Evaluation system

Abstract

To provide an evaluation system capable of evaluating a dispersion state of a filler in a composite material.SOLUTION: An evaluation system comprises an input part, an amount ratio calculation part, a prediction range calculation part, and a determination part. The input part can input an image obtained by photographing a composite material including a polymer and a filler, blending of the composite material, and the area S of a photographic visual field of the photography. The amount ratio calculation part calculates the amount ratio of the filler. The prediction range calculation part calculates a prediction range of the amount ratio of the filler through simulation of dispersion of the filler in the composite material based upon the blending and the area S. The determination part determines whether the amount ratio of the filler calculated by the amount ratio calculation unit is within the prediction range.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present disclosure relates to a rating system. [Background technology]

[0002] Patent Document 1 describes a method for evaluating a polymer compound using a focused ion beam. Patent Document 2 describes a method for evaluating a composite material using a scanning electron microscope. The composite material contains a filler and a polymer. To observe the morphology of the composite material, the composite material may be photographed using a scanning probe microscope or the like to obtain an image. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2012-163480 [Patent Document 2] Patent Publication No. 2021-148491 Summary of the Invention [Problem to be solved by the invention]

[0004] The following method can be considered as a method for evaluating the dispersion state of a filler in a composite material. The composite material is photographed to obtain an image. The filler content ratio (hereinafter referred to as the first content ratio) is calculated from the obtained image. Furthermore, the filler content ratio (hereinafter referred to as the second content ratio) is calculated from the composition of the composite material. The filler dispersion state is evaluated by comparing the first content ratio with the second content ratio.

[0005] When photographing a composite material using a scanning probe microscope or the like, the area of ​​the photographed field of view is small. Therefore, even if the filler is well dispersed, the first content ratio varies. Therefore, it has been difficult to evaluate the filler dispersion state by comparing the first content ratio with the second content ratio.

[0006] In one aspect of the present disclosure, it is preferable to provide an evaluation system capable of evaluating the dispersion state of a filler in a composite material. [Means for solving the problem]

[0007] One aspect of the present disclosure is an evaluation system including: an input unit capable of inputting an image obtained by photographing a composite material containing a polymer and a filler, the composition of the composite material, and an area S of the field of view in the photographing; a quantity ratio calculation unit configured to calculate the amount ratio of the filler from the image; a prediction range calculation unit configured to calculate a prediction range of the amount ratio of the filler by performing a simulation that simulates the dispersion of the filler in the composite material based on the composition and the area S; and a determination unit configured to determine whether the amount ratio of the filler calculated by the quantity ratio calculation unit is within the prediction range.

[0008] The evaluation system that is one aspect of the present disclosure is capable of evaluating the dispersion state of a filler in a composite material. Another aspect of the present disclosure is an evaluation system including: an input unit capable of inputting an image obtained by photographing a composite material containing a polymer and a filler and the composition of the composite material; a quantity ratio calculation unit configured to calculate the quantity ratio of the filler from the image; a prediction range calculation unit configured to calculate a prediction range of the quantity ratio of the filler by performing a simulation that simulates the dispersion of the filler in the composite material based on the composition; and a determination unit configured to determine whether the quantity ratio of the filler calculated by the quantity ratio calculation unit is within the prediction range. Another aspect of the present disclosure is an evaluation system that can evaluate the dispersion state of a filler in a composite material. [Brief explanation of the drawings]

[0009] [Figure 1] FIG. 1 is a block diagram illustrating a configuration of an evaluation system. [Figure 2]10 is a flowchart showing a process executed by the evaluation system. [Figure 3] FIG. 1 is an explanatory diagram showing a simulation of filler dispersion in a composite material. [Figure 4] 4A and 4B are explanatory diagrams showing an example of a set of numbers of simulated fillers and simulated polymers calculated for each of a plurality of cells, respectively. DETAILED DESCRIPTION OF THE INVENTION

[0010] Exemplary embodiments of the present disclosure will be described with reference to the drawings. First Embodiment 1.Configuration of Evaluation System 1 The configuration of the evaluation system 1 will be described with reference to Fig. 1. The evaluation system 1 includes an input unit 3, a control unit 5, and a display unit 7. The input unit 3 is a member that can input data. The input unit 3 includes, for example, a keyboard, a mouse, a touch panel, a voice input device, a switch, a button, etc.

