Material evaluation system, material evaluation method, and program

Abstract

To shorten the time of characteristic evaluation by reducing the data acquisition cost and time cost of a recycled resin material to be evaluated.SOLUTION: Storing a contribution degree table in which a feature amount in a raw material and a contribution degree, which is an index indicating a magnitude of an influence of the feature amount in the raw material on a predetermined mechanical property, are associated with each other for each type of raw material, receiving measured data of a recycled resin material to be evaluated as an input, specifying a feature amount of a larger contribution degree based on the contribution degree table and raw material information of the recycled resin material to be evaluated, creating a molecular model in which the specified feature amount is incorporated into a main raw material of the recycled resin material according to a value of the measured data, and calculating a characteristic value of the mechanical property to be evaluated based on a simulation based on the molecular model; The characteristic value is output.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a material evaluation system, a material evaluation method, and a program for evaluating recycled resin materials. [Background technology]

[0002] In recent years, there has been an increasing demand for recycled resin materials (e.g., recycled plastics) both in Japan and overseas to reduce environmental impact. Recycled plastics are generally recycled as materials from the perspective of energy costs. Therefore, recycled plastics inherit the properties of the original materials with which they are mixed, and in order to understand these properties, actual measurements are necessary.

[0003] Patent Document 1 discloses a technology for predicting the mechanical properties of polymer raw materials. Specifically, Patent Document 1 states that "the polymer raw material data analysis device has a learning model creation unit that creates a learning model by learning the relationship between structural information including at least one of the properties and composition of the polymer raw material and property information including at least one of the mechanical properties and chemical properties of the polymer raw material, and a calculation unit that uses the learning model to perform optimization processing on the structural information and property information of the polymer raw material. The calculation unit performs the optimization processing until predetermined property information is obtained for the polymer raw material." [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Publication No. 2022-13215 Summary of the Invention [Problem to be solved by the invention]

[0005] Currently, to understand the properties of recycled plastics, it is necessary to procure materials, fabricate test specimens, and perform a variety of measurements for each type of recycled plastic (for example, multiple types of measurements for composition analysis and measurements to evaluate mechanical properties). As a result, when evaluating the performance of recycled plastics, the cost of data acquisition and the time required are enormous, and it takes a long time (for example, about two months). Furthermore, as demand for recycled plastics is expected to increase further in the future, there is a demand for technology that can evaluate properties in a shorter time.

[0006] The technology of Patent Document 1 requires optimization processing until predetermined property information is obtained for the polymer raw material, which requires a large number of calculations and takes a long time, and does not take into consideration the need to evaluate the properties of recycled plastics in a short period of time. Therefore, it is considered difficult to solve the above-mentioned problems with the technology of Patent Document 1.

[0007] The present invention has been made in consideration of the above-mentioned problems, and aims to shorten the time required for characteristic evaluation by making it possible to reduce the cost and time required for acquiring data on the recycled resin material being evaluated. [Means for solving the problem]

[0008] The present application includes multiple means for solving at least part of the above-mentioned problems, examples of which are as follows: A material evaluation system according to one aspect of the present invention for solving the above-mentioned problems includes a processor that executes a program and a storage device that stores the program, wherein the storage device stores a contribution table that associates, for each type of raw material, feature quantities of raw materials with contributions, which are indices of the magnitude of the influence that the feature quantities of the raw materials have on predetermined mechanical properties, and the processor receives as input raw material information and actual measurement data related to the feature quantities of a recycled resin material to be evaluated, identifies the feature quantities of the contributions that have a greater influence on the mechanical properties of the material to be evaluated based on the contribution table and the raw material information of the recycled resin material to be evaluated, creates a molecular model that incorporates the identified feature quantities into a main raw material of the recycled resin material according to the values ​​of the actual measurement data of the recycled resin material to be evaluated, performs a predetermined simulation based on the molecular model, and calculates characteristic values ​​of the mechanical properties of the material to be evaluated, and outputs the calculated characteristic values. [Effects of the Invention]

[0009] According to the present invention, it is possible to reduce the cost and time required to acquire data on the recycled resin material to be evaluated, thereby shortening the time required for characteristic evaluation.

[0010] Problems, configurations, and effects other than those described above will become clear from the following description of the embodiments. [Brief explanation of the drawings]

[0011] [Figure 1] 1 is a diagram showing an example of a schematic configuration of a material evaluation system according to a first embodiment. [Figure 2] FIG. 10 is a diagram illustrating an example of contribution degree information. [Figure 3] FIG. 10 is a flow chart showing an example of a material evaluation process. [Figure 4] FIG. 10 is a diagram showing an example of an input screen. [Figure 5]Fig. 5A is a diagram showing an example of a molecular model of a repeating unit structure, and Fig. 5B and Fig. 5C are diagrams showing examples of a molecular model in which the linking positions of feature quantities are replaced. [Figure 6] FIG. 10 is a diagram for explaining application of an external force by molecular dynamics simulation. [Figure 7] FIG. 10 is a diagram showing an example of an output screen. [Figure 8] FIG. 10 is a diagram for explaining application of an external force by molecular dynamics simulation. [Figure 9] FIG. 10 is a diagram for explaining the lattice constant when tension is applied. [Figure 10] FIG. 10 is a diagram showing an example of an output screen. [Figure 11] FIG. 10 is a diagram showing another example of the configuration of the material evaluation system. [Figure 12] FIG. 1 is a diagram illustrating an example of a hardware configuration of a material evaluation system. DETAILED DESCRIPTION OF THE INVENTION

[0012] Hereinafter, each embodiment of the present invention will be described with reference to the drawings.

