Processing apparatus, system, method and program

Abstract

To provide a processing apparatus, a system, a method and a program that calculate a structure factor including total scattered data and data of a structure model.SOLUTION: A processing apparatus 400 that processes a structure factor comprises: a structure factor acquisition unit 410 that acquires a first structure factor based on total scattered data which is actually measured; a data conversion unit 420 that divides the first structure factor into short distance correlation and long distance correlation; and a scattering intensity calculation unit 430 that acquires a structure model indicating atomic arrangement within a finite region, calculates short distance scattering intensity of the structure model, and calculates a second structure factor from the short distance scattering intensity and the long distance correlation.SELECTED DRAWING: Figure 7

Description

[Technical field]

[0001] The present invention relates to a processing device, a system, a method and a program for processing a structure factor. [Background technology]

[0002] Three-dimensional structural information is essential for a deep understanding of material functions. Many conventional materials are crystalline materials, and the purpose could be achieved by determining the crystal structure. However, in recent years, many materials in the fields of batteries and electronics are crystalline materials in which the order has been actively reduced in order to maximize the desired functions and physical properties.

[0003] Conventionally, estimation of the local structure of crystalline materials required the user to set complex parameters in order to calculate the diffraction peaks. Therefore, there is a demand for a method for estimating the local structure of crystalline materials that does not require complex parameter settings.

[0004] Non-Patent Document 1 discloses a method for calculating diffraction peaks using the RMCPOW method. Non-Patent Document 2 discloses a method for calculating diffraction peaks using the RMCProfile method. Patent Document 1 discloses a crystal structure model that reproduces the PDF based on measured values ​​and a method for deriving structural parameters. [Prior art documents] [Non-patent literature]

[0005] [Non-Patent Document 1] A. Mellergard, RL McGreevy, Acta Crystallogr. 55 (1999) 783-789. [Non-Patent Document 2] MG Tucker, MT Dove, DA Keen, J. Appl. Crystallogr. 34 (2001) 630-638. [Patent documents]

[0006] [Patent Document 1] JP 2020-94945 A Summary of the Invention [Problem to be solved by the invention]

[0007] However, Non-Patent Document 1 does not describe how to set the resolution function of the scattering vector Q, and the user must appropriately set the parameters that allow the processing to proceed smoothly. In addition, Non-Patent Document 2 requires the parameters of the profile function to be calculated using a separate software called GSAS. This operation must go through a converter, and the calculation cost is the same as that of performing a normal Rietveld analysis.

[0008] In addition, the method described in Patent Document 1 strictly handles parameters having wave number dependency such as resolution function and atomic scattering factor, so that the user needs to set various parameters, which increases the calculation cost. That is, the methods of Non-Patent Document 1, Non-Patent Document 2, and Patent Document 1 all require the user to set many complicated parameters, and it is not easy to create a structural model that can explain the measured data. In addition, the calculation cost is high.

[0009] As a result of intensive research, the inventors have discovered that by calculating a structure factor including measured total scattering data and structural model data, it is possible to simplify the parameters set by the user when estimating the local structure of a sample, thereby reducing calculation costs, that it is possible to analyze the characteristics of both the total scattering data and the structural model together, and that it is possible to create a structural model with high accuracy that can explain the measured data, and have completed the present invention.

[0010] The present invention has been made in view of the above circumstances, and an object of the present invention is to provide a processing device, system, method, and program for calculating a structure factor including total scattering data and structural model data. [Means for solving the problem]

[0011] (1) In order to achieve the above object, the processing device of the present invention is a processing device that processes structure factors, and is characterized by comprising: a structure factor acquisition unit that acquires a first structure factor based on measured total scattering data; a data conversion unit that separates the first structure factor into short-range correlation and long-range correlation; and a scattering intensity calculation unit that acquires a structural model showing an atomic arrangement within a finite region, calculates the short-range scattering intensity of the structural model, and calculates a second structure factor from the short-range scattering intensity and the long-range correlation.

[0012] (2) In the processing device of the present invention, the value of the boundary between the short-range correlation and the long-range correlation is determined based on the size and shape of the region of the structural model.

[0013] (3) The processing device of the present invention is characterized by further comprising a structure evaluation unit that calculates the degree of agreement or the degree of discrepancy between the first structure factor and the second structure factor.

[0014] (4) Furthermore, the processing device of the present invention is characterized in that it further includes a structure estimation unit that creates the structural model, and the structure evaluation unit outputs the structural model whose degree of agreement or degree of discrepancy satisfies a predetermined condition.

[0015] (5) In the processing device of the present invention, the structure evaluation unit calculates the degree of agreement or discrepancy between the first structure factor and the second structure factor within a range equal to or greater than a lower limit determined based on a boundary value between the short-range correlation and the long-range correlation.

[0016] (6) In the processing device of the present invention, the structure estimation unit creates the structure model by an RMC method.

