Processing device, 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, and the purpose could be achieved by determining the crystal structure. However, in recent years, many materials in fields such as 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 to calculate diffraction peaks. Therefore, there is a need 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 PDFs 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] Japanese Patent Publication No. 2020-94945 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 for the scattering vector Q, requiring the user to appropriately set parameters that would allow the process to proceed smoothly. Furthermore, Non-Patent Document 2 required the user to calculate the profile function parameters separately using software called GSAS. This operation required the use of a converter, which entailed the same computational costs as performing a regular Rietveld analysis.

[0008] Furthermore, the method described in Patent Document 1 strictly handles wavenumber-dependent parameters such as the resolution function and atomic scattering factor, which requires the user to set various parameters, resulting in high computational costs. That is, the methods of Non-Patent Document 1, Non-Patent Document 2, and Patent Document 1 all require the user to set many complex parameters, making it difficult to create a structural model that can explain the measured data. Furthermore, these methods require high computational costs.

[0009] As a result of extensive research, the inventors have discovered that by calculating a structure factor that includes measured total scattering data and data from a structural model, it is possible to simplify the parameters that a user sets when estimating the local structure of a sample, thereby reducing calculation costs, and that it is possible to analyze the characteristics of both the total scattering data and the structural model together, and furthermore, to create a highly accurate structural model that can explain the measured data, thereby completing the present invention.

[0010] The present invention has been made in view of the above circumstances, and has as its object 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 for processing 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 correlations and long-range correlations; and a scattering intensity calculation unit that acquires a structural model showing the 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 boundary value 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 divergence 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 structural evaluation unit outputs the structural model whose degree of agreement or degree of discrepancy satisfies a predetermined condition.

[0015] (5) Furthermore, in the processing device of the present invention, the structure evaluation unit is characterized in that it 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 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) 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, type and composition of constituent elements, 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 having 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 the 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 by 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 correlations and long-range correlations, and a scattering intensity calculation step of acquiring a structural model showing the 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.

[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 the 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 explanation of the drawings]

[0021] [Figure 1] 10 is a graph showing an example of a first structure factor Fobs(Q). [Figure 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). [Figure 3] 10 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. [Figure 5] FIG. 10 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. 10 is a block diagram showing a modified example of the configuration of the control device and the processing device. [Figure 9] FIG. 10 is a block diagram showing a modified example of the configuration of the control device and the processing device. [Figure 10] FIG. 10 is a block diagram showing a modified example of the configuration of the processing device. [Figure 11] FIG. 10 is a block diagram showing a modified example of the configuration of the processing device. [Figure 12] FIG. 10 is a block diagram showing a modified example of the configuration of the processing device. [Figure 13] FIG. 10 is a block diagram showing a modified example of the configuration of the processing device. [Figure 14] 10 is a flowchart illustrating an example of the 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 PDFs and residuals for actual measurements, examples, and comparative examples. [Figure 18] 1 is a histogram of displacements calculated from a structural model created by the method of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0022] Next, an embodiment of the present invention will be described with reference to the drawings. To facilitate understanding of the description, the same reference numerals are used to designate the same components in the drawings, and duplicated descriptions will be omitted.

[0023] [principle] The RMC (Reverse Monte Carlo) method is one 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 estimate 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, as well as the values ​​of the parameters that determine the width of the diffraction peak. Therefore, 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 diffraction peaks from a structural model, it is necessary to calculate 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 calculate diffraction peaks directly from a structural model, so the user does not need to set parameters for calculating diffraction peaks or the resolution function of the scattering vector Q. Furthermore, because only short-range scattering data is calculated from the structural model, there is no need to calculate all scattering data including long-range correlations, which reduces calculation costs.

[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 from X-rays, total scattering data from synchrotron radiation, or total scattering data from particle beams such as neutrons or electrons. 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 to determine the elastic scattering or coherent scattering intensity. The first structure factor is 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 short-range correlation and long-range correlation is a value in the dimension of distance.

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

[0028] Next, a second structure factor including total scattering data and structural model data is calculated from the short-range scattering intensity of the structural 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 structural model data. Next, the degree of agreement or divergence between the first structure factor and the second structure factor is calculated. The degree of 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. If the degree of agreement or divergence does not satisfy the predetermined condition, the structural model is created again and the second structure factor is calculated. If the degree of agreement or divergence satisfies the predetermined condition, the process ends.

