Calculation device, method, and program

Abstract

The present invention provides a calculation device, a method, and a program for calculating a quantitative value of a test component from an X-ray powder diffraction profile. A calculation device 100 calculates a quantitative value of a test component in a test sample. The calculation device 100 includes an information acquisition unit 110 and a test sample analysis unit 130. The test sample consists of the test component and a matrix component. The information acquisition unit 110 acquires a test component intensity which is a measurement intensity derived from the test component and obtained from an X-ray diffraction profile of a first sample consisting of the test component, a test sample intensity which is a measurement intensity derived from the test component and obtained from an X-ray diffraction profile of the test sample, and an addition recovery rate indicating a degree of influence of an absorption coefficient of the matrix component on the measurement intensity of the test component. The test sample analysis unit 130 calculates the quantitative value of the test component in the test sample on the basis of the test component intensity, the test sample intensity, and the addition recovery rate.

Description

Calculation Device, Method, and Program

[0001] The present invention relates to a calculation device, a method, and a program for calculating a quantitative value of a test component from an X-ray powder diffraction profile.

[0002] As techniques for calculating the quantitative value of a test component in a sample (hereinafter simply referred to as the quantitative value) from the X-ray powder diffraction profile of the sample, a calibration curve method and a standard addition method are known. The calibration curve method is a method for determining the quantitative value in an unknown sample by comparing it with a standard sample having a known content rate. The relationship between the content rate of the standard sample and the measured intensity is plotted, a calibration curve is created by a regression line, and the quantitative value is calculated from the measured intensity of the unknown sample based on this calibration curve. Non-Patent Document 1 discloses the principle of the calibration curve method.

[0003] In addition, the standard addition method is a method in which a pure sample of the test component is added to an unknown sample, and the quantitative value of the unknown sample is calculated from the relationship between the added amount and the measured intensity. The standard addition method is often used to obtain high accuracy even for low quantitative values.

[0004] L. Alexander, et al., Anal. Chem., 1948, 20, 10, 886-889

[0005] The measured intensity derived from the test component is not necessarily proportional to the content rate of the test component. That is, if the absorption coefficient of the test component in the sample differs from the absorption coefficient of the portion of the sample other than the test component (hereinafter simply referred to as the matrix component), the accuracy of the quantitative value decreases. When the absorption coefficient of the matrix component of the sample is larger than the absorption coefficient of the test component, more X-rays are absorbed by the matrix component, and the measured intensity derived from the test component decreases. In addition, when the absorption coefficient of the matrix component is smaller than the absorption coefficient of the test component, more X-rays are absorbed by the test component, and the measured intensity derived from the test component increases. In such a case, if the horizontal axis represents the quantitative value and the vertical axis represents the measured intensity, a downward convex curve or an upward convex curve is obtained. As described above, since linearity is not always exhibited over a wide concentration range, it is necessary to create a calibration curve for the target content rate range.

[0006] To create a calibration curve, it is necessary to measure multiple points of standard samples with known content rates. Usually, standard samples are prepared by mixing a target component into a matrix component. However, for the reasons described below, in the region of low quantitative values (for example, 1% or less), creating a calibration curve is a labor-intensive or difficult task.

[0007] The first reason is that sample preparation is labor-intensive. To mix the sample, it is necessary to accurately weigh an extremely small amount of the target component, for example 1% or less relative to the weight of the matrix component, and mix them in a mortar or the like. Delicate work is required to prevent weighing errors and uneven mixing, and furthermore, manual sample preparation using an agate mortar or the like requires a long mixing time (about 30 minutes). Since a plurality of points are generally required to create a calibration curve, this operation must be repeated multiple times.

[0008] The second reason is that a high-purity matrix component containing no target component at all is required. As described above, standard samples are prepared by mixing the target component into the matrix component. If the matrix component contains even a slight amount of the target component and its concentration is unknown, preparation of the standard sample becomes difficult. In particular, this phenomenon has a prominent effect in the region of low quantitative values.

[0009] In the case of the standard addition method, the measurement intensity is obtained by adding a pure substance of the target component to the test sample and performing measurement. Similarly to the reasons related to the calibration curve, the standard addition method also has the drawback that sample preparation is labor-intensive. Furthermore, the standard addition method requires adding the pure substance of the target component to each test sample and repeating the measurement. Therefore, it has not been a suitable method in cases where it is necessary to obtain the quantitative values of a plurality of test samples respectively.

[0010] Apart from these quantitative methods, in the fields of ICP emission spectrometry and ICP mass spectrometry, saturation and recovery tests were sometimes performed to control analytical accuracy. The Ministry of the Environment's Survey Manual for Items Requiring Investigation (Water Quality, Sediment, Aquatic Organisms) (https: / / www.env.go.jp / water / chosa / h12-12 / full.pdf) states the following on page 10: "In saturation and recovery tests, (omitted), it is confirmed that the recovery rate is generally in the range of 80-120%. If the recovery rate deviates significantly from the acceptable range, the cause is investigated and the measurement is repeated." Thus, saturation and recovery rates were typically used to confirm the measurement accuracy of ICP emission spectrometry and ICP mass spectrometry.

[0011] As a result of diligent research, the inventors have completed a calculation method that requires fewer sample preparations, takes into account the absorption coefficient of matrix components, and does not require any matrix components that do not contain the test component, thereby obtaining highly accurate quantitative values.

[0012] This invention has been made in view of these circumstances, and aims to provide a computing device, method, and program for calculating quantitative values ​​of a test component from an X-ray powder diffraction profile.

[0013] (1) In order to achieve the above objective, the computing device of the present invention employs the following means. That is, a computing device according to one aspect of the present invention is a computing device for calculating a quantitative value of a test component in a test sample, wherein the computing device comprises an information acquisition unit and a test sample analysis unit, the test sample consists of the test component and a matrix component, the information acquisition unit acquires the test component intensity, which is the measured intensity derived from the test component obtained from the X-ray diffraction profile of a first sample consisting of the test component, the test sample intensity, which is the measured intensity derived from the test component obtained from the X-ray diffraction profile of the test sample, and the additive recovery rate, which indicates the degree of influence of the absorption coefficient of the matrix component on the measured intensity of the test component, and the test sample analysis unit calculates a quantitative value of the test component in the test sample based on the test component intensity, the test sample intensity, and the additive recovery rate.