[0011] Data that can be input to the input unit 3 includes an image 8 obtained by photographing a composite material containing a polymer and a filler. Examples of polymers include EVA, modified rubber, and polyfunctional acrylate. Examples of fillers include magnesium hydroxide. The composite material is produced, for example, by mixing raw materials containing a polymer and a filler using a kneader or the like.

[0012] Examples of the device for taking the photograph include a microscope that can separate and confirm the filler, a scanning probe microscope, a scanning electron microscope, and a transmission electron microscope.

[0013] Data that can be input to the input unit 3 includes the composition 9 of the composite material that was the subject of the photograph. The composition 9 is data that includes the ratio of the amounts of each component contained in the composite material. The composition 9 includes the ratio of the amount of filler. The ratio of the amounts in the composition 9 may be a volume ratio or a mass ratio.

[0014] The data that can be input to the input unit 3 includes the area S of the field of view when photographing the composite material. The area S is, for example, 10 4 μm 2 The shape of the field of view may be square or rectangular. The input unit 3 may also be capable of inputting other data.

[0015] The control unit 5 includes an amount ratio calculation unit 12, a predicted range calculation unit 14, and a determination unit 15. The amount ratio calculation unit 12 calculates the volume ratio VA of the filler in the composite material from the image 8. The volume ratio VA corresponds to the amount ratio. The following methods, for example, can be used to calculate the volume ratio VA of the filler.

[0016] The following describes a case where the brightness of pixels representing filler in image 8 is higher than the brightness of pixels representing other components. The quantity ratio calculation unit 12 binarizes the brightness of each pixel in image 8. That is, the brightness of pixels whose brightness exceeds a threshold is set to the maximum value, and the brightness of pixels whose brightness is equal to or less than the threshold is set to the minimum value. After binarization, the brightness of pixels representing filler becomes the maximum value, and the brightness of pixels representing other components becomes the minimum value.

[0017] Next, the quantity ratio calculation unit 12 calculates the area of ​​the region with the maximum brightness in the binarized image 8. The ratio of the calculated area to the total area of ​​the image 8 is set as the volume ratio VA of the filler.

[0018] The predicted range calculation unit 14 calculates the predicted range of the filler content ratio by performing a simulation that simulates the dispersion of the filler in the composite material based on the blend 9 and the area S. The method for calculating the predicted range will be described later.

[0019] The determination unit 15 determines whether or not the volume ratio VA of the filler calculated by the quantity ratio calculation unit 12 is within the predicted range. The display unit 7 is a display capable of displaying an image. The display unit 7 displays the content calculated by the control unit 5. The content to be displayed includes the result of the determination by the determination unit 15.

[0020] 2. Processing performed by rating system 1 The processing executed by the evaluation system 1 will be described with reference to Figs. 2 to 4. In step S1 of Fig. 2, data is input to the input unit 3. For example, a user can input data to the input unit 3. The data includes an image 8, a composition 9, and an area S.

[0021] In step S2, the quantity ratio calculation unit 12 calculates the volume ratio VA of the filler from the image 8 input in step S1. In step S3, the prediction range calculation unit 14 calculates the volume ratio VB of the filler in the composite material from the blend 9 input in step S1. Here, the filler volume ratio VB is the value obtained by dividing the volume of the filler contained in the composite material by the total volume of the composite material. If the blend 9 includes a volume ratio of the filler, the prediction range calculation unit 14 uses this as the filler volume ratio VB as is. If the blend 9 includes a mass ratio of the filler, the prediction range calculation unit 14 calculates the filler volume ratio VB by performing a conversion.

[0022] In step S4, the prediction range calculation unit 14 calculates the standard deviation σ F The prediction range calculation unit 14 calculates the standard deviation σ by performing a simulation of the dispersion of the filler in the composite material based on the blend 9 and the area S input in step S1. F Calculate the standard deviation σ F The specific method for calculating is as follows.