[0013] First Embodiment <Schematic Configuration of Materials Evaluation System 1000> FIG. 1 is a diagram showing an example of the schematic configuration of a material evaluation system 1000 according to a first embodiment. The material evaluation system 1000 is implemented by a computer 100 that performs arithmetic processing, and is a system that performs material evaluation of the characteristics of recycled resin materials by creating a molecular model incorporating feature quantities that have a significant effect on the characteristics to be evaluated of the recycled resin material and executing a simulation using the molecular model. The recycled resin material is an olefin-based resin, which includes at least polyethylene and polypropylene. The molecular model is a structural model of a molecular structure that shows the bonding relationships between atoms. Details of the molecular model will be described later.

[0014] Specifically, the material evaluation system 1000 uses accumulated data on various properties and characteristics of recycled resin materials for each base material to calculate the contribution, which indicates the magnitude of the impact on each property, for each characteristic, and creates a database that associates the magnitude of the contribution with each characteristic.

[0015] The material evaluation system 1000 also accepts input of the characteristics that the user wishes to evaluate for the recycled resin material being evaluated, and the actual measurement data required to generate a molecular model that is used in a simulation to determine the predicted values ​​of the characteristics.

[0016] Furthermore, the material evaluation system 1000 identifies, from the database, feature quantities that make a large contribution to the property to be evaluated.

[0017] Furthermore, the material evaluation system 1000 creates a molecular model based on the inputted base material and actual measurement data, and the identified feature quantities with high contributions.

[0018] In addition, the material evaluation system 1000 creates a simulation model for predicting properties based on a molecular model and performs a molecular dynamics simulation to calculate predicted values ​​of the properties to be evaluated for the recycled resin material being evaluated.

[0019] Additionally, the material evaluation system 1000 displays an output screen including the predicted values ​​of the properties or the predicted values ​​and the simulation model.

[0020] Such a material evaluation system makes it possible to reduce the cost and time required to acquire data on the recycled resin material to be evaluated, thereby shortening the time required for characteristic evaluation.

[0021] In the following, recycled plastics (for example, polypropylene, polyethylene, etc.) will be taken as an example of recycled resin materials.

[0022] <Functional Configuration of Material Evaluation System 1000> As shown in FIG. 1, the material evaluation system 1000 is realized by a computer 100, such as a server device or a personal computer, and has an input receiving unit 110, an output information generating unit 120, a communication unit 130, a memory unit 140, and a processing unit 150.

[0023] The input receiving unit 110 is a functional unit that receives instructions and information input from a user via a predetermined input device (for example, an input device provided in the material evaluation system 1000, such as a keyboard, mouse, or microphone). The input receiving unit 110 receives, for example, instructions to execute processing, and input of information regarding actual measurement data and the type of mechanical properties to be evaluated for the recycled plastic to be evaluated.

[0024] The output information generation unit 120 is a functional unit that generates output information (screen information) to be displayed on a predetermined display device (for example, a display device provided in the material evaluation system 1000). The output information generation unit 120 generates, for example, screen information for accepting input of information, screen information including a simulation model of the created molecular model and calculated characteristic values, and displays it on the display device.

[0025] The communication unit 130 is a functional unit that communicates information with a predetermined device outside the system (for example, an external device such as a terminal device used by a user or a cloud server). For example, the communication unit 130 acquires various types of information used in the arithmetic processing of the material evaluation system 1000 from the external device via a predetermined network. The communication unit 130 also transmits information generated by the material evaluation system 1000 to a terminal device used by a user via the network N. The network N is, for example, a communication network such as the Internet, a LAN (Local Area Network), or a WAN (Wide Area Network).

[0026] The storage unit 140 is a functional unit for storing various information. Specifically, the storage unit 140 has a mechanical property database 141, a feature database 142, a contribution database 143, and a molecular model database 144.

[0027] The mechanical property database 141 is a database that stores information about the mechanical properties of recycled plastics (hereinafter, sometimes referred to as mechanical property information). The mechanical property information stores, for example, various mechanical property values ​​obtained by measuring a predetermined number (e.g., 100 to 1000 pieces) of recycled plastics for each main raw material (hereinafter, sometimes referred to as base material) that constitutes the recycled plastic.

[0028] Specifically, the mechanical property information includes, for example, a sample number for identifying the recycled plastic measured for each base material, the type of mechanical property (e.g., tensile modulus, tensile breaking strain, tensile strength, tensile breaking stress, tensile yield stress, flexural modulus, flexural strength, Charpy impact value, etc.), and the measured property value, all associated with each other. Note that these various mechanical properties are information obtained by conducting tensile, flexural, and impact resistance tests on test pieces of recycled plastics, and are information that has been measured in the past and is prepared in advance as accumulated data.

[0029] The feature database 142 is a database that stores information about the feature quantities of recycled plastics (hereinafter, sometimes referred to as feature quantity information). The feature quantity information includes, for example, feature quantities (e.g., functional groups such as carboxyl groups, carbonyl groups, hydroxyl groups, amino groups, sulfo groups, and phosphate groups; foreign matter such as rutile, talc, metals, and glass fillers; molecular weight, crystallinity, viscosity, etc.) acquired by measuring a predetermined number (e.g., 100 to 1000 pieces) of recycled plastics for each base material, strength for each feature quantity, and calculation costs, all registered in association with sample numbers that identify the measured recycled plastics.