[0014] (2) A computing device according to one aspect of the present invention further comprises an additive recovery rate calculation unit, wherein the information acquisition unit acquires the second sample intensity, which is the measured intensity derived from the test component obtained from the X-ray diffraction profile of the second sample consisting of the matrix components, the third sample intensity, which is the measured intensity derived from the test component obtained from the X-ray diffraction profile of the third sample obtained by adding a predetermined amount of the test component to the second sample, and the predetermined amount, and the additive recovery rate calculation unit calculates the additive recovery rate as the ratio of the increase in the quantitative value of the third sample intensity calculated based on the test component intensity to the quantitative value of the second sample intensity calculated based on the test component intensity, and the predetermined amount, and the information acquisition unit acquires the additive recovery rate calculated by the additive recovery rate calculation unit.

[0015] (3) In addition, in a computing device according to one aspect of the present invention, the information acquisition unit is characterized in that it acquires the additive recovery rate corresponding to the sample from a database which includes a combination of four types of information: the wavelength of the X-rays used for measurement, the composition of the component to be tested, the composition of the matrix component, and the additive recovery rate.

[0016] (4) Furthermore, a computing device according to one aspect of the present invention further comprises an additive recovery rate calculation unit, wherein the information acquisition unit acquires the absorption coefficient of the test component and the absorption coefficient of the matrix component, the additive recovery rate calculation unit calculates the additive recovery rate based on the absorption coefficient of the test component and the absorption coefficient of the matrix component, and the information acquisition unit acquires the additive recovery rate calculated by the additive recovery rate calculation unit.

[0017] (5) In addition, in a computing device according to one aspect of the present invention, the test sample analysis unit determines the quantitative value of the test component in the test sample C ｓａｍｐｌｅ (%), the intensity of the test sample is I ｓａｍｐｌｅ , the intensity of the tested component is I ａｎａｌｙｔｅ When the aforementioned additive recovery rate is denoted as SRR (%), the following formula (1) The quantitative value C of the test component in the test sample is obtained using the above method. ｓａｍｐｌｅ It is characterized by its ability to calculate [something].

[0018] (6) Further, in the calculation device according to one aspect of the present invention, the test sample analysis unit sets a tentative quantitative value of the test component in the test sample to C ｔｅｍｐ (%), a quantitative value of the test component in the test sample to C ｓａｍｐｌｅ (%), the test sample intensity to I ｓａｍｐｌｅ , the test component intensity to I ａｎａｌｙｔｅ , and the spike recovery rate to SRR (%), and by using the following formula (2) , calculates the tentative quantitative value C of the test component in the test sample ｔｅｍｐ , and when the tentative quantitative value C of the test component in the test sample ｔｅｍｐ is outside a predetermined range, the tentative quantitative value C of the test component in the test sample ｔｅｍｐ is defined as the quantitative value C of the test component in the test sample ｓａｍｐｌｅ , and when the tentative quantitative value C of the test component in the test sample ｔｅｍｐ is within the predetermined range, the quantitative value C of the test component in the test sample is calculated using the following formula (3) ｓａｍｐｌｅ .

[0019] (7) Further, in the calculation device according to one aspect of the present invention, the second sample contains the test component.

[0020] (8) Further, in the calculation device according to one aspect of the present invention, the content rate of the test component in the test sample is 1% or less.

[0021] (9) Further, the calculation device according to one aspect of the present invention is characterized in that the integrated intensity of one specific diffraction peak derived from the test component is acquired as the test component intensity from the X-ray diffraction profile of the first sample.

[0022] (10) Furthermore, a method according to one aspect of the present invention is a method for calculating a quantitative value of a test component in a test sample, wherein the test sample consists of the test component and a matrix component, and the method is characterized by comprising the steps of: obtaining a test component intensity, which is a measured intensity derived from the test component obtained from the X-ray diffraction profile of a first sample consisting of the test component; obtaining a test sample intensity, which is a measured intensity derived from the test component obtained from the X-ray diffraction profile of the test sample; and obtaining an additive recovery rate that indicates the degree of influence of the absorption coefficient of the matrix component on the measured intensity of the test component; and calculating a quantitative value of the test component in the test sample based on the test component intensity, the test sample intensity, and the additive recovery rate.

[0023] (11) Furthermore, a program according to one aspect of the present invention is a program for calculating a quantitative value of a test component in a test sample, wherein the test sample consists of the test component and a matrix component, and the program is characterized by causing a computer to perform the following steps: a process to obtain the test component intensity, which is the measured intensity derived from the test component obtained from the X-ray diffraction profile of a first sample consisting of the test component, the test sample intensity, which is the measured intensity derived from the test component obtained from the X-ray diffraction profile of the test sample, and an additive recovery rate indicating the degree of influence of the absorption coefficient of the matrix component on the measured intensity of the test component; and a process to calculate a quantitative value of the test component in the test sample based on the test component intensity, the test sample intensity, and the additive recovery rate.

[0024] This is a graph for explaining the 0-100% calibration curve method. (a) is a graph showing the calculation results of the quantitative value of the test sample when the 0-100% calibration curve method is used. (b) is a graph showing the calculation results of the quantitative value when the relationship between intensity and the true quantitative value (content) can be determined. This is a graph showing the calculation method of the quantitative values ​​of the second and third samples. This is a graph showing the relationship between the quantitative value and content obtained by the 0-100% calibration curve method. This is a graph showing the calculation method of the corrected quantitative value using the addition recovery rate. This is a block diagram showing an example of the configuration of the calculation device according to Embodiment 1. This is a graph showing the concept of the method for calculating the addition recovery rate. This is a graph showing an example of the method for calculating the quantitative value. This is a flowchart showing an example of the operation of the calculation device according to Embodiment 1. This is a flowchart showing a modified example of the operation of the calculation device according to Embodiment 1. This is a block diagram showing an example of the configuration of the calculation device according to Embodiment 2. This is a conceptual diagram showing an example of the system configuration. This is a block diagram showing an example of the control device configuration. This is a table showing the quantitative values ​​of each sample calculated in the example, comparative example 1, and comparative example 2.