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

[0030] [Embodiment] The processing method of the present invention is described in detail below. The following describes a method for processing a first structure factor based on total scattering data measured with an X-ray diffraction instrument, calculating a second structure factor including data on the total scattering data and a structural model, calculating the degree of agreement or discrepancy between the first structure factor and the second structure factor, and outputting a structural model whose degree of agreement or discrepancy is below a predetermined threshold. However, the total scattering data to which the present invention is applicable is not limited to that measured with an X-ray diffraction instrument, but can also be applied to total scattering data measured with a probe similar to the total scattering data. Specifically, the present invention can be applied to, for example, total scattering data obtained with synchrotron radiation or total scattering data obtained with particle beams such as neutron beams and electron beams. Furthermore, the present invention does not necessarily require the acquisition of total scattering data; the first structure factor calculated from the total scattering data can also be used as the initial data.

[0031] First, total scattering data measured by an X-ray diffraction instrument is acquired. When the total scattering data is used as the initial data, it is preferable to also acquire information necessary for calculating the structure factor based on the total scattering data, such as the type of radiation source, wavelength, background, sample shape, arrangement, type of constituent elements, composition, and absorption coefficient. This information may be stored in advance, acquired from the X-ray diffraction instrument, or 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 constituent elements, and absorption coefficient, etc. Figure 1 shows the first structure factor F obs 10 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 mathematical 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. The graph shows an example of the short-range correlation F (Q). 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 as r max When 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 This is the boundary value of (Q), but other values ​​can be used.

[0036] First structure factor F obs (Q) is the 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 use (r). obs The calculation of (r) is based on the first structure factor F obs (Q) minimum value Q min and the maximum value Q max is obtained and calculated using the following formula (2): Q min and Q max is the first structure factor F obs This is an incidental factor when calculating (Q). min and Q max may be input by the user.

[0037]

number

[0038] As shown in the following formula (3), G obs By inverting (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 G obs When using (r), for example, short-range correlation F S obs (Q) can be defined by the following formula (5). Also, the short-range correlation F S obs Using (Q), the long-range correlation F is calculated using the following equation (6): L obs (Q) can be found.

[0042]

number

[0043]

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[0044] Next, a structural model showing the atomic arrangement within a finite region is obtained, and the short-range scattering intensity F of the structural model is calculated. S cal 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. 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 arrangement n(x,y,z) of the structure model, the i-th atomic arrangement is i (x i ,y i ,z i ), the jth atomic arrangement is n j (x j ,y j ,z j ) is defined by 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 10 is a graph showing an example of (Q).

[0045]

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[0046]

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[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 includes the total scattering data and the structural model data. cal (Q) is calculated. The second structure factor F cal The calculation of (Q) can be performed, for example, by the following formula (9). This allows the second structure factor Fcal (Q) can be used to analyze the characteristics of both the total scattering data and the structural model. Depending on the application of the second structure factor, the second structure factor can be used as S cal (Q) can 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 structural 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 including (Q) indicating the degree of similarity may be used. The larger the value of the degree of similarity, 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 can be calculated, for example, by R in the following formula (11): P,S(Q) It can be calculated by the formula (11) i is a 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) and S cal (Q) may be used. Figure 4 shows the first structure factor S obs (Q), the second structure factor S cal11 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 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 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]

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[0055] PDF G obs The first structure factor F obtained by inverse transformation 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 defining the next measurement point Q'1 as in the following equation (15), the influence of the truncation error can be sufficiently reduced. 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] The following describes the case where a more appropriate structural model is created using the method of the present invention. It is assumed that a structural model can be created repeatedly by some method. It is preferable to repeatedly create structural models based on the degree of agreement or deviation, and output a structural model whose degree of agreement or deviation satisfies a predetermined condition. FIG. 5 is a schematic diagram showing an example of an output structural model. For example, when the deviation of Equation (11) is used, a predetermined condition can be adopted in which the value of the deviation is 5% or less.