[0023] The predicted range calculation unit 14 assumes a simulated kneader 11 shown in SA in Fig. 3. The simulated kneader 11 is a collection of a plurality of cells 13. The larger the number of cells 13, the larger the standard deviation σ F The accuracy in calculating is high. The number of cells 13 is preferably 25 (for example, 5 × 5) or more, and more preferably 100 (for example, 10 × 10) or more. The upper limit of the number of cells 13 is preferably 2500 (for example, 50 × 50) or less, and more preferably 900 (for example, 30 × 30) or less, so as not to cause the processing load to become too large. Note that each cell 13 corresponds to one image obtained by performing one shooting operation in which the area of ​​the shooting field of view is area S.

[0024] Next, the prediction range calculation unit 14 places simulated fillers MF and simulated polymers MP in each of the cells 13 so that the following conditions J1 to J2 are met. One simulated filler MF represents one filler. One simulated polymer MP represents one polymer.

[0025] (J1) The following equation (1) holds true: Equation (1) N MF / (N MP +N MF )=VB In equation (1), N MF is the total number of all simulated fillers MF in the simulated kneader 11. MP is the total number of all simulated polymers MP in the simulated kneader 11. VB is the volume ratio VB of the filler calculated in step S3.

[0026] (J2) In any cell 13, the total number of simulated fillers MF and simulated polymers MP in one cell 13 is the storage capacity NL. The capacity number NL is a number representing the total number of fillers and polymers present in one image obtained by photographing in which the area of ​​the photographing field of view is area S. Therefore, the capacity number NL is a number proportional to the area S. The predicted range calculation unit 14 sets the capacity number NL according to the area S input in step S1. The predicted range calculation unit 14 is equipped with, for example, a function that outputs the capacity number NL when the area S is input. The predicted range calculation unit 14 obtains the capacity number NL by inputting the area S input in step S1 into this function.

[0027] The number of fillers stored in the function, NL, can be determined, for example, as follows: A single image is actually taken of the composite material obtained by thorough mixing. The area of ​​the photographed field of view is S. In the image obtained by photographing, the number of fillers, N F Calculate the number of fillers N F can be calculated by visually counting, for example. F :V P The capacity NL corresponding to the area S is calculated using the following formula (2).

[0028] In the following, the number of fillers N F There are 69 pieces, and the volume ratio is V F is 45% and the area S is 25 μm 2 The case where the dimensions are (5 μm×5 μm) will be described. According to the following formula (2), the number of ML contained in one cell 13 is 153.333 (= 69 × (45 + 55) / 45), but for the convenience of the simulation, this was rounded to an integer, and NL = 153 was used. Furthermore, 68.85 simulated fillers MF (= 153 × 0.45) and 84.15 simulated polymers MP (= NL - MF) are contained per cell 13. In this embodiment, the calculated number of ML contained in one cell was used to calculate the number of simulated fillers MF again, but the number of simulated fillers MF was also calculated by multiplying the number of fillers N by the number of fillers N. F In this case, the number of simulated fillers MF per square 13 is 69 (=N F) and 84 simulated polymer MPs (=NL-N F ) and the capacity is 153 NL.

[0029] The number of containers NL is, for example, when the area S is 100 μm 2 If the particle size is (10 μm × 10 μm), the number of particles will be 612 (= 153 × 100 / 25). If the amount of filler mixed is reduced to half of the above condition, that is, if the volume ratio V F is 22.5% and the area S is 25 μm 2 In the case where the size of the matrix is ​​(5 μm × 5 μm), the number of NL contained in one cell 13 is 153, and 34.425 (= 153 × 0.225) simulated fillers MF are contained in one cell 13, and 118.575 (= 153 - 34.425) simulated polymers MP are contained in one cell 13. F ) to prepare composite materials and change the number of fillers N F Then, the capacity NL corresponding to the area S may be calculated using equation (2).