[0025] Next, embodiments of the present invention will be described with reference to the drawings. To facilitate understanding of the description, the same reference numerals are used for identical components in each drawing, and redundant descriptions are omitted.

[0026] (Principle of Measurement Method) The principles of the conventional measurement method and the measurement method of the present invention will be briefly explained below. The 0-100% calibration curve method will be explained using Figure 1. Figure 1 is a graph for explaining the 0-100% calibration curve method. In the 0-100% calibration curve method, measurement and quantification are performed in the following procedure. Procedure 1: Measure the first sample consisting of the test component and determine the test component intensity I ａｎａｌｙｔｅ To obtain: Step 2: Measure the test sample and obtain the test sample intensity I, which is the intensity derived from the test component. ｓａｍｐｌｅ Step 3: Based on the strength of the test sample and the strength of the test component, obtain the quantitative value C of the test component in the test sample. ｔｅｍｐ Calculate.

[0027] However, the above method does not take into account the difference in absorption coefficients between the test sample and the first sample, so it is possible that a quantitative value different from the content rate will be calculated. Note that the quantitative value refers to the result calculated by the calculation, while the content rate refers to the true weight fraction contained in the sample. Figure 2(a) is a graph showing the calculation results of the quantitative value of the test sample when the 0-100% calibration curve method is used. Figure 2(b) is a graph showing the calculation results of the quantitative value when the relationship between intensity and the true quantitative value (content rate) can be determined. The solid line in Figure 2(b) shows the relationship between intensity and the true quantitative value. As shown in Figures 2(a) and 2(b), if the calibration curve is not linear, the correct content rate cannot be obtained. Therefore, in this invention, the additive recovery rate is calculated or obtained and the quantitative value obtained in step 3 above is corrected. The correction method is described below.

[0028] Let's define a test sample as consisting of a test component and a matrix component, and consider the case where the proportion of the test component in the test sample is very small. In that case, we can assume that the absorption coefficients of the test sample and the sample consisting of the matrix component are similar.

[0029] When the above assumption is true, the corrected quantitative values ​​can be obtained by following steps 4 to 7 below. Figure 3 is a graph showing the calculation method for the quantitative values ​​of the second and third samples. Step 4: Measure the second sample consisting of matrix components and obtain the second sample intensity I, which is the intensity derived from the test component. ２ This is obtained. Then, the second sample intensity I ２ and the intensity of the test component I ａｎａｌｙｔｅ Based on this, the quantitative value C of the test component in the second sample ２ The following is calculated. Note that in Figure 3, the second sample shows an example in which the test component is included in addition to the matrix component. Procedure 5: Measure the third sample obtained by adding a small amount of the test component to the second sample, and calculate the third sample intensity I, which is the intensity derived from the test component. ３ This is obtained. And the third sample intensity I ３ and the intensity of the test component I ａｎａｌｙｔｅ Based on this, the quantitative value C of the test component in the third sample. ３Calculate the following. Step 6: From the relationship between the quantitative value of the test component in the second sample and the quantitative value of the test component in the third sample, and the amount of test component added in Step 5, determine the addition recovery rate, which is the ratio of the increase in the quantitative value to the amount added. Step 7: Using the addition recovery rate obtained in Step 6, calculate the quantitative value C of the test component obtained in Step 3. ｔｅｍｐ Correct the value and obtain the corrected quantitative value C ｓａｍｐｌｅ To obtain.

[0030] Step 6 will be explained using Figure 4. Figure 4 is a graph showing the relationship between the quantitative value obtained by the 0-100% calibration curve method and the content. In the 0-100% calibration curve method, the measured intensity and the quantitative value are in a proportional relationship. Therefore, the intensity axis in Figure 2(b) is set to I ａｎａｌｙｔｅ Dividing by allows conversion to a quantitative value. That is, the solid line in Figure 2(b) can be considered as the relationship between the quantitative value and the content rate, as shown in Figure 4, by changing the scale of the graph. In Figure 4, the added recovery rate is the slope between points A and B, and the quantitative value C of the test component in the second sample. ２ and the quantitative value C of the test component in the third sample ３ This can be determined from the amount added.

[0031] Step 7 will be explained using Figure 5. Figure 5 is a graph showing the method for calculating the corrected quantitative value using the added recovery rate. The straight line passing through the origin with the slope between points A and B obtained in Step 6 is used as the corrected calibration curve. The vertical axis is plotted on the quantitative value C obtained using the 0-100% calibration curve method. ｔｅｍｐ When you input this, the corrected quantitative value C ｓａｍｐｌｅ This is calculated.

[0032] By using steps 1 through 7 described above, it becomes possible to calculate quantitative values ​​that take into account the absorption of matrix components. Note that this description of the principle is intended to explain the concept of correction using the added recovery rate and is merely one example of an implementation. Therefore, the scope of rights is not limited to this description.

[0033] [Embodiments] (Embodiment 1) [Calculation device] Embodiment 1 describes a case in which the addition recovery rate is calculated and the quantitative value of the test component in the test sample is calculated based on the strength of the test component, the strength of the test sample, and the addition recovery rate. Figure 6 is a block diagram showing an example of the configuration of the calculation device 100 according to Embodiment 1. The calculation device 100 may be connected to the X-ray diffractometer 200 via a control device 300 that controls the X-ray diffractometer 200, which will be described later, or directly to the X-ray diffractometer 200.

[0034] The computing device 100 calculates the quantitative value of the test component in the test sample. The computing device 100 is composed of a computer with a CPU (Central Processing Unit), ROM (Read Only Memory), RAM (Random Access Memory), and memory connected to a bus. The computing device 100 may be a PC terminal or a server on the cloud. Furthermore, not only the entire device, but also some of the devices or some of the functions within the device may be provided on the cloud. The input device 510 and the display device 520 are connected to the CPU of the computing device 100 via an appropriate interface. The input device 510 is, for example, a keyboard and mouse, and provides input to the computing device 100. The display device 520 is, for example, a display, and displays the test component intensity, test sample intensity, addition recovery rate, second sample intensity, third sample intensity, predetermined amount, X-ray diffraction profile of each sample, absorption coefficient of the test component (linear absorption coefficient or mass absorption coefficient), or absorption coefficient of the matrix component.