[0060] When repeatedly creating a structural model, any method for creating the structural model may be used. However, for example, the RMC method is preferred. The RMC method has a wide search space and can obtain globally minimal solutions, making it effective as a solution to complex optimization problems. Therefore, applying the RMC method to the present invention increases the likelihood of obtaining a structural model that reproduces the measured scattering data. In the RMC method, the atomic arrangement of the structural model is randomly shifted, and if the degree of identity or divergence after the manipulation is better (closer) than the degree of identity or divergence before the manipulation, further random shifts are performed based on the atomic arrangement. On the other hand, if the degree of identity or divergence after the manipulation is not better (closer) than the degree of identity or divergence before the manipulation, the manipulation is canceled, and random shifts are performed again from the atomic arrangement before the manipulation. This manipulation is repeated until the degree of identity or divergence satisfies a predetermined condition. The method for creating a structural model may also be the MD (Molecular Dynamics) method or the MC (Monte Carlo) method.

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

[0062] [Overall system] Figure 6 is a conceptual diagram showing an example of the configuration of an X-ray diffraction measurement system 100. The system 100 includes 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 onto a sample and detects diffracted X-rays generated from the sample, and the optical system includes a goniometer. Note that the configuration shown in Figure 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. Furthermore, not only the entire device, but also some of the devices or some functions within the devices may be provided on the cloud. The input device 510 is, for example, a keyboard or 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, etc.

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

[0065] In FIG. 6, the control device 300 and the processing device 400 are depicted as a single 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 separate 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. As shown in FIG. 8, the processing device 400 may be configured as a partial function included in the control device 300. 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 configurations of the control device 300 and the processing device 400. The following describes the case where the control device 300 and the processing device 400 are configured as separate devices.

[0066] [X-ray diffractometer] 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, incident-side optical unit 220, goniometer 230, sample stage 240, exit-side optical unit 250, and detector 260 that configure the X-ray diffraction apparatus 200 may be general components, and therefore description thereof will be omitted.

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

[0068] The control device 300 comprises 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. Other information required for calculating the structure factor based on the total scattering data may also be included, 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 instrument 200. The measurement data includes total scattering data. The total scattering data may also include information necessary for calculating the structure factor based on the total scattering data, such as the type of radiation source, wavelength, background, sample shape, placement, type of constituent elements, composition, and absorption coefficient. Note that if the background is low, the background need not be included in the information necessary for calculating the structure factor. The display unit 340 displays the measurement data on the display device 520, allowing the user to confirm the measurement data. The user can also issue instructions and specifications to the control device 300, processing device 400, etc. based on the measurement data.

[0071] [Processing equipment] The processing device 400 is configured by a computer having a CPU, a ROM, a RAM, and a memory connected via 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 are configured separately, 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 apparatus 200. The structure factor acquisition unit 410 may acquire a first structure factor calculated by the 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 correlations and long-range correlations. 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 correlations and long-range correlations using the PDF. The data conversion unit 420 may also separate the first structure factor into short-range correlations and long-range correlations using a method that does not use the PDF.

[0075] The boundary value 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 that indicates the atomic arrangement within a finite region, and calculates the short-range scattering intensity of the structural model. The scattering intensity calculation unit 430 calculates a second structure factor from the short-range scattering intensity and the long-range correlation. The scattering intensity calculation unit 430 may acquire a structural model created by another device. The scattering intensity calculation unit 430 may also 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 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 structural model reproduces the measured total scattering data.

[0078] The structure evaluation unit 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 structural model. The structure estimation unit 450 preferably reserves a calculation area based on the size, shape, atomic arrangement, etc. of the structural model and creates the structural model. The size, shape, initial atomic arrangement, etc. of the structural 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 structural 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 configurations 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 source type, wavelength, background, sample shape, arrangement, constituent element type, composition, and absorption coefficient of the total scattering data. Note that 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 the structure factor calculation unit 405.