[0030] Equation (2) NL=N F ×((V F +V P ) / V F ) Next, the prediction range calculation unit 14 performs an exchange process. The exchange process is a process of exchanging any simulated filler MF or simulated polymer MP contained in any cell 13 with any simulated filler MF or simulated polymer MP contained in any adjacent cell 13, as shown in SA in FIG. 3 . The exchange process simulates the process of mixing a composite material in an actual kneader. Here, the exchange process was performed under the following conditions: the total number of cells 13 was 400 (20 × 20), the total number of simulated filler MF was 27,540 (68.85 × 400), the total number of simulated polymer MP was 33,660 (84.15 × 400), and the number of cells accommodated NL was 153 ((27,540 + 33,660) / 400).

[0031] The predicted range calculation unit 14 repeats the replacement process a sufficient number of times. As a result, the simulated filler MF and simulated polymer MP are dispersed evenly throughout the simulated kneader 11, as shown by SB in Fig. 3. Each mass 13 shown by SB in Fig. 3 corresponds to an image obtained by taking a single photograph of a composite material in a state in which the filler and polymer are dispersed evenly throughout the composite material (hereinafter referred to as an average dispersion state), with the photographed field of view having an area S.

[0032] Next, as shown in Fig. 4A, for example, the prediction range calculation unit 14 calculates the number of simulated filler MFs in one cell 13 for each cell 13. In the example shown in Fig. 4A, the set obtained as the numbers of simulated filler MFs in one cell 13 is 60, 61, 70, 73, 64, 58, 76, 64, 72, etc.

[0033] 4B, for example, the prediction range calculation unit 14 calculates the number of simulated polymers MP in one cell 13. In the example shown in FIG. 4B, the set obtained as the numbers of simulated polymers MP in one cell 13 is 93, 92, 83, 80, 89, 95, 77, 89, 81, etc. In the examples shown in FIGS. 4A and 4B, the storage capacity NL is 153.

[0034] Next, the prediction range calculation unit 14 calculates the average value NAV of the set of numbers of simulated fillers MF calculated for each of all the squares 13. F and the standard deviation Nσ in the set of numbers of simulated fillers MF calculated for all masses 13 F and calculate.

[0035] In addition, the prediction range calculation unit 14 calculates the average value NAV M and the standard deviation Nσ in the set of numbers of simulated polymer MPs calculated for all masses 13 P and calculate.

[0036] Next, the prediction range calculation unit 14 calculates the standard deviation Nσ F Dividing by the number of fillings NL gives the standard deviation σ of the filler volume ratio. F Calculate the standard deviation σ F is the standard deviation of the filler volume ratio in one image obtained by taking a single photograph of a composite material in an average dispersion state with a field of view of area S.

[0037] In addition, the prediction range calculation unit 14 calculates the standard deviation Nσ P Dividing by the capacity NL gives the standard deviation σ of the polymer volume ratio. P Calculate the standard deviation σ P is the standard deviation of the polymer volume fraction in a single image obtained by taking a single photograph of a composite material in an average dispersion state with a field of view of area S.

[0038] In step S5, the prediction range calculation unit 14 calculates the prediction range. The prediction range is, for example, VB-2σ F is the lower limit, VB+2σ F This prediction range is centered on VB and has an upper limit of σ F It is a range that has a spread according to.

[0039] VB at the upper and lower limits is the volume ratio VB of the filler calculated in step S3. F is the standard deviation σ of the volume ratio of the filler calculated in step S4 F is.

[0040] The prediction range has the following meaning: It is assumed that a composite in an average dispersion state is photographed once with a field of view area of ​​S to obtain one image 8. The probability that the filler volume ratio VA calculated from this image 8 falls within the prediction range is equal to or greater than a predetermined reference value.

[0041] In step S6, the determination unit 15 determines whether the filler volume ratio VA calculated in step S2 is within the predicted range calculated in step S5. If it is determined that the filler volume ratio VA is within the predicted range, the process proceeds to step S7. If it is determined that the filler volume ratio VA is outside the predicted range, the process proceeds to step S8.