[0017] (7) Furthermore, the processing device of the present invention further includes a structure factor calculation unit that acquires total scattering data of a sample and calculates the first structure factor based on the type of radiation source, wavelength, background, shape and arrangement of the sample, types of constituent elements, composition, and absorption coefficient of the total scattering data, and the structure factor acquisition unit acquires the first structure factor calculated by the structure factor calculation unit.

[0018] (8) The system of the present invention is characterized by comprising an X-ray diffraction apparatus including an X-ray generating unit that generates X-rays, a detector that detects X-rays, and a goniometer that controls the rotation of the sample, and a processing apparatus described in any one of (1) to (7) above.

[0019] (9) Furthermore, the method of the present invention is a method for processing structure factors, characterized in including a structure factor acquisition step of acquiring a first structure factor based on measured total scattering data, a data conversion step of separating the first structure factor into short-range correlation and long-range correlation, and a scattering intensity calculation step of acquiring a structural model showing an atomic arrangement within a finite domain, calculating the short-range scattering intensity of the structural model, and calculating a second structure factor from the short-range scattering intensity and the long-range correlation.

[0020] (10) Furthermore, the program of the present invention is a program for processing structure factors, characterized in that it causes a computer to execute the following processes: a process for acquiring a first structure factor based on measured total scattering data; a process for separating the first structure factor into short-range correlation and long-range correlation; a process for acquiring a structural model showing an atomic arrangement within a finite region, calculating the short-range scattering intensity of the structural model, and calculating a second structure factor from the short-range scattering intensity and the long-range correlation. [Brief description of the drawings]

[0021] [Figure 1] 1 is a graph showing an example of a first structure factor Fobs(Q). [Diagram 2]1 is a graph showing an example of a first structure factor Fobs(Q), a short-range correlation FS obs(Q), and a long-range correlation FL obs(Q). [Diagram 3] 1 is a graph showing an example of the short-range scattering intensity FS cal(Q) of a structural model. [Figure 4] 1 is a graph showing an example of a first structure factor Sobs(Q), a second structure factor Scal(Q), and their residuals. [Diagram 5] FIG. 13 is a schematic diagram showing an example of an output structural model. [Figure 6] FIG. 1 is a conceptual diagram showing an example of the configuration of an X-ray diffraction measurement system. [Figure 7] FIG. 2 is a block diagram showing an example of the configuration of a control device and a processing device. [Figure 8] FIG. 13 is a block diagram showing a modified example of the configuration of the control device and the processing device. [Figure 9] FIG. 13 is a block diagram showing a modified example of the configuration of the control device and the processing device. [Figure 10] FIG. 13 is a block diagram showing a modified example of the configuration of the processing device. [Figure 11] FIG. 13 is a block diagram showing a modified example of the configuration of the processing device. [Figure 12] FIG. 13 is a block diagram showing a modified example of the configuration of the processing device. [Figure 13] FIG. 13 is a block diagram showing a modified example of the configuration of the processing device. [Figure 14] 10 is a flowchart showing an example of an operation of the processing device. [Figure 15] 10 is a flowchart showing a modified example of the operation of the processing device. [Figure 16] 10 is a flowchart showing a modified example of the operation of the processing device. [Figure 17] 1 is a graph showing the PDF and residuals of actual measurements, examples, and comparative examples. [Figure 18] 1 is a histogram of the displacements calculated from a structural model created by the method of the present invention. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0022] Next, an embodiment of the present invention will be described with reference to the drawings. In order to facilitate understanding of the description, the same reference numerals are used to refer to the same components in each drawing, and duplicated description will be omitted.

[0023] [principle] The RMC method (Reverse Monte Carlo) is a method for estimating the local structure of a sample. The RMC method uses random numbers to move the atomic arrangement of a given structural model, and estimates a structural model that reproduces the actual measured values. Local structure estimation using the RMC method presupposes that the crystalline phase of the material for which the local structure is to be estimated is known, and that the values ​​of the parameters that determine the width of the diffraction peak are known, and the parameters for calculating the diffraction peak and the Q resolution function must be set by the user each time.

[0024] Furthermore, in order to calculate the diffraction peaks from the structural model, it is necessary to calculate the total scattering data from the structural model, which requires computational costs such as computer memory, CPU capacity, and computation time.

[0025] The method of the present invention does not directly calculate diffraction peaks from a structural model, and therefore does not require the user to set parameters for calculating diffraction peaks or a resolution function of the scattering vector Q. In addition, since only short-range scattering data is calculated from the structural model, there is no need to calculate all scattering data including long-range correlations, and the calculation cost can be reduced.

[0026] In the method of the present invention, first, measured total scattering data is acquired, and a first structure factor is created. The total scattering data can be, for example, total scattering data by X-rays, total scattering data by synchrotron radiation, or total scattering data by particle beams such as neutron beams or electron beams. The structure factor is defined as the Fourier transform of the spatial correlation of the electron density distribution (or nuclear density distribution) in a substance, and is a value used when determining the elastic scattering or coherent scattering intensity. The first structure factor is a structure factor created from the measured total scattering data. Next, the first structure factor is separated into short-range correlation and long-range correlation. The short-range correlation and long-range correlation are obtained by separating the correlation function in real space obtained by Fourier transforming the structure factor at a predetermined boundary value. Therefore, the boundary value between the short-range correlation and the long-range correlation is a value of the dimension of distance.