[0030] Virgin polypropylene is available on the market in block PP (hereinafter referred to as "polypropylene"), random PP, and homo PP, and in addition to PP as the main component, block PP and random PP contain PE (polyethylene), antioxidants, nucleating agents, clarifiers, processability improvers, lubricants, UV absorbers, light stabilizers, flame retardants, antistatic agents, etc. depending on the application. In recycled plastics, these are collected randomly, and when they are recycled, the above functional groups and foreign matter that originate from the additives and correspond to the characteristic quantities can be detected.

[0031] These feature quantities are obtained by compositional analysis of measurement data obtained through various measurements of recycled plastics. Specifically, the types of measurements include Fourier Transform Infrared Spectroscopy (FT-IR), X-ray Diffraction (XRD), spectrophotometer, melt flow rate (MFR), thermogravimetric analysis (TG), differential thermal analysis (DTA), and TG-DTA, which simultaneously performs thermogravimetric analysis and differential thermal analysis. Such feature quantity information is information that has been previously measured and prepared as accumulated data.

[0032] The intensities registered in the feature information refer to the abundance ratio of periodic structures indicated by the peak intensity of the measured spectrum. For example, in XRD measurements, the abundance ratio of periodic structures can be confirmed as intensity. In the case of XRD, this is generally the number of counts of X-rays reflected by the material and entering the detector, and the peaks of the measured spectrum can be quantified; the greater this intensity, the greater the abundance ratio.

[0033] Similarly, measurement spectra can be obtained using FT-IR and TG-DTA, and these measurements can obtain information indicating the type of feature (including not only functional groups but also types of recycled plastics such as polypropylene and polyethylene), height, and approximate amount and ratio based on the peak position. Note that, because the results of different types of measurements cannot be compared as is, they are normalized and registered in the feature information.

[0034] The calculation cost registered in the feature information indicates the calculation time required for each simulation using a molecular model, and the larger the number of atoms or the more complex the structure, the longer the calculation time required for each calculation. Therefore, taking these factors into consideration, the storage unit 140 stores information (not shown) that defines the calculation cost in advance for each feature, such as various functional groups, foreign matter, molecular weight, and crystallinity. The calculation cost is defined by the Particle Mesh Ewald (PME) method or the Fast Multipole Method (FMM), which depends on the number n of atoms.

[0035] The contribution database 143 is a database that stores information relating to the contribution of each feature amount, which indicates the magnitude of the influence on the machine characteristics (hereinafter, may be referred to as contribution information 160). The contribution information 160 is information generated by the processing unit 150 (a contribution calculation unit described later) based on the machine characteristic information and feature amount information, and the contribution of each machine characteristic calculated by the processing unit 150 is registered in the contribution information 160 in association with each feature amount.

[0036] 2 is a diagram showing an example of contribution information 160. As shown in the figure, the contribution information 160 is registered, for example, in a table format (contribution table), with the corresponding strength, frequency, calculation cost, and contribution associated with each feature and each type of mechanical property. Note that the mechanical properties basically inherit the mechanical properties registered in the feature information, but it is not necessary to have all of these types of mechanical properties; it is sufficient that at least some (one or more) of the mechanical properties are registered.

[0037] The intensity is information common to the intensity of the feature amount information, and an average value of the intensities registered in the feature amount information for each base material is registered.

[0038] The frequency indicates the number of times each feature is registered in the feature information for each base material, that is, the number of times each feature is detected based on measurements of the base material of the sample.

[0039] The calculation cost is information indicating a numerical value proportional to the calculation time required for each feature quantity to simulate a molecular model, and the value is defined in advance based on the number of atoms and the complexity of the structure.

[0040] The contribution is information indicating the magnitude of the influence that each feature has on the associated mechanical property, and is calculated based on the product of the intensity, frequency, and calculation cost (intensity x frequency x calculation cost). The contribution also takes into account the calculation cost, which is information indicating the calculation time required for each simulation using a molecular model. Therefore, the contribution is an index indicating the magnitude of the influence that a feature has on a mechanical property, and also an index indicating the degree to which the feature contributes to the calculation time of the mechanical property to be evaluated.

[0041] Such contribution information 160 is created by the processing unit 150 (a contribution calculation unit to be described later) using the machine property information and feature amount information, and is stored in the contribution database 143.

[0042] Returning to Fig. 1, the molecular model database 144 is a database that stores information about molecular models. Specifically, the molecular model database 144 stores molecular models created based on the contribution information 160 and actual measurement data of the recycled plastic to be evaluated, and the results of molecular dynamics simulations executed using simulation models corresponding to the molecular models (for example, predicted values ​​of mechanical properties to be evaluated).

[0043] Next, we will explain the processing unit 150. The processing unit 150 is a functional unit that performs various processes executed in the material evaluation system 1000. Specifically, the processing unit 150 has a contribution calculation unit 151, a higher-order structure calculation unit 152, and a characteristic value calculation unit 153 as individual functional units that perform each process.

[0044] The contribution calculation unit 151 is a functional unit that generates contribution information 160 including the contribution degree. Specifically, the contribution calculation unit 151 calculates the contribution degree of each feature quantity corresponding to each mechanical property for each base material by using the mechanical property information and feature quantity information. In addition, the contribution calculation unit 151 generates the contribution information 160 including the contribution degree and stores it in the contribution database 143.

[0045] The higher-order structure calculation unit 152 is a functional unit that generates a molecular model and a simulation model used in molecular dynamics simulations using the contribution information 160 and actual measurement data of the recycled plastic to be evaluated.