[0042] In step S7, the display unit 7 displays that the filler is well dispersed in the composite material. In step S8, the display unit 7 displays that the dispersion of the filler in the composite material is poor. In this embodiment, the average volume ratio of the filler AV F , A.V. F -σ F , and A.V. F +σ F For example, the average volume ratio of the filler, AV, is as shown in Table 1 below. F is the average value of the number of simulated filler MFs NAV F This is the value obtained by dividing by the capacity NL. [Table 1] In addition, Table 1 shows the case where the volume ratio VB is 45% and the area S is 25 μm 2 For example, compared to the case shown in Table 1, if the area S is doubled (i.e., 50 μm 2 ), the average volume ratio of the filler, AV F does not change, and its variability (standard deviation σ F ) is multiplied by 1 / √2. The first case is when the filler volume ratio VB input in step S1 is 45%. The second case is when the filler volume ratio VB input in step S1 is 22.5% and the other conditions are the same as in the first case. In the second case, the filler volume ratio VB is 1 / 2 times that in the first case. In the second case, the average filler volume ratio AV is 1 / 2 times that in the first case. F is halved, and its variation (standard deviation σ F ) is multiplied by √(1 / 2).

[0043] 3. Effects of Evaluation System 1 (1A) As described above, the prediction range is a range in which the probability of including the filler volume ratio VA calculated from a composite in an average dispersion state is equal to or greater than a predetermined reference value. Therefore, if the filler is well dispersed in the composite material, the filler volume ratio VA is likely to fall within the prediction range, and a positive determination is likely to be made in step S6.

[0044] On the other hand, if the filler is poorly dispersed in the composite material, the volume ratio VA of the filler is likely to fall outside the predicted range, and a negative determination is likely to be made in step S6. In this way, the judgment result in step S6 reflects whether the filler is dispersed in the composite material, and therefore the evaluation system 1 can judge whether the filler is dispersed in the composite material based on the judgment result in step S6.

[0045] (1B) Evaluation system 1 performs a simulation to calculate the standard deviation σ F Calculate the standard deviation σ F The predicted range is calculated using the formula: Therefore, the evaluation system 1 can calculate the predicted range more appropriately. As a result, the evaluation system 1 can more accurately determine whether the filler is dispersed in the composite material.

[0046] (1C) The prediction range is centered on the filler volume ratio VB, with a standard deviation σ F This is a range that has a spread according to the dispersion of the filler in the composite material. Therefore, the evaluation system 1 can more appropriately calculate the predicted range. As a result, the evaluation system 1 can more accurately determine whether the dispersion of the filler in the composite material is good or bad.

[0047] (1D) The area S is, for example, 10 4 μm 2 In this case, the evaluation system 1 can be used when photographing a minute area.

[0048] <Other embodiments> Although the embodiments of the present disclosure have been described above, the present disclosure is not limited to the above-described embodiments and can be implemented in various modified forms.

[0049] (1) In the first embodiment, the quantity ratio may be something other than a volume ratio, and may be, for example, a mass ratio. (2) The simulation method may be different from that in the first embodiment.

[0050] (3) The variability is the standard deviation σ F For example, the variation may be a standard deviation σ F The square of etc. can be used. (4) The method for calculating the volume ratio VA of the filler may be different from that in the first embodiment.

[0051] (5) The evaluation system 1 does not have to be equipped with a display unit 7. In that case, the evaluation system 1 can, for example, transmit a signal representing the judgment result of step S6 to an external device or store the judgment result. Furthermore, when the imaging magnification is fixed, the evaluation system 1 may omit displaying the area S of the imaging field of view on the display unit 7 and inputting the area S in step S1.

[0052] (6) The prediction range may be different from that in the first embodiment. For example, the prediction range may be, for example, VB-mσ F is the lower limit, VB+mσ F The upper limit of the range is m. m is any positive real number. Examples of m include 1, 3, and 4.

[0053] (7) The control unit 5 and the method described herein may be implemented by a special-purpose computer configured by configuring a processor and memory programmed to execute one or more functions embodied in a computer program. Alternatively, the control unit 5 and the method described herein may be implemented by a special-purpose computer configured by configuring a processor with one or more dedicated hardware logic circuits. Alternatively, the control unit 5 and the method described herein may be implemented by one or more special-purpose computers configured by combining a processor and memory programmed to execute one or more functions with a processor configured with one or more hardware logic circuits. Furthermore, the computer program may be stored as instructions executed by a computer on a computer-readable non-transitory tangible recording medium. The method for implementing the functions of each unit included in the control unit 5 does not necessarily need to include software; all of the functions may be implemented using one or more hardware.