[0027] Next, a structural model showing the atomic arrangement in a finite region is created and acquired, and the short-distance scattering intensity of the structural model is calculated. The structural model is data showing the atomic arrangement in a finite region, and shows, for example, the arrangement of a finite number of atoms in a cube, a rectangular parallelepiped, or a parallelepiped. The short-distance scattering intensity is the scattering intensity calculated from the atomic arrangement in the finite region. In order to reproduce the total scattering data measured from the structural model, a calculation including long-range correlation is required, so a large structural model is required. On the other hand, since the short-distance scattering intensity does not include long-range correlation, it can be calculated even with a small structural model. Since the size of the structural model and the calculation cost are correlated, the calculation cost for calculating the short-distance scattering intensity is smaller than the calculation cost for calculating the total scattering data measured. In other words, the present invention can reduce the calculation cost more than the conventional technology.

[0028] Next, a second structure factor including total scattering data and data of the structure model is calculated from the short-range scattering intensity of the structure model and the long-range correlation of the first structure factor. The second structure factor is a structure factor including both the measured total scattering data and data of the structure model. Next, the agreement or divergence between the first structure factor and the second structure factor is calculated. The agreement or divergence between the first structure factor and the second structure factor is an index showing the degree of closeness between the first structure factor and the second structure factor. Then, if the agreement or divergence does not satisfy a predetermined condition, a structure model is created again and the second structure factor is calculated. If the agreement or divergence satisfies the predetermined condition, the process is terminated.

[0029] The second structure factor calculated as above includes both the measured total scattering data and the data of the structure model, and by analyzing this, it is possible to confirm to what extent a given structure model reproduces the measured total scattering data. Furthermore, a structure model whose degree of agreement or discrepancy satisfies a predetermined condition can be said to be a structure model with high accuracy that can explain the measured data. The detailed processing method of the present invention will be described in detail in the embodiment.

[0030] [Embodiment] The processing method of the present invention will be described in detail below. The following describes a method for processing a first structure factor based on total scattering data measured by an X-ray diffraction apparatus, calculating a second structure factor including data on the total scattering data and a structure model, calculating the degree of agreement or divergence between the first structure factor and the second structure factor, and outputting a structure model in which the degree of agreement or divergence is equal to or less than a predetermined threshold. However, the total scattering data to which the present invention can be applied is not limited to the total scattering data measured by an X-ray diffraction apparatus, but can be applied to total scattering data measured by a probe similar thereto. Specifically, for example, the present invention can be applied to total scattering data by synchrotron radiation, and total scattering data by particle beams such as neutron beams and electron beams. In addition, the present invention does not necessarily need to acquire total scattering data, and the first structure factor calculated from the total scattering data may be the first data.

[0031] First, total scattering data measured by an X-ray diffraction apparatus is obtained. When the total scattering data is used as the initial data, it is preferable to also obtain information necessary for calculating the structure factor based on the total scattering data, such as the type of radiation source, wavelength, background, shape and arrangement of the sample, type of constituent elements, composition, and absorption coefficient. This information may be stored in advance or may be obtained from the X-ray diffraction apparatus. It may also be input by the user.

[0032] Next, the first structure factor F is calculated based on the total scattering data. obs (Q) is calculated. The first structure factor F obs It is preferable to calculate (Q) based on the type of radiation source of the total scattering data, wavelength, background, shape and arrangement of the sample, type and composition of the constituent elements, and absorption coefficient, etc. obs 13 is a graph showing an example of (Q).

[0033] Next, the first structure factor F obs (Q) is the short-range correlation F S obs (Q) and long-range correlation F L obs (Q). The first structure factor F obs (Q) is the short-range correlation F S obs (Q) and long-range correlation F L obs Using (Q), it is expressed as the following formula (1). Figure 2 shows the first structure factor F obs (Q) and short-range correlation F S obs (Q), and long-range correlation F L obs 2. This is a graph showing an example of the short-range correlation F S obs (Q) and long-range correlation F L obs (Q) is the first structure factor F in Figure 1 obs The graph shows the separation of (Q).

[0034]

number

[0035] Short-range correlation F S obs (Q) and long-range correlation F L obs The boundary value of (Q) is preferably determined based on the size and shape of the region of the structural model. For example, the radius of the largest sphere included in the structural model is set to r max Then, r max The short-range correlation F S obs (Q) and long-range correlation F L obs It is preferable to set the boundary value of (Q). In the following, r max The short-range correlation F S obs (Q) and long-range correlation F L obs (Q) is the boundary value, but other values ​​can be used.