[0046] The characteristic value calculation unit 153 is a functional unit that executes a molecular dynamics simulation and calculates predicted values ​​of the mechanical characteristics to be evaluated for the recycled plastic to be evaluated.

[0047] An example of the functional configuration of the material evaluation system 1000 has been described above.

[0048] <Material evaluation processing> 3 is a flow diagram showing an example of material evaluation processing executed by the material evaluation system 1000. The material evaluation processing starts when an execution instruction is received from a user via the input receiving unit 110, for example.

[0049] When the process starts, the contribution calculation unit 151 generates contribution information 160 and stores it in the contribution database 143 (step S10). Specifically, the contribution calculation unit 151 calculates the average value of the strength registered in the feature information for each base material. Furthermore, the contribution calculation unit 151 uses the feature information to count the number of times each feature is registered (the frequency of occurrence), thereby calculating the frequency of each feature for each base material. Furthermore, the contribution calculation unit 151 extracts the calculation cost defined for each feature using predetermined information (not shown) in the storage unit 140. Furthermore, the contribution calculation unit 151 calculates the contribution of each feature corresponding to each mechanical property by multiplying the strength, frequency, and calculation cost. Furthermore, the contribution calculation unit 151 generates contribution information 160 in which the strength, frequency, calculation cost, and contribution are registered in association with each feature, and stores the information in the contribution database 143.

[0050] Next, the higher-order structure calculation unit 152 receives input of predetermined information about the recycled plastic to be evaluated (e.g., polypropylene) (step S20). Specifically, the higher-order structure calculation unit 152 displays a predetermined input screen on the display device 620 via the output information generation unit 120, and receives input of information about the base material of the recycled plastic to be evaluated, the type of mechanical property to be evaluated, and actual measurement data of the recycled plastic to be evaluated via the input reception unit 110.

[0051] FIG. 4 is a diagram showing an example of an input screen 200. The illustrated example shows an input example for determining the tensile modulus of recycled polypropylene. As shown in the figure, the input screen displays a field 201 for inputting the base material (in this example, polypropylene) for the recycled plastic to be evaluated, a field 202 for inputting the type of mechanical property (in this example, tensile modulus) that the user wishes to evaluate, and a field 203 for inputting measured data for each measurement type (at least one of XRD, FT-IR, thermogravimetric analysis (TG), differential thermal analysis (DTA), and TG-DTA). The user inputs information (measured data) required to generate a molecular model via this input screen 200.

[0052] Next, the higher-order structure calculation unit 152 generates (models) a molecular model to be used in simulating the mechanical properties to be evaluated (step S30). Specifically, the higher-order structure calculation unit 152 identifies the mechanical properties to be evaluated by the user based on the input information. The higher-order structure calculation unit 152 also identifies feature quantities that contribute more to the identified mechanical properties from the contribution information 160. If there are multiple feature quantities whose differences from the largest contribution are within a predetermined range, the higher-order structure calculation unit 152 identifies these multiple feature quantities as feature quantities with the largest contributions. A known technique, such as the filter method, wrapper method, or embedded method, can be used to select each feature quantity corresponding to such multiple contributions. In this example, for example, a carboxyl group (COOH) and polyethylene (PE) are identified as feature quantities with the largest contribution to the tensile modulus.

[0053] Furthermore, the higher-order structure calculation unit 152 identifies the value of the feature (the feature with the greater contribution) based on the input actual measurement data. The value of the feature is, for example, the content of carboxyl groups or polyethylene contained in the polypropylene to be evaluated.

[0054] Furthermore, the higher-order structure calculation unit 152 generates a molecular model of the recycled plastic to be evaluated, which is used to simulate the mechanical properties to be evaluated, by incorporating the specified feature into the base material according to the value of the feature. Specifically, the higher-order structure calculation unit 152 generates a molecular model by incorporating the number of atoms, molecules, or functional groups of the specified feature into the molecular structure of the base material according to the value of the specified feature. The higher-order structure calculation unit 152 also performs a structural optimization process to replace the connection positions of the feature with the most stable positions in terms of energy and structure, thereby generating a structurally optimized molecular model. Note that the structural optimization process is a well-known technique, so a detailed description will be omitted.

[0055] Fig. 5 shows an example of a generated molecular model. Fig. 5A shows an example of a generated molecular model, which is a molecular model of a repeating unit structure. Fig. 5B and Fig. 5C show examples of a molecular model in which the linking positions of feature quantities have been replaced based on a structural optimization process.

[0056] Next, the higher-order structure calculation unit 152 uses these generated molecular models to generate a simulation model to be used in a molecular dynamics simulation to obtain predicted values ​​of the mechanical properties to be evaluated (step S40). Specifically, the higher-order structure calculation unit 152 overlaps the generated molecular models (each molecular model shown in FIGS. 5A to 5C) to generate a simulation model so that the number of predetermined molecular structures (e.g., carbon atoms) within the periodic boundary 250 is a predetermined number (e.g., 10,000 or more).

[0057] Next, the characteristic value calculation unit 153 executes a molecular dynamics simulation using the generated simulation model to calculate predicted values ​​of the mechanical properties to be evaluated (step S50). Specifically, the characteristic value calculation unit 153 executes a simulation in which an external force corresponding to the mechanical properties to be evaluated is applied to the simulation model, thereby calculating predicted values ​​of the mechanical properties. More specifically, the characteristic value calculation unit 153 calculates predicted values ​​of the mechanical properties to be evaluated, such as the tensile modulus, tensile strain at break, tensile strength, tensile stress at break, tensile yield stress, flexural modulus, flexural strength, and Charpy impact value, by reproducing, for example, tensile, bending, and impact resistance tests as the external force applied in the simulation.