[0082] [Measurement method] A sample S is placed in the X-ray diffraction instrument 200, and the goniometer is driven under predetermined conditions under the control of the control device 300. X-rays are then incident on the sample, and diffracted X-rays generated from the sample are detected. This acquires diffraction data. The X-ray diffraction instrument 200 transmits the acquired diffraction data and other information about the instrument 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, a second structure factor including total scattering data and structural model data 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 degree of 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 degree of 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 explanation of operations that have already been explained may be omitted. The steps from obtaining the first structure factor (step T1) to calculating the second structure factor (step T5) are the same as steps S1 to S5 described above. The processing device 400 then calculates the degree of agreement or discrepancy between the first structure factor and the second structure factor (step T6) and terminates. If necessary, the second structure factor, the structure model, and the degree of agreement or discrepancy between the first structure factor and the second structure factor may be output. This makes it possible to confirm the degree to which the structure model reproduces the measured total scattering data.

[0085] (Explanation of the flow to output a structural model that meets 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. The acquisition of the first structural factors (step U1) and the separation of the first structural factors (step U2) are the same as the steps described above. 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 determines whether the degree of agreement or divergence satisfies the set predetermined conditions. If the predetermined conditions are not met (step U8-NO), the processing device 400 returns to step U3 and repeats the processing up to step U7. On the other hand, if the degree of agreement or divergence satisfies the set predetermined conditions (step U8-YES), the processing device 400 outputs the structural model (step U9) and ends the process. 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 allows a structural model that satisfies the set predetermined conditions to be created and output.

[0087] In the above flowcharts, the first structure factor is used as the initial data and the process starts with a step of acquiring the first structure factor. However, the process may also include a step of acquiring total scattering data as the initial data and creating a first structure factor from the total scattering data before 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 data was used to calculate the first structure factor and PDF. Next, using the method of the present invention, a structural model was repeatedly created using the RMC method until the discrepancy 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 discrepancy satisfied a predetermined condition. Then, the discrepancy between the PDF created from the first structure factor and the PDF created from the second structure factor was confirmed. The discrepancy was calculated using R P,G(r) This was confirmed using the w in equation (16). i is a 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 deviation 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 this.

[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 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 that is 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] We also examined histograms of the displacements calculated from the Ni atomic configuration before and after refinement using the method of the present invention and Rietveld analysis, as well as their standard deviations. Figure 18 shows a histogram of the displacements calculated from the structural model created using the method of the present invention. The standard deviation of the displacements calculated using the method of the present invention was 0.0920 Å, while it was 0.0756 Å when calculated using Rietveld analysis. This confirmed that the displacements calculated using the structural model created using the method of the present invention were comparable to those calculated using 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. It also makes it possible to analyze the characteristics of both total scattering data and structural models. Furthermore, it makes it possible to create highly accurate structural models that can explain measured data.

[0095] It goes without saying that the present invention is not limited to the above-described embodiments. The scope of the present invention extends to various modifications and equivalents that fall within the technical spirit of the present invention. Furthermore, the names, structures, shapes, numbers, positions, sizes, etc. of the components shown in each drawing are for the convenience of explanation and may be changed as appropriate. [Explanation of symbols]

[0096] 100 systems 200 X-ray Diffractometer 210 X-ray generator 220 Incident optical unit 230 Goniometer 240 Sample stage 250 Output optical unit 260 detector 300 control device 310 Control Unit 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 Department 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, A processing device, wherein the boundary values ​​between the short-range correlation and the long-range correlation are determined based on the size and shape of the region of the structural model.

2. 2. The processing apparatus according to claim 1, 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.

3. further comprising a structure estimation unit that creates the structural model, 3. The processing apparatus according to claim 2, wherein the structural evaluation unit outputs the structural model in which the degree of agreement or the degree of discrepancy satisfies a predetermined condition.

4. 3. The processing apparatus according to claim 2, 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 value of a scattering vector determined based on a boundary value between the short-range correlation and the long-range correlation.

5. 4. The processing apparatus according to claim 3, wherein the structure estimation unit creates the structural model by an RMC method.

6. 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.

7. 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 a sample; A system comprising: a processing device according to any one of claims 1 to 6.

8. 1. A method for processing a structure factor, comprising: 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; 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, The method of claim 1, wherein the values ​​of the boundaries between the short-range correlation and the long-range correlation are determined based on the size and shape of a region of the structural model.

9. A program for processing structure factors, A process of acquiring a first structure factor based on measured total scattering data; separating the first structure factor into short-range correlations and long-range correlations; 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; The program is characterized in that the boundary value 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.

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