[0036] First structure factor F obs (Q) is short-range correlation F S obs (Q) and long-range correlation F L obs Any method may be used to separate the first structure factor F obs PDF (Pair Distribution Function) G obtained by Fourier transform of (Q) obs Calculate (r) and G obs It is convenient and preferable to carry out the procedure using (r). obs The calculation of (r) is based on the first structure factor F obs (Q) minimum Q min and the maximum value Q max and perform the calculation using the following formula (2): Q min and Q max is the first structure factor F obs This is ancillary to the calculation of (Q). Q min and Q max may be input by the user.

[0037]

number

[0038] As shown in the following formula (3), G obs By inversely transforming (r), the first structure factor F obs (Q). Therefore, the short-range correlation F S obs (Q) and long-range correlation F L obs The boundary value of (Q) is r max Then, the first structure factor F obs (Q) can be separated as shown in the following equation (4).

[0039]

number

[0040]

number

[0041] Therefore, the first structure factor F obs (Q) separation into G obs When using (r), for example, the short-range correlation F S obs (Q) can be defined by the following formula (5). The short-range correlation F calculated by formula (5) S obs Using (Q), the long-range correlation F is calculated using the following formula (6): L obs (Q) can be found.

[0042]

number

[0043]

number

[0044] Next, a structural model showing the atomic arrangement in a finite region is obtained, and the short-range scattering intensity F S cal (Q) is calculated. The structural model can be given as data showing the arrangement of a finite number of atoms in a cube, rectangular prism, or parallelepiped, depending on the sample. The short-range scattering intensity F of the structural model is calculated as S cal The calculation of (Q) can be performed, for example, by the following formula (7). In formula (7), N is the number of atoms in the structural model. ij For the atomic array n(x,y,z) of the structure model, the i-th atomic array is i (x i ,y i ,z i ), the jth atomic sequence is n j (x j ,y j ,z j ) is defined as in Equation (8). i and f j are the scattering factors of the i-th and j-th atoms, respectively. Q is the scattering vector. Figure 3 shows the short-range scattering intensity F S cal 13 is a graph showing an example of (Q).

[0045]

number

[0046]

number

[0047] And the short-range scattering intensity F of the structural model S cal (Q) and the long-range correlation F of the first structure factor L obs (Q) to the second structure factor F, which contains the total scattering data and the structure model data cal Calculate the second structure factor F cal The calculation of (Q) can be performed, for example, by the following formula (9). This results in the second structure factor Fcal (Q) can be used to analyze the characteristics of both the total scattering data and the structure model. Depending on the application of the second structure factor, the second structure factor can be used as S cal (Q) may be calculated as the second structure factor S cal The calculation of (Q) can be performed, for example, by the following formula (10).

[0048]

number

[0049]

number

[0050] To check how well a given structure model reproduces the measured total scattering data, the first structure factor F obs (Q) and the second structure factor F cal It is preferable to calculate the degree of agreement or divergence of (Q). The calculation of the degree of agreement or divergence is carried out by using the first structure factor F obs (Q) and the second structure factor F cal Any value that indicates the degree of similarity may be used, including Q. The larger the value of the degree of match, the greater the degree of similarity. The smaller the value of the degree of discrepancy, the greater the degree of similarity. The degree of discrepancy is, for example, R P,S(Q) It can be calculated by the formula (11) w i is the weighting factor, e.g., w i = 1 / N. Also, S obs (Q)=F obs (Q)+1, S cal (Q)=F cal (Q)+1. As shown in formula (11), the degree of agreement or discrepancy between the first and second structure factors is calculated as S obs (Q) or S cal (Q) may be used. FIG. 4 shows the first structure factor S obs (Q), the second structure factor S cal13 is a graph showing an example of (Q) and its residual. The formula for calculating the degree of agreement or the degree of discrepancy is not limited to formula (11).

[0051]

number

[0052] First structure factor F obs (Q) and the second structure factor F cal When calculating the degree of agreement or discrepancy of (Q), the short-range correlation F S obs (Q) and long-range correlation F L obs It is preferable to calculate the degree of agreement or the degree of discrepancy within a range equal to or greater than the lower limit determined based on the boundary value of (Q). obs (Q) to G obs The calculation of (r) can be performed using the above formula (2), which is a combination of the following formulas (12) and (13). α(Q) is a step function, and the first structure factor F obs This is an example of a function that cuts off data on the short and long distance sides of (Q).

[0053]

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[0054]

number

[0055] PDF G obs The first structure factor F, which is back-transformed from (r) obs (Q) shows the effect of the step function. Q min The effect of truncation error is G obs The boundary value of (r) (in the above formula (4), r max ), and Q min The resolution of Q is ΔQ'0 max Using this, it can be expressed as the following equation (14).

[0056]

number

[0057] Therefore, the first structure factor F obs Q of Q min By determining the next measurement point Q'1 as in the following formula (15), the influence of the truncation error can be sufficiently reduced. That is, the short-range correlation F S obs (Q) and long-range correlation F L obs It is preferable to calculate the degree of agreement or the degree of discrepancy within a predetermined range equal to or greater than Q'1, with Q'1 being the lower limit determined based on the boundary value of (Q). min may be the lower limit of the actually measured Q.