[0058] The molecular dynamics simulation may be performed using known simulation software capable of executing predetermined molecular dynamics calculations.

[0059] FIG. 6 is a diagram for explaining the application of an external force by molecular dynamics simulation. In the illustrated example, the direction in which the created molecular model chains are superimposed is defined as the a-axis, and the molecular model chain direction is defined as the c-axis. The characteristic value calculation unit 153 applies a tension of, for example, 0.1 MPa to 1000 MPa to the simulation model, and executes a simulation to determine the tensile modulus from an elongation region of the lattice constant of 0.05 to 0.25%. As a result, the characteristic value calculation unit 153 calculates a characteristic value (predicted value) of, for example, 2100 MPa as the tensile modulus.

[0060] Furthermore, the characteristic value calculation unit 153 associates the calculated predicted values ​​of the mechanical characteristics, the simulation model, and the molecular model corresponding to the simulation model, and stores them in the molecular model database 144.

[0061] Next, the output information generating unit 120 generates display information for the output screen including the calculated predicted values ​​of the mechanical properties, and displays it on the display device (step S60).

[0062] 7 is a diagram showing an example of an output screen 300 including predicted values ​​of mechanical properties. The output information generating unit 120 displays the output screen 300 including the predicted values ​​of mechanical properties and a molecular model simulation model as a simulation result. Note that it is sufficient that the output screen 300 includes at least the calculated predicted values ​​of mechanical properties, and as shown in the figure, the simulation model may be displayed together with the predicted values ​​of mechanical properties.

[0063] After displaying the screen information, the output information generating unit 120 ends the processing of this flow.

[0064] The material evaluation process has been described above.

[0065] Such a material evaluation system makes it possible to reduce the cost and time required to acquire data on the recycled resin material being evaluated, thereby shortening the time required for characteristic evaluation.

[0066] In particular, the material evaluation system uses accumulated data to create a database in which each feature is associated with a contribution level based on the impact on each characteristic, and can use this database to identify feature quantities that have a large impact on the characteristics to be evaluated for the recycled resin material being evaluated. That is, the material evaluation system can easily identify feature quantities that have a large impact on the characteristics to be evaluated from a database created in advance for recycled resin materials that are mixed with original materials through material recycling. Therefore, the material evaluation system does not need to perform processing to identify the feature quantities that have a large impact.

[0067] Furthermore, the material evaluation system can create a molecular model by simply accepting the minimum amount of actual measurement data required, such as FT-IR, depending on the type of feature that has a significant impact on the properties, and then use molecular dynamics simulation to determine the mechanical properties. Since the shape of the recycled plastic used for measurements such as FT-IR is not important, it can eliminate the need to create test specimens that meet specific standards. As a result, the material evaluation system can significantly reduce the cost and time required to acquire actual measurement data.

[0068] Furthermore, the material evaluation system can identify the molecular structure of the recycled plastic being evaluated based on the contribution information and actual measurement data. For example, if the feature identified from the contribution information is C=O (carboxyl group), a C=O (carbonyl group) peak is observed in FT-IR measurement, and the approximate content of carboxyl groups can be estimated from the detected intensity of the spectrum from the measurement. Therefore, a molecular model can be created by incorporating X C=Os per molecular chain. Therefore, the material evaluation system does not, for example, attempt to reconstruct the molecular structure hundreds of times, thereby significantly reducing calculation costs.

[0069] Second Embodiment In the first embodiment described above, the case of obtaining a predicted value of the tensile modulus of polypropylene was described. However, the material evaluation system 1000 can calculate predicted values ​​of various mechanical properties, and in this embodiment, as an example, the case of obtaining the breaking elongation of recycled polypropylene by molecular dynamics simulation will be described.

[0070] In this embodiment, as in the first embodiment, the base material is polypropylene, and at least one of XRD, FT-IR, TG, and TG-DTA is input as measured data (step S20). Furthermore, the higher-order structure calculation unit 152 identifies carboxyl groups and polyethylene (PE) as feature quantities that contribute significantly to the breaking elongation to be evaluated. Furthermore, the higher-order structure calculation unit 152 generates a molecular model shown in FIGS. 5A to 5C (step S30), and generates a simulation model shown in FIG. 6 based on the molecular model (step S40).

[0071] FIG. 8 is a diagram for explaining the application of an external force by molecular dynamics simulation. FIG. 9 is a diagram for explaining the lattice constant when tension is applied. In FIG. 8, as in the first embodiment, the direction in which the created molecular model chains are superimposed is defined as the a-axis, and the molecular model chain direction is defined as the c-axis. The characteristic value calculation unit 153 applied a tension of, for example, 0.1 MPa to 1000 MPa to the simulation model. At this time, the characteristic value calculation unit 153 calculated the elongation of the lattice constant a when the polypropylene (PP) block breaks when tension is applied in the a-axis direction as the characteristic value of the breaking elongation.

[0072] As shown in the figure, application of tension in the c-axis direction elongates the carbon chains, resulting in a large elongation of the lattice constant c. On the other hand, application of tension in the a-axis direction breaks the material at a lower tension than when tension is applied in the c-axis direction, because the carbon chains are not connected by direct bonds but by intermolecular interactions. The break of polypropylene is defined as the lattice constant a when lattice constant c is smallest when tension is applied in the a-axis direction (FIG. 9). Based on this definition, the characteristic value calculation unit 153 calculated the break elongation to be 4.2% when an applied tension of 150 MPa is applied.