[0035] The computing device 100 includes an information acquisition unit 110, an additive recovery rate calculation unit 120, and a test sample analysis unit 130. Each unit can send and receive information via a control bus L.

[0036] The information acquisition unit 110 acquires the intensity of the test component, the intensity of the test sample, and the dosing recovery rate. The intensity of the test component is the measured intensity derived from the test component obtained from the X-ray diffraction profile of the first sample consisting of the test component. The intensity of the test sample is the measured intensity derived from the test component obtained from the X-ray diffraction profile of the test sample. The dosing recovery rate is the ratio of the increase in the quantitative value to the amount added. In other words, the dosing recovery rate can be rephrased as a value that indicates the degree of influence of the absorption coefficient of the matrix component on the measured intensity of the test component. Thus, the dosing recovery rate of the present invention is used in a different sense from the conventional dosing recovery rate used until now.

[0037] Preferably, the intensity of the component under test acquired by the information acquisition unit 110 is the integrated intensity of a specific diffraction peak originating from the component under test in the X-ray diffraction profile of the first sample. In this case, the intensity of the sample under test, the intensity of the second sample, and the intensity of the third sample are also the integrated intensity of the same diffraction peak. When calculating the integrated intensity using a specific characteristic diffraction peak among the diffraction peaks originating from the component under test in this way, it is possible to measure only a narrow angular range, thus reducing the cost of measurement. Furthermore, it is possible to calculate an intensity that is less affected by the grain size and crystallinity of the contained component under test, improving the accuracy of the quantitative value.

[0038] A test sample consists of a test component and a matrix component. That is, the matrix component is the component of the test sample other than the test component. The matrix component may contain two or more substances.

[0039] The content of the test component in the test sample is preferably 1% (mass%) or less. In the correction using the addition recovery rate, the calibration curve is corrected by assuming that the absorption coefficient of the test sample is close to the absorption coefficient of the matrix component. That is, if the content of the test component in the test sample is high, the absorption coefficients of the test sample and the matrix component will be different, making accurate analysis impossible. The method of the present invention can obtain a highly accurate quantitative value when the content of the test component in the test sample is low. Note that "%" in quantitative value, content, or addition concentration means "mass%".

[0040] The first sample consists of the test component. The first sample consisting of the test component means that the content of components other than the test component in the first sample is 1% or less. That is, the first sample may contain impurities of 1% or less in addition to the test component whose composition is known. Here, "containing the test component" means that it contains the same composition as the test component in the test sample. Therefore, components other than composition, such as crystal grain size and crystallinity, may differ. For example, a reagent containing the test component may be used.

[0041] The information acquisition unit 110 may acquire information necessary to calculate the additive recovery rate instead of the additive recovery rate itself. For example, the information acquisition unit 110 may acquire the second sample intensity, the third sample intensity, and a predetermined amount. Alternatively, for example, the information acquisition unit 110 may acquire the absorption coefficient (linear absorption coefficient or mass absorption coefficient) of the test component and the absorption coefficient of the matrix component. In these cases, the additive recovery rate calculation unit 120 calculates the additive recovery rate based on the acquired information, and the information acquisition unit 110 acquires the calculated additive recovery rate.

[0042] The information acquisition unit 110 may acquire the X-ray diffraction profile of the first sample consisting of the test component and the X-ray diffraction profile of the test sample instead of the test component intensity and the test sample intensity. In this case, the calculation device 100 may include a qualitative analysis unit that analyzes the measured intensity derived from the test component in each X-ray diffraction profile.

[0043] The additive recovery rate calculation unit 120 calculates the additive recovery rate. When the information acquisition unit 110 acquires the second sample intensity, the third sample intensity, and a predetermined amount, the additive recovery rate calculation unit 120 calculates the additive recovery rate based on the second sample intensity, the third sample intensity, and the predetermined amount. The second sample intensity is the measured intensity derived from the test component obtained from the X-ray diffraction profile of the second sample. The third sample intensity is the measured intensity derived from the test component obtained from the X-ray diffraction profile of the third sample.

[0044] The second sample consists of matrix components. The statement that the second sample consists of matrix components means that the content of components other than the matrix components in the second sample is 10% or less. That is, the second sample may contain impurities of 10% or less in addition to the matrix components whose composition is known. The second sample preferably contains 90% or more matrix components, more preferably 95% or more, and more preferably 99% or more. Here, "containing matrix components" means that it contains the same composition as the matrix components of the test sample. Therefore, components other than composition, such as crystal grain size and crystallinity, may differ. For example, a reagent containing matrix components may be used. The overall linear absorption coefficient of the second sample is preferably close to that of the matrix components. The second sample may contain the test component. The second sample may also be the test sample. The third sample is the second sample to which a predetermined amount of the test component has been added. The addition concentration corresponding to the predetermined amount is preferably 5% or less, more preferably 3% or less, and even more preferably 1% or less.

[0045] As a method for calculating the additive recovery rate based on the second sample strength, the third sample strength, and a predetermined amount, for example, it can be calculated as the ratio of the increase in the quantitative value of the third sample strength relative to the quantitative value of the second sample strength to the predetermined amount.

[0046] Figure 7 is a graph illustrating the concept of the method for calculating the spike recovery rate. The spike recovery rate is expressed as SRR (Spike Recovery Rate) (%), and the intensity of the test component is expressed as I. ａｎａｌｙｔｅ , the intensity of the second sample is I ２ , the intensity of the third sample is I ３ The additive concentration corresponding to the predetermined amount is defined as AC (Addition Concentration) (%). First, the intensity of the test component I ａｎａｌｙｔｅ In contrast, the intensity of the test component I ａｎａｌｙｔｅ A point is plotted on the graph at the position where the value is 100%, and connected to the origin to create a 0-100% calibration curve. Next, on the 0-100% calibration curve, the second sample intensity I ２ The corresponding quantitative value C ２ , and third sample intensity I ３ The corresponding quantitative value C ３The following is calculated: Then, the quantitative value C of the second sample intensity is calculated. ２ Quantitative value C of the third sample intensity relative to [value] ３ The ratio of the increase in the amount to the additive concentration corresponding to the predetermined amount is calculated and defined as the additive recovery rate (SRR). The mass of the second sample is M. ２ (g), the specified amount M ｐ When expressed as (g), the additive concentration AC (%) corresponding to a predetermined amount can be calculated, for example, by the following formula (4). The position of the point corresponding to the intensity of the test component may be changed according to the concentration of the test component in the first sample.