[0058]

number

[0059] In the following, a case where a more appropriate structural model is created using the method of the present invention will be described. It is assumed that a structural model can be repeatedly created by some method. It is preferable to repeatedly create a structural model based on the degree of agreement or the degree of discrepancy, and output a structural model whose degree of agreement or the degree of discrepancy satisfies a predetermined condition. FIG. 5 is a schematic diagram showing an example of an output structural model. For example, when the degree of discrepancy of the formula (11) is used, a value of the degree of discrepancy of 5% or less can be adopted as a predetermined condition.

[0060] When the structural model is repeatedly created, any method may be used for creating the structural model, but it is preferable to create the structural model by the RMC method, for example. The RMC method has a wide search space and can obtain a global minimum solution, so it is effective as a method for solving complex optimization problems. Therefore, when the RMC method is applied to the present invention, it is highly likely that a structural model that reproduces the measured scattering data can be obtained. In the RMC method, the atomic arrangement of the structural model is randomly moved, and if the degree of agreement or deviation after the operation is better (the degree of closeness is large) than the degree of agreement or deviation before the operation, further random movement is performed based on the atomic arrangement. On the other hand, if the degree of agreement or deviation after the operation is not better (the degree of closeness is not large) than the degree of agreement or deviation before the operation, the operation is canceled, and random movement is performed again from the atomic arrangement before the operation. Such operations are performed until the degree of agreement or deviation satisfies a predetermined condition. The method for creating the structural model may be the MD method (Molecular Dynamics method) or the MC method (Monte Carlo method).

[0061] In this way, a structural model can be created that reproduces the measured total scattering data with sufficient accuracy.

[0062] [Entire system] Fig. 6 is a conceptual diagram showing an example of the configuration of an X-ray diffraction measurement system 100. The system 100 has an X-ray diffraction device 200, a control device 300, and a processing device 400. The X-ray diffraction device 200 forms an optical system that irradiates X-rays on a sample and detects diffracted X-rays generated from the sample, and the optical system has a goniometer. Note that the configuration shown in Fig. 6 is just one example, and various other configurations can be adopted.

[0063] The control device 300 is connected to the X-ray diffraction device 200, and controls the X-ray diffraction device 200 and processes and stores acquired data. The processing device 400 processes the structure factor. The control device 300 and the processing device 400 are devices equipped with a CPU and memory, and may be PC terminals or servers on the cloud. In addition to the entire device, some devices or some functions within the devices may be provided on the cloud. The input device 510 is, for example, a keyboard and a mouse, and inputs data to the control device 300 and the processing device 400. The display device 520 is, for example, a display, and displays structure factors, PDFs, structural models, and the like.

[0064] Using such a system 100, it is possible to measure total scattering data, process structure factors calculated from the total scattering data, create a structural model, and calculate a second structural factor that includes the total scattering data and data from the structural model, thereby allowing the local structure of the sample to be estimated.

[0065] In FIG. 6, the control device 300 and the processing device 400 are described as the same PC. However, as described above, the method of the present invention can acquire and process total scattering data or structure factors independently of the X-ray diffraction device 200 and the control device 300. Therefore, as shown in FIG. 7, the processing device 400 may be configured as a device different from the control device 300. FIG. 7 is a block diagram showing an example of the configuration of the control device 300 and the processing device 400. Also, as shown in FIG. 8, the processing device 400 may be configured as a part of the function included in the control device 300. Also, as shown in FIG. 9, the processing device 400 and the control device 300 may be configured as an integrated device. FIGS. 8 and 9 are block diagrams showing modified examples of the configuration of the control device 300 and the processing device 400. In the following, a case where the control device 300 and the processing device 400 are configured as different devices will be described.

[0066] [X-ray diffraction equipment] The X-ray diffraction apparatus 200 includes an X-ray generation unit 210 that generates X-rays from an X-ray focus, i.e., an X-ray source, an incident side optical unit 220, a goniometer 230, a sample stage 240 on which a sample is placed, an exit side optical unit 250, and a detector 260 that detects X-rays. The X-ray generation unit 210, the incident side optical unit 220, the goniometer 230, the sample stage 240, the exit side optical unit 250, and the detector 260 that configure the X-ray diffraction apparatus 200 may be general components, and therefore a description thereof will be omitted.

[0067] [Control device] The control device 300 is configured by a computer having a CPU (Central Processing Unit), a ROM (Read Only Memory), a RAM (Random Access Memory), and memories connected to a bus. The control device 300 is connected to the X-ray diffraction device 200 and receives information from the X-ray diffraction device 200.

[0068] The control device 300 includes a control unit 310, a device information storage unit 320, a measurement data storage unit 330, and a display unit 340. Each unit can send and receive information via a control bus L. The input device 510 and the display device 520 are connected to the CPU via an appropriate interface.