[0073] 10 is a diagram showing an example of an output screen 310 including predicted values ​​of mechanical properties to be evaluated. The output information generating unit 120 displays the output screen 310 including the calculated predicted values ​​of mechanical properties (in this example, breaking elongation) and a molecular model simulation model as a simulation result. Note that it is sufficient that the output screen 310 includes at least the calculated predicted values ​​of mechanical properties, and as shown in the figure, the simulation model may be displayed together with the predicted values ​​of mechanical properties.

[0074] In this way, the material evaluation system can calculate predicted values ​​for various types of mechanical properties through simulations using molecular models.

[0075] Third Embodiment Plastics have temperatures at which their properties change significantly (melting point at which they change from rubbery to liquid and glass transition temperature at which they change from rubbery to glassy), and being able to predict mechanical properties according to temperature is extremely important, for example, in terms of product safety standards or operation. The material evaluation system 1000 of this embodiment uses molecular dynamics simulation to determine predicted values ​​of mechanical properties of recycled plastics in a temperature range above the glass transition temperature and below the melting point.

[0076] The material evaluation system 1000 determines the tensile modulus of recycled polypropylene at 60°C by molecular dynamics simulation. Specifically, the characteristic value calculation unit 153 executes the molecular dynamics simulation by setting the constraint condition of the operating environment to 60°C. Note that the temperature constraint condition during simulation execution can be set by the user via, for example, the input screen 200 in FIG. 4.

[0077] In this embodiment, as in the first embodiment, the base material is polypropylene, and at least one of XRD, FT-IR, TG, and TG-DTA is input as measured data (step S20). Furthermore, the higher-order structure calculation unit 152 identifies carboxyl groups and polyethylene (PE) as feature quantities that contribute significantly to the tensile modulus to be evaluated. Furthermore, the higher-order structure calculation unit 152 generates a molecular model shown in FIGS. 5A to 5C (step S30), and generates a simulation model shown in FIG. 6 based on the molecular model (step S40).

[0078] The direction in which the molecular model chains are superimposed is defined as the a-axis, and the molecular model chain direction is defined as the c-axis. The characteristic value calculation unit 153 applies a tension of, for example, 0.1 MPa to 1000 MPa to the simulation model, and executes a simulation to obtain the tensile modulus from an elongation region of the lattice constant of 0.05 to 0.25%. At this time, the characteristic value calculation unit 153 calculates a characteristic value (predicted value) of 1500 MPa as the tensile modulus, which is different from that in the first embodiment.

[0079] In this way, the material evaluation system can predict the mechanical properties of the recycled plastic being evaluated or of a product that uses that recycled plastic at the operating temperature from its structural information (molecular model) based on the set temperature. In other words, even if actual measurement data for the recycled plastic being evaluated was acquired at room temperature, the material evaluation system can calculate, based on simulations, predicted values ​​of properties that are used as determining factors for whether or not a product using the recycled plastic being evaluated can be used in the operating temperature range, and present these values ​​to the user.

[0080] <Fourth embodiment> The material evaluation system 1000 of the third embodiment determined the mechanical properties of recycled plastics in a temperature range above the glass transition temperature and below the melting point, but the material evaluation system 1000 of the present embodiment determines predicted values ​​of the mechanical properties of recycled plastics in a temperature range below the glass transition temperature using molecular dynamics simulation.

[0081] The glass transition temperature of polypropylene is -20°C to 0°C, while that of polyethylene is -120°C, making polypropylene alone more difficult to handle than polyethylene in terms of cold resistance. Also, because recycled polypropylene is a mixture of polypropylene and polyethylene, it is important to understand its mechanical properties when blending materials for, for example, cold-climate automobile parts and internal parts of freezers.

[0082] The material evaluation system 1000 of this embodiment determined the tensile modulus of recycled polypropylene at −20° C. by molecular dynamics simulation. Specifically, the characteristic value calculation unit 153 performed the molecular dynamics simulation by setting the operating environment at −20° C. as a constraint and the cooling rate to −20° C. Note that the temperature constraint condition during simulation execution can be set by the user via, for example, the input screen 200 in FIG. 4.

[0083] In this embodiment, as in the first embodiment, the base material is polypropylene, and at least one of XRD, FT-IR, TG, and TG-DTA is input as measured data (step S20). Furthermore, the higher-order structure calculation unit 152 identifies carboxyl groups and polyethylene (PE) as feature quantities that contribute significantly to the tensile modulus to be evaluated. Furthermore, the higher-order structure calculation unit 152 generates a molecular model shown in FIGS. 5A to 5C (step S30), and generates a simulation model shown in FIG. 6 based on the molecular model (step S40).

[0084] The direction in which the created molecular model chains are superimposed is defined as the a-axis, and the molecular model chain direction is defined as the c-axis. The characteristic value calculation unit 153 applies a tension of, for example, 0.1 MPa to 1000 MPa to the simulation model, and performs a simulation to determine the tensile modulus from an elongation region of the lattice constant of 0.05 to 0.25%. In this simulation, the characteristic value calculation unit 153 calculated a characteristic value (predicted value) of 2400 MPa as the tensile modulus, which is different from that in the first embodiment. This result shows that recycled polypropylene in a -20°C environment has a higher tensile modulus than recycled polypropylene in a room temperature environment of, for example, 25°C.