[0047]

[0048] The additive recovery rate calculation unit 120 can also calculate the additive recovery rate using only mathematical formulas, without relying on graphs. The additive recovery rate is set to SRR (%), and the intensity of the test component is set to I. ａｎａｌｙｔｅ , the intensity of the second sample is I ２ , the intensity of the third sample is I ３ The additive concentration corresponding to a predetermined amount is defined as AC (%). The additive recovery rate calculation unit 120 can calculate the additive recovery rate SRR, for example, using the following formula (5). Also, the additive recovery rate is defined as SRR, and the quantitative value of the second sample intensity is defined as C. ２ (%), the quantitative value of the third sample intensity is C ３ (%), and the additive concentration corresponding to a predetermined amount is defined as AC (%). The additive recovery rate calculation unit 120 can calculate the additive recovery rate SRR, for example, using the following formula (6).

[0049]

[0050]

[0051] When the information acquisition unit 110 acquires the absorption coefficient of the test component and the absorption coefficient of the matrix component, the additive recovery rate calculation unit 120 calculates the additive recovery rate based on the absorption coefficient of the test component and the absorption coefficient of the matrix component. This eliminates the need for measurement to calculate the additive recovery rate, thereby reducing costs. The absorption coefficient may be a value obtained by measurement, or it may be a value calculated theoretically based on the composition, etc.

[0052] The additive recovery rate calculation unit 120 calculates the additive recovery rate as SRR (%) and the linear absorption coefficient of the test component as μ ａｎａｌｙｔｅ (cm －１ ), the linear absorption coefficient of the matrix component is μ ｍａｔｒｉｘ (cm －１ When this is the case, the additive recovery rate (SRR) can be calculated, for example, by the following formula (7). Note that the additive recovery rate calculated in this way will have the same value as the ratio of the increase in the quantitative value to the amount added.

[0053]

[0054] For example, if the component being tested is crystalline silica (SiO ２ ), the matrix component is calcium carbonate (CaCO3). ３ ) Let's assume that this is the case. In this case, SiO ２ The linear absorption coefficient is 103.4 (cm²). －１ ), CaCO ３ The linear absorption coefficient is 196.2 (cm²). －１ Therefore, the additive recovery rate (SRR) is calculated to be 52.7%.

[0055] The sample analysis unit 130 calculates the quantitative value of the test component in the test sample based on the strength of the test component, the strength of the test sample, and the recovery rate. As described above, various methods can be considered for calculating the recovery rate. Therefore, various methods can be considered for calculating the quantitative value of the test component in the test sample based on the method for calculating the recovery rate. The calculation device 100 may also directly calculate the quantitative value of the test component in the test sample using a formula that includes a formula for calculating the recovery rate, without calculating the recovery rate itself. Even when directly calculating the quantitative value of the test component in the test sample using such a formula, it is included in calculating the quantitative value of the test component in the test sample based on the strength of the test component, the strength of the test sample, and the recovery rate.

[0056] In the following, we consider the case where the recovery rate is calculated as either "the ratio (%) of the increase in the quantitative value of the third sample intensity, calculated based on the test component intensity, relative to the quantitative value of the second sample intensity, calculated based on the test component intensity, and the additive concentration corresponding to a predetermined amount" or "the ratio (%) of the linear absorption coefficient of the test component to the linear absorption coefficient of the matrix component."

[0057] The test sample analysis unit 130, for example, determines the quantitative value of the test component in the test sample. ｓａｍｐｌｅ (%), the strength of the test sample is I ｓａｍｐｌｅ , the intensity of the test component is I ａｎａｌｙｔｅ When the recovery rate is denoted as SRR (%), the quantitative value C of the test component in the test sample is obtained using the following formula (8). ｓａｍｐｌｅ It is possible to calculate this.

[0058]

[0059] Figure 8 is a graph showing an example of a method for calculating quantitative values. The test sample analysis unit 130 calculates, for example, a provisional quantitative value of the test component in the test sample C ｔｅｍｐ (%), the quantitative value of the test component in the test sample C ｓａｍｐｌｅ (%), the strength of the test sample is I ｓａｍｐｌｅ , the intensity of the test component is I ａｎａｌｙｔｅ When the added recovery rate is denoted as SRR (%), a provisional quantitative value of the test component in the test sample can be calculated using the following formula (9).

[0060]

[0061] And, a provisional quantitative value C ｔｅｍｐ If the value is outside the predetermined range (less than the lower limit or greater than the upper limit), the sample analysis unit 130 calculates a provisional quantitative value C. ｔｅｍｐ The quantitative value C ｓａｍｐｌｅ This can be done. On the other hand, the provisional quantitative value C ｔｅｍｐ If the value is within a predetermined range (above the lower limit and below the upper limit), the sample analysis unit 130 uses the following formula (10) to determine the quantitative value C ｓａｍｐｌｅThis allows for the calculation of the following. The predetermined range may be predetermined or set by the user. The predetermined range may be from 0 to a predetermined value. The predetermined range may depend on the reference value that the user intends to test. For example, it can be appropriately selected from a range of 1 / 10 to 10 times the reference value. With this configuration, after obtaining a rough quantitative value using the 0-100% calibration curve method, matrix correction can be performed only on those close to the reference value. For example, in the analysis of crystalline silica, it is important whether the amount of crystalline silica in the sample exceeds 0.1%. In that case, if the quantitative value obtained using the 0-100% calibration curve method deviates significantly from 0.1%, it is possible to determine whether it exceeds or does not exceed 0.1% without performing correction using the additive recovery rate. Only those that do not deviate significantly need to consider the matrix component and perform correction using the additive recovery rate, which is expected to improve throughput.