[0069] The control unit 310 controls the operation of the X-ray diffraction instrument 200. The instrument information storage unit 320 stores instrument information acquired from the X-ray diffraction instrument 200. The instrument information includes information about the X-ray diffraction instrument 200, such as the instrument name, type of radiation source, wavelength, background, etc. In addition, the instrument information may include information necessary for calculating a structure factor based on total scattering data, such as the shape and arrangement of the sample, the type of constituent elements, composition, and absorption coefficient.

[0070] The measurement data storage unit 330 stores the measurement data acquired from the X-ray diffraction device 200. The measurement data includes total scattering data. The total scattering data may include information necessary for calculating the structure factor based on the total scattering data, such as the type of radiation source, wavelength, background, shape and arrangement of the sample, type of constituent elements, composition, and absorption coefficient. When the background is low, the information necessary for calculating the structure factor does not need to include the background. The display unit 340 displays the measurement data on the display device 520. This allows the user to check the measurement data. The user can also give instructions and designations to the control device 300, the processing device 400, etc. based on the measurement data.

[0071] [Processing device] The processing device 400 is configured by a computer having a CPU, a ROM, a RAM, and a memory connected to a bus. The processing device 400 may be connected to the X-ray diffraction device 200 via the control device 300.

[0072] The processing device 400 includes a structure factor acquisition unit 410, a data conversion unit 420, and a scattering intensity calculation unit 430. Each unit can send and receive information via a control bus L. When the processing device 400 and the control device 300 have different configurations, the input device 510 and the display device 520 are also connected to the CPU of the processing device 400 via an appropriate interface. In this case, the input device 510 and the display device 520 may be different from those connected to the control device 300.

[0073] The structure factor acquisition unit 410 acquires a first structure factor based on the measured total scattering data. The structure factor acquisition unit 410 may acquire a first structure factor calculated by another device based on the measured total scattering data by the X-ray diffraction device 200. The structure factor acquisition unit 410 may acquire a first structure factor calculated by a structure factor calculation unit 405 (described later) based on the measured total scattering data.

[0074] The data conversion unit 420 separates the first structure factor into short-range correlation and long-range correlation. It is preferable that the data conversion unit 420 calculates a pair distribution function (PDF) from the first structure factor acquired by the structure factor acquisition unit 410, and separates the first structure factor into short-range correlation and long-range correlation using the PDF. The data conversion unit 420 may separate the first structure factor into short-range correlation and long-range correlation using a method that does not use the PDF.

[0075] The value of the boundary between the short-range correlation and the long-range correlation when the data conversion section 420 separates the first structure factor into the short-range correlation and the long-range correlation is preferably determined based on the size and shape of the region of the structural model.

[0076] The scattering intensity calculation unit 430 acquires a structural model showing an atomic arrangement in a finite region, and calculates the short-distance scattering intensity of the structural model. The scattering intensity calculation unit 430 calculates a second structure factor from the short-distance scattering intensity and the long-distance correlation. The scattering intensity calculation unit 430 may acquire a structural model created by another device. The scattering intensity calculation unit 430 may acquire a structural model created by a structure estimation unit 450, which will be described later.

[0077] Fig. 10 is a block diagram showing a modified example of the configuration of the processing device 400. As shown in Fig. 10, the processing device 400 preferably includes a structure evaluation unit 440. The structure evaluation unit 440 calculates the degree of agreement or discrepancy between the first structure factor and the second structure factor. This makes it possible to confirm to what extent the structure model reproduces the measured total scattering data.

[0078] The structure evaluation section 440 preferably calculates the degree of agreement or discrepancy between the first structure factor and the second structure factor within a range equal to or greater than a lower limit determined based on the boundary value between short-range correlation and long-range correlation.

[0079] FIG. 11 is a block diagram showing a modified example of the configuration of the processing device 400. As shown in FIG. 11, the processing device 400 preferably includes a structure estimation unit 450. The structure estimation unit 450 creates a structure model. The structure estimation unit 450 preferably secures a calculation area and creates a structure model based on the size, shape, atomic arrangement, etc. of the structure model. The size, shape, initial atomic arrangement, etc. of the structure model may be configured to be specified by the user. When the processing device 400 includes the structure estimation unit 450, the structure evaluation unit 440 preferably outputs a structure model whose degree of agreement or degree of discrepancy satisfies a predetermined condition.

[0080] The structure estimation unit 450 preferably creates a structural model by the RMC method.

[0081] 12 and 13 are block diagrams showing modified examples of the configuration of the processing device 400. As shown in FIG. 12 or 13, the processing device 400 preferably includes a structure factor calculation unit 405. The structure factor calculation unit 405 acquires total scattering data of the sample, and calculates a first structure factor based on the type of source, wavelength, background, shape and arrangement of the sample, type of constituent elements, composition, and absorption coefficient of the total scattering data. If the background is low, the first structure factor may be calculated without using it. When the processing device 400 includes the structure factor calculation unit 405, the structure factor acquisition unit 410 acquires the first structure factor calculated by the structure factor calculation unit 405. The block diagram of FIG. 10 may further include a structure factor calculation unit 405.