[0085] In this way, by setting the cooling rate to the operating environment (down to -20°C), the material evaluation system can predict the mechanical properties of the recycled plastic being evaluated or the product in which the recycled plastic is used at the operating temperature from its structural information (molecular model), even if the actual measurement data for the recycled plastic being evaluated was obtained at room temperature.

[0086] It should be noted that the material evaluation system 1000 is not limited to these embodiments and can be modified in various ways. For example, if there is no accumulated data (mechanical property information, feature amount information, etc.) on recycled plastics, the user may create a test piece, perform measurements using FT-IR or the like, and add the measurement results to the storage unit 140 as accumulated data.

[0087] Alternatively, the material evaluation system 1000 may acquire stored data or information input by a user from a predetermined device outside the system via the network N, and display the output screen 300 on the predetermined device.

[0088] Fig. 11 is a diagram showing another example of the configuration of the material evaluation system 1000. Note that the same components and functions as those in Fig. 1 are given the same reference numerals, and detailed explanations thereof will be omitted.

[0089] As shown in the figure, the material evaluation system 1000 has a computer 101, a terminal device 400, and an external device 500, which are connected via a predetermined network N so as to be able to communicate with each other.

[0090] The basic configuration of the computer 101 is the same as that of the above-described embodiment, but differs in that it does not have a storage unit 140 that stores various databases. In this modification, the various databases stored in the storage unit 140 in FIG. 1 are stored in an external device 500.

[0091] The terminal device 400 is a personal computer, a smartphone, a tablet terminal, etc. used by a user. In this case, the user inputs actual measurement data via the input screen 200 displayed on the terminal device 400, and the output screen 300 generated by the material evaluation system 1000 is displayed on the terminal device 400.

[0092] The external device 500 is, for example, a computer such as a server device placed on a cloud. The external device 500 also has each database in the storage unit 140 of the computer 100 in Fig. 1. The external device 500 transmits necessary information to the computer 101 as appropriate in accordance with the processing executed by the computer 101.

[0093] As with the above-described embodiment, this type of material evaluation system 1000 also makes it possible to reduce the cost and time required to acquire data on the recycled resin material being evaluated, thereby shortening the time required for characteristic evaluation.

[0094] <Hardware configuration of the material evaluation system 1000> 12 is a diagram showing an example of the hardware configuration of a materials evaluation system 1000. As shown in the figure, the materials evaluation system 1000 has an input device 610, a display device 620, a processing device 630, a main memory device 640, an auxiliary memory device 650, a communication device 660, and a bus 670 that electrically interconnects these devices.

[0095] The input device 610 is, for example, a touch panel, a keyboard, a mouse, etc. The display device 620 is a display device such as a liquid crystal display or an organic display.

[0096] The processing device 630 is, for example, a processor such as a CPU (Central Processing Unit) or a GPU (Graphics Processing Unit). The main storage device 640 is a memory device (memory resource) such as a RAM (Random Access Memory) or a ROM (Read Only Memory). The material evaluation system 1000 has at least one processor and one or more memory resources.

[0097] The auxiliary storage device 650 is a non-volatile storage device capable of storing digital information, such as a so-called hard disk drive, a solid state drive (SSD), or a flash memory.

[0098] The communication device 660 is a wired communication device that performs wired communication via a network cable, or a wireless communication device that performs wireless communication via an antenna.

[0099] An example of the hardware configuration of the material evaluation system 1000 has been described above.

[0100] The processing unit 150 of the material evaluation system 1000 is realized by a program that causes the processing device 630 to perform processing. This program is stored in the main memory device 640 or the auxiliary memory device 650, and is loaded onto the main memory device 640 and executed by the processing device 630 when the program is executed.

[0101] The storage unit 140 is realized by a main storage device 640, an auxiliary storage device 650, or a combination thereof. The communication unit 130 is realized by a communication device 660.

[0102] Furthermore, the above-described configurations, functions, processing units, and processing means of the materials evaluation system 1000 may be partially or entirely realized in hardware, for example, by designing them as integrated circuits. The above-described configurations and functions may also be realized in software, with a processor interpreting and executing a program that realizes each function. Information such as the programs, tables, and files that realize each function can be stored in a storage device such as a memory, hard disk, or SSD, or in a recording medium such as an IC card, SD card, or DVD.

[0103] Furthermore, the present invention is not limited to the above-described embodiments and modifications, and includes various modifications within the scope of the same technical concept. For example, the above-described embodiments have been described in detail to clearly explain the present invention, and the present invention is not necessarily limited to those including all of the described configurations. Furthermore, it is possible to replace part of the configuration of one embodiment with the configuration of another embodiment, or to add the configuration of another embodiment to the configuration of one embodiment. Furthermore, it is possible to add, delete, or replace part of the configuration of each embodiment with other configurations.

[0104] In addition, in the above explanation, the control lines and information lines are those that are considered necessary for the explanation, and do not necessarily show all the control lines and information lines in the product. In reality, it can be considered that almost all components are interconnected. [Explanation of symbols]

[0105] 1000···Materials evaluation system, 100(101)···Computer, 110···Input receiving unit, 120···Output information generating unit, 130···Communication unit, 140···Memory unit, 141···Mechanical property database, 142···Feature database, 143···Contribution database, 144···Molecular model database, 150···Processing unit, 151···Contribution calculation unit, 152···Higher-order structure calculation unit, 153···Property value calculation unit, 400···Terminal device, 500···External device, 610···Input device, 620···Display device, 630···Processing device, 640···Main memory device, 650···Auxiliary memory device, 660···Communication device, 670···Bus, N···Network