[0054] (8) The function of one component in each of the above embodiments may be shared among multiple components, or the functions of multiple components may be performed by one component. Also, part of the configuration of each of the above embodiments may be omitted. Furthermore, at least part of the configuration of each of the above embodiments may be added to or substituted for the configuration of another of the above embodiments.

[0055] (9) In addition to the evaluation system 1 described above, the present disclosure can also be realized in various forms, such as a higher-level system that includes the evaluation system 1 as a component, a program for causing a computer to function as the control unit 5, a non-transitory tangible recording medium such as a semiconductor memory on which the program is recorded, and a method for evaluating the dispersion of a filler in a composite material.

[0056] [Technical idea disclosed in this specification] [Item 1] an input unit that can input an image obtained by photographing a composite material containing a polymer and a filler, the composition of the composite material, and the area S of the field of view in the photographing; an amount ratio calculation unit configured to calculate an amount ratio of the filler from the image; a prediction range calculation unit configured to calculate a prediction range of the amount ratio of the filler by performing a simulation simulating the dispersion of the filler in the composite material based on the blend and the area S; a determination unit configured to determine whether the filler amount ratio calculated by the amount ratio calculation unit is within the predicted range; Equipped with Rating system. [Item 2] an input unit capable of inputting an image obtained by photographing a composite material containing a polymer and a filler, and a composition of the composite material; an amount ratio calculation unit configured to calculate an amount ratio of the filler from the image; a prediction range calculation unit configured to calculate a prediction range of the amount ratio of the filler by performing a simulation that simulates the dispersion of the filler in the composite material based on the blend; a determination unit configured to determine whether the filler amount ratio calculated by the amount ratio calculation unit is within the predicted range; Equipped with Rating system. [Item 3] The evaluation system according to item 1 or 2, the prediction range calculation unit is configured to calculate a variation in the amount ratio of the filler by performing the simulation, and to calculate the prediction range using the variation; Rating system. [Item 4] Item 3. The evaluation system according to item 3, the predicted range is a range having a center at the amount ratio of the filler calculated based on the blending of the composite material and a spread according to the variation; Rating system. [Item 5] The evaluation system according to item 1, The area S is 10 4 μm 2 Below is the Rating system. [Explanation of symbols]

[0057] 1...Evaluation system, 3...Input unit, 5...Control unit, 7...Display unit, 8...Image, 9...Blending, 11...Simulated kneader, 12...Quantity ratio calculation unit, 13...Mass, 14...Prediction range calculation unit, 15...Determination unit, MF...Simulated filler, MP...Simulated polymer

Claims

1. an input unit capable of inputting an image obtained by photographing a composite material containing a polymer and a filler, the composition of the composite material, and an area S of the photographed field of view in the photographing; an amount ratio calculation unit configured to calculate an amount ratio of the filler from the image; a prediction range calculation unit configured to calculate a prediction range of the amount ratio of the filler by performing a simulation simulating the dispersion of the filler in the composite material based on the blending and the area S; a determination unit configured to determine whether the filler amount ratio calculated by the amount ratio calculation unit is within the predicted range; Equipped with Rating system.

2. an input unit capable of inputting an image obtained by photographing a composite material containing a polymer and a filler, and a composition of the composite material; an amount ratio calculation unit configured to calculate an amount ratio of the filler from the image; a prediction range calculation unit configured to calculate a prediction range of the amount ratio of the filler by performing a simulation that simulates the dispersion of the filler in the composite material based on the blend; a determination unit configured to determine whether the filler amount ratio calculated by the amount ratio calculation unit is within the predicted range; Equipped with Rating system.

3. 3. The evaluation system according to claim 1 or 2, the prediction range calculation unit is configured to calculate a variation in the amount ratio of the filler by performing the simulation, and to calculate the prediction range using the variation; Rating system.

4. The evaluation system according to claim 3, the predicted range is a range having a center at the amount ratio of the filler calculated based on the blending of the composite material and a spread according to the variation; Rating system.

5. 2. The evaluation system according to claim 1, The area S is 10 ４ μm ２ Below is the Rating system.

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