[0082] [Measurement method] A sample S is placed in the X-ray diffraction device 200, and the goniometer is driven under predetermined conditions under the control of the control device 300. In addition, X-rays are irradiated onto the sample, and diffracted X-rays generated from the sample are detected. As a result, diffraction data is acquired. The X-ray diffraction device 200 transmits device information and the acquired diffraction data to the control device 300 as measurement data.

[0083] [Processing method] (Explanation of the flow up to calculating the second structure factor) FIG. 14 is a flowchart showing an example of the operation of the processing device 400. FIG. 14 shows an example of the operation up to the calculation of the second structure factor. First, the processing device 400 acquires the first structure factor (step S1). Next, the first structure factor is separated into short-range correlation and long-range correlation (step S2). Next, a structural model is acquired (step S3). Next, the short-range scattering intensity of the structural model is calculated (step S4). Then, the second structure factor is calculated from the short-range scattering intensity and the long-range correlation (step S5), and the process ends. If necessary, the second structure factor and the structural model may be output. In this way, the second structure factor including the total scattering data and the data of the structural model can be calculated, and the characteristics of both the total scattering data and the structural model can be analyzed together using the second structure factor.

[0084] (Explanation of the flow up to calculating the agreement or discrepancy between the first and second structure factors) FIG. 15 is a flowchart showing a modified example of the operation of the processing device 400. FIG. 15 shows an example of the operation up to the calculation of the agreement or discrepancy between the first structure factor and the second structure factor. In the following explanation of the flowchart, characteristic operations will be explained in detail, and the explanation of the operations that have already been explained may be omitted. From the acquisition of the first structure factor (step T1) to the calculation of the second structure factor (step T5), it is the same as the above steps S1 to S5. Then, the processing device 400 calculates the agreement or discrepancy between the first structure factor and the second structure factor (step T6) and ends. If necessary, the second structure factor, the structure model, and the agreement or discrepancy between the first structure factor and the second structure factor may be output. This makes it possible to confirm to what extent the structure model reproduces the measured total scattering data.

[0085] (Explanation of the flow to output a structural model that satisfies the conditions) Fig. 16 is a flowchart showing a modified example of the operation of the processing device 400. Fig. 16 shows an example of the operation up to outputting a structural model that satisfies the conditions. Acquisition of the first structural factor (step U1) and separation of the first structural factor (step U2) are similar to the above steps. Next, a structural model is created (step U3). The structural model may be created by the processing device 400, or one created by another device or function may be used.

[0086] The steps from obtaining a structural model (step U4) to calculating the degree of agreement or divergence between the first structural factor and the second structural factor (step U7) are the same as those described above. Next, the processing device 400 judges whether the degree of agreement or divergence satisfies a set predetermined condition, and if the predetermined condition is not met (step U8-NO), returns to step U3 and performs the process up to step U7 again. On the other hand, if the degree of agreement or divergence satisfies the set predetermined condition (step U8-YES), outputs the structural model (step U9) and ends. If necessary, the second structural factor and the degree of agreement or divergence between the first structural factor and the second structural factor may be output. This makes it possible to create and output a structural model that satisfies the set predetermined condition.

[0087] In the above flowcharts, all of the steps start with a step of acquiring the first structure factor using the first structure factor as the initial data, but the steps may also include a step of acquiring total scattering data using total scattering data as the initial data and a step of creating a first structure factor from the total scattering data prior to the step of acquiring the first structure factor.

[0088] [Example] The total scattering data of Ni was measured using the system 100 configured as described above. This was used to calculate the first structure factor and PDF. Next, using the method of the present invention, the creation of a structural model was repeated by the RMC method until the deviation between the first structure factor and the second structure factor became sufficiently small. Next, a PDF was created from the second structure factor when the deviation satisfied a predetermined condition. Then, the deviation between the PDF created from the first structure factor and the PDF created from the second structure factor was confirmed. The deviation was calculated using the R P,G(r) This was confirmed by using the w i is the weighting factor, e.g., w i = 1 / N. Also, G obs (r) is the PDF created from the first structure factor, G cal (r) shows the PDF created from the structural factors including the data of the structural model. The discrepancy R P,G(r) is an index in which the smaller the value, the greater the degree of similarity between two PDFs.

[0089]

number

[0090] As a comparative example, a structural model was created from the first structural factor using the conventional method PDFgui, and the structural factor and PDF were created using the model. The discrepancy R between the PDF created from the first structural factor and the PDF created using PDFgui was calculated. P,G(r) I confirmed.

[0091] 17 is a graph showing the PDF created from the first structure factor, which is an actual measurement value, the PDF created from the second structure factor created by the method of the present invention, and the PDF created by the method of the comparative example, along with their respective residuals. Note that Obs indicates the PDF created from the first structure factor, RMC indicates the PDF created by the method of the present invention, and PDFgui indicates the PDF created by the method of the comparative example.