Claims

1. A processor that executes a program and a storage device that stores the program, the storage device stores a contribution degree table in which feature quantities of raw materials and contribution degrees, which are indices indicating the magnitude of influence of the feature quantities of the raw materials on predetermined mechanical properties, are associated with each type of raw material; The processor: Accepts as input the raw material information and actual measurement data on the characteristic quantities of the recycled resin material to be evaluated, Based on the contribution table and raw material information of the recycled resin material to be evaluated, the feature value of the contribution that has the greatest influence on the mechanical properties of the evaluation target is identified, and a molecular model is created in which the identified feature value is incorporated into the main raw material of the recycled resin material according to the value of the actual measurement data of the recycled resin material to be evaluated; calculating characteristic values ​​of the mechanical properties of the object to be evaluated by performing a predetermined simulation based on the molecular model; outputting the calculated characteristic value; A material evaluation system characterized by:

2. 2. The material evaluation system according to claim 1, The processor: calculating the contribution for each feature based on the product of the feature intensity, frequency, and computational cost; the intensity is the abundance ratio of the periodic structure of the feature amount to the recycled resin material, the frequency is the frequency of appearance of the feature, The calculation cost is the time required for the simulation according to the number of atoms of the feature amount. A material evaluation system characterized by:

3. 3. The material evaluation system according to claim 2, The degree of contribution is an index indicating the magnitude of the influence on the mechanical properties of the evaluation target, and is also an index indicating the degree to which the mechanical properties of the evaluation target contribute to the calculation time by the simulation. A material evaluation system characterized by:

4. 2. The material evaluation system according to claim 1, The processor: When a plurality of feature quantities that have a greater contribution and whose difference falls within a predetermined range are identified, the plurality of feature quantities are incorporated into the molecular structure or molecular chain of the main raw material to generate the molecular model. A material evaluation system characterized by:

5. 2. The material evaluation system according to claim 1, The main raw material of the recycled resin material is an olefin-based resin, which includes at least polypropylene or polyethylene. A material evaluation system characterized by:

6. 2. The material evaluation system according to claim 1, The characteristic quantities include functional groups, foreign matter, molecular weight, crystallinity, and viscosity. A material evaluation system characterized by:

7. 2. The material evaluation system according to claim 1, The mechanical properties include at least one of tensile modulus, breaking stress, breaking strain, breaking elongation, yield stress, tensile strength, flexural modulus, flexural strength, and Charpy impact value. A material evaluation system characterized by:

8. 2. The material evaluation system according to claim 1, The measured data for the recycled resin material to be evaluated is obtained based on at least one of FT-IR (Fourier Transform Infrared Spectrometer), XRD (X-ray Diffraction), spectrophotometer, MFR (Melt Flow Rate), thermogravimetric analysis, differential thermal analysis, or TG-DTA (Thermogravimetric analysis-Differential Thermal Analysis), which simultaneously performs thermogravimetric analysis and differential thermal analysis. A material evaluation system characterized by:

9. 2. The material evaluation system according to claim 1, The processor: generating a simulation model to be used in the simulation by using the molecular model so that a predetermined number of predetermined molecular structures are included within a periodic boundary; A molecular dynamics simulation is performed to apply an external force to the simulation model, thereby calculating the mechanical properties of the object to be evaluated. A material evaluation system characterized by:

10. 2. The material evaluation system according to claim 1, The processor: A simulation model of the molecular model is output together with the calculated characteristic values. A material evaluation system characterized by:

11. 2. The material evaluation system according to claim 1, The processor: Accepting input of temperature constraints according to the operating environment of the recycled resin material; By executing the simulation, the mechanical characteristics at a temperature corresponding to the operating environment are calculated. A material evaluation system characterized by:

12. A material evaluation method executed by a material evaluation system having a processor that executes a program and a storage device that stores the program, comprising: the storage device stores a contribution degree table in which feature quantities of raw materials and contribution degrees, which are indices indicating the magnitude of influence of the feature quantities of the raw materials on predetermined mechanical properties, are associated with each type of raw material; The processor executes the program, receiving as input actual measurement data relating to raw material information and feature quantities of the recycled resin material to be evaluated; Identifying the feature of the contribution that has the greatest influence on the mechanical properties of the object to be evaluated based on the contribution table and the raw material information of the recycled resin material to be evaluated, and creating a molecular model incorporating the identified feature into the main raw material of the recycled resin material according to the value of the actual measurement data of the recycled resin material to be evaluated; calculating a characteristic value of the mechanical property of the object to be evaluated by executing a predetermined simulation based on the molecular model; and outputting the calculated characteristic value. A material evaluation method characterized by:

13. A material evaluation system having a processor that executes a program and a storage device that stores the program, the program being read and executed by the processor, the storage device stores a contribution degree table in which feature quantities of raw materials and contribution degrees, which are indices indicating the magnitude of influence of the feature quantities of the raw materials on predetermined mechanical properties, are associated with each type of raw material; The program executed by the processor comprises: Accepts as input the raw material information and actual measurement data on the characteristic quantities of the recycled resin material to be evaluated, Based on the contribution table and raw material information of the recycled resin material to be evaluated, the feature value of the contribution that has the greatest influence on the mechanical properties of the evaluation target is identified, and a molecular model is created in which the identified feature value is incorporated into the main raw material of the recycled resin material according to the value of the actual measurement data of the recycled resin material to be evaluated; calculating characteristic values ​​of the mechanical properties of the object to be evaluated by performing a predetermined simulation based on the molecular model; outputting the calculated characteristic value; A program characterized by:

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