes the computer of the virtual X-ray diffraction profile data creation device 1 to execute a peak height derivation process step (S3) for calculating each peak height as a virtual X-ray diffraction element using an intensity ratio based on the crystal system, space group, lattice constant, diffraction angle, and peak integrated intensity of the target substance, a peak width and shape derivation process step (S4) for calculating the width and shape of the peak of each peak profile as a virtual X-ray diffraction element using the half-width curve, crystallite size, and lattice distortion of the target substance, a theoretical profile derivation process step (S5) for making the virtual X-ray diffraction element obtained in the peak height derivation process step (S3) and the virtual X-ray diffraction element obtained in the peak width and shape derivation process step (S4) into theoretical profile data, and a profile synthesis process step (S6) for synthesizing the theoretical profile data into virtual profile data. As a result, by synthesizing the theoretical profile data and the virtual profile data, the influence of the lattice distortion of the virtual profile data can be removed, and virtual X-ray diffraction profile data that enables more accurate analysis of the crystal structure can be created.

[0075] In addition, it is preferable that the peak width / shape derivation processing step (S4) selects Lorentzian profile calculation processing for calculating crystallite size, selects Gaussian profile calculation processing for calculating lattice distortion, and allows selection of pseudo-Voigt profile calculation processing when simultaneously calculating crystallite size and lattice distortion. In this case, since the theoretical profile data can be obtained in more detail by using different profiles, it is possible to create more accurate virtual X-ray diffraction profile data by combining it with the virtual profile data.

[0076] According to the program configured as described above, it is possible to create virtual X-ray diffraction profile data that can analyze the crystal characteristics of a target substance in detail. Furthermore, by simply installing the program in an information processing device such as a personal computer or a tablet terminal, the information processing device can be made to function as the virtual X-ray diffraction profile data creation device 1. The program may be distributed in a state recorded on a computer-readable recording medium such as a CD-ROM or a USB memory, or may be distributed via a two-way communication network or communication line such as the Internet or a one-way communication network such as a television broadcast.

[0077] (Virtual X-ray diffraction profile data creation method) A part or all of the processing steps in the virtual X-ray diffraction profile data creation program may be configured by hardware. That is, the virtual X-ray diffraction profile data creation device 1 may be configured to be able to execute the virtual X-ray diffraction profile data creation method. Specifically, the virtual X-ray diffraction profile data creation method includes a diffraction element derivation processing step of determining the width, shape, and halo intensity of an X-ray diffraction peak as virtual X-ray diffraction elements based on an X-ray diffraction pattern of a known target substance in which the position (2θ) of the diffraction line and the X-ray intensity are represented by a bar graph, and a profile derivation processing step of determining virtual profile data by applying the virtual X-ray diffraction elements determined in the diffraction element derivation processing step to the X-ray diffraction pattern, and making the virtual profile data into virtual X-ray diffraction profile data. That is, the virtual X-ray diffraction profile data creation method includes the processing steps (S1) to (S6) of FIG. 13.

[0078] The virtual X-ray diffraction profile data created as described above may be recorded on a computer-readable recording medium. That is, the virtual X-ray diffraction profile data includes virtual profile data in which the width, shape and halo intensity of the X-ray diffraction peak obtained based on the X-ray diffraction pattern of a known target substance, which is a bar graph showing the positions (2θ) of the diffraction lines and the X-ray intensities, are assigned to the X-ray diffraction pattern as virtual X-ray diffraction elements, and has a structure used in a process for analyzing the crystal characteristics of the target substance, and may be recorded on a computer-readable recording medium.

[0079] It should be noted that within the scope of the concept of the present invention, a person skilled in the art may come up with various modifications and alterations. It is understood that such modifications and alterations fall within the scope of the present invention. For example, even if a person skilled in the art appropriately adds, deletes, or modifies the design of the above-described embodiment, or adds, omits, or modifies the conditions of a process, these modifications and alterations are included in the scope of the present invention as long as they include the gist of the present invention. [Explanation of symbols]

[0080] 1. Virtual X-ray diffraction profile data creation device 11 Creation control section 111 Profile synthesis unit 112 Theoretical Profile Derivation 113 Peak width and shape calculation section 1131 Selection Section 1132 Pseudo-Voigt Profile Calculation Unit 1133 Gaussian Profile Calculation Unit 1134 Lorentzian Profile Calculation Unit 114 Peak height derivation part 115 Profile Derivation Unit 116 Diffraction element lead-out section 2 Storage section 21 2nd storage area 22 1st storage area 3. User terminal 4 User 5. Internet 7 Crystal analyzer 8 Crystal property analysis support equipment 90 Gradient Color Bar 91 New materials and new material development areas 92 New materials and new material development areas

Claims

1. a diffraction element deriving unit for determining the width, shape and halo intensity of an X-ray diffraction peak as virtual X-ray diffraction elements based on an X-ray diffraction pattern of a known target substance, the X-ray diffraction pattern being represented by a bar graph showing the position (2θ) of a diffraction line and the X-ray intensity; a profile derivation unit that obtains virtual profile data by applying the virtual X-ray diffraction elements obtained by the diffraction element derivation unit to the X-ray diffraction pattern, and sets the virtual profile data as virtual X-ray diffraction profile data; A virtual X-ray diffraction profile data creation device comprising:

2. a peak height deriving unit that calculates each peak height as the virtual X-ray diffraction element by using an intensity ratio based on a crystal system, a space group, a lattice constant, a diffraction angle, and a peak integrated intensity of the target substance; a peak width / shape deriving unit that calculates the width and shape of a peak in each peak profile as the virtual X-ray diffraction element using a half-width curve, a crystallite size, and a lattice distortion of the target substance; a profile synthesis unit that synthesizes the virtual X-ray diffraction element obtained by the peak height derivation unit and the virtual X-ray diffraction element obtained by the peak width / shape derivation unit into the virtual profile data as theoretical profile data; 2. The virtual X-ray diffraction profile data generating device according to claim 1, further comprising:

3. The peak width / shape deriving unit The virtual X-ray diffraction profile data creation device according to claim 2, characterized in that a Lorentzian profile is used to calculate the crystallite size, a Gaussian profile is used to calculate the lattice distortion, and a pseudo-Voigt profile is selectively used when the crystallite size and the lattice distortion are simultaneously calculated.

4. a theoretical profile derivation unit for determining theoretical profile data by performing calculations using all of the profile function of the X-ray diffraction peak, the wavelength of the characteristic X-ray, the selection of the presence or absence of Kα2, the application of non-uniform strain, and the crystallite size; a profile synthesis unit that synthesizes the theoretical profile data obtained by the theoretical profile derivation unit with the virtual profile data; 2. The virtual X-ray diffraction profile data generating device according to claim 1, further comprising:

5. The virtual X-ray diffraction profile data is 2. The virtual X-ray diffraction profile data generating device according to claim 1, which is used for any one of multivariate analyses including principal component analysis, factor analysis, cluster analysis, multiple regression analysis, discriminant analysis, and logistic regression analysis.

6. a diffraction element derivation process for determining the width, shape and halo intensity of the X-ray diffraction peak as virtual X-ray diffraction elements based on the X-ray diffraction pattern of a known target substance, the X-ray diffraction pattern being represented by a bar graph showing the position (2θ) of the diffraction line and the X-ray intensity; a profile derivation process step of determining virtual profile data by applying the virtual X-ray diffraction elements determined in the diffraction element derivation process step to the X-ray diffraction pattern, and setting the virtual profile data as virtual X-ray diffraction profile data; A method for creating virtual X-ray diffraction profile data, comprising:

7. On the computer, a diffraction element derivation process step for determining the width, shape and halo intensity of the X-ray diffraction peak as virtual X-ray diffraction elements based on the X-ray diffraction pattern of a known target substance, the X-ray diffraction pattern being represented by a bar graph showing the position (2θ) of the diffraction line and the X-ray intensity; a profile derivation processing step of determining virtual profile data by applying the virtual X-ray diffraction elements determined in the diffraction element derivation processing step to the X-ray diffraction pattern, and setting the virtual profile data as virtual X-ray diffraction profile data; A program for executing.

8. A computer-readable recording medium having recorded thereon virtual X-ray diffraction profile data having a structure used in processing to analyze the crystalline characteristics of the target substance, the virtual X-ray diffraction profile data being provided with virtual profile data in which the width, shape and halo intensity of X-ray diffraction peaks determined based on an X-ray diffraction pattern of a known target substance, the X-ray diffraction pattern being represented by a bar graph showing the position (2θ) of the diffraction line and the X-ray intensity, are assigned to the X-ray diffraction pattern as virtual X-ray diffraction elements.

9. A virtual X-ray diffraction profile data applied to a computer having a crystallinity analysis unit that analyzes crystallinity and a crystal distortion analysis unit that analyzes crystal distortion, The method has hypothetical profile data in which the width, shape and halo intensity of the X-ray diffraction peak are assigned as hypothetical X-ray diffraction elements to an X-ray diffraction pattern of a known target substance, the X-ray diffraction pattern being represented by a bar graph showing the position (2θ) of the diffraction line and the X-ray intensity; causing the crystallinity analysis unit to analyze the crystallinity of the target substance using the virtual X-ray diffraction element; Virtual X-ray diffraction profile data characterized in that it has a structure used in a process of analyzing the crystalline characteristics of the target substance by having the crystal distortion analysis unit analyze the crystalline distortion of the target substance using the virtual X-ray diffraction element.

10. The virtual X-ray diffraction elements are calculated using a Lorentzian profile, a Gaussian profile, and a pseudo-Voigt profile; When the virtual X-ray diffraction element calculated by the Lorentzian profile is used, the crystallinity analysis unit is caused to analyze the crystallinity of the target substance; When the virtual X-ray diffraction element calculated by the Gaussian profile is used, the crystal distortion analysis unit is caused to analyze the crystal distortion of the target material; The virtual X-ray diffraction profile data according to claim 9, characterized in that, when the virtual X-ray diffraction element calculated by the pseudo-Voigt profile is used, the virtual X-ray diffraction profile data has a structure used in a process of analyzing the crystalline characteristics of the target substance by having the crystallinity analysis unit and the crystal distortion analysis unit analyze the crystallinity and crystal distortion of the target substance.

Images