[0062]

[0063] The sample analysis unit 130 can easily calculate the quantitative value of the test component in the sample without using the addition recovery rate. For example, the sample analysis unit 130 calculates the quantitative value of the test component in the sample C ｓａｍｐｌｅ (%), the strength of the test sample is I ｓａｍｐｌｅ , the intensity of the second sample is I ２ , the intensity of the third sample is I ３ When the additive concentration corresponding to a predetermined amount is denoted as AC (%), the quantitative value C of the test component in the test sample can be calculated using the following formula (11). ｓａｍｐｌｅ This method allows for the calculation of the third sample intensity I. ３ Second sample intensity I ２ This method of calibration involves using the ratio of the increase in amount to the additive concentration AC (%) corresponding to a predetermined amount as the slope, and using a straight line passing through the origin as the calibration curve.

[0064]

[0065] Figure 9 is a flowchart illustrating an example of the operation of the calculation device 100 according to Embodiment 1. Figure 9 shows an example of the operation when calculating the additive recovery rate and then calculating the quantitative value of the test component in the test sample based on the test component strength, the test sample strength, and the additive recovery rate. First, the information acquisition unit 110 of the calculation device 100 acquires information (step S1). The information to be acquired is the test component strength, the test sample strength, and the information necessary to calculate the additive recovery rate. Next, the additive recovery rate calculation unit 120 calculates the additive recovery rate (step S2). The method for calculating the additive recovery rate varies depending on the information to be acquired, but for example, it can be calculated using the above formulas (5) to (7).

[0066] The test sample analysis unit 130 then calculates the quantitative value of the test component in the test sample based on the test component strength, the test sample strength, and the recovery rate (step S3), and then terminates. If necessary, the test component strength, test sample strength, recovery rate, or quantitative value may be output. In this way, the recovery rate can be calculated, and the quantitative value of the test component in the test sample can be calculated based on the test component strength, the test sample strength, and the recovery rate.

[0067] Figure 10 is a flowchart showing a modified operation of the calculation device 100 according to Embodiment 1. Figure 10 shows an example of operation when calculating a provisional quantitative value of the test component in the test sample and deciding whether to correct it using the addition recovery rate according to the relationship between the provisional quantitative value and a predetermined range. Steps T1 to T2 are the same as steps S1 to S2.

[0068] Next, the test sample analysis unit 130 of the calculation device 100 calculates a provisional quantitative value of the test component in the test sample based on the test component strength and the test sample strength (step T3). Next, it determines whether the provisional quantitative value is within a predetermined range (step T4). If the provisional quantitative value is within the predetermined range (step T4-YES), the test sample analysis unit 130 calculates the quantitative value using the addition recovery rate (step T5). On the other hand, if the provisional quantitative value is outside the predetermined range (step T4-NO), the test sample analysis unit 130 determines the provisional quantitative value to be the quantitative value and terminates. If necessary, the test component strength, test sample strength, addition recovery rate, provisional quantitative value, or quantitative value may be output. In this way, a provisional quantitative value of the test component in the test sample can be calculated, and it is possible to determine whether to correct the quantitative value of the test component in the test sample using the addition recovery rate according to the relationship between the provisional quantitative value and the predetermined range.

[0069] (Embodiment 2) [Calculation device] The calculation device 100 may not calculate the additive recovery rate, but may acquire a pre-stored additive recovery rate. Embodiment 2 describes a case in which the additive recovery rate is acquired, and the quantitative value of the test component in the test sample is calculated based on the strength of the test component, the strength of the test sample, and the additive recovery rate. Figure 11 is a block diagram showing an example of the configuration of the calculation device 100 according to Embodiment 2. As shown in Figure 11, the calculation device 100 includes an information acquisition unit 110 and a test sample analysis unit 130. That is, the calculation device 100 does not need to include an additive recovery rate calculation unit 120. The calculation device 100 of Embodiment 2 has the same features as the calculation device 100 of Embodiment 1, except for the calculation of the additive recovery rate.

[0070] The information acquisition unit 110 acquires the intensity of the test component, the intensity of the test sample, and the dosing recovery rate. In this case, it is preferable that the information acquisition unit 110 acquires the dosing recovery rate corresponding to the test sample from a database that includes combinations of four types of information: the wavelength of the X-rays used for measurement, the composition of the test component, the composition of the matrix component, and the dosing recovery rate. This eliminates the need for measurement to calculate the dosing recovery rate, thereby reducing costs. The dosing recovery rate may be a value obtained by measurement for each combination of the test component and the matrix component, or it may be a value theoretically calculated based on the composition of the test component and the composition of the matrix component. The database may also include information other than the four types of information mentioned above (such as the crystal grain size and crystallinity of the test component and the matrix component).

[0071] [Overall System] The calculation device 100 or calculation method of the present invention can acquire information and calculate quantitative values ​​independently of the X-ray diffractometer 200 and the control device 300. Therefore, the calculation device 100 does not need to be used simultaneously with the X-ray diffractometer 200 and the control device 300. On the other hand, it can also be integrated into a system with the X-ray diffractometer 200 and the control device 300. Figure 12 is a conceptual diagram showing an example of the configuration of a system 400 including the calculation device 100 and the X-ray diffractometer 200. The system 400 has the calculation device 100, the X-ray diffractometer 200, and the control device 300.

[0072] Note that in Figure 12, the computing device 100 and the control device 300 are depicted as the same PC. However, the computing device 100 may be configured as a different device from the control device 300. The following section will describe the case where the computing device 100 and the control device 300 are configured as different devices.

[0073] [X-ray Diffractometer] The X-ray diffractometer 200 comprises an optical system that incidents X-rays onto a sample and detects reflected X-rays generated from the sample. The X-ray diffractometer 200 comprises at least an X-ray generating unit 210 that generates X-rays from the X-ray focal point, i.e., the X-ray source; a sample stage 240 on which the sample is placed and which controls the rotation of the sample; and a detector 260 that detects X-rays. The X-ray diffractometer 200 may also include an incident optical unit 220, a goniometer 230, or an exit optical unit 250. The X-ray generating unit 210, incident optical unit 220, goniometer 230, sample stage 240, exit optical unit 250, and detector 260 that constitute the X-ray diffractometer 200 can be general-purpose, so a detailed explanation is omitted. Note that the configuration shown in the figure is just one example, and various other configurations can be adopted.