[0092] Deviation R of the PDF created by the method of the present invention P,G(r)The value of R was 6.55%. On the other hand, the deviation R of the PDF created by the method of the comparative example P,G(r) The value of was 8.20%. This confirmed that the method of the present invention can create a PDF closer to the PDF based on the measured data than the method of the comparative example. It was also confirmed that the structural model created by the method of the present invention is a structural model with higher accuracy that can explain the measured data than the structural model created by the method of the comparative example.

[0093] In addition, histograms of the displacements calculated from the atomic arrangement of Ni before and after refinement by the method of the present invention and Rietveld analysis and their standard deviations were confirmed. Figure 18 shows a histogram of the displacements calculated from the structural model created by the method of the present invention. The standard deviation of the displacements calculated by the method of the present invention was 0.0920 Å, whereas it was 0.0756 Å when calculated by the Rietveld analysis. This confirmed that the displacements calculated from the structural model created by the method of the present invention were comparable to those calculated by the Rietveld analysis.

[0094] As a result, the processing device, system, method, and program of the present invention can simplify the parameters set by the user when estimating the local structure of a sample, thereby reducing calculation costs. In addition, the characteristics of both the total scattering data and the structural model can be analyzed together. Furthermore, a highly accurate structural model that can explain the measured data can be created.

[0095] It goes without saying that the present invention is not limited to the above-described embodiment. The scope of the present invention covers various modifications and equivalents included in the technical idea of ​​the present invention. In addition, the names, structures, shapes, numbers, positions, sizes, etc. of the components shown in each drawing are for convenience of explanation and may be changed as appropriate. [Explanation of symbols]

[0096] 100 Systems 200 X-ray Diffraction Instrument 210 X-ray Generator 220 Incident optical unit 230 Goniometer 240 Sample stage 250 Output optical unit 260 Detector 300 Control device 310 Control section 320 Device information storage unit 330 Measurement data storage unit 340 Display section 400 Processing Equipment 405 Structure factor calculation part 410 Structure factor acquisition part 420 Data Conversion Unit 430 Scattering intensity calculation section 440 Structural Evaluation Division 450 Structure estimation part 510 Input Device 520 Display device

Claims

1. A processing device for processing a structure factor, comprising: a structure factor acquisition unit that acquires a first structure factor based on measured total scattering data; a data conversion unit that separates the first structure factor into short-range correlation and long-range correlation; a scattering intensity calculation unit that acquires a structural model that indicates an atomic arrangement within a finite region, calculates a short-range scattering intensity of the structural model, and calculates a second structure factor from the short-range scattering intensity and the long-range correlation.

2. 2. The processing device according to claim 1, wherein the boundary values ​​between the short-range correlation and the long-range correlation are determined based on a size and a shape of a region of the structural model.

3. 2. The processing apparatus according to claim 1, further comprising a structure evaluation unit for calculating a degree of agreement or a degree of discrepancy between the first structure factor and the second structure factor.

4. A structure estimation unit that creates the structural model, 4. The processing apparatus according to claim 3, wherein the structural evaluation section outputs the structural model in which the degree of agreement or the degree of discrepancy satisfies a predetermined condition.

5. 4. The processing device according to claim 3, wherein the structure evaluation unit calculates the degree of agreement or the degree of discrepancy between the first structure factor and the second structure factor within a range equal to or greater than a lower limit determined based on a boundary value between the short-range correlation and the long-range correlation.

6. 5. The processing apparatus according to claim 4, wherein the structure estimation unit creates the structure model by an RMC method.

7. a structure factor calculation unit that acquires total scattering data of a sample and calculates the first structure factor based on the type of radiation source, wavelength, background, shape and arrangement of the sample, type and composition of constituent elements, and absorption coefficient of the total scattering data; 2. The processing apparatus according to claim 1, wherein the structure factor acquisition unit acquires the first structure factor calculated by the structure factor calculation unit.

8. An X-ray diffraction apparatus including an X-ray generating unit that generates X-rays, a detector that detects the X-rays, and a goniometer that controls the rotation of a sample; A system comprising: a processing device according to any one of claims 1 to 7.

9. 1. A method for processing a structure factor, comprising the steps of: a structure factor acquisition step of acquiring a first structure factor based on measured total scattering data; a data transformation step of separating the first structure factor into short-range correlations and long-range correlations; and a scattering intensity calculation step of acquiring a structural model showing an atomic arrangement within a finite region, calculating a short-range scattering intensity of the structural model, and calculating a second structure factor from the short-range scattering intensity and the long-range correlation.

10. A program for processing structure factors, A process of acquiring a first structure factor based on the measured total scattering data; separating the first structure factor into short-range correlations and long-range correlations; A program for causing a computer to execute a process of acquiring a structural model showing an atomic arrangement within a finite region, calculating a short-range scattering intensity of the structural model, and calculating a second structure factor from the short-range scattering intensity and the long-range correlation.

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