[0074] [Control device] The control device 300 is connected to the X-ray diffractometer 200 and controls the X-ray diffractometer 200, as well as processing, storing, and displaying the acquired data.

[0075] Figure 13 is a block diagram showing an example of the configuration of the control device 300. The control device 300 is composed of a computer with a CPU, ROM, RAM, and memory connected to a bus. The control device 300 may be a PC terminal or a server on the cloud. Furthermore, not only the entire system, but also some of the system or some of the functions within the system may be located on the cloud. The control device 300 is connected to the X-ray diffractometer 200 to receive information.

[0076] 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 the control bus L. When the computing device 100 and the control device 300 have different configurations, the input device 510 and the display device 520 are connected to the CPU of the control device 300 via an appropriate interface. In this case, the input device 510 and the display device 520 may be different from those connected to the computing device 100.

[0077] The control unit 310 controls the operation of the X-ray diffractometer 200. The device information storage unit 320 stores device information acquired from the X-ray diffractometer 200. The device information may include information about the X-ray diffractometer 200 such as the device name, type of radiation source, wavelength, and background.

[0078] The measurement data storage unit 330 stores measurement data, including the X-ray diffraction profile acquired from the X-ray diffractometer 200. Along with the measurement data, it may also store necessary information such as the type of radiation source, wavelength, background, and other information related to the X-ray diffractometer 200, as well as the shape, arrangement, type and composition of the constituent elements of the sample, and absorption coefficient. The display unit 340 displays the measurement data on the display device 520. This allows the user to confirm the measurement data. The user can also give instructions and specifications to the control device 300, the calculation device 100, etc., based on the measurement data. If the calculation device 100 does not have a qualitative analysis unit that analyzes the measurement intensity derived from the test component in the X-ray diffraction profile, the control device 300 may have a qualitative analysis unit.

[0079] The computing device 100 may be configured as a part of the control device 300. Alternatively, the computing device 100 and the control device 300 may be configured as an integrated device.

[0080] [Measurement Method] A sample is placed in the X-ray diffractometer 200, and X-rays are incident on the sample based on the control of the control device 300, and the diffracted X-rays and other radiation generated from the sample are detected. If necessary, the sample stage or goniometer is driven under predetermined conditions. This acquires measurement data such as total scattering data. The X-ray diffractometer 200 transmits the acquired measurement data and necessary device information to the control device 300.

[0081] By using the system 400 described above, measurement data can be acquired from the X-ray diffractometer 200 and quantitative values ​​can be calculated.

[0082] [Example] Using the calculation device 100 configured as described above, the quantitative value of crystalline silica in a sample of calcium carbonate mixed with crystalline silica was calculated. Specifically, calcium carbonate (manufactured by Kojun Chemical Laboratory) was used as the matrix. Quartz (manufactured by Kojun Chemical Laboratory), tridymite (Tri.31) (manufactured by the Japan Fibrous Materials Research Association), and cristobalite (1879b) (manufactured by the National Institute of Standards and Technology (NIST)) were used as standard samples. These were wet-mixed with calcium carbonate to concentrations of 0.1%, 0.2%, 0.5%, and 1%, respectively. In addition, a standard sample with a purity of 99.99% was used as the first sample in the method of the present invention.

[0083] Next, measurements were performed using a SmartLab SE X-ray diffractometer (manufactured by Rigaku). The measurement conditions, including measurement time, were as follows: While it is desirable to select the strongest diffraction line for each crystalline silica, the strongest diffraction line for tridymite is close to the diffraction peak of calcium carbonate, so measurements were taken near the second strongest diffraction line. Measurement range: Tridymite: 18° to 21.5° Cristobalite: 21° to 23° Quartz: 25° to 28° Step: 0.02° Speed: 0.5° / min

[0084] Next, the measured intensity derived from the test component of each sample was obtained. Then, using the computing device 100, the quantitative value of crystalline silica in each sample was calculated using the method of the present invention (Example), the 0-100% calibration curve method (Comparative Example 1), and the 0-1% calibration curve method using the matrix matching method (Comparative Example 2). In the method of the present invention, a sample containing only calcium carbonate without crystalline silica was used as the second sample, and a sample with 1% crystalline silica added was used as the third sample, and the recovery rate was calculated. The 0-100% calibration curve method is a method in which the measured intensity (test component intensity) of the first sample is taken as the intensity when it is 100%, and a straight line passing through the point of that intensity and the origin is used as a calibration curve to calculate the quantitative value of each sample.

[0085] Matrix matching is a quantitative method that involves preparing a standard sample to match the matrix of an unknown sample and then measuring it. A key advantage of matrix matching is that it allows for direct correction of intensity due to matrix components. However, it requires a reagent containing matrix components that are either free of or negligibly free of crystalline silica as an impurity. Furthermore, a disadvantage is the need to accurately mix crystalline silica with the high-purity matrix components to create a calibration curve. Figure 14 is a table showing the quantitative values ​​of each sample calculated in the example, comparative example 1, and comparative example 2. Numbers marked with an asterisk (*) indicate values ​​below the limit of quantification.

[0086] The quantitative results obtained using the present invention were found to agree well with the prepared values ​​(weighed values) within the margin of error. Furthermore, it was found that the present invention can calculate quantitative values ​​with the same accuracy as the 0-1% calibration curve method using matrix matching. On the other hand, it was found that the 0-100% calibration curve method cannot quantify with sufficient accuracy in the range of content below 1%.

[0087] Based on the above results, it has been confirmed that the calculation device, method, and program of the present invention can calculate quantitative values ​​of the test component from the X-ray powder diffraction profile with high accuracy.

[0088] It goes without saying that the present invention is not limited to the embodiments described above. The scope of the present invention extends to various variations and equivalents included in the technical concept of the present invention. Furthermore, the names, structures, shapes, numbers, positions, sizes, etc., of the components shown in each drawing are for illustrative purposes only and may be changed as appropriate.

[0089] The functions of the elements disclosed herein may be implemented using circuits or processing circuitry that include general-purpose processors, special-purpose processors, integrated circuits, ASICs (Application Specific Integrated Circuits), FPGAs (Field Programmable Gate Arrays), conventional circuits, and / or combinations thereof that are programmed using one or more programs stored in one or more memories, or otherwise configured to perform the disclosed functions. A processor is considered a circuit or processing circuitry because it includes transistors and other circuits. A processor may be a programmed processor that executes programs stored in memory. In this disclosure, a circuit, unit, or means is hardware that performs the enumerated functions, or hardware programmed to perform the enumerated functions. Hardware may be any hardware disclosed herein that is programmed or configured to perform the enumerated functions.

[0090] 100 Calculation device 110 Information acquisition unit 120 Addition recovery rate calculation unit 130 Sample analysis unit 200 X-ray diffractometer 210 X-ray generation unit 220 Incident optical unit 230 Goniometer 240 Sample stage 250 Exit optical unit 260 Detector 300 Control device 310 Control unit 320 Device information storage unit 330 Measurement data storage unit 340 Display unit 400 System 510 Input device 520 Display device

Claims

1. A calculation device for calculating a quantitative value of a test component in a test sample, wherein the calculation device comprises an information acquisition unit and a test sample analysis unit, the test sample consists of the test component and a matrix component, the information acquisition unit acquires the test component intensity, which is the measured intensity derived from the test component obtained from the X-ray diffraction profile of a first sample consisting of the test component, the test sample intensity, which is the measured intensity derived from the test component obtained from the X-ray diffraction profile of the test sample, and the additive recovery rate, which indicates the degree of influence of the absorption coefficient of the matrix component on the measured intensity of the test component, and the test sample analysis unit calculates a quantitative value of the test component in the test sample based on the test component intensity, the test sample intensity, and the additive recovery rate.

2. The calculation device further comprises an additive recovery rate calculation unit, the information acquisition unit acquires a second sample intensity, which is a measured intensity derived from the test component obtained from the X-ray diffraction profile of a second sample consisting of the matrix components, a third sample intensity, which is a measured intensity derived from the test component obtained from the X-ray diffraction profile of a third sample obtained by adding a predetermined amount of the test component to the second sample, and the predetermined amount, the additive recovery rate calculation unit calculates the additive recovery rate as the ratio of the increase in the quantitative value of the third sample intensity calculated based on the test component intensity to the quantitative value of the second sample intensity calculated based on the test component intensity, and the predetermined amount, and the information acquisition unit acquires the additive recovery rate calculated by the additive recovery rate calculation unit, the calculation device according to claim 1.

3. The computing device according to claim 1, characterized in that the information acquisition unit acquires the additive recovery rate corresponding to the sample from a database that includes a combination of four types of information: the wavelength of the X-rays used for measurement, the composition of the component to be tested, the composition of the matrix component, and the additive recovery rate.

4. The calculation device further comprises an additive recovery rate calculation unit, the information acquisition unit acquires the absorption coefficient of the test component and the absorption coefficient of the matrix component, the additive recovery rate calculation unit calculates the additive recovery rate based on the absorption coefficient of the test component and the absorption coefficient of the matrix component, and the information acquisition unit acquires the additive recovery rate calculated by the additive recovery rate calculation unit, as described in claim 1.

5. The sample analysis unit determines the quantitative value of the test component in the sample. ｓａｍｐｌｅ (%), the intensity of the test sample is I ｓａｍｐｌｅ , the intensity of the tested component is I ａｎａｌｙｔｅ When the aforementioned additive recovery rate is denoted as SRR (%), the following formula (1) The quantitative value C of the test component in the test sample is obtained using the above method. ｓａｍｐｌｅ A calculating device according to any one of claims 1 to 4, characterized by calculating [something].

6. The analyte sample analysis unit sets a tentative quantitative value of the target component in the analyte sample as C ｔｅｍｐ (%), a quantitative value of the target component in the analyte sample as Ｃｓａｍｐ le (%), the analyte sample intensity as I ｓａｍｐｌｅ , the target component intensity as I ａｎａｌｙｔｅ , and the added recovery rate as SRR (%), then using the following formula (2) to calculate the tentative quantitative value C of the target component in the analyte sample ｔｅｍｐ , when the tentative quantitative value C of the target component in the analyte sample ｔｅｍｐ is outside a predetermined range, the tentative quantitative value C of the target component in the analyte sample ｔｅｍｐ is taken as the quantitative value C of the target component in the analyte sample ｓａｍｐｌｅ , and when the tentative quantitative value C of the target component in the analyte sample ｔｅｍｐ is within the predetermined range, the quantitative value C of the target component in the analyte sample is calculated using the following formula (3) ｓａｍｐｌｅ . The calculation device according to any one of claims 1 to 4, wherein the calculation is performed.​ 7. The computing apparatus according to claim 2, characterized in that the second sample contains the test component.

8. The calculation device according to any one of claims 1 to 4, characterized in that the content of the test component in the test sample is 1% or less.

9. The computing device according to any one of claims 1 to 4, characterized in that it obtains the integrated intensity of a specific diffraction peak originating from the test component from the X-ray diffraction profile of the first sample as the test component intensity.

10. A method for calculating a quantitative value of a test component in a test sample, wherein the test sample consists of the test component and a matrix component, and the method comprises the steps of: obtaining the test component intensity, which is the measured intensity derived from the test component obtained from the X-ray diffraction profile of a first sample consisting of the test component; obtaining the test sample intensity, which is the measured intensity derived from the test component obtained from the X-ray diffraction profile of the test sample; and obtaining an additive recovery rate that indicates the degree of influence of the absorption coefficient of the matrix component on the measured intensity of the test component; and calculating a quantitative value of the test component in the test sample based on the test component intensity, the test sample intensity, and the additive recovery rate.

11. A program for calculating a quantitative value of a test component in a test sample, wherein the test sample consists of the test component and a matrix component, and the program is characterized by causing a computer to perform the following steps: a process to obtain the test component intensity, which is the measured intensity derived from the test component obtained from the X-ray diffraction profile of a first sample consisting of the test component, the test sample intensity, which is the measured intensity derived from the test component obtained from the X-ray diffraction profile of the test sample, and an additive recovery rate indicating the degree of influence of the absorption coefficient of the matrix component on the measured intensity of the test component; and a process to calculate a quantitative value of the test component in the test sample based on the test component intensity, the test sample intensity, and the additive recovery rate.

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